A Progressive Approach to Applied Behavior Analysis: The Autism Partnership Method [1 ed.] 0323957412, 9780323957410

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A PROGRESSIVE APPROACH TO APPLIED BEHAVIOR ANALYSIS

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A PROGRESSIVE APPROACH TO APPLIED BEHAVIOR ANALYSIS The Autism Partnership Method JUSTIN B. LEAF Autism Partnership Foundation, Seal Beach, CA, United States

JOSEPH H. CIHON Autism Partnership Foundation, Seal Beach, CA, United States

JULIA L. FERGUSON Autism Partnership Foundation, Seal Beach, CA, United States

RONALD LEAF Autism Partnership Foundation, Seal Beach, CA, United States

JOHN MCEACHIN Autism Partnership Foundation, Seal Beach, CA, United States

TOBY MOUNTJOY Autism Partnership Foundation, Seal Beach, CA, United States

JEREMY LEAF Autism Partnership Foundation, Seal Beach, CA, United States

AMANDA ROGUE Autism Partnership Foundation, Seal Beach, CA, United States

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2024 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN 978-0-323-95741-0 For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

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Contents About the authors

1. Applied behavior analysis What is ABA? Some research examples Recent events Summary References

2. An overview and history of the Autism Partnership Method First tenet: Clinical judgment Second tenet: Learner-centered Third tenet: Meaningful and functional curriculum Fourth tenet: Flexible procedures Fifth tenet: Working with the whole family Sixth tenet: Performance-based staff training Seventh tenet: Compassion The history of the APM References

3. Respondent and operant behavior Reflexes and respondent behavior Operant behavior Some important notes Summary References

4. Stimulus control and generalization Generalization Summary References

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1 2 3 8 11 11

17 18 21 21 22 22 23 23 23 26

29 30 32 33 35 35

39 42 46 46

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Contents

5. Reinforcement: Overview, identification, conditioning Reinforcer identification Conditioning reinforcers Summary References

6. Punishment: Overview, concerns, and use Some concerns with the use of punishment-based procedures Clinical considerations Some punishment-based procedures Summary References

7. Token economies and other contingency systems Components of token systems The commonality of token economies Advantages and disadvantages of token systems Some relevant research Clinical recommendations and progressive approaches to token systems Summary References

8. Respondent conditioning procedures Considerations related to respondent behavior in autism intervention Summary References

9. Task analysis and chaining Task analysis Chaining Research Summary References

10. Shaping A sample of research Clinical recommendations Summary References

49 50 57 60 61

63 64 67 70 71 72

75 76 76 77 78 80 85 85

87 89 93 93

95 95 99 100 101 101

103 103 107 112 112

Contents

11. Prompting Prompt types Prompting systems Flexible prompt fading: The APM prompting system Summary References

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115 115 119 126 130 130

12. Discrete trial teaching

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Components of DTT Summary References

136 153 153

13. Naturalistic instruction

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Incidental teaching Embedded instructions Summary References

158 161 162 163

14. The teaching interaction procedure Overview Teaching interaction procedure research Summary References

15. Cool versus Not Cool procedure Steps of the CNC procedure Misuses of the CNC procedure History and research Summary References

16. Social skills groups Hallmarks of behaviorally based social skills groups Research Summary References

17. Functional behavior assessment and functional analysis Overview of functional behavior assessment Types of functional analysis

165 165 173 176 176

179 179 184 185 188 189

191 192 196 200 200

205 206 209

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History of FBA and functional analysis The autism partnership method approach to FBAs and FAs References

18. Differential reinforcement Differential reinforcement of other behavior Differential reinforcement of alternative behavior Differential reinforcement of incompatible behavior Differential reinforcement of low rates of behavior and differential reinforcement of high rates of behavior Some progressive considerations regarding differential reinforcement Summary References

19. Extinction and response cost Misperceptions and clarifications related to extinction Response cost Misperceptions and clarifications related to response cost Recommendations for practice Summary References

20. Time out from positive reinforcement and the time-in ribbon Time-out from positive reinforcement Research on time-out Autism partnership method and time-out Time-in ribbon Summary References

21. Measurement systems Considerations in selecting a measurement system Measurement systems Measuring with our heart Summary References

212 214 216

219 219 220 221 222 223 226 226

229 230 233 234 235 237 237

239 239 243 244 245 248 248

251 252 254 265 265 265

Contents

22. Formal assessments The assessments Summary References

23. Curriculum assessment Common curriculum assessments Autism Partnership Method and curricular assessment Building the curriculum References

24. Learning-how-to-learn curriculum The skills Summary References

25. Social skills curriculum Reasons why we teach social skills Reasons why social skills development is often not a priority What to teach: The social skills taxonomy How to teach social behavior Reminder Summary References

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279 280 283 286 286

287 288 300 301

303 303 305 307 310 311 311 312

26. Language curriculum

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Language programs Summary References

317 323 323

27. Self-help and adaptive behaviors Toilet training Mealtime challenges Sleep Appearance checks Basic efficiency and organization Walk with me

327 329 333 334 334 335 335

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Crossing the street safely Following a visual or written schedule Self-advocacy Summary References

28. Working with parents of autistic children Prediagnosis stress Diagnostic process stress Postdiagnosis stress Intervention stress Autism partnership method of parent support Research on parent training Summary References

29. Siblings Sibling relationship throughout the lifespan The Autism Partnership Method and siblings References

30. Staff and staff training Characteristics of quality interventionists Additional skills interventionists should display Additional skills supervisors should display Staff training Summary References Index

336 336 337 337 337

341 341 342 342 343 343 350 352 352

355 356 357 359

361 363 372 373 375 376 376 379

About the authors Justin Leaf, PhD, is the executive director for the Autism Partnership Foundation and the Progressive Behavior Analyst Autism Council, the associate director for ABA Doctoral Studies at Endicott College, and the executive director for Contemporary Behavior Consultants. He received his doctorate degree in behavioral psychology from the Department of Applied Behavioral Science at the University of Kansas. His research interests include progressive ABA, improving behavioral intervention, social behavior, and methodologies to improve the lives of autistic/individuals diagnosed with ASD. Justin has more than 140 publications in peer-reviewed journals, books, or book chapters and has presented at both national and international professional conferences and invited events. He has served on numerous editorial boards for behavior analytic and autism journals. His career has been dedicated to improving the field of applied behavior analysis and the lives of autistic individuals. Dr. Joseph H. Cihon received his BS in special education from Fontbonne University, his MS in behavior analysis at the University of North Texas under the mentorship of Drs. Shahla Ala’i, Jesus Rosales-Ruiz, and Manish Vaidya, and his PhD in applied behavior analysis at Endicott College under the mentorship of Dr. Mary Jane Weiss. He is currently the director of research at the Autism Partnership Foundation, an adjunct professor at Endicott College, the certification coordinator at the Progressive Behavior Analyst Autism Council, and on the council for the Autism Special Interest Group. Joseph has 20 years of experience working with children, adolescents, and adults on the autism spectrum and with other developmental disabilities in home, school, and community settings. His research interests in behavior analysis are broad and include evaluating assumptions within practice, examining historical foundations in behavior analysis, training thoroughgoing behavior analysts, examining the effectiveness and training professionals in shaping techniques, increasing favorable interactions among children, their families, and interventionists, developing contingencies to promote generalization and maintenance, and improving mealtimes for selective eaters. He serves on the editorial boards for the International Electronic Journal of Elementary Education and Behavior Analysis in Practice and has published more than 70 peer-reviewed articles, books, and book chapters. xi

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Julia Ferguson, MS, BCBA, CPBA-AP, is the research and assessment coordinator for the Autism Partnership Foundation and the associate director of the Progressive Behavior Analyst Autism Council. She received her bachelor’s degree in applied behavior analysis and her master’s degree in behavior analysis from the University of North Texas. She is currently pursuing her PhD in applied behavior analysis at Endicott College under the advisement of Dr. Mary Jane Weiss. Julia has more than 10 years of experience working with children diagnosed with autism in home, community, and clinical settings. Her research interests include evaluating social skills interventions, evaluating progressive approaches to behavioral interventions, and comparing different teaching methodologies for individuals diagnosed with autism. Julia has published more than 50 peer-reviewed research articles, book chapters, and books and has presented at national and international conferences. Dr. Ronald Leaf is a licensed psychologist with more than 50 years of experience in the field of autism. He began his career working with Prof. Ivar Lovaas while receiving his undergraduate degree at the University of California, Los Angeles (UCLA). Subsequently, he received his doctorate under the direction of Prof. Lovaas. During his years at UCLA, Leaf served as clinic supervisor, research psychologist, lecturer, and interim director of the Young Autism Project. He was extensively involved in several research investigations, contributed to The Me Book, and is a coauthor of The Me Book Videotapes. Dr. Leaf has consulted with families, schools, and agencies on a national and international basis. He is the cofounder and director of the Autism Partnership, which offers comprehensive services for families with children and adolescents diagnosed with autism spectrum disorder (ASD). With offices in 10 countries, Ronald and his team have developed the Autism Partnership Method, a progressive approach to implementing Applied Behavior Analysis (ABA) treatment. He is the coauthor of A Work in Progress, Time for School, It Has to Be Said, Crafting Connections, A Work in Progress Companion Series, Clinical Judgment, Autism Partnership Method: Social Skills Groups, and the Clinician’s Toolbox: Rediscovering Compassionate ABA. He has coauthored more than 100 articles in research journals and presented more than 100 times at professional conferences. Dr. Leaf is also the cofounder of the Autism Partnership Foundation, a nonprofit organization dedicated to advancing professional standards and the treatment of individuals with autism through research and training.

About the authors

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John McEachin, a psychologist and BCBA-D, has been providing behavioral treatment to individuals with autism for more than 40 years. He received his graduate training under Prof. Ivar Lovaas at UCLA on the Young Autism Project. During his 11 years at UCLA, Dr. McEachin served in various roles, including clinic supervisor, research and teaching assistant, and acting director. His research has included the long-term follow-up study of young autistic children who received intensive behavioral treatment, which was published in 1993. In 1994, he joined Ron Leaf in forming the Autism Partnership, which they codirect. In 1999, they published A Work in Progress, a widely used behavioral treatment manual and curriculum for children with ASD. Dr. McEachin has lectured throughout the world and coauthored numerous books and research articles. He consults regularly with families, agencies, and school districts nationally and internationally, assisting in the development of treatment programs and providing training to parents, staff, and classroom personnel. Dr. McEachin’s dedication to the advancement of behavioral treatment through research and quality training led to the cofounding of the Autism Partnership Foundation with Dr. Ron Leaf. Toby Mountjoy is a board-certified behavior analyst and holds a master of science in applied behavior analysis. He also became one of the first certified autism professionals in 2022. With more than 27 years of experience working with individuals with ASD, he has been extensively trained by Drs. Ronald Leaf and John McEachin. Besides overseeing the Autism Partnership operation in Hong Kong, Korea, the Philippines, Singapore, and Beijing, with more than 300 staff, including psychologists, consultants, and therapists, he has also provided consultations to school districts, agencies, and families worldwide. Mr. Mountjoy has also contributed chapters to publications such as Sense & Nonsense and It’s Time for School. In 2007, he founded the charitable Autism Partnership Foundation and Aoi Pui School to offer more services for children with autism. Jeremy Leaf is a clinical director for Autism Partnership. Jeremy received his master’s degree in special education at Loyola Marymount University. He has worked with children, adolescents, and adults diagnosed with autism spectrum disorder (ASD) and other disabilities since 2007. He has worked extensively on creating curriculum in a variety of domains, running social skills groups, and staff training. Additionally, Jeremy has published 16 peer-reviewed publications and was a coauthor of The Autism Partnership Method: Social Skills Groups. He has also presented his research at national and

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international conferences. In addition to his work in Seal Beach, CA, Jeremy also works as a consultant both nationally and internationally, helping staff, children, and families reach their full potential. Amanda Rogue is the site director for Autism Partnership’s clinic in San Francisco, CA. She received her bachelor’s degree in neuroscience from the University of California, Los Angeles, and began working for the Autism Partnership shortly after. She went on to receive her master’s degree in applied behavior analysis from St. Cloud State University. Amanda has more than 11 years of clinical experience working with children and adolescents diagnosed with autism spectrum disorder, but her experience working directly with adolescents and adults with developmental disabilities extends years beyond that. Amanda has a younger brother with a developmental disability that thrives to this day despite being born after just 23 weeks and given only a 10% chance of surviving. Due to this, she is a firm believer that highly skilled and heartfelt care can make a substantial difference in the quality of life for individuals with developmental disabilities.

CHAPTER 1

Applied behavior analysis Contents What is ABA? Some research examples Early research and publications Other seminal research and publications Recent events Certification Equity A progressive approach Summary References

2 3 3 6 8 8 9 10 11 11

It is important that we know where we come from, because if you do not know where you come from, then you don’t know where you are, and if you don’t know where you are, you don’t know where you’re going. And if you don’t know where you’re going, you’re probably going wrong. Pratchett (2010, p. 477)

Many individuals who are just beginning their professional journey in the field of applied behavior analysis (ABA) may not have accessed much information related to its early history. As a result, the purpose of this chapter is to provide an overview and brief history of ABA. This overview is intentionally brief as there are many in-depth sources on the topic that the reader is encouraged to access in order to dig deeper into the history of our science and practice (e.g., Cooper et al., 2020; Michael, 1993; Moore, 2008a, 2008b; Morris et al., 1990, 2005, 2013; Rachlin, 1970). Instead, this chapter is designed to provide the reader with a context in which to view the rest of the content contained in the book. As the opening quote suggests, it is important to know where we have been and where we are currently to prevent making the mistakes of the past and to inform movement forward. It is in that light that progression and regression related to the practice of ABA can be evaluated and determined.

A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00032-5

Copyright © 2024 Elsevier Inc. All rights reserved.

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What is ABA? ABA represents just one of the branches of the science that is behavior analysis. The other branches are the experimental analysis of behavior (sometimes referred to as EAB) and behaviorism, or the philosophy of behavior (sometimes referred to as radical behaviorism; Cooper et al., 2020). ABA is rooted in the influential works of many individuals, including, but not limited to, Sidney Bijou, Betty Hart, Mary Cover Jones, Ivan Pavlov, B. F. Skinner, Edward Thorndike, John Watson, and Joseph Wolpe. ABA, as a term, describes a science that involves a systematic approach to understanding the behavior of social interest or a practice referring to the application of behavior analytic principles to improve socially important behaviors (Baer et al., 1968; Cooper et al., 2020). Baer et al. (1968) outlined some of the defining characteristics that research in ABA should exhibit in their seminal paper “Some current dimensions of applied behavior analysis,” which was revisited 20 years later (i.e., Baer et al., 1987). Although there are many examples of research that may be considered ABA prior to Baer et al.’s (1968) seminal article (e.g., Allen et al., 1964; Ayllon, 1963; Ayllon & Azrin, 1965; Ayllon & Michael, 1959; Etzel & Gewirtz, 1967; Sherman, 1963; Wolf et al., 1963), its publication paired with the establishment of the Journal of Applied Behavior Analysis in 1968 is commonly cited as what established the field of ABA. The dimensions described in this seminal paper are applied, behavioral, analytic, technological, conceptually systematic, effective, and generality (see Table 1 for a description of each dimension). Behavior analytic research is commonly evaluated to determine if a study is reflective of the dimensions described by Baer et al. (1968) to determine if a study is “applied” or “not applied.” However, it may be argued that requiring a study to display all of these dimensions to be considered ABA was not the original intent of Baer and colleagues (1968). While it may be the case that some of these dimensions may be more important and should be included in all research considered as ABA (e.g., behavioral), all lines of research need to start somewhere, which may result in sacrifices with one dimension over another. For instance, a study involving a topic of the utmost importance to society that is the first of its kind (i.e., applied) may lack in other areas (e.g., analytic). Nevertheless, that study may be considered as falling under ABA due to other dimensions displayed fully in the research article.

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Table 1 Some dimensions of applied behavior analysis. Dimension

Baer et al. (1968) quote

Applied

“the behavior, stimuli, and/or organism under study are chosen because of their importance to man and society, rather than their importance to theory” (p. 92) “it usually studies what subjects can be brought to do rather than what they can be brought to say; unless, of course, a verbal response is the behavior of interest” (p. 93) “a believable demonstration of the events that can be responsible for the occurrence or non-occurrence of that behavior” (pp. 93–94) “the techniques making up a particular behavioral application are completely identified and described” (p. 95) “strive for relevance to principle” (p. 96)

Behavioral

Analytic

Technological Conceptually systematic Effective Generality

“produce large enough effects for practical value” (p. 96) “proves durable over time, if it appears in a wide variety of possible environments, or if it spreads to a wide variety of related behaviors” (p. 96)

It is important to note the importance of the word some in Baer et al.’s (1968) title. Some, rather than the, implies that there are likely more dimensions than just the seven laid out in their seminal article. In fact, Baer and colleagues never made the case, explicitly or otherwise, that they were providing an exhaustive list of the dimensions of ABA. This is exemplified by Wolf’s (1978) publication describing the importance of social validity within ABA. Although not directly mentioned by Baer et al. (1968), it seems evident that the use and measurement of social validity is also a dimension of ABA. Viewing the dimensions of ABA as dynamic and evolving permits the science to continue to progress and improve (Leaf et al., 2016).

Some research examples Early research and publications The following section provides a sample of some early, influential studies related to the origins of ABA. It is difficult to select a small number of articles as examples given that the number of articles that could be included would fill a book themselves. We acknowledge the potential for bias toward certain early publications in our selection of articles to include here. However, this

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bias is informed by years of experience within the field including, but not limited to, conducting applied behavior analytic research, providing ABA-based intervention for several populations and abilities, and teaching undergraduate, graduate, and doctoral students the history of behavior analysis. For more detailed descriptions and analyses of the origins of ABA through its publications, we refer the reader to readings such as Morris et al. (2013) and Morris et al. (1990). Ayllon and Michael (1959) published an article in the Journal of the Experimental Analysis of Behavior in which they trained aides, psychiatric nurses, and registered nurses on the application of behavioral techniques to address the undesired behavior of 19 patients in a hospital. For most of the patients, attention from the staff was identified as a strong reinforcer, so the researchers set out to demonstrate how the contingent use of attention could alter undesired patterns of behavior. The staff were instructed to no longer provide reinforcement for undesired behavior (i.e., extinction; see Chapter 19) and, instead, provide reinforcement for incompatible behavior (i.e., differential reinforcement of an incompatible behavior; DRI; see Chapter 18). Two patients, who would not eat unless aided by the hospital staff, were treated using a combination of noninvasive, naturally occurring punishment (i.e., food spilling), and social reinforcement was provided for self-feeding. Finally, reinforcement and satiation (see Chapter 5) were used to address the hoarding behavior of four of the patients. Ayllon and Michael were able to demonstrate in this early study the effectiveness of behavior analytic techniques for improving behavior that was not responsive to prevailing methods among all the patients that participated. Isaacs et al. (1960), published in the Journal of Speech and Hearing Disorders, evaluated the use of operant conditioning techniques to reinstate the vocal verbal behavior of two individuals within the Anna State hospital that were described as “mute psychotics” (p. 8). More specifically, Isaacs et al. provided an early example of shaping (see Chapter 10), in which the experimenters attempted to shape “the available behaviors into the desired form, capitalizing upon both the variability and regularity of successive behaviors” (p. 9). The reinforcer used during the shaping process was identified, somewhat serendipitously, through observing subtle changes in the participant’s behavior when gum happened to fall out of the experimenter’s pocket. Following careful application of operant conditioning techniques, both participants demonstrated rather robust language repertoires that generalized to other persons and contexts.

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Staats et al. (1962) published an article in the Journal of the Experimental Analysis of Behavior that evaluated the effectiveness of behavior analytic techniques to teach six 4-year-old children to read several words and then sentences. Specifically, the researchers compared the use of prompts and reinforcement to a no-reinforcement condition. The reinforcement condition consisted of delivering a variety of tangible reinforcers contingent upon an appropriate response. The no-reinforcement condition consisted of praise (which had been determined to not function as a reinforcer, e.g., “all right,” “good,” “fine”) contingent upon an appropriate response. All six participants performed better and learned more in the reinforcement condition when compared to the no-reinforcement condition. This study provided early evidence that behavior analytic techniques are effective when teaching language skills and addressed some of the criticisms for using “extrinsic” reinforcers when teaching language skills. Wolf et al. (1963) published a research article in Behaviour Research and Therapy which provided one of the first examples of an evaluation of the effectiveness of behavior analytic techniques when teaching autistic children.a This seminal study is commonly referred to as “the Dicky study” after the pseudonym used for the name of the participant. Dicky was a 3-year-old boy referred to by the researchers because an ophthalmologist predicted that Dicky would go blind if he did not start wearing glasses within 6 months. Wolf and colleagues (1963) demonstrated the effectiveness of a variety of behavior analytic techniques (e.g., extinction, time-out from positive reinforcement, shaping) to increase Dicky’s glasses wearing and improving his language skills as well as reducing a variety of undesired behaviors (e.g., tantrums, bedtimes problems, throwing glasses). In a postintervention followup, his mother reported to the researchers that “six months after the child’s return home, Dicky continues to wear his glasses, does not have tantrums, has no sleeping problems, is becoming increasingly verbal, and is a new source of joy to the members of his family” (Wolf et al., 1963, p. 312). Many of the early works credited with the development of ABA, including those sampled here, have some common themes. First, they were problem oriented. When presented with a problem they went to the science of behavior analysis to see how the problem could be remedied. Behavior a

The authors recognize that there are varied preferences and conventions related to personand identify-first language among the academic and autistic communities. The terminology selected for use in this book (e.g., “autistic children”) is based on grammar and stylistic needs and does not reflect a particular terminological intent.

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analysis, and the principles thereof, was their compass, and it led them to substantial outcomes. Second, there was a focus on the analysis of behavior and environmental variables. These early pioneers did not have a wealth of resources and research to lean on like the behavior analysts of today. They were forced to evaluate and analyze the behavior of their participants in the moment. In doing so, they applied the principles of behavior analysis and manipulated contingencies which led to many demonstrations of novel applications of behavior analytic techniques (see Leaf et al., 2018).

Other seminal research and publications Lovaas et al. (1973), published in the Journal of Applied Behavior Analysis, provided one of the first evaluations of comprehensive behavioral intervention for 20 individuals diagnosed with ASD between 3 and 10 years of age. The comprehensive behavioral intervention involved the use of discrete trial teaching, shaping, and differential reinforcement. Some of the parents of the children who participated were trained to implement behavioral intervention in the later stages of the study. Lovaas and colleagues evaluated progress across multiple behavioral measures and standardized assessments. The results demonstrated that the comprehensive behavioral intervention was effective, and that continued improvement was observed for those participants whose parents received training, while participants who returned to state hospitals regressed. They also found that younger children tended to have better outcomes. Iwata et al. (1982), published in the Analysis and Intervention in Developmental Disabilities, provided the first formal development and evaluation of a standardized protocol to analyze the possible functions of problem behavior, the standard functional analysis (SFA). It is important to note, however, that there are many examples of early research related to functional relationships with respect to problem behavior (e.g., Carr et al., 1976; Ferster, 1964; Lovaas et al., 1965). Iwata et al. (1982) used a multielement experimental design to expose participants to four different conditions that involved manipulating antecedent and consequent events to determine if these conditions evoked self-injurious behavior (SIB). The presence of a positive reinforcement contingency was evaluated by having the interventionist sit away from the individual in a room and act busy. Attention in the form of social disapproval (e.g., "Don’t do that!") was only provided contingent on the occurrence of SIB. The presence of a negative reinforcement contingency was evaluated by delivering demands which were discontinued contingent

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on the occurrence of SIB. The presence of an automatic reinforcement contingency was evaluated by putting the participants in a barren environment, with no social attention, edibles, or tangibles. Finally, a control condition occurred in which Iwata et al. provided noncontingent attention, placed no demands, and presented enrichment materials. The results demonstrated that SIB was correlated mainly with a single condition which varied across the participants. Iwata and colleagues (1982) concluded that the use of an SFA to identify the probable function of problem behavior could help inform the choice of intervention strategy and be more useful than applying and arbitrary interventions. Lovaas (1987), published in the Journal of Consulting and Clinical Psychology, extended the findings of Lovaas et al. (1973) and is perhaps the most cited behavioral research for autistic individuals. Lovaas compared an intensive model of behavioral intervention (i.e., an average of 40 h of direct behavioral intervention per week) to a nonintensive (i.e., an average of 10 h of direct intervention per week) eclectic model with 38 children diagnosed with autism. The children were quasirandomly assigned into the two treatment groups (i.e., it was deemed unethical to do pure random assignment since it seemed clear that intensive intervention would be superior, so the decision was based on the availability of the treatment team prior to contact) and each participant received 2 or more years of intervention. The outcomes were divided into three broad categories (i.e., “recovered,” “aphasic,” and “autistic/retarded”) based on IQ, school placement, and clinical evaluation. We refer to these outcomes as best, fair, and poor, respectively. The results revealed that 47%, 42%, and 10% in the intensive group reached best, fair, and poor outcome, respectively. This is in comparison to the nonintensive treatment group in which 0%, 42%, and 58% reached best, fair, and poor outcome, respectively. Van Houten et al. (1988) described “The Right to Effective Behavioral Treatment” in the Journal of Applied Behavior Analysis discussing ways that behavior analysts can be more compassionate, achieve better outcomes for clients, and implement quality intervention. Specifically, Van Houten and colleagues outlined six rights “to direct both the ethical and appropriate application of behavioral treatment” (p. 381). These six rights were: (a) the right to a therapeutic environment, (b) the right to services whose overriding goal is personal welfare, (c) the right to treatment by a competent behavior analyst, (d) the right to programs that teach functional skills, (e) the right to behavioral assessment and ongoing evaluation, and (f ) the right to the most effective treatment procedures available.

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Bannerman et al. (1990), published in the Journal of Applied Behavior Analysis, challenged the field of behavior analysis and behavioral treatment to consider the balance between the right to habilitation and the right to personal liberties (sometimes referred to as the “doughnut paper”). In particular, Bannerman et al. (1990) discussed ways in which personal liberties could be compromised by service providers in the name of habilitation and provided several suggestions for ways in which choice can be integrated into the habilitation process to decrease the likelihood of compromising personal liberties. These suggestions included: (a) teaching independent living skills and other adaptive behaviors that the client prefers, (b) ensuring clients have input in the decisions related to the targeted skills and the way in which they are targeted, (c) teaching clients how to make choices, and (d) giving clients opportunities to make choices across settings and activities.

Recent events Certification The founding of ABA as a practice has created a burgeoning field, partially sparked by the application of behavior analytic techniques for autistic individuals. There are now thousands of certified behavior analysts and countless others that practice and apply the principles of ABA across a wide population of individuals (Behavior Analyst Certification Board, n.d.). As a result, there have been efforts to ensure consumers of behavior analytic techniques are protected (e.g., Leaf et al., 2017, 2021). Perhaps the best known and widely spread effort was the development of the Behavior Analyst Certification Board (BACB). The mission of the BACB is to “protect consumers of behavior analysis services worldwide by systematically establishing, promoting, and disseminating professional standards” (Behavior Analyst Certification Board, 2020, Mission and Vision). As of April 3, 2023 the BACB had certified 61,337 Board Certified Behavior Analysts (BCBAs), 5520 Board Certified Assistant Behavior Analysts (BCaBAs), and 136,113 Registered Behavior Technicians (RBTs; Behavior Analyst Certification Board, n.d.) for a total of 202,970 certified individuals. There have been several examples of professional discourse related to certification within the practice wing of our field. The concerns typically discussed within this discourse includes, but is not limited to, what determines if a person is qualified, how many training hours are sufficient, the skills that should be trained and tested, and how to assess competency (Carr et al., 2017; Eikeseth, 2010; Ellis & Glenn, 1995; Leaf et al., 2017,

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2021; Moore & Shook, 2001). Discourse like this is not a sign of fractures in the field of ABA; rather, it is an example of a field that is reflective and corrective like any science should be and is always progressing. However, it should be noted that some of the concerns that have been raised are related to the aforementioned commonalities in the early research. That is, some are concerned we have moved too far away from discovery and analysis, and instead are much more prescriptive and protocol driven than we once were (Leaf et al., 2017, 2021). These concerns have led to the development of new certifications such as the International Behavior Analysis Organization and the Progressive Behavior Analyst Autism Council.

Equity The reader may have noticed at this point that many of the researchers and behavior analysts referenced up to this point are not representative of the field at large. The discussion of underrepresentation and inequality within our science is not a new topic (e.g., Poling et al., 1983). In fact, when asked about a list of pioneers in behavior analysis, Baer was quoted replying, “Your list reflects an even more sexist field than it was at the time; the women were there, but mainly were ignored” (Wesolowski, 2002, p. 146). While this may not be a new topic, at least as it relates to the representation of women in behavior analysis, it has gained, rightfully, more attention within the recent literature. Nosik et al. (2019) updated Poling et al.’s (1983) analysis of women’s representation in behavior analysis. Specifically, Nosik and colleagues evaluated the representation of women across “ABAI fellows, professional awards, leadership roles, invited presentation speakers, editorial board appointments to behavior-analytic journals, authorship in behavior-analytic journals, new faculty hires at ABAI-accredited training programs, and behavior-analyst certification” (p. 214). Nosik and colleagues found more representation of women in the categories of analysis associated with earlier stages in a career and much less representation by women in milestones occurring later in a career. Based on these results, Nosik et al. predicted that individuals from the earlier career categories would begin to appear in later career categories, which would result in an increase in women’s representation over time. Overall, while progress has been made, it is likely that contingencies within the discipline continue to create barriers to the representation and advancement of some women.

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The discussion of equity and diversity has also extended beyond gender and sex. For example, Fong et al. (2016) provided a discussion of strategies for understanding the cultural contingencies for behavior analysts and their clients, integrating cultural awareness practices into service delivery, supervision, and professional development, and developing cultural awareness within practice. Miller et al. (2019) further extended the discussion of equity and diversity in behavior analysis. Specifically, Miller and colleagues examined issues of colonial hegemony in behavior analytic leadership (i.e., Caucasian, male, and Western), commodification of practice, a focus on internal validity, and dominant cultural norms determining the goals of intervention. Ultimately, these issues create both tensions and possibilities for behavior analysts to “evolve their practice at both the individual and organizational levels commensurate with the developments in other fields and society as a whole” (Miller et al., 2019, p. 26).

A progressive approach Leaf et al. (2016) provided a discussion highlighting the spirit and method of science involved in ABA that should be maintained to ensure ABA, as a science, continues to progress. Part of the impetus for the article was concerns about a loss of analysis in ABA, meaning the field drifting away from analysis of continually fluctuating environment-behavior relations and becoming more reliant on a set of unvarying rules. While this progressive approach to ABA was discussed in the context of behaviorally-based interventions for individuals diagnosed with ASD, the tenets could be extended to ABA as a whole. Much of Leaf and colleagues’ emphasis was in the training of behavior analysts and the essential repertoires needed to ensure the continued progression of the field. Specifically Leaf and colleague stated that, Appropriately trained behavior interventionists are truly analysts; rather than merely carrying out a protocol, they must analyze behavior and environment interactions moment by moment (Shook et al., 2002). Analysts take into account critical learning variables, such as the child’s current motivation, responsiveness, and behaviors that may signal emotional states and contingencies (Leaf & McEachin, 1999). They assess the current functions of behavior and determine if disruptive behaviors are potentially operant or respondent. They identify the optimal shaping and prompting strategies based upon past and present performance as well as the importance and difficulty of the tasks (Green, 2010; Soluaga et al., 2008). Critical factors also include the child’s nonverbal behaviors (e.g., facial expressions and body language) and the child’s physical state. In effect, during intervention they are shaped by clear goal specification, knowledge of principles, scientific method, and current environmental contingencies, instead of rigid adherence to

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unresponsive protocols. They are able to achieve more rapid change in behavior by following the intent of the protocol rather than being bound to the letter of the protocol (p. 721).

The present book is designed with this progressive approach to ABA at its heart. There is a strong emphasis on knowledge of principles of behavior, relevant environmental variables, and analysis-informed interventions.

Summary Although ABA may be considered a young science and field to some, it has a rich and interesting history. While this book’s focus will be on the application of ABA-based techniques, methods, and interventions for autistic individuals, it is important to note that methodologies born from ABA have been applied in many areas such as, but not limited to, sports (e.g., Luiselli & Reed, 2011; Tai & Miltenberger, 2017), addiction (e.g., Silverman et al., 2008), human safety (e.g., Dickson & Vargo, 2017; Geller, 2005), space travel (e.g., Brady, 2007), gerontology (e.g., Dwyer-Moore & Dixon, 2007), juvenile delinquency (e.g., Serna et al., 1986), education (e.g., Keller, 1968), healthcare (e.g., Friman et al., 1986), counseling (e.g., Patterson & Fleischman, 1979), and sustainability (e.g., Bekker et al., 2010). In each area that the philosophy and the methodologies of ABA have been applied, substantial improvement has been accomplished. Knowledge of the history of ABA could help to develop more effective behavior analytic repertoires. This knowledge could inform analyses, the development of new and novel procedures, the avoidance of dated and less effective procedures, and the continued progression of the field. The content of the chapters within this book is representative of our history and continued progression.

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Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. https://doi.org/ 10.1901/jaba.1968.1-91. Baer, D. M., Wolf, M. M., & Risley, T. R. (1987). Some still-current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 20(4), 313–327. https://doi.org/ 10.1901/jaba.1987.20.313. Bannerman, D. J., Sheldon, J. B., Sherman, J. A., & Harchik, A. E. (1990). Balancing the right to habilitation with the right to personal liberties: The rights of people with developmental disabilities to eat too many doughnuts and take a nap. Journal of Applied Behavior Analysis, 23(1), 79–89. https://doi.org/10.1901/jaba.1990.23-79. Behavior Analyst Certification Board. (2020). About the BACB. Retrieved from https:// www.bacb.com/about/. Behavior Analyst Certification Board. (n.d.). BACB certificant data. Retrieved from https:// www.bacb.com/BACB-certificant-data. Bekker, M. J., Cumming, T. D., Osborne, N. K. P., Bruining, A. M., McClean, J. I., & Leland, L. S. (2010). Encouraging electricity savings in a university residential hall through a combination of feedback, visual prompts, and incentives. Journal of Applied Behavior Analysis, 43(2), 327–331. https://doi.org/10.1901/jaba.2010.43-327. Brady, J. V. (2007). Behavior analysis in the space age. The Behavior Analyst Today, 8(4), 398–412. https://doi.org/10.1037/h0100640. Carr, E. G., Newsom, C. D., & Binkoff, J. A. (1976). Stimulus control of self-destructive behavior in a psychotic child. Journal of Abnormal Child Psychology, 4(2), 139–153. https://doi.org/10.1007/BF00916518. Carr, J. E., Nosik, M. R., & DeLeon, I. G. (2017). The registered behavior technician credential: A response to Leaf et al. (2017). Behavior Analysis in Practice, 10(2), 164–166. https://doi.org/10.1007/s40617-017-0172-1. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Dickson, M. J., & Vargo, K. K. (2017). Training kindergarten students lockdown drill procedures using behavioral skills training. Journal of Applied Behavior Analysis, 50(2), 407–412. https://doi.org/10.1002/jaba.369. Dwyer-Moore, K. J., & Dixon, M. R. (2007). Functional analysis and treatment of problem behavior of elderly adults in long-term care. Journal of Applied Behavior Analysis, 40(4), 679–683. https://doi.org/10.1901/jaba.2007.679-683. Eikeseth, S. (2010). Examination of qualifications required of an EIBI professional. European Journal of Behavior Analysis, 11(2), 239–246. https://doi.org/ 10.1080/15021149.2010.11434348. Ellis, J., & Glenn, S. S. (1995). Behavior-analytic repertoires: Where will they come from and how can they be maintained? The Behavior Analyst Today, 18(2), 285–292. https://doi. org/10.1007/BF03392715. Etzel, B. C., & Gewirtz, J. L. (1967). Experimental modification of caretaker-maintained high-rate operant crying in a 6- and a 20-week-old infant (Infans tyrannotearus): Extinction of crying with reinforcement of eye contact and smiling. Journal of Experimental Child Psychology, 5(3), 303–317. https://doi.org/10.1016/0022-0965(67)90058-6. Ferster, C. B. (1964). Reinforcement and punishment in the control of human behavior by social agencies. In Experiments in behaviour therapy (pp. 189–206). New York, NY: Macmillan Co. Fong, E. H., Catagnus, R. M., Brodhead, M. T., Quigley, S., & Field, S. (2016). Developing the cultural awareness skills of behavior analysts. Behavior Analysis in Practice, 9(1), 84–94. https://doi.org/10.1007/s40617-016-0111-6. Friman, P. C., Finney, J. W., Glasscock, S. G., Weigel, J. W., & Christophersen, E. R. (1986). Testicular self-examination: Validation of a training strategy for early cancer

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detection. Journal of Applied Behavior Analysis, 19(1), 87–92. https://doi.org/10.1901/ jaba.1986.19-87. Geller, E. S. (2005). Behavior-based safety and occupational risk management. Behavior Modification, 29(3), 539–561. https://doi.org/10.1177/0145445504273287. Green, G. (2010). Training practitioners to evaluate evidence about interventions. European Journal of Behavior Analysis, 11(2), 223–228. https://doi.org/ 10.1080/15021149.2010.11434346. Isaacs, W., Thomas, J., & Goldiamond, I. (1960). Application of operant conditioning to reinstate verbal behavior in psychotics. Journal of Speech and Hearing Disorders, 25(1), 8–12. https://doi.org/10.1044/jshd.2501.08. Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1982). Toward a functional analysis of self-injury. Analysis and Intervention in Developmental Disabilities, 2(1), 3–20. https://doi.org/10.1016/0270-4684(82)90003-9. Keller, F. S. (1968). Good-bye, teacher …. Journal of Applied Behavior Analysis, 1(1), 79–89. https://doi.org/10.1901/jaba.1968.1-79. Leaf, R., Leaf, J. B., & McEachin, J. (2018). Clinical judgment. DRL Books. Leaf, J. B., Leaf, R., McEachin, J., Bondy, A., Cihon, J. H., Detrich, R., Eshleman, J., Ferguson, J. L., Foxx, R. M., Freeman, B. J., Gerhardt, P., Glenn, S. S., Miller, M., Milne, C. M., Mountjoy, T., Parker, T., Pritchard, J., Ross, R. K., Saunders, M. S., & Streff, T. (2021). The importance of professional discourse for the continual advancement of practice standards: The RBT® as a case in point. Journal of Autism and Developmental Disorders, 51(5), 1789–1801. https://doi.org/10.1007/ s10803-020-04631-z. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Ala’i-Rosales, S., Ross, R. K., Smith, T., & Weiss, M. J. (2016). Applied behavior analysis is a science and, therefore, progressive. Journal of Autism and Developmental Disorders, 46(2), 720–731. https://doi.org/ 10.1007/s10803-015-2591-6. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Smith, T., Harris, S. L., Freeman, B. J., Mountjoy, T., Parker, T., Streff, T., Volkmar, F. R., & Waks, A. (2017). Concerns about the Registered Behavior Technician™ in relation to effective autism intervention. Behavior Analysis in Practice, 10(2), 154–163. https://doi.org/10.1007/s40617-0160145-9. Leaf, R. B., & McEachin, J. J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. Different Roads to Learning. Lovaas, O. I. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55(1), 3–9. https://doi.org/10.1037//0022-006x.55.1.3. Lovaas, O. I., Freitag, G., Gold, V. J., & Kassorla, I. C. (1965). Experimental studies in childhood schizophrenia: Analysis of self-destructive behavior. Journal of Experimental Child Psychology, 2(1), 67–84. https://doi.org/10.1016/0022-0965(65)90016-0. Lovaas, O. I., Koegel, R., Simmons, J. Q., & Long, J. S. (1973). Some generalization and follow-up measures on autistic children in behavior therapy. Journal of Applied Behavior Analysis, 6(1), 131–165. https://doi.org/10.1901/jaba.1973.6-131. Luiselli, J. K., & Reed, D. D. (2011). Behavioral sport psychology: Evidenced-based approaches to performance enhancement. Springer. Michael, J. L. (1993). Historical antecedents of behavior analysis. In J. L. Michael (Ed.), Concepts and principles of behavior analysis (pp. 93–104). Association for Behavior Analysis. Miller, K. L., Cruz, A. R., & Ala’i-Rosales, S. (2019). Inherent tensions and possibilities: Behavior analysis and cultural responsiveness. Behavior and Social Issues, 28(1), 16–36. https://doi.org/10.1007/s42822-019-00010-1. Moore, J. (2008a). History of behaviorism and behavior analysis: 1800–1930. In J. Moore (Ed.), Conceptual foundations of radical behaviorism (pp. 15–36). Sloan Publishing.

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Moore, J. (2008b). History of behaviorism and behavior analysis: 1930–1980. In J. Moore (Ed.), Conceptual foundations of radical behaviorism (pp. 37–55). Sloan Publishing. Moore, J., & Shook, G. L. (2001). Certification, accreditation, and quality control in behavior analysis. The Behavior Analyst, 24(1), 45–55. https://doi.org/10.1007/BF03392018. Morris, E. K., Altus, D. E., & Smith, N. G. (2013). A study in the founding of applied behavior analysis through its publications. The Behavior Analyst Today, 36(1), 73–107. https:// doi.org/10.1007/BF03392293. Morris, E. K., Smith, N. G., & Altus, D. E. (2005). B. F. Skinner’s contributions to applied behavior analysis. The Behavior Analyst Today, 28(2), 99–131. https://doi.org/10.1007/ BF03392108. Morris, E. K., Todd, J. T., Midgley, B. D., Schneider, S. M., & Johnson, L. M. (1990). The history of behavior analysis: Some historiography and a bibliography. The Behavior Analyst Today, 13(2), 131–158. https://doi.org/10.1007/BF03392530. Nosik, M. R., Luke, M. M., & Carr, J. E. (2019). Representation of women in behavior analysis: An empirical analysis. Behavior Analysis: Research and Practice, 19(2), 213–221. https://doi.org/10.1037/bar0000118. Patterson, G. R., & Fleischman, M. J. (1979). Maintenance of treatment effects: Some considerations concerning family systems and follow-up data. Behavior Therapy, 10(2), 168–185. https://doi.org/10.1016/s0005-7894(79)80034-9. Poling, A., Grossett, D., Fulton, B., Roy, S., Beechler, S., & Wittkopp, C. J. (1983). Participation by women in behavior analysis. The Behavior Analyst Today, 6(2), 145–152. https://doi.org/10.1007/BF03392393. Pratchett, T. (2010). I shall wear midnight. Doubleday. Rachlin, H. (1970). Background. In H. Rachlin (Ed.), Introduction to modern behaviorism (pp. 1–56). W. H. Freeman and Co. Serna, L. A., Schumaker, J. B., Hazel, J. S., & Sheldon, J. B. (1986). Teaching reciprocal social skills to parents and their delinquent adolescents. Journal of Clinical Child Psychology, 15(1), 64–77. https://doi.org/10.1207/s15374424jccp1501_8. Sherman, J. A. (1963). Reinstatement of verbal behavior in a psychotic by reinforcement methods. Journal of Speech and Hearing Disorders, 28(4), 398–401. https://doi.org/ 10.1044/jshd.2804.398. Shook, G. L., Ala’i-Rosales, S., & Glenn, S. (2002). Training and certifying behavior analysts. Behavior Modification, 26(1), 27–48. https://doi.org/10.1177/0145445502026001003. Silverman, K., Roll, J. M., & Higgins, S. T. (2008). Introduction to the special issue on the behavior analysis and treatment of drug addiction. Journal of Applied Behavior Analysis, 41(4), 471–480. https://doi.org/10.1901/jaba.2008.41-471. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j. rasd.2008.03.005. Staats, A. W., Staats, C. K., Schutz, R. E., & Wolf, M. (1962). The conditioning of textual responses using “extrinsic” reinforcers. Journal of the Experimental Analysis of Behavior, 5(1), 33–40. https://doi.org/10.1901/jeab.1962.5-33. Tai, S. S. M., & Miltenberger, R. G. (2017). Evaluating behavioral skills training to teach safe tackling skills to youth football players. Journal of Applied Behavior Analysis, 50(4), 849–855. https://doi.org/10.1002/jaba.412. Van Houten, R., Axelrod, S., Bailey, J. S., Favell, J. E., Foxx, R. M., Iwata, B. A., & Lovaas, O. I. (1988). The right to effective behavioral treatment. Journal of Applied Behavior Analysis, 21(4), 381–384. https://doi.org/10.1901/jaba.1988.21-381. Wesolowski, M. D. (2002). Pioneer profiles: An interview with Don Baer. The Behavior Analyst Today, 25(2), 135–150. https://doi.org/10.1007/BF03392053.

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Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203. Wolf, M., Risley, T., & Mees, H. (1963). Application of operant conditioning procedures to the behaviour problems of an autistic child. Behaviour Research and Therapy, 1(2), 305–312. https://doi.org/10.1016/0005-7967(63)90045-7.

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CHAPTER 2

An overview and history of the Autism Partnership Method Contents First tenet: Clinical judgment Second tenet: Learner-centered Third tenet: Meaningful and functional curriculum Fourth tenet: Flexible procedures Fifth tenet: Working with the whole family Sixth tenet: Performance-based staff training Seventh tenet: Compassion The history of the APM References

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It seems logical and preferred that all interventionists implement behavioral intervention in a manner that best meets the needs of the learner with a high degree of quality and fidelity. Unfortunately, in our experience, this is not how behavioral intervention is provided for many autistic individuals around the world. Rather, there is a wide range of how behavioral intervention is implemented across providers, agencies, and interventionists. Some interventionists may implement behavioral interventions with rigid adherence to a protocol (e.g., Cowan et al., 2022; Grow & LeBlanc, 2013) while others may implement behavioral intervention because a behavior analytic procedure is part of intervention, but the procedures are implemented poorly. That is, there exists a continuum upon which behavioral interventions for autistic individuals are provided with rigid adherence to protocols and poor implementation toward one end and in-the-moment analysis and flexibility at the other end. We do not think it is the case that anyone gets into human services or autism intervention to provide inadequate care. Regrettably, many interventionists likely believe they are implementing quality intervention that is actually substandard, and the recipients of behavioral treatment are not making necessary or possible gains. This creates problems for the consumer when the term applied behavior analysis (ABA) is used to describe all A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00015-5

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behavioral interventions for autistic individuals. That is, one person’s ABA may differ greatly in terms of quality, compassion, and effectiveness from another’s. As such, we feel that it is imperative to describe the components of what constitutes quality behavioral intervention and provide a name for the type of quality behavioral intervention we have endeavored to provide over the past 40 years. We call this approach to autism intervention the Autism Partnership MethodSM (APMa). The main goal of the APM is to provide highly individualized quality behavioral intervention for autistic individuals while targeting meaningful and functional curriculum and ensuring generalization. To accomplish this goal, the interventionist must be well trained in the principles of behavior analysis, child development, clinical sensitivity, and autism spectrum disorder (ASD). Within the APM, the behavior analyst ensures that parents become knowledgeable about the needs of their child and have a solid and practical understanding of ABA. The APM is an approach that can and should be implemented in multiple settings including treatment centers, the home, the community, and school. There are many tenets that help define the APM, and what follows is a description of some of the current tenets of this approach. It is important to note the importance of the word some here. The science of behavior analysis and the methods informed by that science should be constantly evolving based on new discoveries. As such, the tenets discussed here should, and will, evolve over time.

First tenet: Clinical judgment Many behavior analysts may feel as though a term like clinical judgment is mentalistic, nonobjective, arbitrary, and, therefore, antithetical to behavior analysis. This could not be further from the truth. The term clinical judgment describes a decision-making model that was derived from the medical field that “combines scientific theory, personal experience, patient perspectives and other insights” (Redelmeier et al., 2001, p. 358). In the context of a progressive approach to ABA, clinical judgment is a skill set that involves analyzing several environmental and learner variables and making in-themoment decisions based on this analysis in the manner that best leads to a

We understand and acknowledge the problems that are associated with “branding” within behavioral interventions for autistic individuals. However, “ABA” is commonly used as a term to refer to all behavioral interventions for autistic individuals and we contend that those interventions do not often resemble quality, ABA-based interventions. As a result, it has become more necessary than ever to differentiate one “ABA” from the next.

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desired outcomes. This is akin to doctors, pilots, and chefs who make moment-by-moment decisions based on a plethora of factors. There are countless variables that an interventionist must analyze and respond to when using clinical judgment. For example, one variable for the interventionist to analyze is the learner’s nonverbal behavior. The interventionist should evaluate the learner’s expressions (e.g., smiling, frowning, eyebrows raised) and body language (e.g., slouching in seat, relaxed, tense). A second variable that an interventionist must analyze is the learner’s verbal behavior; what the learner is saying and how are they saying it (e.g., voice tone, volume). A well trained, quality interventionist constantly evaluates the learner’s nonverbal and verbal behavior to make decisions about whether and how to alter the procedure or curriculum being implemented. A third variable that an interventionist should analyze is the presence or absence of undesired behavior. The interventionist should attend to the topography of the undesired behavior (e.g., kicking, screaming, flopping, biting, head-banging, inattention). By evaluating the topography of the undesired behavior, the interventionist can assess if the behavior is dangerous (e.g., aggression, self-injurious behavior) or nondangerous (e.g., screaming, flopping to floor, inattention) which would inform how, and if, the interventionist responds. Simultaneously, the interventionist must determine the level to which the undesired behavior is interfering with the learning process or resulting in missed social opportunities. Further, the interventionist must continually assess why the behavior is occurring (i.e., the function). It is important to note that undesired behavior, just like desired behavior, is dynamic and often involves a confluence of functions that shift over shorter and longer time spans. As a result, one cannot solely rely on the results of a past standard functional analysis (e.g., Iwata et al., 1982) or functional behavioral assessment. Additionally, the interventionist should decide if the undesired behavior is primarily, or currently, operant or respondent. Each of these factors should help inform the best course of action of how to address the undesired behavior in-the-moment. A highly skilled interventionist can assess these factors in-the-moment and make immediate adjustments to an intervention plan to increase learner success and safety. A fourth variable an interventionist should continuously evaluate is the learner’s receptivity to learning. For instance, does the learner appear eager to be a part of the learning process (e.g., favorable affect, quickly responding, approaching the interventionist) or do they appear bored and disinterested (e.g., neutral or unfavorable affect, fleeting attending, slow to respond)? Has the learner been in a session all day and are they tired or is it just the

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beginning of the day? A learner’s receptivity may be very different in the morning versus after lunch or in the later afternoon. What is the learner’s current motivation to learn (e.g., are reinforcers easily identified and used)? Do I have items/activities that function as a reinforcer? Any learner’s receptivity to learning is likely to vary at some point due to a variety of variables, and the interventionist needs to constantly assess and adjust their intervention accordingly. This includes if the learner is engaged, motivated, and eager to learn in which case, the interventionist may increase the complexity of the skill being taught and continue to use the same teaching strategy to maximize learning. Fifth, the interventionist must assess the presence or absence of a learner’s learning-how-to-learn skills. Where and to what is the learner attending to during and in-between instructions (e.g., the interventionist, relevant materials, irrelevant materials)? Is the learner guarding reinforcing items or giving them back to the interventionist without engaging in undesired behavior? Can the learner sit comfortably in a manner that does not disrupt the learning process? Is the learner responsive to the current contingency? Can the learner articulate the contingency? Is the learner demonstrating skills related to waiting? Does the learner respond well to prompts? Is the learner engaged in the learning process? How well does the learner retain information? Does the learner have basic deductive reasoning (i.e., if it’s not A, then it’s B)? Continually assessing the presence or absence of learning-how-to-learn skills will help inform changes to the intervention process and if learning-howto-learn skills should be prioritized over other skills. Sixth, the interventionist must continually assess if and how many reinforcing items and activities they have that can be used during the intervention process. Just because a learner prefers an item, does not guarantee it will function as a reinforcer. Similarly, just because the outcome of a formal preference assessment identifies a possible reinforcer, it does not mean that the item will always function as a reinforcer. For example, it might be preferred with noncontingent access but what is the effect on behavior or performance when used contingently? Without identifying reinforcing items and activities, it becomes highly difficult, if not impossible, to change a learner’s behavior. As such, the interventionist should continually assess if behaviors are changing following the delivery of a putative reinforcer, how often potential reinforcers have been used, and the conditions under which one item or activity will or will not function as a reinforcer. Another variable that must be evaluated is the learner’s physical and emotional health. Relevant medical and psychological history may include

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previously diagnosed neurological issues, emotional trauma, or other comorbid diagnoses. Assessing the learner’s health should be an ongoing process that includes, but is not limited to, how they slept, if they ate a good breakfast, any body aliments (e.g., stomach pains or headaches), and other major events occurring at home (e.g., a new sibling in the family, social distancing or isolation, divorce). Each of these variables is likely to impact the learner within and across sessions and the interventionist should adjust their behavior accordingly. Finally, the interventionist must also track what occurs and does not occur through collecting constant objective data. This means that an interventionist must analyze what has occurred in previous sessions as well as what is occurring in the current session. The interventionist needs to decide whether to collect continuous data or use time sampling procedures and whether to use frequency, duration, or ratio data. Based on these objective data, the interventionist can determine if it is best to adjust the teaching or curriculum or if it is better to continue implementing the current procedures or curriculum. Each of the aforementioned variables affect the learning process and must be monitored by the interventionist at any given moment so that they can make any necessary changes to the intervention.

Second tenet: Learner-centered A second tenet of the APM is that the entire method is learner centered. This means that the selection of interventions, procedures, and curriculum are all in the best interest of the learner’s short- and long-term goals. The interventionist makes decisions that will maximize the learner’s progress and ensure that risks are minimized. This includes involving the learner in the decisionmaking process when possible and developing skills that empower and enhance choices and options. Interventions, procedures, and methods are all conducted with compassion and empathy to ensure that meaningful progress is being made.

Third tenet: Meaningful and functional curriculum A third tenet characteristic of the APM is that curriculum is meaningful, authentic, and functional. The goal of teaching curricular targets should be to teach skills that will have maximum impact for the learner, not only in the moment, but also in the long term. This means targeting the development of repertoires that promote independence, enhance the number of

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available options and choices, and result in the learner living their best life possible. Thus, it is important for an interventionist to always consider the “small picture” and “big picture” related to the learner’s goals. Said differently, will the skill be beneficial to the learner in a week? What about 20 years from now? As a result, interventionists do not follow any one curriculum or assessment. Rather, interventionists use a variety of curriculums and assessments to develop a more comprehensive and individualized plan for each learner. Even more importantly, interventionists create their own individualized programs, goals, and curriculum so the individual needs of the learner are being met.

Fourth tenet: Flexible procedures Throughout this book, we describe a variety of procedures (e.g., discrete trial teaching, teaching interaction procedure, shaping) which can be used to develop desired behavior and/or reduce undesired behavior. Often within the field of ABA, these procedures are implemented with the aid of a protocol that outlines steps, rules, and/or guidelines. Within a conventional approach to ABA-based intervention for autistic individuals, interventionists adhere to a narrow range of protocols, whether it is repeating the same instruction every time, following a single prompting protocol to a “t,” or collecting data using only one methodology. In these instances, the main source for the interventionist’s behavior is the protocol. Within the APM, however, the main source of control for the interventionist’s behavior is the learner’s behavior and other environmental variables. As such, interventionists have flexibility in how they implement the various procedures. This means the interventionist has more discretion in making a wide range of decisions including which behaviors to prioritize, when and how to prompt, and what level of reinforcement and which reinforcers to use, relying on their clinical judgment.

Fifth tenet: Working with the whole family A fifth tenet of the APM is working with the entire family, not just the learner diagnosed with ASD. The learner diagnosed with ASD is part of a whole family unit and the learner’s condition and intervention received impacts the entire family. As such, it is not uncommon within the APM that parents receive education and support, that siblings are part of sibling support groups, and the intervention, procedures, and goals are selected to be most

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appropriate for the whole family. This support is provided by behavior analysts, and from other professionals such as licensed psychologists and marriage and family therapists.

Sixth tenet: Performance-based staff training The sixth tenet of the APM is that staff receive extensive, ongoing, and performance-based supervision and training. This results in highly skilled staff who can implement quality intervention and teach meaningful skills. Training goes beyond the bare minimum required to obtain credentials and certifications for direct interventionists and supervisors. As such, training is not time-, but, rather, performance-based. Initial training continues until the interventionist can demonstrate implementation competently across several learners and contexts. This differs from continuing training until the interventionist can answer questions about implementation on a multiplechoice exam. Further, even when initial training is concluded, ongoing training and supervision continues to occur to ensure maintenance of the skill and the development of new skills. Every interventionist and supervisor continues to learn and develop their clinical skills. Thus, the learning process for an interventionist is never ending.

Seventh tenet: Compassion The final tenet of the APM that will be discussed here is compassion. While there has been a recent buzz and increase in discussions surrounding compassionate ABA, compassion has been a core tenet of the APM since its inception (see Leaf et al., 2023). Interventionists and supervisors are trained in the clinical components of empathy, unconditional positive regard, collaboration, and active listening. This training cultivates an understanding of the importance of developing a therapeutic alliance.

The history of the APM Although we have only recently titled this intervention approach as the APM (Leaf et al., 2020), the method has a history dating back to the early 1970s. The APM can be traced back to the UCLA Young Autism Project (Lovaas, 1981, 1987). It was here that Dr. Ivar Lovaas was applying the principles of behavior analysis to the treatment of autism. It was at the UCLA Young Autism Project that Lovaas demonstrated that comprehensive and

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intensive behavioral intervention can make life altering changes for autistic individuals and their families (Lovaas, 1987; McEachin et al., 1993). At the UCLA Young Autism Project was also where senior level staff of Autism Partnership and Autism Partnership Foundation (i.e., Ronald Leaf, John McEachin, Tracee Parker, Sandy Slater, Andi Waks) first started to work with autistic individuals. It was also where many important lessons were learned such as: (a) the importance of comprehensive training and comprehensive scope of treatment, (b) the importance of parental involvement, (c) the value of teamwork, (d) how to problem solve, (e) how to think critically when evaluating interventions, and (f ) flexibility within therapy. All these lessons greatly shaped what is now called the APM. Although the results of the UCLA Young Autism Project were groundbreaking, the findings did not result in widespread adoption of behavioral methods for treating autism. As such, the senior staff of the UCLA Young Autism Project, and who are now senior staff of Autism Partnership and/or the Autism Partnership Foundation, took what they learned from Ivar Lovaas and other mentors (e.g., Tony Cuvo, Nate Azrin, Roger Popin, Irv Maltzman) and applied it to different populations (e.g., Prader-Willi syndrome, ADHD, mood and anxiety disorder, intellectual impairment, schizophrenia, relationship issues). In the mid-1980s, previous senior staff of the UCLA Young Autism Project worked in group homes and community settings with adults diagnosed with ASD and other intellectual and developmental disabilities. It was working in these group homes, with all the legal and regulatory constraints (e.g., what can and cannot be used as a reinforcer), as well as working with adults (e.g., ethical rights, meaningful skills, long-term outcomes, self-advocacy) that helped shape the current goals and skills taught today in the APM and the procedures used to teach those skills. In addition to working in group homes and with adults, the former leaders of the UCLA Young Autism Project provided psychotherapy to neurotypical adults. It was here that they continued to learn how to connect with families, how to work effectively with families, and the daily stressors that families often face. It was these experiences that led to a bigger emphasis on compassionate care within the APM. In 1993, behavioral intervention for autism came back into favor, largely due to the book Let Me Hear Your Voice written by Catherine Maurice (Maurice, 1993). Maurice’s book brought knowledge of behavioral intervention to persons who did not have access to peer-reviewed literature and were unfamiliar with how to interpret scientific research. In 1994, Ronald Leaf and John McEachin opened Autism Partnership with the

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mission to provide quality behavioral intervention for autistic individuals and their families. In doing so, they worked collaboratively with parents in providing the best practices possible. Among the first people hired included Jon Rafuse, Lety Palos Rafuse, Rick Schroeder, Doris Soluaga, and Marlene Boehm Driscoll. Their initial training did not look anything like it does today. Much of the training occurred "in the trenches", much as it did in the pioneering days of ABA. People had to learn on the fly. It was an exciting time for Autism Partnership, as old procedures (e.g., discrete trial teaching, incidental teaching, prompting) were improved upon and even more flexible and new procedures (e.g., the teaching interaction procedure, Cool versus Not Cool, and social skills groups) were first implemented and developed. From 1994 to 2010, there was tremendous growth in the APM, even though it was not called the APM at the time. Rather, it was called either contemporary ABA (Prizant & Rubin, 1999) or a structured, yet flexible approach to ABA. It was during this time that procedures were under continual refinement and our first curriculum book was developed (i.e., A Work in Progress; Leaf & McEachin, 1999). It was during this time that we learned how to provide intervention across different settings including the home, clinic, community, and school. Autism Partnership started to implement new treatment methodologies such as intensive 1-week programs called Jumpstarts. We also started to recognize and describe the problems we saw in conventional ABA (e.g., Sense and Nonsense in Behavioral Treatment: It Has to Be Said, Leaf et al., 2008). It was during this time that we brought up the next wave of supervisors who helped shape the current iteration of the APM. Even more importantly, we were able to expand to other countries by opening international offices including Hong Kong, Singapore, Australia, Canada, and the United Kingdom. This helped us learn how the APM could be implemented and altered to meet the needs of different cultures. A major shift in this philosophy occurred starting in or around 2010. It was here that two major events occurred. First, a research team was formed at Autism Partnership Foundation. The team was heavily influenced by training that occurred at the University of Kansas and the University of North Texas through the mentorship of Dr. James Sherman, Dr. Jan Sheldon, and Dr. Shahla Ala’i. It was during this time that many of the procedures that were being implemented clinically throughout the years of Autism Partnership were beginning to be experimentally evaluated (e.g., Leaf et al., 2011, 2012). Research conducted at that time and since then have not only demonstrated that the method was effective, but that often it was

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more efficient than other approaches to ABA (e.g., Ferguson et al., 2022; Milne et al., 2022). Additionally, at this time a new wave of supervisors were being trained in how to be even more precise in their implementation of procedures. During this time, the research team started to disseminate the model through peer-reviewed papers, presentations, workshops, books, and book chapters. After a talk at Yale University, a seminal paper was written entitled “Applied Behavior Analysis is a Science and Therefore Progressive” (Leaf et al., 2016). It was in this paper that we laid out what constitutes our approach and labeled the model as a progressive approach to ABA. Unfortunately, professionals in the field claimed they were implementing a progressive approach to ABA when in fact they were not. They co-opted the term “progressive” to describe their approach even though narrowly defined protocols were often used, meaningful curriculum was not being taught, and clinical judgment was not used. As a result, we now call our approach to behavioral intervention the APM. By calling it the APM, it is our hope that we are better able to provide training, guidelines, and feedback regarding correct implementation of our philosophy in behavioral intervention.

References Cowan, L. S., Lerman, D. C., Berdeaux, K. L., Prell, A. H., & Chen, N. (2022). A decisionmaking tool for evaluating and selecting prompting strategies. Behavior Analysis in Practice. https://doi.org/10.1007/s40617-022-00722-8. Advance online publication. Ferguson, J. L., Cihon, J. H., Majeski, M. J., Milne, C. M., Leaf, J. B., McEachin, J., & Leaf, R. (2022). Toward efficiency and effectiveness: Comparing equivalence-based instruction to progressive discrete trial teaching. Behavior Analysis in Practice. https:// doi.org/10.1007/s40617-022-00687-8. Advance online publication. Grow, L., & LeBlanc, L. (2013). Teaching receptive language skills: Recommendations for instructors. Behavior Analysis in Practice, 6(1), 56–75. https://doi.org/10.1007/ BF03391791. Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1982). Toward a functional analysis of self-injury. Analysis and Intervention in Developmental Disabilities, 2(1), 3–20. https://doi.org/10.1016/0270-4684(82)90003-9. Leaf, R., Dayharsh, J., Rafuse, J., McEachin, J., & Leaf, J. B. (2023). The clinician’s toolbox: Rediscovering compassionate ABA. DRL Books. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Ala’i-Rosales, S., Ross, R. K., Smith, T., & Weiss, M. J. (2016). Applied behavior analysis is a science and, therefore, progressive. Journal of Autism and Developmental Disorders, 46(2), 720–731. https://doi.org/ 10.1007/s10803-015-2591-6. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, R., McEachin, J., & Taubman, M. (2008). Sense and nonsense in the behavioral treatment of autism: It has to be said. DRL Books.

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Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The Autism partnership method: Social skills groups. Different Roads to Learning. Leaf, R. B., Taubman, M. T., McEachin, J. J., Leaf, J. B., & Tsuji, K. H. (2011). A program description of a community-based intensive behavioral intervention program for individuals with autism spectrum disorders. Education and Treatment of Children, 34(2), 259–285. Leaf, J. B., Tsuji, K. H., Griggs, B., Edwards, A., Taubman, M., McEachin, J., Leaf, R., & Oppenheim-Leaf, M. L. (2012). Teaching social skills to children with autism using the cool versus not cool procedure. Education and Training in Autism and Developmental Disabilities, 47(2), 165–175. Lovaas, O. I. (1981). Teaching developmentally disabled children: The me book (1st ed.). Pro-Ed. Lovaas, O. I. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55(1), 3–9. https://doi.org/10.1037//0022-006x.55.1.3. Maurice, C. (1993). Let me hear your voice: A family’s triumph over autism. Ballantine Books. McEachin, J. J., Smith, T., & Lovaas, O. I. (1993). Long-term outcome for children with autism who received early intensive behavioral treatment. American Journal of Mental Retardation, 97(4), 359–372. Milne, C. M., Leaf, J. B., Weiss, M. J., Ferguson, J. L., Cihon, J. H., Lee, M. S., Leaf, R., & McEachin, J. (2022). A preliminary evaluation of conventional and progressive approaches of discrete trial teaching for teaching tact relations with children diagnosed with autism. Education and Treatment of Children. https://doi.org/10.1007/s43494-02200084-4. Advance online publication. Prizant, B. M., & Rubin, E. (1999). Contemporary issues in interventions for autism spectrum disorders: A commentary. Journal of the Association for Persons with Severe Handicaps, 24(3), 199–208. https://doi.org/10.2511/rpsd.24.3.199. Redelmeier, D. A., Ferris, L. E., Tu, J. V., Hux, J. E., & Schull, M. J. (2001). Problems for clinical judgement: Introducing cognitive psychology as one more basic science. Canadian Medical Association Journal, 164(3), 358–360.

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CHAPTER 3

Respondent and operant behavior Contents Reflexes and respondent behavior Respondent conditioning Operant behavior Operant conditioning Some important notes The respondent/operant distinction Operant prominence Response classes Summary References

30 30 32 33 33 33 34 34 35 35

The term behavior has several meanings across cultures and communities. Commonly, behavior or behaviors is used to describe undesired or challenging behavior (e.g., “Myles is having behaviors again,” “How are we going to fix Ezra’s behavior?”) and behave is typically used to describe desired behavior (e.g., “If you behave tonight, you can have some ice-cream on the way home,” “You better behave at the recital”). Within applied behavior analysis (ABA), however, behavior has a different meaning. It is a term used to describe anything an organism does across space and time that can be objectively measured. That is, the observable movement of any organism can be classified as behavior through a behavior analytic lens.a This is a rather broad definition of behavior and encompasses everything from crawling to talking and hugging to hitting. Through this lens, behavior comprises the movement of organisms that may be more desired (e.g., conversation) or less desired (e.g., aggression). Within behavior analysis, behavior is grounded in an assumption of determinism. This means that behavior is viewed as lawful and orderly and does not occur at random or without cause. Behavior is systematically a

It should be noted that some behaviors are observable to only the one engaging in the behavior. This does not put behavior outside of scope of behavior analysis, nor does it mean that unobservable, or covert, behavior is governed by laws any different from observable behavior.

A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00023-4

Copyright © 2024 Elsevier Inc. All rights reserved.

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correlated with other events that occur within our physical world. Decades of basic and applied research and clinical practice have resulted in evidence that behavior is influenced by events that occur before any specific response and events that occur after any specific response. This chapter provides a description of two categories of behavior and their controlling relations (i.e., respondent and operant behavior; but see Pear & Eldridge, 1984). It should be noted, however, that while it is often convenient to categorize behavior as respondent or operant, behavior commonly ebbs and flows within the nonexperimental world and the fine lines between respondent or operant are often blurred—a point discussed more later.

Reflexes and respondent behavior We all come into the world with a genetic predisposition to respond to particular stimuli without any prior learning (e.g., the sucking motion made by babies when the roof of their mouth is touched). This helps increase the likelihood of the survival of the individual organism as well as the species. These unlearned correlations between stimuli and responses are referred to as reflexes. For example, when something enters your eye (unconditioned stimulus), you blink (unconditioned response) and your eyes produce tears to clear out any debris; or when food (unconditioned stimulus) is presented, you salivate (unconditioned response). No special learning was required for these and other reflexes to occur. The response portion of a reflex is commonly referred to as respondent behavior. Respondent behavior refers to responses that are elicited, or induced, by stimuli that precede the response. No other special conditions (e.g., states of deprivation, reinforcement, punishment) or learning are necessary for the response to occur.

Respondent conditioning Reflexes on their own, like in the previous examples, have limited use when trying to account for everything we do (i.e., all human behavior). There is not a finite number of stimuli that elicit a finite number of responses. If this were the case, we would simply need to discover all possible stimuli and all possible reflexes to have a complete account of an organism’s behavior. Furthermore, some stimuli that have not previously elicited a response can come to elicit similar responses. This process is referred to as respondent conditioning (sometimes referred to as classical conditioning, associative conditioning, or Pavlovian conditioning). More specifically, respondent conditioning refers

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Table 1 Respondent behavior, conditioning, and extinction. Response/ process/outcome

Reflex Respondent conditioning (process) Respondent conditioning (outcome) Respondent extinction (process) Respondent extinction (outcome)

Stimulus

Response

Notes


!
!

Salivation (UR) Salivation (UR)

Unlearned Repeated pairings across trials


!

Salivation (CR)

Picture of food (CS)


!

Salivation (CR)

Food (US)


!

Salivation (UR)

Picture of food (NS)


!

No salivation

Food (US) Food (US) + picture of food (NS) Picture of food (CS)

Repeated presentation across trials

to a process in which previously neutral stimuli can come to elicit an unconditioned response (i.e., UR; see Table 1 for an example). While there is a plethora of literature related to respondent conditioning, Ivan Pavlov is most associated with respondent conditioning in popular media as well as the behavior analytic community. In a famous series of experiments, Pavlov (1927) demonstrated how previously neutral stimuli came to elicit salivation (i.e., conditioned response) following being paired with the presentation of food (i.e., unconditioned stimulus). To do this, Pavlov started a metronome just before presenting food to a dog. Initially, the metronome failed to elicit salivation (i.e., a neutral stimulus). After presenting the sound of the metronome quickly followed by food across several trials, the dogs began salivating in response to the sound of the metronome alone (i.e., a now conditioned stimulus). In a more popularized example, Watson and Rayner (1920) described the conditioning and generalization of a fear response with a 9-month-old boy. This study is commonly referred to as the Little Albert study and is not without its misconceptions and lore within popular culture (e.g., Beck, 2009; Beck et al., 2009; Fridlund et al., 2012; Griggs, 2014; Harris, 1979, 2011). The definition of the fear response Watson and Rayner

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developed was individualized by observing Albert’s startle response when a steel bar was struck with a hammer. Prior to any conditioning, Albert was presented with a white rat, rabbit, dog, monkey, masks, and cotton to which Albert did not display any fear responses. To condition the fear response, the white rat was presented. When Albert reached toward the white rat, the steel bar was struck with the hammer making a loud noise. Following repeated pairings, Albert began to exhibit fear responses to the presence of the white rat alone. This fear response also generalized to other animals and items with shared features (e.g., rabbit, fur coat, mask with white fur). Watson and Rayner intended to uncondition the fear response developed within the experiment; however, Albert was withdrawn from the hospital before unconditioning could occur. Jones (1924) provided a follow-up to Watson and Rayner (1920), albeit with a different participant. Peter, the participant in the study, was a nearly 3-year-old boy who after conditioning exhibited similar fear responses to Watson and Rayner’s (1920) participant, Albert, in that “he was afraid of a white rat, and this fear extended to a rabbit, a fur coat, a feather, cotton wool, etc.” ( Jones, 1924, p. 309). The unconditioning process involved Peter and three other children coming to the laboratory for play time. The three children were selected because they did not demonstrate any fear responses to the rabbit. The planned sequence of extinction trials involved gradually increasing proximity to the rabbit which was initially in a cage and ending with allowing the rabbit to nibble his fingers. Following limited progress across the tolerance steps, counterconditioning was added by pairing the rabbit with presentation of one of Peter’s preferred foods. Peter’s fear response to the rabbit was then rapidly eliminated and the treatment effect also generalized to the other items.

Operant behavior While respondent behavior is controlled, or elicited, by a stimulus preceding the response, there is another class of behavior that is determined predominantly through its history of consequences. This type of behavior is referred to as operant behavior. For example, when a baby presses a button on a sound book, the book begins playing music. In other words, the baby is operating on the environment which creates changes in that environment, and the resulting environmental changes (i.e., consequences), affect the response in very important ways. For instance, if the occurrence of music increases or decreases the likelihood of button pressing, that behavior would be

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considered operant behavior. This differs from respondent behavior in that the book did not elicit the baby’s response, but, rather, set the occasion for the baby to reach for the book and press the button. That is, operant behavior is selected, shaped, and maintained by its consequences. Whereas respondent behavior has a one-to-one correspondence between stimulus and response, operant behavior does not. Instead, a stimulus preceding operant behavior alters the probability of a response but does not elicit it.

Operant conditioning Skinner (1935) first outlined the distinction between respondent and operant behavior in the peer-reviewed literature (see Konorski & Miller, 1937; Miller & Konorski, 1969), which has been expanded upon in theoretical and experimental articles. Operant conditioning, unlike respondent conditioning, refers to a process by which the consequences of operant behavior affect the probability of similar responses occurring in the future. Within operant conditioning, operant behavior can be affected by two classes of consequences: reinforcement and punishment (see Chapters 5 and 6 for a more in-depth discussion). If a consequence increases the likelihood of similar responses in similar situations, that consequence is said to be reinforcing. For example, if the baby in the previous example is more likely to press buttons on books, then the resulting music is considered reinforcing. If a consequence decreases the likelihood of similar responses in similar situations, that consequence is said to be punishing. For example, if the baby in the previous example is less likely to press buttons on books, then the music playing is considered punishing.

Some important notes The respondent/operant distinction As previously noted, it is sometimes convenient to separate behavior as respondent or operant. However, the fluid nature of behavior, particularly outside of the experimental environment, makes the line between respondent and operant blurry (see Keenan, 2017). For example, food has been well documented to elicit a salivary response. The delivery of a cookie (i.e., a food) contingent upon the vocal response “cookie” may increase the likelihood of similar responses in the future, which would be classified as reinforcement of an operant behavior. However, the consumption of the cookie, or merely the presentation of the cookie, may elicit a salivary

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response, which would be classified as respondent behavior. The parallel occurrence of respondent and operant processes can also be observed in the laboratory. For example, the delivery of food contingent upon a rat pressing a lever may increase the likelihood of similar responses in the future, which would be classified as reinforcement of an operant behavior. However, the consumption of the food, or merely the presentation of the food, may elicit a salivary response in the rat, which would be classified as respondent behavior. This is not to imply that lever pressing by a rat or a child vocally stating “cookie” is respondent behavior. Rather, it is meant to illustrate the importance of considering both classes of behavior within our analyses.

Operant prominence Within the ABA literature, particularly related to autism intervention, there has been a large focus primarily on operant behavior and processes. However, respondent behavior is also needed to provide a full account for all behavior and should be considered within functional assessments of behavior (in-the-moment or otherwise). Within a progressive approach to ABA for autistic individuals, assessment of whether a particular response or class of responses is operant or respondent plays a large role. This is an important inclusion because, as previously stated, the processes of respondent and operant conditioning differ. As such, the methods used during intervention for autistic individuals should differ based on the type of target behavior. Furthermore, it is likely that reflexive and respondent behavior plays a role when we are assessing emotions and emotional behavior (Friman et al., 1998). As such, avoiding what may be considered operant bigotry (Leaf & McEachin, 2016) and routinely considering both respondent and operant processes will result in practitioners capturing the full range of environmental variables in a way that is more conceptually systematic (Baer et al., 1968) with ABA than other, alternative approaches (Cihon et al., 2022).

Response classes Respondent and operant analyses of behavior represent a correlation of stimulus classes and response classes (Skinner, 1931). A stimulus class refers to a group of stimuli that occasion similar responses. For example, pictures of a Labrador Retriever, German Shepherd, Golden Retriever, Bulldog, and Beagle may all occasion the response “dog.” A response class refers to a group of responses that all result in the same consequence. For example, opening

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the refrigerator and grabbing a beer, asking someone to hand you a beer, and going to the store and buying a beer all result in the same outcome (i.e., getting a beer) and, therefore, comprise a response class. Said differently, there is not a one-to-one correspondence between a stimulus and a response. No one response is exactly the same as previous responses. This can be illustrated with an example as simple as opening a door. There is a myriad of ways in which the door can be opened. With the left hand, right hand, left foot, right foot, elbow, the hook of an umbrella, pushing with a shoulder, leaning with your back, etc. All these ways in which the door can be opened would be considered a class of behavior related to opening the door. When operant conditioning occurs, the entire response class is strengthened, not just a particular member of that class of responses (i.e., all methods to open the door have an increased likelihood of occurring in the future).

Summary Human behavior is complex. However, decades of basic and applied research and clinical practice have demonstrated a parsimonious explanation for human behavior. Behavior is a product of its circumstances. Some behavior is controlled mainly through events that precede it (i.e., reflexive or respondent behavior), while other behavior is controlled mainly through contingent events that follow it (i.e., operant behavior). This objective and eloquently simple explanation for behavior has permitted the development of a natural science of behavior. This science has paved the way for behavioral technologies that have been applied wherever people behave including, but not limited to, sports (e.g., Luiselli et al., 2011; Tai & Miltenberger, 2017), addiction (e.g., Silverman et al., 2008), human safety (e.g., Dickson & Vargo, 2017; Geller, 2005), space travel (e.g., Brady, 2007), gerontology (e.g., Dwyer-Moore & Dixon, 2007), juvenile delinquency (e.g., Serna et al., 1986), education (e.g., Keller, 1968), healthcare (e.g., Friman et al., 1986), and sustainability (e.g., Bekker et al., 2010).

References Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. https://doi.org/ 10.1901/jaba.1968.1-91. Beck, H. (2009). Finding little Albert: Reports on a seven-year search for psychology’s lost boy. American Psychologist, 64(7), 605–614.

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Beck, H. P., Levinson, S., & Irons, G. (2009). Finding little Albert: A journey to John B. Watson’s infant laboratory. American Psychologist, 64(7), 605–614. https://doi.org/ 10.1037/a0017234. Bekker, M. J., Cumming, T. D., Osborne, N. K. P., Bruining, A. M., McClean, J. I., & Leland, L. S. (2010). Encouraging electricity savings in a university residential hall through a combination of feedback, visual prompts, and incentives. Journal of Applied Behavior Analysis, 43(2), 327–331. https://doi.org/10.1901/jaba.2010.43-327. Brady, J. V. (2007). Behavior analysis in the space age. The Behavior Analyst Today, 8(4), 398–412. https://doi.org/10.1037/h0100640. Cihon, J. H., Schlinger, H. D., Ferguson, J. L., Leaf, J. B., & Milne, C. M. (2022). Is ACTraining behavior analytic? A review of Tarbox et al. (2020). Behavior Analysis in Practice. https://doi.org/10.1007/s40617-022-00680-1. Dickson, M. J., & Vargo, K. K. (2017). Training kindergarten students lockdown drill procedures using behavioral skills training. Journal of Applied Behavior Analysis, 50(2), 407–412. https://doi.org/10.1002/jaba.369. Dwyer-Moore, K. J., & Dixon, M. R. (2007). Functional analysis and treatment of problem behavior of elderly adults in long-term care. Journal of Applied Behavior Analysis, 40(4), 679–683. https://doi.org/10.1901/jaba.2007.679-683. Fridlund, A. J., Beck, H. P., Goldie, W. D., & Irons, G. (2012). Little Albert: A neurologically impaired child. History of Psychology, 15(4), 302–327. https://doi. org/10.1037/a0026720. Friman, P. C., Finney, J. W., Glasscock, S. G., Weigel, J. W., & Christophersen, E. R. (1986). Testicular self-examination: Validation of a training strategy for early cancer detection. Journal of Applied Behavior Analysis, 19(1), 87–92. https://doi.org/10.1901/ jaba.1986.19-87. Friman, P. C., Hayes, S. C., & Wilson, K. G. (1998). Why behavior analysts should study emotion: The example of anxiety. Journal of Applied Behavior Analysis, 31(1), 137–156. https://doi.org/10.1901/jaba.1998.31-137. Geller, E. S. (2005). Behavior-based safety and occupational risk management. Behavior Modification, 29(3), 539–561. https://doi.org/10.1177/0145445504273287. Griggs, R. A. (2014). The continuing saga of little albert in introductory psychology textbooks. Teaching of Psychology, 41(4), 309–317. https://doi.org/ 10.1177/0098628314549702. Harris, B. (1979). Whatever happened to little Albert? American Psychologist, 34(2), 151–160. https://doi.org/10.1037/0003-066x.34.2.151. Harris, B. (2011). Letting go of little Albert: Disciplinary memory, history, and the uses of myth. Journal of the History of the Behavioral Sciences, 47(1), 1–17. https://doi.org/ 10.1002/jhbs.20470. Jones, M. C. (1924). A laboratory study of fear: The case of Peter. Journal of Genetic Psychology, 31, 308–315. https://doi.org/10.1080/00221325.1991.9914707. Keenan, M. (2017). The fuzzy outline of an operant. The Behavior Analyst Today, 1, 1–5. https://doi.org/10.1007/s40614-017-0097-6. Keller, F. S. (1968). Good-bye, teacher …. Journal of Applied Behavior Analysis, 1(1), 79–89. https://doi.org/10.1901/jaba.1968.1-79. Konorski, J., & Miller, S. (1937). On two types of conditioned reflex. Journal of General Psychology, 16(1), 264–272. https://doi.org/10.1080/00221309.1937.9917950. Leaf, R., & McEachin, J. (2016). The Lovaas model: Love it or hate it, but first understand it. In R. G. Romanczyk, & J. McEachin (Eds.), Comprehensive models of autism spectrum disorder treatment (pp. 7–43). Springer. Luiselli, J. K., Woods, K. E., & Reed, D. D. (2011). Review of sports performance research with youth, collegiate, and elite athletes. Journal of Applied Behavior Analysis, 44(4), 999–1002. https://doi.org/10.1901/jaba.2011.44-999.

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Miller, S., & Konorski, J. (1969). On a particular form of conditioned reflex. Journal of the Experimental Analysis of Behavior, 12(1), 187–189. https://doi.org/10.1901/ jeab.1969.12-187. Pavlov, P. I. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex. Annals of Neurosciences, 17(3), 136–141. https://doi.org/10.5214/ ans.0972-7531.1017309. Pear, J. J., & Eldridge, G. D. (1984). The operant-respondent distinction: Future directions. Journal of the Experimental Analysis of Behavior, 42(3), 453–467. https://doi.org/10.1901/ jeab.1984.42-453. Serna, L. A., Schumaker, J. B., Hazel, J. S., & Sheldon, J. B. (1986). Teaching reciprocal social skills to parents and their delinquent adolescents. Journal of Clinical Child Psychology, 15(1), 64–77. https://doi.org/10.1207/s15374424jccp1501_8. Silverman, K., Roll, J. M., & Higgins, S. T. (2008). Introduction to the special issue on the behavior analysis and treatment of drug addiction. Journal of Applied Behavior Analysis, 41(4), 471–480. https://doi.org/10.1901/jaba.2008.41-471. Skinner, B. F. (1931). The concept of the reflex in the description of behavior. Journal of General Psychology, 5(4), 427–458. https://doi.org/10.1080/00221309.1931.9918416. Skinner, B. F. (1935). Two types of conditioned reflex and a pseudo type. Journal of General Psychology, 12(1), 66–77. https://doi.org/10.1080/00221309.1935.9920088. Tai, S. S. M., & Miltenberger, R. G. (2017). Evaluating behavioral skills training to teach safe tackling skills to youth football players. Journal of Applied Behavior Analysis, 50(4), 849–855. https://doi.org/10.1002/jaba.412. Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology, 3(1), 1–14. https://doi.org/10.1037/h0069608.

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CHAPTER 4

Stimulus control and generalization Contents Generalization Summary References

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What is the point of behavioral intervention? Do we teach children to share so they can share their toys with their therapists? No! Do we teach children to label pictures of superheroes so they can tact (i.e., label) correctly 100% of the time during the teaching session only? No! Do we work on decreasing self-injurious behavior so that learners no longer display this behavior only in the clinic? No! The entire point of behavioral intervention is that the learners can display the acquired skills across contexts and people. Most importantly, the goal is that the learners will display these new skills within their natural environment and the skills will lead to a higher quality of life. Therefore, with the aforementioned examples, we want children to share their toys with peers, be able to talk about superheroes with their friends, and to reduce their self-injurious behavior in all environments. For interventionists to meet this goal, they first need to understand the concept of stimulus control. When we respond differentially in two different conditions, it is referred to as stimulus control, discriminated responding, or a discriminated operant (Catania, 1998). All the stimuli that are present at the time a response is made come to have stimulus control over the response. This includes not only the instruction (e.g., “point to the apple”) but also the person who is giving the instruction, the specific apple that is displayed (e.g., whole red apple), and even the room where they are learning. Other stimuli that are not present (e.g., parents, a green apple cut in half, being outdoors) are not gaining stimulus control. The result is that the behavior is more likely to occur in the presence of one antecedent event as opposed to a different antecedent event (Cooper et al., 2020). The more times that reinforcement occurs with the same stimuli present, the greater the A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00005-2

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discrepancy becomes between stimuli that control the behavior and those that do not. For example, a learner may be more likely to share their toys with a familiar peer than with a child that they have never met. Stimulus control occurs when “the rate, latency, duration, and magnitude of a response is altered in the presence of an antecedent stimulus” (Cooper et al., 2020, p. 396). Thus, one of the goals of intervention is that the learner’s behavior comes under the control of the interventionist’s instruction and/or their environment. For example, one goal is for the learner to copy the interventionist’s behavior during a nonverbal imitation program or that the learner is responding when their parents ask questions. With respect to stimulus control, there are two basic types of discriminations: simple and conditional. A pure simple discrimination does not rely on contextual control of other conditions or stimuli and is in fact rare, even though it may appear that only a single stimulus is controlling a behavior (Cihon et al., 2023). Conditional discriminations are when behavior comes under the control of one stimulus when it is in the presence or context of another stimulus (Catania, 1998). For example, cooperation with requests may initially be established in the clinic, and because there is a specific context (i.e., the clinic setting), there may inadvertently be formed conditional discrimination such that requests only control behavior in the clinic and not in other settings. Such discrimination is undesirable and for the behavior to generalize to other settings, the behavior must also be practiced and reinforced in those settings. An example of a desirable conditional discrimination would be if during classroom instruction the learner responds to a question when their name is called (i.e., conditional discriminative stimulus) and does not respond when a peer’s name is called (i.e., conditional stimulus delta). With respect to academic tasks, conditional discrimination involves the simultaneous occurrence of two antecedent stimuli, both of which are required to be able to respond correctly. For example, if we show a picture of a dog to a child and ask, “What is this?” and the child learns to respond by saying, “Dog,” there are two antecedent stimuli operating: the question and the picture. However, until the child experiences the same picture combined with a different question (e.g., “What sound does this animal make?”) they may only have learned a simple discrimination because the question never varied. In other words, the response “dog” is only correct when the question is “What is this?” In fact, most stimulus-response associations that will be taught in an early intervention program will be conditional discriminations.

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In addition to the desire for our learners to develop conditional discriminations, generalization is also desired when teaching skills. Generalization is essentially the opposite of discrimination and means that a learner responds to stimuli that share similar features/properties with the original discriminative stimulus. If we are teaching the concept of dog to a child, we must make sure they will say “dog” when they see a dog, and not say “dog” when they see a cat. If we start with a picture of a brown cocker spaniel, we may have to also teach them that a white poodle and a black terrier are also dogs. In this case, we want to loosen the stimulus control to include the entire category of dogs, but not so much that they lose the distinction of dog versus cat. Similarly, when teaching a learner to expressively label pictures of Batman, stimulus generalization occurs if the learner states “Batman” when various versions of Batman are presented that differ from the version that was originally taught. We would like them to label all possible portrayals of the Batman character without having to be taught every single example. Many of the procedures (e.g., discrete trial teaching, differential reinforcement, shaping) that are described in this book are all ways that help develop desired instructional stimulus control and generalization. Those who have endorsed or described a conventional approach to behavioral intervention rely on certain widely adopted methods to achieve desired stimulus control and avoid undesired stimulus control (i.e., when the learner is responding to an antecedent stimulus that is irrelevant). Green (2001) described the then-current status of stimulus control procedures used in applied settings. Green outlined several recommendations of how to develop desired stimulus control within a match-to-sample task. These recommendations included: (1) the interventionist should use a different sample stimulus on each trial; (2) the comparison array contains at least three stimuli; (3) the target stimuli are presented an equivalent number of times during a teaching session; (4) a single target stimulus is never presented on two consecutive teaching trials; (5) the interventionist rotates the stimuli in the comparison array on each trial; (6) the interventionist requires the learner to make an observing response prior to an instruction; (7) the interventionist uses the simplest instruction possible (e.g., “ball” as opposed to “Where’s the ball?”); (8) the interventionist arranges the stimuli out-of-view of the learner; (9) teaching occurs using errorless learning procedures (e.g., most-to-least prompting, constant time-delay). Grow and LeBlanc (2013) reiterated and expanded upon Green’s recommendations (e.g., minimizing inadvertent cues and conduct formal preference assessments) when it came

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to teaching receptive labels for autistic individuals using practices based on off the stimulus control research. The recommendations provided by Green (2001) and Grow and LeBlanc (2013) were aimed at preventing faulty stimulus control, which is to say a learner’s response coming under the control of an irrelevant antecedent event. An example of this would be a learner responding to a receptive labeling task based on some irrelevant feature of the picture (e.g., blue background) versus the subject of the picture itself (e.g., a cow). Researchers have demonstrated that autistic individuals can engage in this type of overselectivity (Dube et al., 2016). Overselectivity is the narrowing of attention or attending to irrelevant features of a stimulus (Dube et al., 2016). We contend that describing this as faulty stimulus control is a misconception. As Cihon et al. (2023) stated “a better way to describe this relationship would be undesired stimulus control. That is, the conditional discrimination that was established is not the desired conditional discrimination of the interventionist” (p. 200). Unfortunately, what Green (2001) and Grow and LeBlanc (2013) meant to be general recommendations have resulted in rigid adherence to these recommendations as unvarying rules; a hallmark of what we describe as a conventional approach to applied behavior analysis (ABA). Fortunately, we now have more nuanced guidance from recent research using a progressive approach that has been shown to be more effective than rigid adherence to these recommendations (e.g., Milne et al., 2022). That is to say that a progressive approach can more effectively establish the desired stimulus control by directly countering ineffective learning strategies. For example, if it is observed that a learner is defaulting to a specific stimulus or location of a stimulus, the interventionist should ensure that the correct response never corresponds to the incorrect selection strategy of the learner. That is, if a learner consistently chooses the middle location when matching pictures in a field of three pictures on the table, the interventionist never puts the sample item in the middle location. The incorrect selection strategy will therefore never be reinforced. By contrast, a counterbalancing strategy that follows a predetermined protocol would allow the learner to contact reinforcement 33% of the time.

Generalization Generalization has always been a hallmark of ABA. In fact, Baer et al. (1968) listed it as one of the current dimensions of ABA. Baer and colleagues stated,

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“A behavioral change may be said to have generality if it proves durable over time, if it appears in a wide variety of possible environments, or if it spreads to a wide variety of related behaviors” (p. 96). Baer and colleagues also advocated that interventionists should not assume that generalization will automatically happen, stating “that generality is not automatically accomplished whenever behaviors change also needs occasional emphasis, especially in the evaluation of applied behavior analysis” (p. 96). Stokes and Baer (1977) conducted a review of the literature with respect to generalization in an attempt to help develop a technology of generalization. Stokes and Baer argued that interventionists need to explicitly program for generality: The frequent need for generalization of therapeutic behavior change is widely accepted, but it is not always realized that generalization does not automatically occur simply because of behavior change is accomplished. Thus, the need actively to program generalization, rather than passively to accept it as an outcome of certain training procedures, is a point requiring both emphasis and effective techniques (p. 350).

Stokes and Baer described seven ways in which generalization could be programmed, directly and indirectly. The first of those, “train and hope” is the one method they regarded as least likely to produce generalization because it is just teaching and hoping that generalization will occur without any planning. Within the Autism Partnership Method (APM), we recognize that the greatest likelihood that generalization will occur is via the other six methods. The second method described by Stokes and Baer is known as sequential modification. In sequential modification, the interventionist teaches one skill to mastery and continues to introduce skills sequentially until generalization occurs. For example, if a learner has mastered expressively labeling a picture of a specific dog (e.g., saying “dog” in the presence of a picture of a Golden Retriever) but cannot expressively label pictures of other dogs (e.g., Husky, Labrador Retriever, Yorkshire Terrier), then generalization has not occurred. Using sequential modification, the interventionist would introduce a new picture of a dog, until the learner generalizes the expressive label of “dog” to all dogs. A third method to promote generalization is to introduce naturally maintaining contingencies. This requires identifying the contingencies that occur in the environment in which the learner should engage in the targeted behavior and ensuring that targeted behavior will contact those contingencies in that environment. Sometimes this means gradually shifting the contingencies from the intervention environment (e.g., a token board), to the

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contingencies in the terminal environment (e.g., praise) and ultimately for the learner to be internally reinforced (e.g., by pride in their accomplishments). Sometimes this means teaching the learner to solicit reinforcement from others or ensuring the naturally occurring reinforcement occurs when they engage in the targeted behavior in the terminal environment. For example, when teaching a child to initiate play with a peer, the naturally maintaining contingency would be the peer agreeing to play. We may need to initially prompt the peer to agree to play following an initiation to ensure the learner contacts the naturally maintaining contingencies. A fourth method used to promote generalization is to train multiple exemplars. This method of programming for generalization involves continuing to present varied exemplars until generalization occurs (i.e., the learner can demonstrate correct responding on the first presentation of stimuli that have not been previously trained). This could involve introducing several different stimuli (e.g., several different pictures of dogs), several different contexts (e.g., training the same response in multiple rooms or locations), and/or several different responses. There is no magic formula for determining the number of exemplars that will be sufficient for generalization to occur (Stokes & Baer, 1977). The sufficient number of exemplars varies across learners and is affected by variables such as complexity of the skill and previous learning related to the skill. Knowing what extent of variation in teaching is necessary to ensure generalization requires clinical judgment and in-the-moment assessment. As such, this method of programming for generalization is commonly used within the APM. Another commonly used method of programming for generalization within the APM is to “train loosely.” Within training loosely, intervention occurs “with relatively little control over the stimuli presented and the correct responses allowed, so as to maximize sampling of relevant dimensions for transfer to other situations and other forms of the behavior” (Stokes & Baer, 1977, p. 357). This means, but is not limited to, using a variety of instructions, changing and rotating target and nontarget stimuli, and/or teaching in a variety of locations (e.g., outside, at the table, on the floor). With this description of training loosely, it could be rephrased as training with flexibility, and this is similar to how interventionists using the APM use clinical judgment and flexibility within each session. It should be noted, however, that training loosely or training with flexibility does not mean teaching randomly or without a plan. Rather, interventionists using a progressive approach develop a plan for teaching but adjust the timing to take full advantage of unplanned learning opportunities. Nevertheless, from the

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perspective of the learner, or an outside observer, the use of clinical judgment in the APM may appear random. The sixth method to program for generalization outlined by Stokes and Baer (1977) is to use indiscriminate contingencies. This method to program for generalization involves using intermittent schedules of reinforcement and punishment. Intermittent schedules commonly are more resistant to extinction (i.e., are more likely to continue to occur if reinforcement is not delivered for each response), and, therefore, may result in better generalization across people and contexts. The magic number token system (see Chapter 7; Cihon et al., 2019) that is commonly used within the APM takes advantage of this approach to programming for generalization. Within this token system, the earning requirement (i.e., the number of tokens required to exchange) remains unknown to the learner and the interventionist has the flexibility to change the number based on the learner’s responding. The final strategy described by Stokes and Baer (1977) is to program common stimuli. This method to program for generalization involves using materials within the teaching environment that share sufficient components with those that are present in the terminal environment. For example, if an interventionist is targeting responses to signs (e.g., restroom, stop, exit) they would use the actual signs (or signs that very closely resemble the actual signs) that occur in the learner’s environment. This would make it more likely the learner will respond to the actual signs when they are contacted in the learner’s environment. This is why, within the APM, we strive for intervention to occur within the learner’s naturally occurring environment, or the intervention environment is structured in a way to maximize similarity to the learner’s naturally occurring environment. In addition to the strategies outlined by Stokes and Baer (1977), there are at least three other methods to program for generalization that interventionists use when implementing the APM. First, like training sufficient exemplars, it is important that a variety of interventionists target the same skill. This way the learner must engage in the target behavior across interventionists which will increase the likelihood of generalization to novel people. Second, like training loosely, it is important to conduct sessions in different places and at different times. This way the learner must engage in the target behavior in different settings which will increase the likelihood of generalization in novel environments. Third, when teaching pro-social behaviors, interventionists implementing the APM systematically increase the provocativeness (or level of challenge) of the setting event. For example, when working on resisting peer pressure, the interventionist might start with a

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scenario that the learner may easily resist (e.g., asking them if they want a paperclip), but over time the scenarios will increase in their provocativeness making it more difficult to resist (e.g., asking them if they want to take some candy and eat it without the teacher knowing). Similarly, the interventionist should also systematically decrease the predictability of evocative events within and outside of teaching sessions.

Summary Using methods to develop the desired stimulus control and program for generalization are key components of ABA-based interventions for autistic individuals. The methods outlined here are likely to be most effective when used in combination with quality intervention. Rigid methods can lead to overly tight stimulus control which undermines generalization. Conversely, the APM makes use of flexible teaching methods such as training loosely with indiscriminate contingencies to promote the development of the desired stimulus control and generalization.

References Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. https://doi.org/ 10.1901/jaba.1968.1-91. Catania, A. C. (1998). Learning (4th ed.). Upper Saddle River, NJ: Prentice Hall. Cihon, J. H., Ferguson, J. L., & Leaf, J. B. (2023). Conditional discrimination: What’s in a name? In J. L. Matson (Ed.), Handbook of applied behavior analysis (pp. 197–210). Springer. https://doi.org/10.1007/978-3-031-19964-6_12. Cihon, J. H., Ferguson, J. L., Milne, C. M., Leaf, J. B., McEachin, J., & Leaf, R. (2019). A preliminary evaluation of a token system with a flexible earning requirement. Behavior Analysis in Practice, 12(3), 548–556. https://doi.org/10.1007/s40617-018-00316-3. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Dube, W. V., Farber, R. S., Mueller, M. R., Grant, E., Lorin, L., & Deutsch, C. K. (2016). Stimulus overselectivity in autism, down syndrome, and typical development. American Journal on Intellectual and Developmental Disabilities, 121(3), 219–235. https://doi.org/ 10.1352/1944-7558-121.3.219. Green, G. (2001). Behavior analytic instruction for learners with autism: Advances in stimulus control technology. Focus on Autism and Other Developmental Disabilities, 16(2), 72–85. https://doi.org/10.1177/108835760101600203. Grow, L., & LeBlanc, L. (2013). Teaching receptive language skills: Recommendations for instructors. Behavior Analysis in Practice, 6(1), 56–75. https://doi.org/10.1007/ BF03391791.

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Milne, C. M., Leaf, J. B., Weiss, M. J., Ferguson, J. L., Cihon, J. H., Lee, M. S., Leaf, R., & McEachin, J. (2022). A preliminary evaluation of conventional and progressive approaches of discrete trial teaching for teaching tact relations with children diagnosed with autism. Education and Treatment of Children, 45, 357–381. https://doi.org/10.1007/ s43494-022-00084-4. Stokes, T. F., & Baer, D. M. (1977). An implicit technology of generalization. Journal of Applied Behavior Analysis, 10(2), 349–367. https://doi.org/10.1901/jaba.1977.10-349.

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CHAPTER 5

Reinforcement: Overview, identification, conditioning Contents Reinforcer identification Formal preference assessments A progressive approach to reinforcer identification IMRA research Some considerations in identifying possible reinforcers Conditioning reinforcers Research examples Some considerations in conditioning reinforcers Summary References

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Reinforcement refers to any context in which a response is followed by an event (i.e., stimulus change) that results in an increase in the future probability of similar responses in similar situations. Positive reinforcement refers to contexts in which a response is followed immediately by a stimulus change that increases the future probability of similar responses in similar situations. Take, for example, a child saying “book” to their parents, which results in the parents giving the child the book. If this results in an increased probability of the child saying “book” in the future, this is an instance of positive reinforcement. Negative reinforcement refers to a context in which a response produces the termination, reduction, postponement, or avoidance of a stimulus/event, which increases the probability of similar responses in similar situations. For example, in the presence of a loud beeping from a malfunctioning fire alarm, one removes the battery which results in stopping the loud beeping. If this results in an increased probability of removing batteries when malfunctioning fire alarms are beeping loudly, this is an instance of negative reinforcement. Various terms and parts of speech are used in the context of reinforcement (see Cooper et al., 2020 for a more detailed description). Reinforcer, as a noun, refers to a stimulus or stimulus change that results in an increase A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00012-X

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in the probability of similar responses in similar situations. For example, “Tokens were used as a reinforcer for the child’s correct responses.” Reinforcing, as an adjective, refers to a property of a particular stimulus. For example, “The interventionist provided the reinforcing toy more often than nonreinforcing book.” Reinforcement, as a noun, can be used to describe an operation or a process. As an operation, reinforcement refers to the delivery of a consequence following a response. For example, “The schedule of reinforcement dictated that a token should be delivered after every correct response.” As a process, reinforcement refers to an increase in the probability of similar responses that results from reinforcement. For example, “The intervention clearly demonstrated reinforcement produced by nonsocial consequences.” To reinforce, as a verb, can also refer to an operation or a process. As an operation, to reinforce refers to the delivery of a consequence contingent upon a response. For example, “Tokens were used to reinforce correct responses.” As a process, to reinforce refers to an increase in the probability of similar responses that results from reinforcement. For example, “The intervention plan was designed to determine if tokens would reinforce correct responses.”

Reinforcer identification Identifying consequent events that may serve as effective reinforcers is an essential component of any applied behavior analysis (ABA)-based intervention for autistic individuals. For many individuals, including those with an autism diagnosis, simply asking, “What are some things you like?” can result in the identification of potential reinforcers. However, for many autistic individuals, asking, “What are some things you like?” may not be sufficient or effective due to limited language skills, interfering behaviors, and lack of comprehension or play skills (Pace et al., 1985). Furthermore, verbal reports are notorious for being inaccurate (Cooper et al., 2020; Howard & Dailey, 1979; Kazdin, 2011). Considerable effort has been made within behavior analytic literature and practice to develop and examine effective means to assess preference and identify potential reinforcers using formal preference assessments (Reid et al., 2003).

Formal preference assessments Formal preference assessments can be implemented directly and/or indirectly. Indirect assessments typically involve a parent or professional ranking items on a list based on the parent’s or professional’s knowledge of the individual and knowledge of the individual’s preference for the various items

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(e.g., Matson et al., 1999). Direct assessments involve a parent or professional directly observing the individual in their typical environment or in a setting where the availability of items is systematically manipulated. Several different direct preference assessments have been developed and experimentally evaluated such as single-stimulus (Pace et al., 1985), paired-stimulus (Fisher et al., 1992), multiple-stimulus (DeLeon & Iwata, 1996), and free-operant (Roane et al., 1998). Single-stimulus preference assessments involve presenting each stimulus separately and requiring the individual to emit a response to gain access to the item (Pace et al., 1985). Paired-stimulus preference assessments involve presenting the stimuli in pairs and requiring the individual to select one of the stimuli presented (Fisher et al., 1992). Multiple-stimulus preference assessments involve presenting multiple stimuli at the same time and requiring the individual to select one from an array (DeLeon & Iwata, 1996). Multiple-stimulus preference assessments can occur with and without replacing the item previously selected by the individual. Free-operant preference assessments commonly involve arranging the environment with multiple items available, instructing the individual they can “Go play” with anything, and measuring duration of engagement with the items rather than rate (Roane et al., 1998). Formal preference assessments are regularly implemented within many ABA-based clinical settings (Graff & Karsten, 2012). Graff and Karsten (2012) reported that the majority of behavior analysts who participated in a survey reported using a least one formal preference assessment published within the literature. Furthermore, 13.4% of those behavior analysts surveyed reported conducting a full-scale preference assessment at least once weekly (Graff & Karsten, 2012). Given the common use of formal preference assessments within the experimental and clinical settings, the use of formal preference assessments in traditional methods is viewed as the “gold standard” in identifying potentially reinforcing stimuli within intervention for autistic individuals.

A progressive approach to reinforcer identification While formal preference assessments are common within research and ABA-based interventions for autistic individuals, the aforementioned formal preference assessments are not the only means clinicians can use to identify potentially reinforcing stimuli. Within a progressive approach to ABA and the Autism Partnership Method for autistic individuals, potentially reinforcing

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items are commonly identified through in-the-moment reinforcer analysis (IMRA). Within IMRA, the interventionist assesses the client’s behavior and other relevant contextual variables, in the moment, to determine potential reinforcing items/events. These variables include, but are not limited to, the client’s affect, duration of engagement with the item/event, frequency of contact with the item/event, change in the targeted behavior, and similarities to other previously identified reinforcing items/events. The outcome of assessing each of these variables comes to control the interventionist’s behavior with respect to the selection of potentially reinforcing items. For example, if a client displays favorable affect while engaged with an item for a sustained period, the interventionist may be more likely to select that item to use contingent upon engagement in a desired behavior. Conversely, if a client displays neutral/negative affect while engaged with an item for a sustained period, the interventionist may be less likely to use that item contingent upon a targeted behavior (see Table 1 for more examples). Table 1 Some variables to assess within an in-the-moment reinforcer analysis and considerations based on the outcome of that assessment. Variable

Descriptor

Consideration

Affect

Negative/neutral

It is unlikely this item/event will function as a reinforcer It is likely this item/event will function as a reinforcer It is unlikely this item/event will function as a reinforcer It is likely this item/event will function as a reinforcer It is unlikely this item/event will function as a reinforcer It is likely this item/event will function as a reinforcer It is unlikely this item/event functions as a reinforcer

Positive Duration of engagement

Short/fleeting Sustained

Frequency of contact

Limited contact Frequent contact

Change in target behavior

Similarity to other reinforcing items/ events

Decrease in the likelihood of the behavior Increase in the likelihood of the behavior Not similar Very similar

It is likely this item/event functions as a reinforcer It is unlikely this item/event will function as a reinforcer It is likely this item/event will function as a reinforcer

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IMRA research Leaf, Leaf, et al. (2015) provided the first experimental evaluation of an IMRA. Specifically, Leaf, Leaf and colleagues evaluated the effectiveness and efficiency of an IMRA and a formal paired-stimulus preference assessment with three children diagnosed with ASD. Interviews were first conducted with the members of each participant’s clinical team to identify 10 items believed to be highly preferred. Two formal paired-stimulus preference assessments were conducted with the 10 items to identify the top three preferred items (i.e., the three items selected most frequently across the two assessments). During the paired-stimulus condition, these three items were evenly distributed across six trials (i.e., each item was available two times). In the IMRA condition, the interventionist did not have access to the results of the two formal paired-stimulus preference assessments but did have access to all 10 items. The interventionist relied on in-themoment assessment to determine the item to use on each trial. Across both conditions, the participants were required to sort colored tokens/chips. The contingent delivery of an item in both conditions was determined based on baseline performance. During the first paired-stimulus or IMRA session, participants were required to sort 20% more colored chips than their average during baseline. After every two consecutive sessions in which the participant reached the targeted number of chips, the targeted number of chips was increased by 20%. A third, control condition was included in which no items were available contingent upon sorting any number of chips. The results demonstrated little difference in the rate of responding across the two conditions, found that IMRA was more efficient, and that the interventionists in the IMRA condition selected items other than the top three identified by the two formal paired-stimulus preference assessments. Leaf et al. (2018) extended Leaf, Leaf, et al.’s (2015) findings when comparing the use of a formal paired-stimulus preference assessment to an IMRA to identify potential reinforcers to teach expressive labels with two preschool-aged children diagnosed with ASD. The methods used were similar to those used by Leaf, Leaf, et al. (2015); however, the delivery of a potential reinforcer was contingent upon accurate responses to the targeted expressive labels. One participant was taught the names of popular comic book characters, while the other participant was taught associations (e.g., Q: Who may live in a castle?; A: Queen). During the paired-stimulus condition, one of the top three preferred items (as identified during two

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paired-stimulus preference assessments) were provided contingent upon a correct response. The item delivered on each trial in which the child responded correctly was predetermined and semirandomized to ensure the items were evenly distributed across all trials. During the IMRA condition, the interventionist had access to the 10 items from the formal paired-stimulus preference assessments but did have access to the outcomes of those assessments. In this condition, in-the-moment assessment was used to determine which item to use when the child responded correctly on each trial. Leaf et al. (2018) obtained similar results to Leaf, Leaf, et al. (2015) in that the participants demonstrated skill acquisition across both conditions. This study also demonstrated that the IMRA condition was more efficient, and no noteworthy difference was found with respect to skill acquisition, responding, or maintenance. Alcalay et al. (2019) compared the relative effectiveness and efficiency of a multiple stimulus without replacement (MSWO) preference assessment to IMRA on the rate of sorting for four children diagnosed with ASD. Two MSWO preference assessments were used to evaluate the participants’ preferences among 10 items that were individualized for each participant. The three items with the highest average rank across the two MSWO preference assessments were used during the MSWO condition, while all 10 items were available for the interventionist during the IMRA condition. The participants were required to sort a specific number of colored tokens/chips, similar to the methods Leaf, Leaf, et al. (2015) outlined, across both conditions to access reinforcement. The three items used in the MSWO condition were evenly distributed across six trials. Within the IMRA condition, the interventionist had the flexibility to select any of the 10 items on each trial. The interventionists in the IMRA condition were also asked to provide or select from an array of rationales for the selection of a particular item on each trial. The results indicated minimal differences in the rate of responding for all four participants across both conditions and that conducting the MSWO preference assessments required a considerable amount of additional time when compared to using an IMRA. Furthermore, interventionists in the IMRA condition often reported that they were responding to multiple variables in-the-moment (i.e., affect, interaction, frequency, skill improvement, similar quality, and/or conditioning) when selecting an item to use contingently upon sorting and provided novelty and child request as written in rationales.

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Some considerations in identifying possible reinforcers Context Formal preference assessments often occur in environments outside an individuals’ typical learning environment. This can create challenges for practitioners as some have noted that some individuals with severe developmental disabilities may not generalize preferences from one setting to the next. This is not surprising as behavior analytic work has demonstrated that the conditions under which stimuli serve a specific function vary along several dimensions. Contextual variables certainly play a role in the assessment of potentially reinforcing stimuli. For instance, a crayon may not serve a reinforcing function without paper or a coloring book, and a skateboard may only serve a reinforcing function after the snow melts on the sidewalk in the winter. As such, one must consider “the conditions under which the items evaluated in the preference assessment will be available in the natural environment” (Kodak et al., 2009, p. 1075). That is, the environment in which a potentially preferred item is “consumed” may affect the relative preferred value of that item (Steinhilber & Johnson, 2007). For example, an individual’s preference for a basketball may not be best evaluated if it is “consumed” in the absence of the other aspects of basketball related stimuli (e.g., a team, a hoop). Also, items are often available concurrently in formal preference assessments (e.g., paired-stimulus preference assessments), and may not occur concurrently in the natural setting. More importantly, concurrent availability does not necessarily suggest the item not selected will not still function as a reinforcer (Alcalay et al., 2019; Leaf et al., 2018; Leaf, Leaf, et al., 2015). It is critical that when assessing preference, formally and informally, the stimuli are presented as similar to the way they occur in the natural environment as possible. Measures Direct assessments of preference typically involve selection, approach, or engagement-based measures. Selection and approach-based assessments involve the individual performing some response to gain access to the item or items (e.g., walking or reaching toward, looking at). Engagement-based assessments measure the duration an individual engages with the items assessed. Researchers and clinicians may have several reasons for selecting one measure over another. However, if “the purpose of preference

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assessments is to identify items that will function as reinforcers in the clinical or natural setting … consideration of the context in which the potential reinforcers will be used may [should] lead to different assessment decisions” (Steinhilber & Johnson, 2007, p. 772). Namely, the stimuli to be assessed should be instrumental in informing the measures rather than defaulting to a presumed “standard” method of assessment. Some items may be better assessed with engagement measures (e.g., video games, play sets) while others may be better assessed with selection-based measures (e.g., edible items, manipulatives). This underscores the importance of using different measures for different items (Kodak et al., 2009; Steinhilber & Johnson, 2007). In judging what measure might be the most suitable, one should exercise caution with the use of duration-based measures. While an individual may engage with an item or activity for long periods of time, that may not be indicative of relative reinforcing value (e.g., it may take longer to put together a puzzle than to watch a spinning light, eat some chocolate, or get hugs and tickles, but that does not necessarily indicate the puzzle is more reinforcing). As such, it is important to pay close attention to how the stimuli being assessed are used in the natural environment and select appropriate measures accordingly. Time Walsh (2008) in a presentation at the Association for Behavior Analysis Annual Autism Conference described her philosophy of “no second wasted.” The context was about not wasting time on unproven interventions (e.g., facilitated communication, dolphin therapy, Social Thinking). We think the philosophy applies equally to evaluating the implementation of our own procedures. Formal preference assessments may fall into this category. That is, the time spent conducting formal preference assessments could otherwise be used more effectively and efficiently. Leaf, Leaf, et al. (2015) noted that formal preference assessments required up to 49 min to complete. This is a large amount of time devoted to identifying items that can be used as potential reinforcers, especially when well-trained clinicians should be able to condition a large variety of items to become reinforcers. A similar concern is that the time spent accessing reinforcers during formal preference assessments is effectively burning up some of the precious reinforcement “fuel” without accomplishing any learning. A more “fuel conserving” approach would be to imbed the reinforcer evaluation within the teaching sessions at the precise time that a student is accessing reinforcement for accomplishing work. Therefore, it may be beneficial for the serial

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use of formal preference assessments within clinical settings be drastically reduced, if not eliminated completely, to provide more time for effective teaching.

Conditioning reinforcers The effectiveness of formal preference assessments to identify potential reinforcers should not lead clinicians to neglect the vast literature on conditioning various stimuli to serve as effective reinforcers. Autistic individuals often have limited interests and a limited pool of stimuli that function as reinforcers (American Psychiatric Association, 2013). Clinicians within progressive, comprehensive treatment programs should constantly strive to condition nonpreferred or neutral stimuli to function as reinforcers (Leaf, Leaf, et al., 2016). Conditioning reinforcers has always been an important concept discussed by behavior analysts (e.g., Skinner, 1953). Research has demonstrated the effectiveness of conditioning procedures to change a child’s preference by selecting a previously nonpreferred item over a previously preferred item (e.g., Cihon et al., 2021; Dozier et al., 2012; Greer & Singer-Dudek, 2008; Leaf et al., 2012).

Research examples Leaf et al. (2012) conducted two studies that examined the effects of observing an adult selecting and engaging with a less-preferred item in new and exciting ways on the preferences of three children diagnosed with ASD. A paired-stimulus preference with 10 items was conducted to determine the most and least preferred items for each of the participants. A preference assessment was also conducted to determine the participants’ most-preferred staff member. The participants were then required to place 10 small counting bears into a cup, following which they were offered a choice between the high-preferred item, low-preferred item, and a blank index card (which was used as a control measure and resulted in a 30 s without programmed reinforcement). The conditioning procedure consisted of observing the preferred staff member complete the same task and then selecting the participant’s low preferred item while stating how much they wanted to play with the item and playing with the item in novel and exciting ways. The results showed that the participants began to select the item they observed the preferred staff member select indicating that preferences can be altered based on the observational procedure.

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Leaf, Kassardjian, et al. (2015) replicated and extended the Leaf et al.’s (2012) results with a different participant demographic. Leaf, Kassardjian, et al. (2015) evaluated a similar observational procedure with four children diagnosed with ASD with IQ scores of 60 or below. The methods were similar to those described by Leaf et al. (2012). That is, an adult completed the same task but selected and interacted with the low preferred item which the participant observed. The way in which the adult interacted with the lowpreferred items was individualized for each participant. This commonly involved playing with the item in ways the participant played with other toys, pretending the item was a different toy the participant frequently played with, playing with the item in novel and diverse ways, and commenting on exciting ways to play with the item and how much fun they were having. The results indicated partial replication in that the observation procedure was effective in changing the preferences for three of the four participants. However, two of the participants required additional modifications (e.g., interacting with the participant during the observational procedure) for changes in preference to occur. Leaf et al. (2012) and Leaf, Kassardjian, et al. (2015) both involved shifting preferences within the same stimulus class (i.e., toys). Leaf, OppenheimLeaf, et al. (2016) examined the effectiveness of a similar observational procedure when shifting preferences from tangible to social activities (e.g., telling jokes, hungry chicken, fast high fives) with three children diagnosed with ASD. Additionally, Leaf, Oppenheim-Leaf, et al. (2016) also used a peer, rather than an adult, during the observational procedure. All three participants consistently selected the tangible item over the social activities prior to the observational procedure. Leaf, Oppenheim-Leaf, et al. (2016) yielded results similar to prior research (i.e., Leaf et al., 2012; Leaf, Kassardjian, et al., 2015), in that all three participants selected the social activity (i.e., low-preferred) following the observational learning procedure. Cihon et al. (2021) attempted to replicate and extend the prior research on the observational effects on preferences but with food, as opposed to tangible items or social activities. Specifically, Cihon et al. evaluated the effectiveness of an observational learning procedure on the selection and ingestion of food items with three children diagnosed with ASD. The methods were similar to previous research (i.e., Leaf et al., 2012; Leaf, Kassardjian, et al., 2015; Leaf, Oppenheim-Leaf, et al., 2016), except for the use of food items during the assessment of preference and the observational procedure. The results demonstrated that all three participants only

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began to select the low-preferred food following the introduction of the observational procedure. However, there were individual differences across the participants’ results, and all three participants demonstrated variability in the selection of the low-preferred and high-preferred food items. With respect to mealtime behavior and food consumption, this may be a desired outcome. That is, eating a variety of foods may be more preferred than shifting from eating only one food to only eating another food.

Some considerations in conditioning reinforcers Limited interests, as a core deficit of autism, can create a myriad of challenges for autistic individuals and their families (Ala’i-Rosales et al., 2019). As such, expanding and/or shifting the preferences of autistic individuals should be a consideration throughout any progressive, comprehensive approach when providing behavioral intervention. Furthermore, given the deficits often associated with an ASD diagnosis, perhaps more time should be allocated to training staff in conditioning and expanding reinforcers, rather than training staff to conduct formal preference assessments on a regular basis. What follows are some considerations with respect to conditioning reinforcers for autistic individuals. Individual preferences Conditioning as many items/events to function as reinforcers as possible is a logical goal. Most people have an almost infinite number of items/events that function as reinforcers. However, it is important that individual preferences are considered throughout the course of any progressive, comprehensive approach to behavioral intervention. When possible, this can be done through discussing preferences directly with the client. In situations where this is not possible (e.g., limited vocal/verbal repertoire), discussing preferences with the client’s parents or caregivers as well as observing the client across a wide variety of contexts could help inform an approach to conditioning items/events that align with the client’s goals and values. However, the client’s individual preferences must also be balanced with therapeutic necessity. There are some items/events that have more therapeutic value or may be safer when they function as reinforcers. Take, for example, if peer and teacher attention function as reinforcers, the intervention may be smoother and the client may be more likely to be successful in many contexts (e.g., school, work). A second advantage of an expanded repertoire of reinforcers is the increased availability of alternatives to detrimental preferred items (e.g., healthier food choices). Ultimately, the development of new

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reinforcers and alterations in preferences should be a collaborative process as much as possible. Reinforcers in the desired environment When conditioning new items/events to function as reinforcers it is important to consider what items/events occur in the desired environment. This can be done by observing others interacting and generally behaving in the environment of interest. Those items/events that are identified should be included as targets to be developed as conditioned reinforcers throughout the course of treatment. In many contexts, there is a strong reliance on social events to function as reinforcers. For example, attention from the teacher for completing homework on time, approval from peers for responding in a particular way, high fives from the baseball coach for playing good defense, praise from an interventionist for correct responses, and cheers from the crowd during a gymnastic meet would all be convenient to function as reinforcers. As such, a strong focus of any progressive, comprehensive intervention should be the conditioning of social events to function as reinforcers. Reinforcement is relative Reinforcement is relative. What functions as a reinforcer across time, trials, contexts, and people is likely to vary and change based on a variety of variables. What may function as a reinforcer in one instance, may not in another. While this is another important rationale for ensuring that any progressive intervention involves conditioning a variety of items/events to function as reinforcers, it also has other implications. Throughout the course of intervention, it is important to constantly assess, in the moment, if consequent events actually function as reinforcers. This would involve exploring and assessing all the variables outlined in Table 1. It is also important to ensure that putative reinforcers are rotated regularly enough to prevent satiation. Logically, the larger the number of items/events that function as reinforcers, the easier it is to constantly rotate reinforcers, a further argument for conditioning a larger number of reinforcers.

Summary Reinforcement is not new or restricted to the science of behavior analysis. What ABA-based intervention offers, however, is the systematic use of reinforcement. It can sometimes be difficult to identify possible therapeutic reinforcers for autistic individuals. In these instances, we recommend the use of

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IMRA and assessing all the variables outlined in Table 1. Given the core diagnostic criteria for an autism diagnosis, it is equally, if not more, important for a progressive, comprehensive approach to ABA-based intervention to have a strong emphasis on the conditioning of new items/events to function as reinforcers.

References Ala’i-Rosales, S., Cihon, J. H., Currier, T. D. R., Ferguson, J. L., Leaf, J. B., Leaf, R., McEachin, J., & Weinkauf, S. M. (2019). The big four: Functional assessment research informs preventative behavior analysis. Behavior Analysis in Practice, 12(1), 222–234. https://doi.org/10.1007/s40617-018-00291-9. Alcalay, A., Ferguson, J. L., Cihon, J. H., Torres, N., Leaf, J. B., Leaf, R., McEachin, J., Schulze, K. A., & Rudrud, E. H. (2019). Comparing multiple stimulus preference assessments without replacement to in-the-moment reinforcer analysis on rate of responding. Education and Training in Autism and Developmental Disabilities, 54(1), 69–82. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Author. Cihon, J. H., Weiss, M. J., Ferguson, J. L., Leaf, J. B., Zane, T., & Ross, R. K. (2021). Observational effects on the food preferences of children with autism spectrum disorder. Focus on Autism and Other Developmental Disabilities, 36(1), 25–35. https://doi.org/ 10.1177/1088357620954368. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. DeLeon, I. G., & Iwata, B. A. (1996). Evaluation of a multiple-stimulus presentation format for assessing reinforcer preferences. Journal of Applied Behavior Analysis, 29(4), 519–532. https://doi.org/10.1901/jaba.1996.29-519. Dozier, C. L., Iwata, B. A., Thomason-Sassi, J., Worsdell, A. S., & Wilson, D. M. (2012). A comparison of two pairing procedures to establish praise as a reinforcer. Journal of Applied Behavior Analysis, 45(4), 721–735. https://doi.org/10.1901/jaba.2012.45-721. Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25(2), 491–498. https://doi. org/10.1901/jaba.1992.25-491. Graff, R. B., & Karsten, A. M. (2012). Assessing preferences of individuals with developmental disabilities: A survey of current practices. Behavior Analysis in Practice, 5(2), 37–48. https://doi.org/10.1007/BF03391822. Greer, R. D., & Singer-Dudek, J. (2008). The emergence of conditioned reinforcement from observation. Journal of the Experimental Analysis of Behavior, 89(1), 15–29. https://doi.org/10.1901/jeab.2008.89-15. Howard, G. S., & Dailey, P. R. (1979). Response-shift bias: A source of contamination of self-report measures. Journal of Applied Psychology, 64(2), 144–150. Kazdin, A. E. (2011). Single-case research designs: Methods for clinical and applied settings. Oxford University Press. Kodak, T., Fisher, W. W., Kelley, M. E., & Kisamore, A. (2009). Comparing preference assessments: Selection- versus duration-based preference assessment procedures. Research in Developmental Disabilities, 30(5), 1068–1077. https://doi.org/10.1016/j.ridd. 2009.02.010. Leaf, J. B., Kassardjian, A., Oppenheim-Leaf, M. L., Tsuji, K. H., Dale, S., Alcalay, A., Leaf, J. A., Ravid, D., Milne, C., Leaf, R., Taubman, M., & McEachin, J. (2015).

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Observational effects on preference selection for four children on the autism spectrum: A replication. Behavioral Interventions, 30(3), 256–269. https://doi.org/10.1002/ bin.1411. Leaf, J. B., Leaf, R., Alcalay, A., Leaf, J. A., Ravid, D., Dale, S., Kassardjian, A., Tsuji, K., Taubman, M., McEachin, J., & Oppenheim-Leaf, M. L. (2015). Utility of formal preference assessments for individuals diagnosed with autism spectrum disorder. Education and Training in Autism and Developmental Disabilities, 50(2), 199–212. Leaf, J. B., Leaf, R., Leaf, J. A., Alcalay, A., Ravid, D., Dale, S., Kassardjian, A., Tsuji, K., Taubman, M., McEachin, J., & Oppenheim-Leaf, M. L. (2018). Comparing pairedstimulus preference assessments with in-the-moment reinforcer analysis on skill acquisition: A preliminary investigation. Focus on Autism and Other Developmental Disabilities, 33(1), 14–24. https://doi.org/10.1177/1088357616645329. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Ala’i-Rosales, S., Ross, R. K., Smith, T., & Weiss, M. J. (2016). Applied behavior analysis is a science and, therefore, progressive. Journal of Autism and Developmental Disorders, 46(2), 720–731. https://doi.org/ 10.1007/s10803-015-2591-6. Leaf, J. B., Oppenheim-Leaf, M. L., Leaf, R., Courtemanche, A. B., Taubman, M., McEachin, J., Sheldon, J. B., & Sherman, J. A. (2012). Observational effects on the preferences of children with autism. Journal of Applied Behavior Analysis, 45(3), 473–483. https://doi.org/10.1901/jaba.2012.45-473. Leaf, J. B., Oppenheim-Leaf, M. L., Townley-Cochran, D., Leaf, J. A., Alcalay, A., Milne, C., Kassardjian, A., Tsuji, K., Dale, S., Leaf, R., Taubman, M., & McEachin, J. (2016). Changing preference from tangible to social activities through an observation procedure. Journal of Applied Behavior Analysis, 49(1), 49–57. https:// doi.org/10.1002/jaba.276. Matson, J. L., Bielecki, J., Mayville, E. A., Smalls, Y., Bamburg, J. W., & Baglio, C. S. (1999). The development of a reinforcer choice assessment for persons with severe and profound mental retardation. Research in Developmental Disabilities, 20(5), 379–384. https://doi. org/10.1016/s0891-4222(99)00018-9. Pace, G. M., Ivancic, M. T., Edwards, G. L., Iwata, B. A., & Page, T. J. (1985). Assessment of stimulus preference and reinforcer value with profoundly retarded individuals. Journal of Applied Behavior Analysis, 18(3), 249–255. https://doi.org/10.1901/jaba.1985.18-249. Reid, D. H., DiCarlo, C. F., Schepis, M. M., Hawkins, J., & Stricklin, S. B. (2003). Observational assessment of toy preferences among young children with disabilities in inclusive settings. Efficiency analysis and comparison with staff opinion. Behavior Modification, 27(2), 233–250. https://doi.org/10.1177/0145445503251588. Roane, H. S., Vollmer, T. R., Ringdahl, J. E., & Marcus, B. A. (1998). Evaluation of a brief stimulus preference assessment. Journal of Applied Behavior Analysis, 31(4), 605–620. https://doi.org/10.1901/jaba.1998.31-605. Skinner, B. F. (1953). Science and human behavior. Macmillan. Steinhilber, J., & Johnson, C. (2007). The effects of brief and extended stimulus availability on preference. Journal of Applied Behavior Analysis, 40(4), 767–772. https://doi.org/ 10.1901/jaba.2007.767-772. Walsh, M. B. (2008). Because our kids are worth it: A parent’s perspective on behavioral interventions at home and school. In Symposium presented at the 2nd annual Applied Behavior Analysis International Autism Conference, Atlanta, GA.

CHAPTER 6

Punishment: Overview, concerns, and use Contents Some concerns with the use of punishment-based procedures Emotional responses Escape/avoidance Behavioral contrast Overuse Clinical considerations Punishment is a natural behavioral principle Response probability Contextual effects Punishment is temporary Punishment teaches what not to do Some punishment-based procedures Corrective feedback Time-in ribbon Summary References

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Punishment is a term commonly used in everyday language (i.e., outside of the behavior analytic community). Informally, punishment is commonly used to refer to instances in which a penalty is inflicted upon a person as retribution for doing something that has been deemed undesirable. Instances such as being ejected from a baseball game, reprimands, speeding citations, time-out, and loss of privileges are commonly known among the society as punishment or punishments. In nontechnical usage, punishment often has the connotation of “an eye for an eye” and is rife with controversy and concern regarding its use and effectiveness (e.g., Baer, 1970; Gast, 2011; LaVigna & Donnellan, 1986; McGee et al., 1987; Risley, 1968). Within behavior analysis, however, punishment has a very different meaning. In behavior analysis, punishment refers to any context in which a response is followed by an event (i.e., stimulus change) that results in a decrease in the future probability of similar responses in similar situations. A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00027-1

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It is important to emphasize that punishment results in a decreased probability of similar responses and not the complete elimination of behavior. While the probability may become very low, it is never zero. Unlike its everyday definition, the behavior analytic definition of punishment refers to procedures in the context of their effect on behavior. This definition is free from the things commonly associated with an informal description of punishment such as pain, fear, aversive, and discomfort. From this perspective, punishment, just like reinforcement, is a naturally occurring principle of behavior that “occurs like the wind and the rain” (Vollmer, 2002, p. 469). Positive punishment refers to contexts in which a response is followed immediately by the presentation of a stimulus change that decreases the future probability of similar responses in similar situations. For example, a person cuts in a line/queue and another person in the queue comments, “That’s rude.” If that person’s cutting in line subsequently decreases, we can reasonably conclude that positive punishment occurred. Furthermore, we would refer to the person saying “That’s rude” as a punisher. Negative punishment refers to a context in which a response is followed immediately by the removal of a stimulus/event that results in a decrease in the future probability of similar responses in similar situations. For example, a child may lose access to a phone or tablet for staying up too late. If episodes of staying up too late subsequently decrease, we can reasonably conclude that negative punishment occurred, and we would refer to losing access to a phone or tablet as a punisher.

Some concerns with the use of punishment-based procedures Despite punishment being a naturally occurring principle of behavior, there are some documented concerns with the use of punishment-based procedures. It is important, however, to view these concerns in context. That is, many of these concerns stem from laboratory research and/or the use of more intrusive forms of punishment-based procedures (e.g., shock, intense heat, reprimands) rather than less intrusive forms of more commonly used punishment-based procedures (e.g., saying “no” following an incorrect response). Additionally, there can be problematic side effects from the incorrect use of punishment.

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Emotional responses Laboratory research with nonhuman animals has documented reflexive aggression elicited by the use of shock (e.g., Azrin et al., 1963; Ulrich & Azrin, 1962; Ulrich et al., 1962). This is commonly referred to as respondent or elicited aggression. While the research on this phenomenon is limited (Lerman & Vorndran, 2002), elicited aggression is more commonly associated with inescapable, intense punishment. Elicited aggression during punishmentbased procedures has been mitigated when a response permits escape (i.e., avoiding the punisher; Azrin & Holz, 1966). It is unlikely that any intervention for autistic individuals would include the use of inescapable, intensive punishment. As such, the likelihood of elicited aggression within autism intervention is very low. In fact, some research has demonstrated that the use of punishment-based procedures resulted in a decrease in the behavior targeted for decrease as well as an increase in the instances of more desired behavior (e.g., contextual compliance and toy play; Koegel et al., 1974; Rolider et al., 1991). Nevertheless, interventionists should be acutely aware of this possibility while using punishment-based procedures. Leaf et al. (2019) provided a descriptive analysis evaluating the clinical implementation of common, minimally invasive punishment-based procedures (e.g., verbal corrective feedback, loss of a toy/privilege, loss of a token, denial of request) with 15 individuals diagnosed with ASD. Specifically, Leaf et al. observed several 30-min clinical sessions for each participant to measure the frequency of punishment-based procedures used, variables involved in the use of these techniques (e.g., participant responses that resulted in their use), frequency and type of participant responses to the use of a punishmentbased procedure, and any relationship between the type of procedure and the participant’s response. Leaf et al. found that there were minimal negative responses (i.e., less than 10% of opportunities across all participants) following the use of punishment techniques across all 15 participants. Also, when negative responses occurred, they were mild (i.e., not harmful). Aggression, self-injury, and property misuse accounted for less than 1% of all negative responses.

Escape/avoidance Punishment-based procedures that rely on positive punishment can result in escape from or avoidance of the context in which the punishment-based procedure occurs. For instance, a child confronted with having to try

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unpreferred foods at every mealtime may avoid the mealtime context altogether. When the intensity of punishment increases, so does the likelihood of escape or avoidance. Take the previous example. If the child is only confronted with having to try nonpreferred foods at a few interspersed mealtimes, they may be less likely to avoid the mealtime context. If, however, the child is confronted with having to try nonpreferred foods at every mealtime, they may be much more likely to avoid the mealtime context (note, we are not advocating to use this method to treat mealtime challenges. Rather, see Cihon et al., 2022). Like elicited emotional responses, the possibility for escape and avoidance can be mitigated by targeting desirable alternatives to the problem behavior that result in access to reinforcement as well as avoidance of punishment.

Behavioral contrast Behavior contrast refers to an increase or decrease in the rate of a response that is accompanied by a change in the response rate in the opposite direction in another stimulus context. For example, a child who spends an equal amount of time playing with an iPad in the presence of their mother and father is then reprimanded by their father for playing with the iPad. This may result in a decrease in the amount of time the child spends on the iPad while their father is present and a corresponding increase in the amount of time the child spends on the iPad while their mother is present but their father is not present. Behavioral contrast resulting from the use of punishment-based procedures can also be mitigated through consistently punishing occurrences of the target behavior in all relevant contexts, minimizing access to reinforcement for the target behavior, and providing reinforcement for alternative behaviors.

Overuse The biggest likely concern of the use of punishment-based procedures within intervention for autistic individuals is the possibility of overuse. Punishment-based procedures may result in a negative reinforcement contingency for the interventionist using the punishment-based procedure. For example, a punishment-based procedure may result in the termination, reduction, postponement, or avoidance of aggression, which may increase the likelihood of the interventionist using a punishment-based procedure in the presence of similar responses (e.g., property misuse). This is especially problematic when challenging behavior exhibited by the child does not

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necessitate the use of a punishment-based procedure. While this is a common concern with the use of punishment-based procedures, there is a dearth of literature that has directly evaluated changes in the interventionist’s behavior resulting from the use of punishment-based procedures (Lerman & Vorndran, 2002). Furthermore, the research that does exist does not support the concern that using punishment-based procedures negatively affects the interventionist’s behavior toward the recipient of the punishment-based procedure.

Clinical considerations Punishment is a natural behavioral principle The use of punishment-based procedures, within and outside of behavior analysis, is often fraught with controversy and misunderstanding. It is our contention that this is mainly due to attempts to align a behavior analytic description of punishment with a colloquial description of punishment. As previously stated, behavior analytic and colloquial descriptions of punishment differ in some very important ways. It is worth restating that from a behavior analytic perspective, punishment is a naturally occurring principle of behavior that “occurs like the wind and the rain” (Vollmer, 2002, p. 469). Simply stating, “no” following an incorrect response resulting in that decreased likelihood or incorrect responses is an example of punishment. However, the Ethics Code for Behavior Analysts (Behavior Analyst Certification Board, 2020) states that certified behavior analysts recommend and implement restrictive or punishment-based procedures only after demonstrating that desired results have not been obtained using less intrusive means, or when it is determined by an existing intervention team that the risk of harm to the client outweighs the risk associated with the behavior-change intervention (p. 12).

It seems that the likelihood that practicing behavior analysts exhaust all less intrusive means before simply stating “no” is low. However, as punishmentbased procedures increase in intensity and intrusiveness, this part of the Ethics Code for Behavior Analysts (Behavior Analyst Certification Board, 2020) may become more applicable. It appears the Ethics Code for Behavior Analysts (Behavior Analyst Certification Board, 2020) is written with those more intense and intrusive punishment-based procedures in mind. Those implementing interventions for autistic individuals are tasked with developing skills, enhancing choices, and preparing those individuals for the

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contexts in which they are going to live (Bannerman et al., 1990). While it may be undesired, and behavior analysts should be actively involved in attempts to change it, the society is riddled with the use of punishment-based procedures. As such, one could argue that, depending on the terminal context, it may be unethical to indiscriminately avoid the use of all punishmentbased procedures throughout the course of intervention. For example, if a school aged client never contacts corrective feedback (e.g., “No,” “That’s incorrect,” “Wrong”) throughout the course of intervention, they may be underprepared for the school setting. As with reinforcing contingencies, it is essential that interventionists assess the contingencies responsible for the development and maintenance of behavior in the desired/terminal context. If some of those contingencies are punishment-based, those contingencies should also be systematically programmed into the intervention context.

Response probability As previously stated, punishment results in a decreased probability of similar responses in similar situations, not the complete elimination of behavior. This is a crucial point that can be overlooked within clinical practice. Punishment-based procedures cannot be viewed as a method to completely eliminate a behavior from someone’s repertoire. The punished response is never completely “gone” and is likely to emerge again if the conditions are right (e.g., a context in which the response has never been punished). Therefore, clinicians should avoid relying on punishment to completely eliminate a response from a learner’s repertoire. The emphasis should always be on reinforcement-based procedures and the promotion of functional replacement behavior.

Contextual effects All behavior occurs within a specific context. That context comes to play a large role in the probability of that behavior. This is the case with reinforcement as well as punishment, although perhaps more pronounced with punishment. If a response is punished in one context but not in others, the probability of similar responses in other contexts may not be affected. This is especially the case if the punishment context differs greatly from other contexts. As such, if punishment-based procedures are used within the course of intervention for autistic individuals, measures of generalization to other contexts should be taken. If necessary, the punishment-based procedure should be systematically applied to the other contexts. It should be

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noted that this recommendation should be considered with the use of reinforcement-based procedures as well. That is, reinforcing a response in one context does not guarantee similar responses are likely to occur in other contexts in which the response has not been reinforced.

Punishment is temporary The effects of punishment are temporary. However, this is the case with any contingency, reinforcing or punishing. If the contingency is not maintained or withdrawn, the behavior resulting from that contingency will not be maintained. As such, if a punishment-based procedure is going to be used, it will be important to ensure that effective punishment-based contingencies remain in effect long enough to allow positive reinforcement for alternative behavior to become the primary maintaining contingency. Temporary use of punishment can offset the availability of competing problematic reinforcers as well as allow for the conditioning of new reinforcers. If sufficiently strong reinforcement is maintained, it becomes increasingly possible to reduce the use of punishment. Those contingencies should also be designed to match the contingencies operating in the terminal context. If the contingencies operating in the terminal context are punishment-based, it may be easier to make this systematic change. If, however, the contingencies operating in the terminal context are reinforcement-based, it may be more difficult to make this systematic change. Similar to the use of prompts, any contingencies that are put into place during the course of intervention that are not part of the terminal context will need to be systematically faded or shifted.

Punishment teaches what not to do Colloquially speaking, punishment teaches one what not to do, while reinforcement teaches one what to do. Telling someone what not to do does not assist them in identifying what they should be doing. This is one of the rationales for ensuring punishment-based procedures are not implemented in isolation. The effects of punishment decrease the probability of similar responses in similar situations. While punishment-based procedures have in some instances been documented to produce increases in other, sometimes more desired, responses (Koegel et al., 1974; Rolider et al., 1991), reinforcement-based procedures are likely necessary to develop and maintain desired alternatives to the punished response(s). The goals of progressive intervention for autistic individuals involve developing skills and enhancing

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available choices. As such, any progressive approach to ABA for autistic individuals is not likely to include solely punishment-based procedures. Rather, there should be a balance of developing desirable, applied skills, and minimizing less desirable behavior.

Some punishment-based procedures Corrective feedback Corrective feedback (sometimes referred to as error correction) is a common part of most instruction including behaviorally-based interventions for autistic individuals. Phrases such as “No, that’s not it,” “That is incorrect,” and “Try again,” are commonly used following incorrect or undesired responses. While corrective feedback is not always categorized as a punishment-based procedure, likely due to its mild emotional impact and common use, it is functionally a punishment procedure if it results in a decreased probability of similar responses. There are many examples of the use of corrective feedback within peer-reviewed literature (e.g., Leaf et al., 2014, 2020). However, corrective feedback is commonly included as a component of a larger intervention package (e.g., Dahlquist & Gil, 1986; Hagopian et al., 2009). Leaf et al. (2020) conducted a randomized clinical trial to compare the relative efficiency and effectiveness of an error correction procedure to an errorless learning procedure to teach tact relations to 28 children diagnosed with ASD. The errorless learning condition consisted of a most-to-least prompting system using a full echoic prompt, a partial echoic prompt, and no prompt. The error correction condition consisted of providing corrective and informative feedback (e.g., “No, it is Daredevil.”) following incorrect responses. Praise was provided for independent correct responses across both conditions. The results indicated that both procedures were effective and resulted in significant changes from pre- to postprobes. There were no significant differences in the occurrence of aberrant behavior (i.e., aggression, self-injurious behavior, stereotypic behavior, crying, or yelling) across the two conditions. That is, error correction did not increase the likelihood of aberrant behavior for the participants included in the study.

Time-in ribbon A time-in ribbon, sometimes referred to as a time-out ribbon, consists of an individual wearing a visual stimulus (e.g., ribbon, bracelet, button, necklace)

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that signals the availability of reinforcement. The time-in visual stimulus is maintained (i.e., the individual keeps the visual stimulus) as long as the individual does not engage in the behavior targeted for decrease. Thus, the visual stimulus comes to function as a discriminative stimulus that reinforcement is available contingent upon not engaging in the targeted behavior. If the individual engages in the behavior targeted for decrease, the visual stimulus is removed, and the individual loses access to reinforcement. Time-in ribbon procedures commonly include a specific criterion to access the visual stimulus again (e.g., completing a specific task, an absence of the targeted behavior for a specific time). The time-in ribbon is a noninvasive contingency system that can be implemented in settings in which social stigmatization is a consideration (e.g., school, community). One of the benefits of the time-in ribbon is that it signals to all observers that the individual is meeting a behavioral goal and therefore occasions the delivery of incidental social acknowledgement (e.g., by a principal who is visiting a classroom). Leaf et al. (2012) provided a clinical case study describing the implementation of a time-in ribbon with an adolescent diagnosed with autism. Prior to the evaluation of the effectiveness of the time-in ribbon, Leaf et al. provided reinforcement for wearing the visual stimulus (i.e., a Livestrong band) and used the Cool versus Not Cool procedure to teach which behaviors would result in the loss of the band. The time-in ribbon procedure consisted of telling the participant to remove the band contingent upon the targeted behavior. The participant was then required to take five deep breaths. Each deep breath resulted in obtaining a token. Once the five tokens were earned, the band was provided and placed back on the participant’s wrist. The results indicated that the time-in procedure was effective at reducing the likelihood of the targeted behavior. Additionally, the participant engaged in less aberrant behavior during 5-min observations without the band that directly followed the time-in procedure.

Summary Punishment is a commonly used term within society. However, it has special meaning within behavior analysis. Within behavior analytic intervention, punishment refers to any context in which a response is followed by a stimulus change that results in a decrease in the probability of similar responses in similar situations in the future. There is nothing inherently bad, dangerous, painful, or harmful within a behavior analytic understanding of punishment. While some procedures may be closely paired with those terms

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(e.g., contingent shock), they do not represent the numerous punishmentbased contingencies and procedures that are available. While they should always be used with careful consideration, guidance, and care, we believe that punishment-based procedures should not be indiscriminately avoided.

References Azrin, N. H., & Holz, W. C. (1966). Punishment. In W. K. Honig (Ed.), Operant behavior: Areas of research and application (pp. 380–447). Prentice-Hall. Azrin, N. H., Holz, W. C., & Hake, D. F. (1963). Fixed-ratio punishment. Journal of the Experimental Analysis of Behavior, 6(2), 141–1148. https://doi.org/10.1901/ jeab.1963.6-141. Baer, D. M. (1970). A case for the selective reinforcement of punishment. In J. L. M. C. Neuringer (Ed.), Behavior modification in clinical psychology (pp. 243–249). Prentice-Hall. Bannerman, D. J., Sheldon, J. B., Sherman, J. A., & Harchik, A. E. (1990). Balancing the right to habilitation with the right to personal liberties: The rights of people with developmental disabilities to eat too many doughnuts and take a nap. Journal of Applied Behavior Analysis, 23(1), 79–89. https://doi.org/10.1901/jaba.1990.23-79. Behavior Analyst Certification Board. (2020). Ethics code for behavior analysts. https://bacb. com/wp-content/ethics-code-for-behavior-analysts/. Cihon, J. H., Tereshko, L., Marshall, K. B., & Weiss, M. J. (Eds.). (2022). Behavior analytic approaches to promote enjoyable mealtimes for individuals with autism and their families. Wilmington, DE: Vernon Press. https://vernonpress.com/book/1589. Dahlquist, L. M., & Gil, K. M. (1986). Using parents to maintain improved dental flossing skills in children. Journal of Applied Behavior Analysis, 19(3), 255–260. https://doi.org/ 10.1901/jaba.1986.19-255. Gast, D. L. (2011). A rejoinder to Leaf: What constitutes efficient, applied, and trial and error. Evidence-Based Communication Assessment and Intervention, 5(4), 234–238. https://doi.org/ 10.1080/17489539.2012.689601. Hagopian, L. P., Kuhn, D. E., & Strother, G. E. (2009). Targeting social skills deficits in an adolescent with pervasive developmental disorder. Journal of Applied Behavior Analysis, 42(4), 907–911. https://doi.org/10.1901/jaba.2009.42-907. Koegel, R. L., Firestone, P. B., Kramme, K. W., & Dunlap, G. (1974). Increasing spontaneous play by suppressing self-stimulation in autistic children. Journal of Applied Behavior Analysis, 7(4), 521–528. https://doi.org/10.1901/jaba.1974.7-521. LaVigna, G. W., & Donnellan, A. M. (1986). Alternatives to punishment: Solving behavior problems with non-aversive strategies. Irvington. Leaf, J. B., Alcalay, A., Leaf, J. A., Tsuji, K., Kassardjian, A., Dale, S., McEachin, J., Taubman, M., & Leaf, R. (2014). Comparison of most-to-least to error correction for teaching receptive labelling for two children diagnosed with autism. Journal of Research in Special Educational Needs, 16(4), 217–225. https://doi.org/10.1111/1471-3802.12067. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Milne, C. M., Leaf, R., & McEachin, J. (2020). Comparing error correction to errorless learning: A randomized clinical trial. The Analysis of Verbal Behavior, 36(1), 1–20. https://doi.org/10.1007/s40616-019-00124-y. Leaf, J. B., Oppenheim-Leaf, M. L., & Streff, T. (2012). The effects of the time-in procedure on decreasing aberrant behavior. Clinical Case Studies, 11(2), 152–164. https://doi.org/ 10.1177/1534650112443003. Leaf, J. B., Townley-Cochran, D., Cihon, J. H., Mitchell, E., Leaf, R., Taubman, M., & McEachin, J. (2019). Descriptive analysis of the use of punishment-based techniques

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with children diagnosed with autism spectrum disorder. Education and Training in Autism and Developmental Disabilities, 54(2), 107–118. Lerman, D. C., & Vorndran, C. M. (2002). On the status of knowledge for using punishment implications for treating behavior disorders. Journal of Applied Behavior Analysis, 35(4), 431–464. https://doi.org/10.1901/jaba.2002.35-431. McGee, J. J., Menolascino, F. J., Hobbs, D. C., & Menousek, P. E. (1987). Gentle teaching: A nonaversive approach to helping persons with mental retardation. Human Sciences Press. Risley, T. R. (1968). The effects and side effects of punishing the autistic behaviors of a deviant child. Journal of Applied Behavior Analysis, 1(1), 21–34. https://doi.org/10.1901/ jaba.1968.1-21. Rolider, A., Cummings, A., & Van Houten, R. (1991). Side effects of therapeutic punishment on academic performance and eye contact. Journal of Applied Behavior Analysis, 24(4), 763–773. https://doi.org/10.1901/jaba.1991.24-763. Ulrich, R. E., & Azrin, N. H. (1962). Reflexive fighting in response to aversive stimulation. Journal of the Experimental Analysis of Behavior, 5(4), 511–520. https://doi.org/10.1901/ jeab.1962.5-511. Ulrich, R. E., Wolff, P. C., & Azrin, N. H. (1962). Shock as an elicitor of intra and interspecies fighting behavior. Animal Behavior, 12(1), 14–15. https://doi.org/10.1016/00033472(64)90095-8. Vollmer, T. R. (2002). Punishment happens: Some comments on Lerman and Vorndran’s review. Journal of Applied Behavior Analysis, 35(4), 469–473. https://doi.org/10.1901/ jaba.2002.35-469.

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CHAPTER 7

Token economies and other contingency systems Contents Components of token systems The commonality of token economies Advantages and disadvantages of token systems Some relevant research Clinical recommendations and progressive approaches to token systems Clinical recommendations Some progressive approaches to token systems Summary References

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A token economya is a contingency system in which tokens are provided contingent upon engaging in a desired behavior. These tokens can then be exchanged for presumably reinforcing items and/or activities. Token economies are commonly used in behavioral intervention to increase the probability of desired behavior and decrease the probability of undesired behavior (Hackenberg, 2018; Kazdin, 1977; Matson & Boisjoli, 2009). Ayllon and Azrin (1965) provided an early description of the use of a token economy with residents in a state hospital. In their work with psychiatric patients, Ayllon and Azrin provided tokens contingent upon residents displaying predetermined target behaviors (e.g., self-grooming, doing laundry). The tokens could then be exchanged for a variety of activities (e.g., walking around the hospital grounds). Their results demonstrated that the token economy was effective at developing and improving the targeted behaviors for all the residents who participated. Since Ayllon and Azrin’s seminal work, token economies have been used to improve and/or develop a variety of desired behaviors with a wide a

It should be noted that token economies involve just that, an economy (e.g., the collective activities and exchanges of producers and consumers). In this chapter, we will use the term token system for the use of conditioned generalized reinforcers that are not used in the context of a full token economy.

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population of individuals. These populations have included, but are not limited to, children and adults diagnosed with autism spectrum disorder (ASD), typically developing children and adults and children diagnosed with intellectual and developmental disabilities other than ASD. Within and across these populations, token economies have been demonstrated to be effective at improving or developing many different behaviors such as studying (e.g., Birnbrauer et al., 1965), class participation (e.g., Cotler et al., 1972), social interactions (e.g., Odom et al., 1985), self-help skills (e.g., Murphy, 1976), question asking (e.g., Hung, 1977), attending (e.g., Jones & Kazdin, 1975), and food refusal (e.g., Kahng et al., 2003).

Components of token systems Prior to the implementation of a token economy, it is important that the target behavior(s) are clearly defined (Ghezzi et al., 2008) and the settings/contexts in which the token economy will be used are specified. It is also important to determine what stimuli will be used as tokens. The durability and ease of handling and storage of the stimuli should be considered when making this decision. Furthermore, the client’s age, preferences, and the contexts in which the token economy will be used should be considered. Since the tokens should function as conditioned (and, preferably, generalized) reinforcers, it is necessary to identify reinforcers that will be available in exchange for the tokens (Ghezzi et al., 2008). It is also necessary to determine the schedule of reinforcement which includes how many and how often tokens are delivered contingent upon the desired behavior(s). Finally, an earning requirement must be established that “specifies exactly how many tokens are needed to buy exactly how much or how many of the things and activities that constitute the backups” (Ghezzi et al., 2008, p. 568). Within a progressive approach to ABA for autistic individuals, many of these components are flexible and determined using in-the-moment assessment (described later).

The commonality of token economies One concern some have about the use of token economies is the use of extrinsic reinforcement (Cameron et al., 2001; Cameron & Pierce, 2016; McGinnis et al., 1999). Extrinsic reinforcement is said to decrease intrinsic (or internal) motivation. For example, if a child who enjoys reading accesses external reinforcement (e.g., points, tokens) for reading, the child may come

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to read less once the external reward (e.g., points, tokens) is discontinued. However, it should be noted that for a child who is already reading, it is not logical to implement additional reinforcement, nor would it be recommended to do so. Furthermore, these concerns overlook how common token economies and external reinforcement are within society. We earn money from our employers for completing the tasks associated with our jobs, grades for completing our homework in school, and poker chips for winning hands in poker. It is unlikely that employers would maintain employees if they were to stop paying them for their work—even if the employees have stated that they like their jobs. Furthermore, concerns about properly implemented reinforcement decreasing intrinsic motivation are not supported by the literature (Cameron et al., 2001; Cameron & Pierce, 2016; McGinnis et al., 1999; Staats et al., 1962).

Advantages and disadvantages of token systems There are several advantages to the use of token systems during intervention for autistic individuals. First, token systems may permit the delivery of more frequent reinforcement. Depending on the number of tokens required to exchange (i.e., the earning requirement), several tokens could be delivered across a longer period than if solely relying on the delivery of the terminal reinforcer. Second, and relatedly, token systems help “bridge the gap” (i.e., compensate for delay) between performance and the terminal reinforcer. This more closely aligns with contingencies that commonly occur in our environments (e.g., we work for 2 weeks prior to accessing our paycheck, we exchange money we have saved to purchase a gift for a loved one). Third, token systems can be designed to be mobile and easy to take from place to place. This means that during the course of intervention, the token system can be taken across all contexts the client enters. This allows the contingencies to remain consistent across contexts, regardless of the additional contingencies that may occur in that context (e.g., teacher instructions in a classroom). Fourth, token systems permit more control over the timing of the delivery of reinforcement. Finally, tokens can be faded to become virtual markers of reinforcement, as in “give yourself an (imaginary) point” and eventually be replaced by self-monitoring. Tokens are easy to manage and deliver, which can make the timing of the reinforcer delivery more accurate. This can help prevent the inadvertent reinforcement of undesired behaviors and decrease the likelihood of developing unwanted behavior chains.

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While there are several advantages to the use of token systems, it does require time to design, train staff, and ensure correct implementation. Consistency is important in the delivery of tokens to ensure the desired behavior is contacting the amount of reinforcement necessary to develop the skill. At least initially, the same contingency should be in effect across environments. Consistency is required across interventionists to ensure that the token system is being used in the same way by each person. Failure to ensure consistency, especially early in the implementation of the token system, could lead to the token system being less effective or others concluding that token systems are ineffective. Token systems also require fading. Like prompts (see Chapter 11) or any other supplemental procedures, token systems are commonly added during intervention to increase the rate of learning. Anything added during intervention, which is not part of the terminal context, needs to be faded. This does not mean, however, fading to no reinforcement. Rather, the contingencies developed using a token system must be shifted to the contingencies that maintain and develop behavior in the terminal context.

Some relevant research Research on the effectiveness of token systems is vast (Hackenberg, 2009; Kim et al., 2021; Maggin et al., 2011; Matson & Boisjoli, 2009). A comprehensive literature review on token systems will not be provided here as many are currently available in the existing literature. What follows are some selected examples of relevant research as it applies to a progressive approach to the use of token systems for autistic individuals. Cihon, Ferguson, Milne, et al. (2019) provided an evaluation of a token system with a flexible earning requirement. Specifically, Cihon, Ferguson, Milne, et al. evaluated the effectiveness of a token economy with a flexible earning requirement to increase the rate of commenting during a snack context for three children diagnosed with ASD. The flexible earning requirement, referred to as a “magic number,” differs from other commonly used token systems that have a fixed earning requirement. For example, 10 tokens might be required to exchange for the terminal reinforcer. Instead, when using a magic number token system, the exchange rate is determined by the interventionist and informed by their clinical judgment. This means that instead of the learner earning a terminal reinforcer after a static number of tokens earned (e.g., 10), the learner does not know how many tokens will need to be earned to access the terminal

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reinforcer (e.g., 3, or 15, or 8). In this study, the magic number token system involved providing a tally mark on a dry-erase board for each comment the participants made during snack time with the interventionist. If, following 3 min, the number of marks met or exceeded the interventionist’s magic number, the participant was then given access to a treasure chest that contained various small, age-appropriate toys. The interventionist was asked to provide a rationale for their selection of the magic number during each session. The most cited rationales were “Based off previous session,” followed by “Ensure participant contacted reinforcement,” and “Based off current session.” The results demonstrated that the token economy with a flexible earning requirement was effective at increasing the rate of commenting for all three participants. Furthermore, there was an increase in novel comments for all the three participants even though there were no programmed contingencies for novel comments. Cihon, Ferguson, Leaf, et al. (2019) evaluated the effectiveness of a level system to improve synchronous engagement with two dyads of children diagnosed with ASD. Unlike most level systems, Cihon, Ferguson, Leaf, et al. used a structured, yet flexible approach to movement within and across the levels. Synchronous engagement was defined as times both children within a dyad simultaneously exhibited favorable affect while engaged in the same activity. This differs from engagement alone which was defined as both children within a dyad being involved with the same activity (e.g., touching, manipulating). As such, synchronous engagement provides some evidence that not only were the participants engaged in the same activity, but they were both enjoying the engagement as well (e.g., smiling, laughing). The level system consisted of three tiers. The bottom tier indicated that the participant would not earn access to a treasure chest to play with a toy when the session ended. The middle tier indicated that the participant would earn 2 min of access to the treasure chest but could not take the item home. The top tier indicated that the participant would earn 2 min of access to the treasure chest and could take the item home. In the dyad, each participant had a clip that was clipped onto the level chart. During 5 min sessions, the interventionist checked in with the participants every minute to move the clips up, down, or remain in the same place. Each participant’s clip moved independently of the other member of the dyad. The interventionist used in-the-moment assessment to determine movement up or down the chart. If the participant exhibited general improvement during the interval, the clip was moved up, and if the participant’s behavior was below what was reasonable to expect, the clip was moved down. The results

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demonstrated that the level system was effective in improving synchronous engagement for all four participants.

Clinical recommendations and progressive approaches to token systems What follows are some clinical recommendations to the implementation of token systems as well as some progressive approaches to token systems that are often implemented as part of the Autism Partnership Method (APM). These recommendations should be viewed as that—recommendations, not rules.

Clinical recommendations Determine if a token system is necessary Given that token systems should be systematically faded, and contingencies need to be shifted to ones that occur naturally in the terminal environment, deciding to implement a token system requires serious consideration. Token systems should not be seen as a default intervention for autistic individuals. Just like any other behavior analytic procedure, one must consider the conditions under which a token system is necessary and appropriate for each learner. This would include ensuring any prerequisite skills are in place for the learner prior to the implementation of a token system. For instance, it will be important that several reinforcers have been identified. It will also likely be necessary for simple contingencies to be developed prior to the implementation of a token system. Start simple and teach the basics When first introducing the token system, it may be necessary to start with a simple contingency and gradually build from there. This may involve first teaching the exchange of the token board itself for access to the terminal reinforcer. This permits the development of the exchange response early in the process. Prompting the client to give the interventionist the token board, then immediately providing access to a reinforcer is a great way to develop this response. Following the development of the exchange response, it is now possible to add the delivery of a token into the chain. It is important that the client observes the delivery of the token as much as possible. This can be done through visual observation (e.g., seeing the token be added to the token board) or auditory observation (e.g., hearing the sound of the token being applied to the board). Following the delivery

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of the token, the client should then hand the token board to the interventionist (i.e., teaching the exchange response). Determine the earning requirement As previously stated, it is common for token systems to have a fixed earning requirement (e.g., 10 tokens). This may be appropriate and necessary in some instances. In these instances, the number of tokens required prior to exchanging would remain consistent across trials, sessions, interventionists, and contexts. There are, however, many instances in which a flexible earning requirement may be more appropriate and desired. In these instances, the number of tokens required to be earned prior to the exchange would vary and would be informed by the interventionist’s in-the-moment assessment of a variety of variables. A flexible earning requirement has several benefits. First, the learner’s motivation to engage in the target behavior(s) may be less likely to be abolished once a certain number of tokens is obtained. Second, a flexible earning requirement may be more effective for developing target behaviors that should not have an artificial ceiling. That is, an unknown earning requirement could function as an establishing operation, which momentarily increases the probability of behavior that would set the occasion for token delivery and the reinforcing effectiveness of tokens. Third, allowing in-the-moment flexibility for the determination of the earning requirement aligns more closely to the use of shaping behavior in real-world contexts. Move quickly, but don’t rush Progression through the stages of the development and teaching of a token system should happen quickly, but not too quickly. Unfortunately, there is no magic algorithm for determining how slowly or quickly to progress for each individual. As with most ABA-based procedures for autistic individuals, clinical judgment, in-the-moment assessment, and data should be used. That said, progression through the development and use of a token system should happen when the client is ready. This progress is likely to look different across clients, but all clients should be progressing. This progress should also involve moving toward the naturally occurring contingencies and contingency systems in the client’s terminal environment. For example, if a client is using a token board in the clinic, but the terminal environment is a 1st grade classroom in which the teacher uses a level system (e.g., Cihon, Ferguson, Leaf, et al., 2019), progress toward the use of a level system should occur as quickly as possible.

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Some progressive approaches to token systems Reduction of the field Reduction of the field is commonly discussed as a prompting system within ABA-based interventions for teaching receptive discrimination or matching to autistic individuals (e.g., Leaf et al., 2014). As a prompting system, the number of stimuli in the field is reduced to increase the likelihood of the learner engaging in a correct response. With fewer stimuli in the field, the possibility of an error is reduced. Reduction of the field, however, can also be used as a contingency system by removing stimuli from the field contingent upon desired responses. The decision to remove the stimulus can be made contingent on any of several aspects of the learner’s response such as being correct on the first try, speed, or absence of stereotypic behavior during the trial. Once the field has been depleted, the terminal reinforcer becomes available. Functionally, reduction of the field as a contingency system is a combined positive and negative reinforcement contingency. Work is gradually removed contingent upon desired responding, and access to the terminal reinforcer is available contingent upon work being completed. This is not unlike many contingencies operating in society. For example, once your work has been completed, you may access a break as well as access to other reinforcers. Stimuli can also be added to the field contingent upon undesired behavior. This approach can also be used with naturally closed-ended activities such as an inset puzzle or a deck of flashcards. With the puzzle, a response accompanied by undesired behavior would be interrupted and the piece would be replaced on the table. With the flashcard, if a card is answered correctly without a prompt on the first try, it would be placed in the all-done pile. As such, reduction of the field contingency systems can be used to increase the likelihood of desired behaviors and decrease the likelihood of undesired behaviors. Due to its ease of implementation and clear contingency, this system may be preferred during the beginning stages of intervention, and with newer staff that may have had less training opportunities. Magic number As previously discussed, a magic number token system is one that involves a flexible earning requirement. The learner does not know in advance how many tokens (or points) are needed in order to cash in for the top prize. Prior to the implementation of this system, it is common to inform the client about the

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token system. For example, Cihon, Ferguson, Milne, et al. (2019) told participants, Today we are going to work on talking. Each time you talk, I will give you a mark [interventionist put a mark on the dry-erase board]. If you have enough marks to meet or beat my magic number [interventionist drew a circle on the dry-erase board], you can take something home from the treasure chest [interventionist pointed to the treasure chest] (p. 552).

While this is a widespread practice, it is unclear if it is a necessary component of a magic number token system. Within this system, the interventionist determines the earning requirement as well as how often an exchange may be possible. The interventionist may choose an exchange interval based on time (e.g., 3 min; Cihon, Ferguson, Milne, et al., 2019), or based on the contingency they want the client to contact. For example, if the client is performing at their best, the interventionist may choose to offer an exchange immediately with a magic number the client has met to ensure the client accesses reinforcement. If, however, the client is performing poorly, the interventionist may choose to offer an exchange immediately with a magic number the client has not met to ensure the client does not access reinforcement. The magic number selected by the interventionist could be based on a variety of variables. For example, if the goal is to increase the rate of responding, the interventionist could gradually increase the magic number to shape higher rates of responding. These elements make this system highly flexible and effective in the hands of a highly trained interventionist. Competitive Another commonly used, but less researched, contingency system is a competitive token system. Within this system, the client is earning tokens while competing with the interventionist or another peer. The client continues to earn tokens contingent upon the desired target behavior(s). The competitive partner also earns tokens contingent upon the client engaging in undesired behavior(s) or for engaging in a designated target behavior specific to the partner. If the client reaches the earning requirement first, they then access reinforcement. If the competitive partner reaches the earning requirement first, then reinforcement is not available for the client. There are several variations that are possible when implementing a competitive token system. First, if the competitive partner reaches the earning

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requirement first, then the interventionist could select what occurs. This could involve the client simply missing the opportunity to access reinforcement and returning to work. The interventionist could also provide the client with access to a less preferred item (e.g., something that is less preferred than the desired reinforcer, but more preferred than returning back to work) or they could extend the earning period allowing the learner to get some value for the tokens they did earn (avoiding an all-or-none contingency). Second, the interventionist and the client could both earn tokens for engaging in the desired targeted behavior(s). This leverages observational learning by permitting the interventionist to model the targeted behavior(s) as well as accessing reinforcement for engaging in the targeted behavior(s). As the client is more successful, the interventionist could fade out the model which increases the reinforcement available for the client. Third, graduated reinforcement could be used based on the number of tokens the client earns. For example, if the client earns many more tokens than the competitive partner, they could access reinforcement for a longer duration than if the client earns the same amount as the competitive partner. Level systems Level systems are contingency systems that commonly combine multiple behavior change techniques such as the use of positive reinforcement, contingency contracting, response cost, shaping, and fading (Bauer et al., 1986; Smith & Farrell, 1993). Within a level system, an individual moves up and down, within, and across the levels. The number of levels used in a system varies, with no consensus on the ideal number of levels. As such, the number of levels should be selected based on what will work best for the client and the context. The greater the number of levels, the greater the possible outcomes associated with each level. Each level corresponds with a different overall standard of behavior and consequence. For example, in the aforementioned study by Cihon, Ferguson, Leaf, et al. (2019), there were three levels and each level correlated with a differential outcome that was based on the participant’s behavior during a 5 min observation. While level systems are commonly used within school settings, they have a limited empirical literature base for use with autistic individuals and some have advocated for abandoning their use altogether (e.g., Jung & Smith, 2018). Many of the systems that are employed do not reflect best practice in that they rely exclusively on response cost and do not have a reinforcement component. However, there is nothing inherently bad about level systems, and no research has demonstrated any cause for concern over their use.

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Nonetheless, just like any other procedure, level systems can be implemented incorrectly, leading to blaming the system as opposed to the inappropriate application of the system. Within the APM, we have used level systems within our clinical practice and research with great success. In doing so, we have found that using level systems with a flexible approach to movement within and across levels is most preferred. This flexible approach, just like most flexible approaches, requires highly trained staff to be implemented most effectively.

Summary Token economies are commonly used during ABA-based interventions for autistic individuals. They can be very effective at developing and maintaining desired behaviors and decreasing the likelihood of undesired behaviors. There are many different types of token systems, each with its own advantages and limitations. Careful consideration should occur to determine if a token system is necessary or appropriate and which token system should be used. Just like any other systems that are used, the use of/reliance on token systems must be faded as quickly as possible. This does not mean eliminating all reinforcement. Rather, this means shifting to the contingencies that occur in the client’s terminal context.

References Ayllon, T., & Azrin, N. H. (1965). The measurement and reinforcement of behavior of psychotics. Journal of the Experimental Analysis of Behavior, 8(6), 357–383. https://doi.org/ 10.1901/jeab.1965.8-357. Bauer, A. M., Shea, T. M., & Keppler, R. (1986). Levels systems: A framework for the individualization of behavior management. Behavioral Disorders, 12(1), 28–35. Birnbrauer, J. S., Wolf, M. M., Kidder, J. D., & Tague, C. E. (1965). Classroom behavior of retarded pupils with token reinforcement. Journal of Experimental Child Psychology, 2(2), 219–235. https://doi.org/10.1016/0022-0965(65)90045-7. Cameron, J., Banko, K. M., & Pierce, W. D. (2001). Pervasive negative effects of rewards on intrinsic motivation: The myth continues. The Behavior Analyst, 24(1), 1–44. https://doi. org/10.1007/BF03392017. Cameron, J., & Pierce, W. D. (2016). Reinforcement, reward, and intrinsic motivation: A meta-analysis. Review of Educational Research, 64(3), 363–423. https://doi.org/ 10.3102/00346543064003363. Cihon, J. H., Ferguson, J. L., Leaf, J. B., Leaf, R., McEachin, J., & Taubman, M. (2019). Use of a level system with flexible shaping to improve synchronous engagement. Behavior Analysis in Practice, 12(1), 44–51. https://doi.org/10.1007/s40617-018-0254-8. Cihon, J. H., Ferguson, J. L., Milne, C. M., Leaf, J. B., McEachin, J., & Leaf, R. (2019). A preliminary evaluation of a token system with a flexible earning requirement. Behavior Analysis in Practice, 12(3), 548–556. https://doi.org/10.1007/s40617-018-00316-3.

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Cotler, S. B., Applegate, G., King, L. W., & Kristal, S. (1972). Establishing a token economy program in a state hospital classroom: A lesson in training student and teacher. Behavior Therapy, 3(2), 209–222. https://doi.org/10.1016/s0005-7894(72)80081-9. Ghezzi, P. M., Wilson, G. R., Tarbox, R. S. F., & MacAleese, K. R. (2008). Guidelines for developing and managing a token economy. In W. T. O’Donohue, & J. E. Fisher (Eds.), Cognitive behavior therapy: Applying empirically supported techniques in your practice (2nd ed., pp. 565–671). John Wiley & Sons. Hackenberg, T. D. (2009). Token reinforcement: A review and analysis. Journal of the Experimental Analysis of Behavior, 91(2), 257–286. https://doi.org/10.1901/jeab.2009.91-257. Hackenberg, T. D. (2018). Token reinforcement: Translational research and application. Journal of Applied Behavior Analysis, 51(2), 393–435. https://doi.org/10.1002/jaba.439. Hung, D. W. (1977). Generalization of “curiosity” questioning behavior in autistic children. Journal of Behavior Therapy and Experimental Psychiatry, 8(3), 237–245. https://doi.org/ 10.1016/0005-7916(77)90061-1. Jones, R. T., & Kazdin, A. E. (1975). Programming response maintenance after withdrawing token reinforcement. Behavior Therapy, 6(2), 153–164. https://doi.org/10.1016/s00057894(75)80136-5. Jung, L. A., & Smith, D. (2018). Tear down your behavior chart!. ASCD. https://www.ascd. org/el/articles/tear-down-your-behavior-chart. Kahng, S., Boscoe, J. H., & Byrne, S. (2003). The use of an escape contingency and a token economy to increase food acceptance. Journal of Applied Behavior Analysis, 36(3), 349–353. https://doi.org/10.1901/jaba.2003.36-349. Kazdin, A. E. (1977). The token economy: A review and evaluation. Plenum Press. Kim, J. Y., Fienup, D. M., Oh, A. E., & Wang, Y. (2021). Systematic review and metaanalysis of token economy practices in K-5 educational settings, 2000 to 2019. Behavior Modification, 46(6), 1460–1487. https://doi.org/10.1177/01454455211058077. Leaf, J. B., Alcalay, A., Leaf, J. A., Tsuji, K., Kassardjian, A., Dale, S., McEachin, J., Taubman, M., & Leaf, R. (2014). Comparison of most-to-least to error correction for teaching receptive labelling for two children diagnosed with autism. Journal of Research in Special Educational Needs, 16(4), 217–225. https://doi.org/10.1111/1471-3802.12067. Maggin, D. M., Chafouleas, S. M., Goddard, K. M., & Johnson, A. H. (2011). A systematic evaluation of token economies as a classroom management tool for students with challenging behavior. Journal of School Psychology, 49(5), 529–554. https://doi.org/10.1016/j. jsp.2011.05.001. Matson, J. L., & Boisjoli, J. A. (2009). The token economy for children with intellectual disability and/or autism: A review. Research in Developmental Disabilities, 30(2), 240–248. https://doi.org/10.1016/j.ridd.2008.04.001. McGinnis, J. C., Friman, P. C., & Carlyon, W. D. (1999). The effect of token rewards on “intrinsic” motivation for doing math. Journal of Applied Behavior Analysis, 32(3), 375–379. https://doi.org/10.1901/jaba.1999.32-375. Murphy, S. T. (1976). The effects of a token economy program on self-care behaviors of neurologically impaired inpatients. Journal of Behavior Therapy and Experimental Psychiatry, 7(2), 145–147. https://doi.org/10.1016/0005-7916(76)90073-2. Odom, S. L., Hoyson, M., Jamieson, B., & Strain, P. S. (1985). Increasing handicapped preschoolers’ peer social interactions: Cross-setting and component analysis. Journal of Applied Behavior Analysis, 18(1), 3–16. https://doi.org/10.1901/jaba.1985.18-3. Smith, S. W., & Farrell, D. T. (1993). Level system use in special education: Classroom intervention with prima facie appeal. Behavioral Disorders, 18(4), 251–264. https://doi.org/ 10.2307/23887467. Staats, A. W., Staats, C. K., Schutz, R. E., & Wolf, M. (1962). The conditioning of textual responses using “extrinsic” reinforcers. Journal of the Experimental Analysis of Behavior, 5(1), 33–40. https://doi.org/10.1901/jeab.1962.5-33.

CHAPTER 8

Respondent conditioning procedures Contents Considerations related to respondent behavior in autism intervention Some benefits of considering respondent behavior Some respondent conditioning procedures Systematic desensitization Other respondent techniques Summary References

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Respondent behavior refers to any response that is elicited, or induced, by stimuli that precede the response. No special conditions (e.g., states of deprivation, reinforcement, punishment) or learning are necessary for the response to occur (see Chapter 3). Respondent conditioning (also referred to as classical, associative, or Pavlovian conditioning) is a process by which previously neutral stimuli come to elicit respondent behavior. For example, when something enters your eye (unconditioned stimulus), you blink (unconditioned response) and your eyes produce tears to clear out any debris. If a tone (i.e., a previously neutral stimulus) is repeatedly paired with something entering your eye (i.e., the unconditioned stimulus), the tone alone will come to elicit the blink and tears. Given that the source of control in respondent behavior is the antecedent, as opposed to the consequence as in operant behavior, the procedures used for conditioning and unconditioning differ with respondent behavior. As noted in the previous example, conditioning typically occurs by presenting a neutral stimulus just before or at the same time as presenting the stimulus that elicits the unconditioned response (i.e., reflex). While less common and effective, conditioning can occur when the stimulus that elicits the unconditioned response is presented before the neutral stimulus. Unconditioning, or weakening of a previously conditioned stimulus, occurs when the conditioned stimulus is presented repeatedly in the absence of the unconditioned stimulus (i.e., extinction). For example, presenting the tone A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00016-7

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from the aforementioned example in the absence of something entering your eye would eventually result in the tone no longer eliciting the blink and tears. While we often try to make a clear distinction between operant and respondent behavior, they often happen in concert. Take the common basic research example of a rat pressing a lever. Upon successful pressing of the lever, the rat is provided with food. This results in an increase in the probability of the rat pressing the lever under similar conditions. We are often taught this as a clear example of operant behavior. That may be the case if we are only interested in one piece of the rat’s behavior (i.e., lever pressing). However, if we are interested in the rat’s behavior as a whole, there are operant and respondent behaviors at play here. Food is not only an unconditioned reinforcer, but also an unconditioned stimulus that elicits salivation, the unconditioned response. Therefore, anytime food is involved, respondent behavior is also involved. If we take this view, the example gets more complex. Upon pressing the lever, the rat is presented with food. This food elicits salivation. The rat consumes the food with the assistance of the saliva produced by the presence of the food. The rat then is more likely to press the lever in future similar situations. A combination of operant and respondent effects are present. Respondent behavior can also play an important role when discussing behaviors such as emotions. That is, what we commonly refer to as emotions are the result of autonomic (involuntary) responses that are experienced as positive (pleasure, calmness) or negative (anxiety, fear) states. These respondent-elicited emotional states can influence operant behavior. The interplay of respondent and operant behavior related to emotions is well known and used within the world of marketing. For example, Pavlovian (stimulus-stimulus) contingencies embedded in stimulus control arrangements may limit the effectiveness of operant (response-reinforcer) contingencies (see Nevin, 2009). For example, Gorn (1982) evaluated the effectiveness of pairing preferred music with a product (i.e., a blue or beige pen) on the perceived preference for the product with 244 undergraduate students. In this study, the preferred music functioned as the unconditioned stimulus and the product functioned as the neutral stimulus. The results indicated that the pairing resulted in more positive emotional responses to the product and the participants were more likely to select the product when it was paired with preferred music. Watson and Rayner (1920) and Jones (1924) provided what are wellknown research examples of the application of conditioning and

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counterconditioning of respondent behavior. Specifically, Watson and Rayner conditioned a fear response in a 9-month-old boy. The unconditioned fear response was a startle reaction elicited when a steel bar was struck with a hammer. The fear response was conditioned by presenting a white rat and striking the steel bar when Albert reached toward the white rat. Following several pairings, Albert exhibited fear responses to the presence of the white rat alone. The fear response also generalized to other animals and items with shared features (e.g., rabbit, fur coat, mask with white fur). Jones (1924) followed-up on Watson and Rayner’s (1920) work to countercondition a fear response with a different participant, Peter. Peter was nearly 3 years old and exhibited similar fear responses to Albert in that “he was afraid of a white rat, and this fear extended to a rabbit, a fur coat, a feather, cotton wool, etc.” ( Jones, 1924, p. 309). Counterconditioning involved providing edible treats to Peter, with the food (unconditioned stimulus) evoking pleasure which mitigated the fear response as the rabbit was gradually and systematically moved closer to Peter. Ultimately, Peter’s fear response to the rabbit was eliminated, which also generalized to the other items. Joseph Wole was a pioneer in developing treatment based on respondent conditioning, extending the work of Watson, Rayner, and Jones. In Leaf et al.’s (2018) book Clinical Judgment, Wolpe’s work was discussed: Joseph Wolpe was a physician born, raised, and educated in South Africa. His training was in psychoanalysis. During World War II he worked as a medical officer with soldiers who had war neurosis (today referred to as post-traumatic stress disorder) … He found the commonly accepted approach of exploring a patient’s unconscious to be equally ineffective … After first demonstrating that fears could be “counter-conditioned” with cats, he went on to test the applicability of that approach on eliminating acquired anxiety and related emotional responses with humans. This became the foundation for his development of systematic desensitization, which was the first therapy to be termed as “behavior therapy.” … Wolpe’s work was critical to the field of behaviorism. He was able to develop procedures that were immediately effective and did not require years of therapy. If Watson was the father of behaviorism, Wolpe would have to be considered the father of behavior therapy (pp. 26–27).

Considerations related to respondent behavior in autism intervention Most behavior analysts are very conversant with the foundations of operant conditioning. They are knowledgeable with the works of Edward

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Thorndike and B. F. Skinner. Moreover, their understanding of behavior is based on the premise that behaviors are strengthened or weakened by environmental consequences. That is, if a response is followed by a reinforcing consequence, similar responses are more likely to occur in the future. Similarly, if a punishing consequence follows a response, then similar responses are less likely to occur. As a result, many procedures and teaching techniques are based on operant conditioning. Unfortunately, respondent behavior is, at best, an afterthought, and at worst, ignored completely within behavioral intervention for autistic children (Leaf & McEachin, 2016). Leaf and McEachin (2016) referred to this overlooking of respondent behavior in ABA-based interventions for autistic children as operant bigotry—a prejudice against respondent behavior in favor of operant behavior. This is a critical omission given the different procedures used in addressing operant and respondent behavior. That is, if a client is engaging in operant behavior, the methods and approach to addressing that behavior differ greatly than if a client is engaging in respondent behavior. Unsurprisingly, disruptive behaviors can be a result of respondent conditioning (e.g., aggression, crying, and tantrums could be related to stress). In the same way that a large dog may elicit fear as demonstrated by crying and clinging, being told “no,” loud noises, or the introduction of new foods may trigger a variety of disruptive behaviors. Similarly, novel situations may evoke jumping up and down, shrieking, or laughing. Changes in routine, peers or challenging tasks may bring out withdrawal. Clearly, behavior can be a combination of operant and respondent conditioning. For example, a child may avoid a situation as a result of fear (respondent conditioning) and also access reinforcement by escaping a nonpreferred task. Learning is complex! But interpreting behavior solely as a result of operant conditioning and developing a treatment based on this interpretation will likely make the treatment less effective. What follows are some examples of the benefits of considering respondent behavior in the course of ABA-based interventions for autistic children as well as examples of specific respondent conditioning procedures.

Some benefits of considering respondent behavior Extinction-based procedures While a sometimes controversial topic (Chazin et al., 2021; Lerman et al., 1999; Piazza et al., 2003), extinction-based procedures are commonly used within ABA-based interventions (Lerman et al., 1999; Piazza et al., 2003). This involves withholding the reinforcer for a previously reinforced

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response. For example, escape-extinction involves preventing escape for a response that previously resulted in escape. While this is an operant procedure, it can also result in emotional responding (Cooper et al., 2020). In these situations, ignoring the role of respondent behavior could lead to a focus on continuing to prevent escape even though that may not be appropriate or effective. If the behavior being presented is primarily respondent, treating it like operant behavior and continuing to block escape will likely lead to more emotional responding. This may also be a contributing factor to criticisms about ABA-based interventions. Considering respondent behavior throughout the course of intervention would allow the interventionist to alter the intervention and provide a more effective, compassionate intervention. Teaching emotions Given the interplay between operant and respondent behavior within emotional behavior, ABA-based interventions that teach emotions and responses to emotions are likely to be more effective when respondent behavior is included in the analysis. Treating emotions as an interplay between operant and respondent behavior provides the interventionist the flexibility to alter intervention strategies based on the type of behavior being presented. This is also likely to be beneficial when teaching clients how to identify and respond to their various emotions and emotional states. For example, if the only condition under which an interventionist teaches clients how to identify and respond to their various emotions and emotional states is related to operant behavior, an entire component related to emotional behavior is ignored.

Some respondent conditioning procedures Counter conditioning In Jones’ (1924) study, discussed previously, Peter’s fear of the rabbit was counter conditioned by pairing the rabbit with the incompatible response of eating which evoked relaxation. This technique is based on pairing responses that are incompatible with fears and anxiety to extinguish the anxiety. Wolpe identified five responses that are incompatible with anxiety and fear: relaxation, food, laughter, assertiveness, and sex. By pairing these responses with stimuli or situations that evoke fear, disruptive behaviors can be eliminated. As has been previously discussed, the source of control for respondent behavior differs from that of operant behavior. In operant behavior, the main source of control is the consequence—what follows the response.

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In respondent behavior, the main source of control is the antecedent—what precedes the response. This distinction makes how to treat respondent behavior throughout the course of intervention very different than operant behavior. If an anxiety response occurs to an unavoidable stimulus (e.g., getting your shirt a little wet, seeing a dog on a leash across the street), the interventionist must countercondition that stimulus. That can only happen if there is exposure to that stimulus. Protecting the child from exposure only perpetuates the problem. This means continually presenting the anxiety eliciting stimulus in the absence of any traumatic experience (e.g., getting knocked down by a frisky dog) until the emotional response is extinguished. This is a very important point and relevant to commonly used procedures such as flooding (e.g., Harris & Wiebe, 1992), systematic desensitization (e.g., Wolpe, 1961), and graduated exposure (e.g., Ellis et al., 2006) and this process is only possible if one considers operant and respondent behavior during intervention. Flooding can be conceptualized as nongraduated exposure in that the stimulus (or stimuli) that elicit the respondent behavior are all presented at once. For example, if a bee has been demonstrated to elicit a strong emotional response, flooding would involve exposing the individual to many bees at once, as well as bee-related stimuli (e.g., tall grass, flowers, buzzing sounds) all while ensuring that the child does not actually get stung by a bee. While an adult capable of making an informed choice might opt for flooding to achieve extinction in the shortest possible time, there are more humane ways to accomplish extinction with those who cannot make an informed choice. Graduated exposure and systematic desensitization, on the other hand, involve gradually introducing the stimulus (or stimuli) that elicit the respondent behavior taking to care to not exceed the point at which the learner opts to escape from the stimulus. This means gradually decreasing the distance between the individual and a bee, systematically increasing the volume of the buzzing sound, or exposing the individual to just one bee and gradually increasing the number of bees present while prompting coping responses, providing strong reinforcement, and pointing out to the learner the advantages of overcoming their fear.

Systematic desensitization Systematic desensitization uses counterconditioning but incorporates other procedures. First, it involves gradual exposure to the fearful stimulus. For example, while Peter was eating (the incompatible response) the rabbit was gradually introduced (i.e., across the room, halfway across the room,

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3 ft away, next to; Jones, 1924). A hierarchy of stress is established, ranging from stimuli that evoke a small fear response to maximal fear. For example, if a child exhibits fear of transitions, first you would identify all the changes that cause fear. Then create a hierarchy or transitions ranging from those that would be mildly stressful to maximally. For example: recess, snack, play, circle time, and workstations. Once a hierarchy is established and an incompatible response is identified and perhaps taught, intervention would start with counterconditioning at the lowest level of stress. Systematically and gradually proceeding through the hierarchy.

Other respondent techniques There are a number of other respondent techniques such as: extinction, forced extinction, flooding, and covert sensitization. However, these techniques will not be discussed because they are not applicable to autistic children. Moreover, than can be easily misused, have a punitive element, and require extensive training and supervision.

Summary The whole of our behavior is made up of operant and respondent behavior. For too long, conventional ABA-based interventions have ignored the role of respondent behavior within the course of intervention for autistics/individuals diagnosed with ASD. Within a progressive approach to ABA, by not ignoring the fact that our behavior is also comprised of respondent behavior permits the interventionist to be more effective by incorporating respondent and operant conditioning procedures into the intervention.

References Chazin, K. T., Velez, M. S., & Ledford, J. R. (2021). Reducing escape without escape extinction: A systematic review and meta-analysis of escape-based interventions. Journal of Behavioral Education, 31(1), 186–215. https://doi.org/10.1007/s10864-021-09453-2. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Ellis, E. M., Ala’i-Rosales, S. S., Glenn, S. S., Rosales-Ruiz, J., & Greenspoon, J. (2006). The effects of graduated exposure, modeling, and contingent social attention on tolerance to skin care products with two children with autism. Research in Developmental Disabilities, 27(6), 585–598. https://doi.org/10.1016/j.ridd.2005.05.009. Gorn, G. J. (1982). The effects of music in advertising on choice behavior: A classical conditioning approach. Journal of Marketing, 46(1), 94–101. https://doi.org/10.1177/ 002224298204600109.

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Harris, C. V., & Wiebe, D. J. (1992). An analysis of response prevention and flooding procedures in the treatment of adolescent obsessive compulsive disorder. Journal of Behavior Therapy and Experimental Psychiatry, 23(2), 107–115. https://doi.org/10.1016/00057916(92)90008-7. Jones, M. C. (1924). A laboratory study of fear: The case of peter. The Pedagogical Seminary and Journal of Genetic Psychology, 31(4), 308–315. https://doi.org/10.1080/08856559.1924. 9944851. Leaf, R., Leaf, J. B., & McEachin, J. (2018). Clinical judgment. DRL Books. Leaf, R., & McEachin, J. (2016). The Lovaas model: Love it or hate it, but first understand it. In R. G. Romanczyk, & J. McEachin (Eds.), Comprehensive models of autism spectrum disorder treatment (pp. 7–43). Springer. Lerman, D. C., Iwata, B. A., & Wallace, M. D. (1999). Side effects of extinction: Prevalence of bursting and aggression during the treatment of self-injurious behavior. Journal of Applied Behavior Analysis, 32(1), 1–8. https://doi.org/10.1901/jaba.1999.32-1. Nevin, J. A. (2009). Stimuli, reinforcers, and the persistence of behavior. The Behavior Analyst, 32, 285–291. https://doi.org/10.1007/BF03392191. Piazza, C. C., Patel, M. R., Gulotta, C. S., Sevin, B. M., & Layer, S. A. (2003). On the relative contributions of positive reinforcement and escape extinction in the treatment of food refusal. Journal of Applied Behavior Analysis, 36(3), 309–324. https://doi.org/ 10.1901/jaba.2003.36-309. Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology, 3(1), 1–14. https://doi.org/10.1037/h0069608. Wolpe, J. (1961). The systematic desensitization treatment of neuroses. The Journal of Nervous and Mental Disease, 132, 189–203. https://doi.org/10.1097/00005053-19610300000001.

CHAPTER 9

Task analysis and chaining Contents Task analysis Chaining Research Summary References

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Human behavior is complex, often difficult to define, and, therefore, can be difficult to teach. When working with learners diagnosed with autism spectrum disorder (ASD), we often cannot simply describe or model behaviors such as brushing teeth, joining into a game, or sharing toys and expect the learner to acquire the skill. This is because such complex skills consist of multiple behavioral components, sometimes referred to as behavioral steps. Component steps are smaller discrete units of behavior that are linked together in a series (e.g., turning on the faucet, grabbing the toothbrush by the handle, putting the toothbrush bristles under the water, putting toothpaste on the toothbrush) to make a composite behavior (i.e., toothbrushing). When these behavioral steps are put together in a chronological or logical order, they make a behavior chain. Analysis of these behavior chains allows interventionists a method to break down complex behaviors to teach them in a simpler and more manageable step-by-step manner as opposed to targeting the whole composite behavior at once.

Task analysis The process of defining a behavioral chain is known as task analysis, which involves breaking down a behavior into smaller behavioral steps. It should be noted that there is no universal task analysis for any skill, as the number of steps will vary from learner to learner, and relevant contextual variables (e.g., how family members complete the skill, specific environmental arrangements). Thus, within the Autism Partnership Method (APM), each task analysis must be individualized to meet the needs of the learner. It is A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00013-1

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imperative that interventionists have the skills needed to create accurate task analyses so they can more effectively teach complex skills. There are multiple ways to accomplish this goal. First, an interventionist could engage in and practice the targeted skill themselves and note and outline the necessary behavioral steps while completing the skill. In doing so, the interventionist can outline and describe each component and put those steps in the correct, logical order. The interventionist will take into account the specific environment the learner will encounter such as a lever-based faucet or a twist knob. They will also consider the developmental level of the learner and adapt the steps accordingly, such as using a toothpaste delivery method that requires less dexterity (e.g., pump vs flip-cap). A second common way for an interventionist to create a task analysis is to watch a competent model engage in the skill and write out the steps and sequence(s) of those steps. Watching a competent model who is similar to the learner may be imperative when working on social behaviors or language skills, as children often engage in social behaviors differently from adults and behaviors may change from peer group to peer group. In this case, using a same-aged peer model would be the most appropriate. For example, the way that children play tag may differ from school to school or the way adolescents talk to each other may vary from state to state. Thus, creating a task analysis by watching peer models will allow teaching a more authentic version of behavior chains as opposed to decontextualized skills. Another option for a competent model would be to watch a family member of the client complete the task. This may be especially important when it comes to daily living tasks as families often complete daily living tasks in different ways. For example, one family may use a dishwasher and load the dishwasher in a particular way while another family may hand wash and hand dry their dishes. These differences should be considered when developing a task analysis. Third, an interventionist can ask experts and other professionals to help create, define, or redefine a task analysis. Collaborating with others who engage in a complex behavior at a proficient level may help an interventionist create an accurate task analysis of a terminal behavior. However, the expert should be able to describe the method that was successful for them in the beginning stages of their professional development, not necessarily how they perform the skill at an expert level. For example, when teaching a sports skill, it may be important to identify some pivotal steps (e.g., hitting a ball off a tee or kicking a ball that is gently rolled toward them). This, once

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again, can provide an authentic breakdown of a complex skill. It should also be noted that an interventionist can engage more than one of these strategies to develop a task analysis. Regardless of the method used to develop the task analysis, the interventionist should pilot the task analysis with a learner to identify gaps in the steps or steps that need to be further broken down and modify the task analysis as needed. This allows tailoring the task analysis before formally teaching the skill and requires the interventionist to use their clinical judgment in making modifications. Once a task analysis has been created, it is important for the interventionist to determine the mastery criterion. In other words, how many of the behavioral steps does a learner have to engage in for a skill to be considered mastered. There are several variables that should be considered when developing and selecting a mastery criterion. First, what is the level of performance that is reasonable to require of the learner and if there are any steps that can be omitted, thereby allowing them to be more independent. For example, in preparing a cup of hot chocolate, a premeasured packet could be used instead of measuring out the powder from a large container. A second consideration is how many consecutive times the learner would need to complete the complex skill correctly and in how many different contexts. There may be instances where it is okay for a learner to engage in 80% of the behavioral steps (e.g., playing a game, sharing, turn taking) and other instances where a learner should engage in 100% of the steps (e.g., crossing the street, bathing, going to the bathroom). Next, the interventionist should identify which steps in a behavioral chain are critical steps (e.g., steps that a learner must display) and which steps might be nice to accomplish but are not critical. For example, when shopping at a store, a task analysis might consist of: (a) walking in the store, (b) getting a shopping cart, (c) putting items from your shopping list into the cart, (d) walking to the check-out lines, (e) putting your items on the checkout counter, (f ) saying “hi” to the cashier, (g) getting the appropriate amount of cash from their wallet, (h) handing it to the cashier, (i) collecting the change and receipt, (j) putting your items in a grocery bag, and (k) saying “thank you” to the cashier. An interventionist might determine that not all steps in this task analysis are critical for a learner to effectively shop. For example, an interventionist might determine that it might be far easier to teach how to insert a credit card into a terminal than to learn what amount of cash to give the cashier. Even though it might be a goal in the future to teach those math skills, for now the task can be completed without math skills being a barrier to completing a purchase.

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Finally, how the interventionist records data on the learner’s performance must be considered. Table 1 provides an example of a task analysis data sheet that can be used for data collection. The datasheet includes the terminal skill as well as the individual components that comprise the terminal skill. Additionally, an interventionist can mark whether and how the learner engaged in each component: independently correct (“+”); unprompted incorrect or not performed (“ ”); prompted correct (“P+”); or prompted

Table 1 Task analysis datasheet example. Target skill: Losing graciously data sheet Learner name: Behavioral step

Date

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Date

1 2 3

Learner faced the other person Learner made eye contact Learner had a neutral to positive facial expression 4 Learner had a neutral to positive voice tone 5 Learner had a relaxed body posture 6 Learner made a general congratulatory statement (e.g., “good game”) 7 Learner made a specific compliment about the game (e.g., “It was fun playing Uno with you”) 8 Learner made a statement that they would like to play again or asked to play again 9 Learner did not engage in challenging behavior (e.g., negative statements, aggression, crying) Total steps correct Percentage of steps correct + 2 P+ P2

Independent correct Independent incorrect Prompted correct Prompted incorrect

Date

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Table 2 Blank task analysis datasheet. Target skill: Learner name: Behavioral step

Date

Date

Date

Date

Date

1 2 3 4 5 6 7 8 9 10 11 12 Total steps correct Percentage of steps correct + 2 P+ P2

Independent correct Independent incorrect Prompted correct Prompted incorrect

incorrect (“P ”). This permits identification of what parts of the skill the learner needs further teaching to engage in independently. Table 2 provides a blank task analysis data sheet that interventionists can use for their own learners as they develop their own task analyses.

Chaining The creation of a task analysis is only the first step; the interventionist still needs to systematically and effectively teach each of the steps of the task analysis. Teaching one step at a time of a task analysis is commonly referred to as chaining and there are three methods for teaching a behavioral chain. The first chaining method is forward chaining. In forward chaining, a task analysis is created, and each step is targeted in sequential order starting with the first step. Once the first step is mastered, the second step of the task analysis is targeted, and reinforcement occurs when the learner engages in the

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first and second steps. This continues until the learner can demonstrate all steps of the task analysis. The second chaining method is backward chaining. In backward chaining, teaching begins with only teaching the last step. For example, to teach bed making, the learner is brought to a bed that is fully made, except the pillow is not in place, and the instruction is “Let’s learn how to make a bed.” The interventionist will use prompt fading and reinforcement until the learner performs the step independently. Once the learner reaches the mastery criterion on the final step, the second to last step is then targeted. This continues until the learner can proficiently demonstrate all steps of the task analysis. Backward chaining can be beneficial because the learner initially contacts the natural terminal reinforcer after completing only a single step, such as “That’s great, you made your bed! What would you like to have for breakfast?” The third chaining method is total task chaining (sometimes called whole-task presentation/chaining). In this method, the interventionist targets all steps of the task analysis during every teaching session. Thus, the interventionist provides prompts on steps in which the learner needs help and does not provide prompts for steps that the learner is displaying independently.

Research Many studies have been conducted evaluating the effectiveness of using task analyses (e.g., Blair et al., 2018; Lee et al., 2020; Parker & Kamps, 2011) and forward chaining (e.g., DeQuinzio et al., 2008; Guercio & Cormier, 2015; Shrestha et al., 2013), backward chaining (e.g., Edwards et al., 2018; Muharib et al., 2019; Richard & Noell, 2019), and total task chaining (e.g., Kayser et al., 1986; Spooner, 1984). Unfortunately, there have not been many published studies in this area within the APM. One exception was a study conducted by Cuvo et al. (1978). In this study, Cuvo and colleagues taught six janitorial skills to 11 participants diagnosed with intellectual disabilities (one diagnosed with ASD). The six skills included: (a) cleaning a mirror, (b) cleaning a sink, (c) cleaning a urinal, (d) cleaning a toilet, (e) returning equipment and emptying the trash can on each floor, and (f ) mopping the bathroom floor. Across the six skills, there was a total of 181 substeps taught across the skills. Cuvo and colleagues used four different prompt levels to teach the participants the skills and, through a multiple baseline design, the results demonstrated that participants were able to learn the targeted janitorial skills.

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DeQuinzio et al. (2008) taught four children diagnosed with autism how to share using a forward chaining procedure. DeQuinzio and colleagues created a show-give-play chain for sharing and used forward chaining and prompting to teach the participants to share. DeQuinzio and colleagues utilized a multiple baseline design across participants and the results indicated that forward chaining was effective in teaching sharing to the four participants. Although there is a plethora of research on task analysis and chaining, most research occurs in the context of other procedures such as selfmonitoring (e.g., Parker & Kamps, 2011), prompting (e.g., Blair et al., 2018), video modeling (e.g., Taylor et al., 1999), or behavioral skills training (e.g., Steinborn & Knapp, 1982). Therefore, task analysis and chaining procedures are often paired with other procedures that are implemented as part of the APM. Additionally, it is also common within our social skills research to use a task analysis to break down the targeted social skill. Commonly, the teaching interaction procedure and the Cool versus Not Cool procedure are used to teach these social skills based off the task analysis.

Summary Each of these chaining methods comes with its own benefits and limitations. While the research shows all three methods are effective teaching strategies, there is little evidence to show which method in which situations is more efficient with which type of learner. As such, the selection of the chaining method for each learner should be based on the learner, context, research, and the interventionist’s clinical judgment. It will also be important to periodically probe the whole task without any prompts. This allows the interventionist to analyze maintenance of previously mastered steps, assess generalization to nontargeted steps, and move on quickly when a skill is mastered as opposed to continually targeting already mastered skills.

References Blair, B. J., Weiss, J. S., & Ahearn, W. H. (2018). A comparison of task analysis training procedures. Education and Treatment of Children, 41(3), 357–369. https://doi.org/10.1353/ etc.2018.0019. Cuvo, A. J., Leaf, R. B., & Borakove, L. S. (1978). Teaching janitorial skills to the mentally retarded: Acquisition, generalization, and maintenance. Journal of Applied Behavior Analysis, 11(3), 345–355. https://doi.org/10.1901/jaba.1978.11-345. DeQuinzio, J. A., Townsend, D. B., & Poulson, C. L. (2008). The effects of forward chaining and contingent social interaction on the acquisition of complex sharing responses by

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children with autism. Research in Autism Spectrum Disorders, 2(2), 264–275. https://doi. org/10.1016/j.rasd.2007.06.006. Edwards, C. K., Landa, R. K., Frampton, S. E., & Shillingsburg, M. A. (2018). Increasing functional leisure engagement for children with autism using backward chaining. Behavior Modification, 42(1), 9–33. https://doi.org/10.1177/0145445517699929. Guercio, J. M., & Cormier, R. J. (2015). Blending stimulus fading procedures with forward chaining to address treatment resistance in an adult with an autism spectrum disorder. Behavior Analysis in Practice, 8(2), 215–218. https://doi.org/10.1007/s40617-0150060-5. Kayser, J. E., Billingsley, F. F., & Neel, R. S. (1986). A comparison of in-context and traditional approaches: Total task, single trial versus backward chaining, multiple trials. Journal of the Association for Persons with Severe Handicaps, 11(1), 28–38. Lee, G. T., Pu, Y., Xu, S., Lee, M. W., & Feng, H. (2020). Training car wash skills to Chinese adolescents with intellectual disability and autism spectrum disorder in the community. Journal of Special Education, 54(1), 16–28. https://doi.org/10.1177/0022466919852340. Muharib, R., Alzrayer, N. M., Wood, C. L., & Voggt, A. P. (2019). Backward chaining and speech-output technologies to enhance functional communication skills of children with autism spectrum disorder and developmental disabilities. Augmentative and Alternative Communication, 35(4), 251–262. https://doi.org/10.1080/07434618.2019.1704433. Parker, D., & Kamps, D. (2011). Effects of task analysis and self-monitoring for children with autism in multiple social settings. Focus on Autism and Other Developmental Disabilities, 26(3), 131–142. https://doi.org/10.1177/1088357610376945. Richard, P. R., III, & Noell, G. H. (2019). Teaching children with autism to tie their shoes using video prompt-models and backward chaining. Developmental Neurorehabilitation, 22(8), 509–515. https://doi.org/10.1080/17518423.2018.1518349. Shrestha, A., Anderson, A., & Moore, D. W. (2013). Using point-of-view video modeling and forward chaining to teach a functional self-help skill to a child with autism. Journal of Behavioral Education, 22(2), 157–167. https://doi.org/10.1007/s10864-012-9165-x. Spooner, F. (1984). Comparisons of backward chaining and total task presentation in training severely handicapped persons. Education and Training of the Mentally Retarded, 19(1), 15–22. Steinborn, M., & Knapp, T. J. (1982). Teaching an autistic child pedestrian skills. Journal of Behavior Therapy and Experimental Psychiatry, 13(4), 347–351. https://doi.org/ 10.1016/0005-7916(82)90083-0. Taylor, B. A., Levin, L., & Jasper, S. (1999). Increasing play-related statements in children with autism toward their siblings: Effects of video modeling. Journal of Developmental and Physical Disabilities, 11, 253–264. https://doi.org/10.1023/A:1021800716392.

CHAPTER 10

Shaping Contents A sample of research Clinical recommendations Avoid overreliance on protocols Contact the behavior analytic animal training literature Shape and shape often Take a nonlinear perspective Be patient Summary References

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Shaping is a powerful behavior analytic approach to developing and changing behavior. Peterson (2000) defined shaping as “a word that would suggest a distinction between the process of behavioral elaboration directed by constraints in the physical environment with mechanical connections to sources of reinforcement from behavioral elaboration directed by another organism” (p. 9). This description maps closely to Cooper et al.’s (2020) most recent definition, one which most practicing behavior analysts may find familiar, that shaping is a “three-part process whereby the analyst: (a) detects a change in the learner’s behavior, (b) makes a discriminated judgment about whether that change is a progressively closer approximation to a terminal behavior of interest, and then (c) differentially reinforces that closer successive approximation” (p. 541). Said differently, shaping involves expanding and refining response classes through the systematic use of reinforcement and in-the-moment assessment of the learner’s behavior.

A sample of research Shaping has a long history within behavior analysis and behavior analytic practice (Cihon, 2022; Peterson, 2000; Skinner, 1951; Wolf et al., 1963). As a result, there is a long history of research related to shaping. What follows is a brief, selected sample of the use of shaping with autistic individuals. This A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00026-X

Copyright © 2024 Elsevier Inc. All rights reserved.

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sample should not be viewed as an exhaustive literature review on the use of shaping. Wolf et al. (1963) provided an early demonstration and evaluation of the use of shaping with autistic individuals. As discussed in Chapter 1, Wolf and colleagues used shaping to teach a 3-year-old autistic boy, who was identified in this study by the pseudonym of “Dicky,” to wear his glasses. Dicky was at risk of permanent loss of vision because of his refusal to wear glasses. When attempts to physically force Dicky into wearing the glasses were not successful, assistance was sought from Wolf and colleagues. They recommended a shaping procedure and provided a research assistant to assist with the implementation. To begin the shaping procedure, clicks of a toy noisemaker were first conditioned to function as a reinforcer while several empty eyeglass frames were placed in Dicky’s room. Initially, reinforcement was provided anytime Dicky picked up, held, or carried the frames. Subsequently, reinforcement was only provided for approximations of bringing the frames closer to his eyes. However, the person implementing the shaping procedure had substantial difficulty getting Dicky to wear the empty eyeglass frames properly. As a result, the senior researchers (i.e., Montrose Wolf, Todd Risley, and Hayden Mees), who were not previously involved in the direct implementation of the intervention, conducted the shaping procedure for a day. Changes were then made to the frames (e.g., larger earpieces, a roll bar), and access to putative reinforcers (e.g., candy, fruit) was limited outside of shaping sessions. The changes resulted in rapid progress and the participant began to wear his glasses almost continuously during sessions in his room. As Dicky continued to be successful, supplemental reinforcement was shifted to naturally occurring reinforcers/contingences and wearing glasses was paired with preferred activities (e.g., snacks, going for walks). At the end of the study, Dicky was wearing his glasses for approximately 12 h each day upon his release from the hospital (Wolf et al., 1963). Bernal (1972) provided an extensive description and evaluation of the effectiveness of a parent-implemented shaping procedure for their child’s food selectivity. Specifically, Bernal (1972) trained the parents of a child with severe food selectivity to implement a multicomponent intervention that involved providing access to different foods without the requirement of consumption, systematically modifying the portions of preferred foods, and reinforcing approximations of sampling several foods. Prior to the intervention, the child’s mealtime behavior repertoire was analyzed, and consuming a variety of foods from a variety of food groups was selected as the terminal goal. Following establishing self-feeding of preferred foods,

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the first stage of the intervention involved the presentation of foods without a consumption requirement. The result of this stage of intervention was the child sampling three foods she had never eaten. The next stage of intervention was contingent access to a preferred food contingent upon sampling new foods during mealtimes. The mealtime context involved the full meal being available for the rest of the family and the child. Keeping in line with a shaping approach, the child’s responding was constantly assessed and was the basis for progression through the intervention. The results demonstrated that the child was consuming 50 foods she had previously never eaten, and the parents indicated the child’s weight and mealtime behavior (i.e., food selectivity) were no longer a concern. It is common for children, including those diagnosed with autism spectrum disorder (ASD), to be fearful of different contexts or stimuli. Treating fear responses in the general population commonly involves having the client remain in the proximity of the feared stimulus (rather than running away from or avoiding it), so that the anxiety response can extinguish (see Chapter 8). Shaping provides an alternative to the use of procedures that rely on escape extinction. Ricciardi et al. (2006) evaluated the use of shaping to increase approach responses to animatronic objects (e.g., dancing Elmo doll) of an 8-year-old boy with autistic disorder. His mother reported that fear of such common toys made it difficult for him to go to places in the community (e.g., stores, special events). Ricciardi et al. (2006) designed an intervention based on shaping the child’s tolerance of proximity to the feared items. Initially they provided noncontingent access to preferred items that were placed 6 m away from the animatronic objects (i.e., the objects that evoked fear responses). The distance of the animatronic objects from the preferred items was then systematically decreased from 6 m to the terminal criterion of only 1 m away from where the child was playing. The distance was reduced in increments as the child was successfully remaining in the vicinity of the toys for at least 90% of data recording intervals across two consecutive sessions. The results demonstrated that the shaping procedure was effective in that the participant remained in the targeted proximity to the previously avoided animatronic objects. Koegel et al. (2012) evaluated the effectiveness of shaping to increase the level of acceptance of new foods and spontaneous requests for new foods with three children diagnosed with autism. The intervention involved developing a hierarchy of acceptance: (a) refusing a food, (b) touching and motioning a food to the mouth, (c) putting a food on lips, (d) biting a food, (e) biting a food and putting in mouth but not swallowing,

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(f ) chewing a food but not swallowing, (g) swallowing a food reluctantly, and (h) accepting a food without displeasure or disruptive behavior. Participants were informed which step on the hierarchy was required to gain access to the putative reinforcer. Following successful demonstration of the behavior(s) on a level of the hierarchy across three consecutive probes without disruptive behavior, the next level of the hierarchy was targeted. The results indicated that the shaping intervention was successful as all three participants demonstrated an increase in the number of new foods consumed. All three participants were also observed requesting new foods during generalization probes. Fonger and Malott (2019) evaluated the effectiveness of a shaping procedure to teach three preschool-aged children diagnosed with ASD to engage in contextually appropriate eye contact. The intervention consisted of several phases that the participants progressed through the shaping procedure based on their performance in previous phases. To begin a trial, the interventionist prevented access to a preferred item and waited until the participant engaged in the targeted response before returning the item. The general flow of the phases consisted of first targeting orienting to the interventionist, then increasing the duration of eye contact, and then fading in high-probability instructions. It should also be noted that the preferred item was provided to the participant for 5 s after any latencies of the targeted response (e.g., eye contact) longer than 5 s. That is, eye contact was not forced as the preferred item could be obtained through other means. The results indicated that all three participants began to engage in quick, sustained eye contact in the absence of prompting. The results also generalized to other interventionists and contexts, and maintained up to 1 month following the intervention. Cihon et al. (2019) evaluated the effectiveness of shaping within a level contingency system to increase synchronous engagement with two dyads of children diagnosed with ASD. Synchronous engagement was defined as both children in the dyad engaged in the same activity while also displaying favorable affect. The level contingency system involved three tiers in which the participants moved up and down, within, and across levels, based on the interventionist’s in-the-moment assessment of the participants’ behavior. If the participant’s behavior represented a general improvement, the participant’s marker was moved up. If the participant’s behavior represented no improvement or decline, the participant’s marker was moved down. That is, there was no protocol dictating what and when the interventionist was to deliver or not deliver reinforcement. Rather, the interventionist assessed

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the participants’ behavior in-the-moment and the outcome of this assessment set the occasion for the interventionist’s behavior. The results demonstrated that shaping within a level contingency system resulted in an increase in the percentage of intervals in which synchronous engagement was observed for both dyads. Sivaraman et al. (2021) coached caregivers via telehealth on the implementation of graduated exposure and shaping to teach mask wearing for six children diagnosed with ASD. Similar to previous studies, the participants progressed through an exposure hierarchy consisting of 15 steps that started with the facemask being within 30 cm for 5 s and ended with wearing the facemask for 10 min before removing the facemask using the loops. This hierarchy was also modified (i.e., individualized) for two of the participants. The intervention consisted of first conducting a formal preference assessment, providing an instruction to wear a mask and a rationale for why the mask was important, modeling putting on the mask, and presenting the mask to the participant. Upon completing the targeted step in the hierarchy, in the absence of problem behavior, the caregiver provided praise and access to a preferred item. Following two successful occurrences at the targeted step, the next step was targeted. All six participants reached the final steps of the hierarchy, and the caregivers reported the intervention to be favorable.

Clinical recommendations The responsiveness required by the shaping process can result in practitioners requiring a substantial amount of time to attain fluency and effectiveness with shaping. Shaping requires constant assessment of the learner’s current and past behavior as well as any relevant contextual variables (e.g., the terminal goals and environments). It is highly unlikely that a practitioner could be provided with a protocol that they could follow verbatim that would allow them to shape behavior most effectively and efficiently. As a result, what follows are some clinical recommendations related to the use and training of shaping.

Avoid overreliance on protocols Perhaps the biggest challenge related to the use of shaping is training practitioners to be effective and efficient shapers. Commonly effective training methods for newer staff may be less effective or ineffective when shaping is the target skill. As previously stated, it is unfeasible to provide a new staff

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member a protocol with a series of contingencies (e.g., if-then statements) for how to respond based on the learner’s response. Protocols may be initially effective for procedures in which responding is more constrained (e.g., discrete trial teaching, with responding categorized as correct, incorrect, or prompted), but may be less effective when learner responding is less constrained. Furthermore, even if it is the case that a protocol leads to effective shaping, it does not lead to the development of the desired sources of stimulus control for the practitioner (e.g., the learner’s current and past behavior, contextual variables). Instead, practitioner responding would be a result of the protocol, which would interfere with development of reciprocity in the shaping process. Additionally, the use of a protocol may result in the development of a rule-governed repertoire and not a contingencyshaped repertoire, creating a context in which a practitioner could not perform well when there is no previously established rule. As a result, the use of a strict protocol in the use of shaping or training others to shape is not recommended. It should be noted, however, that there are some manualized training methods that rely on the use of an analog setting and direct contact with contingencies that have been developed and should continue to be explored (e.g., Portable Operant Research and Teaching Lab (PORTL); Hunter & Rosales-Ruiz, 2019). To most effectively train practitioners to become fluent and effective shapers, training will likely require extensive observations with a model, in vivo narration, and opportunities to shape in the terminal context (e.g., where intervention occurs). An already fluent, effective shaper can model shaping. While providing the model, they should narrate where possible. This narration could include the rationale and/or variables that are responsible for why they are responding the way in which they are responding. It will be important that the narration does not interfere with the shaping process. To prevent any possible interference, one person could provide the model while another supervisor/trainer discusses what is occurring. This method of training shapers can help explain how more experienced shapers respond to a variety of variables and conditions. Simply observing a model, with or without narration, is not likely to be an effective training method when used in isolation. If simply observing a model was enough, many individuals who watch cooking shows would be much better home cooks. Perhaps the most important recommendation with respect to training others to shape is to provide the trainee with ample opportunities to shape while receiving feedback from the learner and an experienced shaper. Opportunities to shape should involve a wide

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demographic of learners as well as targeted responses. Some responses may be easier to shape than others. Ensuring the trainee has multiple exemplars and opportunities to shape in the terminal context can help ensure the development of the practitioner’s shaping repertoire as contingency shaped as opposed to rule governed.

Contact the behavior analytic animal training literature As previously noted, there is an extensive literature base on the use of shaping. This is in addition to the extensive literature base documenting the effectiveness of the components of the shaping process (e.g., stimulus control, reinforcement, extinction). For those seeking guidance within the literature, we recommend examining the literature on shaping with nonhuman animals (e.g., Ferguson & Rosales-Ruiz, 2001; Pryor, 1999; Schaefer, 1970). The procedures commonly used by practitioners who provide intervention for autistic individuals are often not possible for those shaping the behavior of nonhuman animals. For example, physically prompting a dolphin, modeling for an elephant, or providing a vocal prompt for a nonvocal animal (e.g., rat, pigeon) may not be feasible, advisable, or effective. As a result, those behavior analysts shaping the behavior of nonhuman animals are likely to develop fluent, effective shaping repertoires because they rely on the shaping process in the absence of other supplemental procedures.

Shape and shape often Arguably, one of the best ways to become an effective and fluent shaper is to shape and shape frequently. Considering the reciprocal nature of the shaping process, the more often one shapes, the more opportunities there are for their behavior to be shaped by the learner’s behavior. The effect is expanding the practitioner’s shaping repertoire, which, in turn, allows the practitioner to respond more effectively while shaping.

Take a nonlinear perspective A common description of shaping is the use of differential reinforcement of successive approximations to a terminal response. Most reading this are likely to have encountered that description of shaping or something similar. The problem with this description is that it implies that the shaping process (or learning more generally) is a linear process. That is, moving from the learner’s current responding to the desired/targeted responding occurs along

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a series of unvarying, discrete steps. The result of this could be a list of responses in which one response is reinforced until a mastery criterion is met prior to reinforcing other responses in the list. The top panel of Fig. 1 provides a graphical representation of this linear perspective. Unfortunately, behavior does not always follow the desired path we have laid out

RESPONSES

LINEAR

LINEAR (actual responses)

NON-LINEAR

TIME

Fig. 1 A visual representation of linear and nonlinear approaches to shaping. Target responses within each perspective are represented by closed circles. Responses that may have been candidates for reinforcement but would not be reinforced in a linear perspective are represented by open circles.

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and this linear perspective to shaping may prevent the ultimate goal of being responsive to the moment-to-moment variations in the entire constellation of the learner’s behaviors. Ultimately, a linear view may result in a restricted view of responses that are candidates for reinforcement which could result in slowing or halting the learning process. The middle panel of Fig. 1 illustrates responses that may have been candidates for reinforcement (open circles) but may not be reinforced in a linear perspective if following a strict protocol. Alternately, nonlinear perspective permits the practitioner to focus on expanding response classes, which, in turn, increases the number of responses that may be candidates for reinforcement. The bottom panel on Fig. 1 provides an illustration of a nonlinear approach. As illustrated in Fig. 1, the response class begins rather small. As the shaping process continues, the response class is expanded. This permits the shaper to then narrow the response class to the desired topography during the later stages of the shaping process. A nonlinear perspective aligns with the effects of reinforcement, which is an increase in the probability of similar responses (i.e., expanding response classes) in future similar situations. That is, reinforcement increases the probability of similar responses some of which lead to the terminal goal and some of which may not. From this perspective, shaping increases the number of overall number of responses giving the practitioner more behavior and flexibility while shaping. The probability that these responses could be determined a priori to develop a series of discrete steps is low, at best.

Be patient With other effective procedures available in the practitioner’s toolbox, it can be difficult to remain patient while shaping. For example, many practitioners are likely to be familiar with and effective at using various prompts (e.g., model, physical, trace) and prompting systems (e.g., flexible prompt fading; Soluaga et al., 2008). Prompting, in some instances, may result in the learner displaying the skill more quickly than a pure shaping approach. As a result, practitioners may be quick to abandon shaping in favor of the use of prompts. While this may not create problems in all contexts, it may not always be possible or preferable to use prompts. Difficulty with remaining patient with the shaping process could also result in providing access to reinforcement when it may be more beneficial to withhold access to reinforcement. Hunter and Rosales-Ruiz (2019) examined the effects of providing access to a reinforcer during shaping following a period of no reinforcement

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followed by access to a single reinforcer for a new response. Hunter and Rosales-Ruiz found that a single reinforcer following a period of no reinforcement (which can commonly occur during shaping), resulted in spending more time interacting with an object (that resulted in the reinforcer) than interacting with other objects that had resulted in more frequent reinforcement. Also, the participants’ allocation of responses favored the new response over other responses. Ultimately, Hunter and Rosales-Ruiz noted that “one accidental reinforcer may result in an increase in an unrelated behavior, which could make it difficult to bring the learner back to approximations to the goal behavior” (p. 463). Therefore, it is essential that practitioners remain patient during the shaping process and avoid providing reinforcement for undesired responses at undesired times.

Summary Although shaping has a long history in behavior analysis and is a powerful approach to developing and changing behavior, it can take a substantial amount of time to become a fluent, effective shaper. The time it takes to become a fluent, effective shaper is largely related to the necessity for shaping repertoires to be contingency shaped as opposed to being rule governed. The reciprocal nature of shaping closely aligns with a progressive approach to ABA for autistic individuals which requires in-the-moment assessment and responsiveness to the learner. As a result, shaping is firmly situated within a progressive approach to ABA for autistic individuals.

References Bernal, M. E. (1972). Behavioral treatment of a child’s eating problem. Journal of Behavior Therapy and Experimental Psychiatry, 3(1), 43–50. https://doi.org/10.1016/0005-7916 (72)90032-8. Cihon, J. H. (2022). Shaping: A brief history, research overview, and recommendations. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & M. J. Weiss (Eds.), Handbook of applied behavior analysis interventions for autism (pp. 403–415). Springer. https://doi.org/10.1007/978-3030-96478-8_21. Cihon, J. H., Ferguson, J. L., Leaf, J. B., Leaf, R., McEachin, J., & Taubman, M. (2019). Use of a level system with flexible shaping to improve synchronous engagement. Behavior Analysis in Practice, 12(1), 44–51. https://doi.org/10.1007/s40617-018-0254-8. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Ferguson, D. L., & Rosales-Ruiz, J. (2001). Loading the problem loader: The effects of target training and shaping on trailer-loading behavior of horses. Journal of Applied Behavior Analysis, 34(4), 409–423. https://doi.org/10.1901/jaba.2001.34-409.

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Fonger, A. M., & Malott, R. W. (2019). Using shaping to teach eye contact to children with autism spectrum disorder. Behavior Analysis in Practice, 12(1), 216–221. https://doi.org/ 10.1007/s40617-018-0245-9. Hunter, M., & Rosales-Ruiz, J. (2019). The power of one reinforcer: The effect of a single reinforcer in the context of shaping. Journal of the Experimental Analysis of Behavior, 111(3), 449–464. https://doi.org/10.1002/jeab.517. Koegel, R. L., Bharoocha, A. A., Ribnick, C. B., Ribnick, R. C., Bucio, M. O., Fredeen, R. M., & Koegel, L. K. (2012). Using individualized reinforcers and hierarchical exposure to increase food flexibility in children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42(8), 1574–1581. https://doi.org/10.1007/ s10803-011-1392-9. Peterson, G. B. (2000). The discovery of shaping: Bf skinner’s big surprise. The Clicker Journal: The Magazine for Animal Trainers, 43, 6–13. Pryor, K. (1999). Don’t shoot the dog: The new art of teaching and training (rev. ed.). Bantam. Ricciardi, J. N., Luiselli, J. K., & Camare, M. (2006). Shaping approach responses as intervention for specific phobia in a child with autism. Journal of Applied Behavior Analysis, 39(4), 445–448. https://doi.org/10.1901/jaba.2006.158-05. Schaefer, H. H. (1970). Self-injurious behavior: Shaping “head banging” in monkeys. Journal of Applied Behavior Analysis, 3(2), 111–116. https://doi.org/10.1901/jaba.1970.3-111. Sivaraman, M., Virues-Ortega, J., & Roeyers, H. (2021). Telehealth mask wearing training for children with autism during the covid-19 pandemic. Journal of Applied Behavior Analysis, 54(1), 70–86. https://doi.org/10.1002/jaba.802. Skinner, B. F. (1951). How to teach animals. Scientific American, 185(6), 26–29. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j.rasd.2008.03.005. Wolf, M., Risley, T., & Mees, H. (1963). Application of operant conditioning procedures to the behaviour problems of an autistic child. Behaviour Research and Therapy, 1(2–4), 305–312. https://doi.org/10.1016/0005-7967(63)90045-7.

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CHAPTER 11

Prompting Contents Prompt types Prompting systems Common conventional prompting systems Flexible prompt fading: The APM prompting system Summary References

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Children diagnosed with autism spectrum disorder (ASD) often require assistance during teaching to engage in a targeted skill correctly. When an interventionist assists a learner to engage in a correct response, it is known as a prompt. A prompt is defined as any behavior that an interventionist engages in that increases the probability of the learner engaging in the correct response (Wolery et al., 1992). Since a prompt can be any type of behavior, there are multiple prompt types that can be implemented. A prompt type can be a controlling prompt (i.e., a prompt that guarantees the learner is going to respond correctly; Wolery et al., 1992) or a noncontrolling prompt (i.e., a prompt that does not guarantee the learner is going to respond correctly; Wolery et al., 1992). To help interventionists make decisions regarding how to prompt, when to prompt, and when to fade prompts, prompting systems have been developed. Similar to prompt types, there are multiple prompting systems that can be implemented throughout intervention. In this chapter, we first discuss prompt types and then prompt systems.

Prompt types Numerous prompt types are available to interventionists. One prompt type that is commonly used is a point/gestural prompt, which refers to pointing or gesturing to the correct stimulus such as pointing to the correct object immediately following the instruction when working on a receptive labeling task (e.g., touching different objects). An example would be asking for an item (e.g., “Where is the block?”) from a five-item array (e.g., apple, ball, A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00019-2

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block, cup, bear) and immediately pointing to the block to increase the likelihood of the learner selecting the correct item. A second type of prompt is a verbal prompt which is useful when the skill being taught involves spoken language. A full verbal prompt is the most assistive level of verbal prompt and involves the interventionist saying completely the word or phrase that is the desired response from the learner. For example, if the interventionist displays a ball and asks, “What is this?” and wishes to maximize the likelihood of the learner correctly naming the item, they would say the word “ball” as they display it, or shortly afterward. A partial verbal prompt involves saying only part of the word and is a less assistive level of prompt. In the example of teaching the label “ball,” the interventionist may say “ba” or “b” following the instruction. A model prompt involves modeling an action following an instruction that requires an action response. The model prompt can be a picture, video, or in vivo demonstration. For example, if the instruction is “kick the ball,” the interventionist could show a picture of the targeted response (e.g., kicking a ball) to facilitate the learner engaging in that action (e.g., kicking a ball) or the interventionist could model the targeted response (e.g., kicking a ball). The previously mentioned full verbal prompt could also be classified as a model prompt. Another prompt type is a written prompt. A written prompt involves writing out what action is to be performed by the learner and presenting the written text at the moment the action is expected. For example, giving the learner a piece of paper with “Hi, how are you?” written on it following an initiation from a peer. Many people rely on written prompts in their everyday actions (e.g., presenter notes in a slide presentation, instructions written on a box of frozen food). This type of prompt is also often used in procedures such as social and play scripts in which specified actions are written out and used as a prompt for the learner to engage in a target response. A physical prompt involves some form of hands-on guidance. A full physical prompt involves fully manipulating the learner’s body to engage in the correct response and is a controlling response. For example, the interventionist might take the learner’s hand and help them grip and throw a baseball. Or they may take a learner’s hand and fingers and manipulate them to properly grip a pencil. A partial physical prompt involves guiding the learner to the correct response through a light physical touch or gentle nudge and is a less assistive prompt. This can include a touch on the elbow, tapping a learner’s arm, or partially lifting a learner’s hand. A partial physical prompt could be

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nonspecific if it does not give away the answer, but just encourages the learner to get going. By comparison, a full physical prompt precludes the learner from being able to perform any part of the response on their own. There are three additional prompt types that are often associated with the Autism Partnership Method (APM). One of these is a positional prompt. A positional prompt is when “the teacher positions the target item closer to the student than the other objects, thereby increasing the likelihood the student will select the correct item” (Lovaas, 2003, p. 67). For example, when teaching a learner to select one of three picture cards, the interventionist might place the targeted card closer to the learner so they will be more likely to select that card. Some professionals have recommended against the use of positional prompts because of concern that it could lead to undesired stimulus control (e.g., location bias) or prompt dependency (see Grow & LeBlanc, 2013). Despite this recommendation, research has shown positional prompts can be effective in teaching skills to certain learners. Leaf, Cihon, et al. (2016) evaluated the use of positional prompts within in a least-to-most hierarchy for six children diagnosed with ASD. The only prompt type that was used was a positional prompt and the hierarchy ranged from having the target stimulus placed 12 in. closer to the learner, then 6 in. closer to the learner, and then no difference in placement in relation to the learner and the stimulus array. Leaf, Cihon, and colleagues taught participants to receptively identify college football teams, comic book characters, dinosaurs, or professional athletes and used a nonconcurrent multiple baseline design and found that positional prompts were effective for most participants. Thus, these results demonstrated that positional prompts can be an effective way to teach autistic individuals. Another useful type of prompt is recency prompt. When targeting vocabulary and conditional discrimination, the interventionist can increase the likelihood of a correct response by giving a closely spaced opportunity to repeat the same response in the presence of the same instruction. In this scenario, the prompt occurs before the trial begins, since the very recent occurrence of the same target increases the likelihood of making the correct response. For example, on trial 1, the interventionist shows a picture of a cow and asks, “What is this?” followed by immediately modeling the word, “cow.” When the learner correctly repeats the word, they access reinforcement. Then there is a brief pause and trial 2 consists of the same sequence, except the interventionist does not provide the modeling prompt. In this case, the very recent occurrence of trial 1 greatly increases the probability of a correct response on trial 2. It is easy to see how the immediate

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presentation of a third trial of the same target would also constitute a prompted trial using a recency prompt. This type of prompt can be faded by increasing the delay between trials or by interspersing trials with a different target, either of which weakens the strength of the recency prompt. There is one other usage of recency as a prompt which is sometimes referred to as priming. This is used in situations where there is a specific behavior that is desired in an upcoming situation. A priming prompt is provided in advance of the moment where the response is expected and can be faded by providing the prompt farther in advance of the situation where the response is desired. For example, “Remember, when you raise your hand in class, and the teacher does not call on you, you should quietly put your hand down and if you are feeling upset you can take a deep breath.” Priming prompts can also be faded by being less specific, such as saying, “Remember what to do when you don’t get called on in class” or “Remember what you are working on during group time.” Another prompt type that is commonly associated with the APM is reduction of the field. A reduction of the field prompt involves reducing the number of possible responses that the learner could make, thus increasing the probability of responding correctly as the number of possible choices is reduced. For example, if the interventionist is teaching a learner to match to sample in a field of three, the interventionist might take away one of the items from the sample array (i.e., making it a field of two) therefore increasing the chances of the learner responding correctly. There are several examples in the research where a reduction of the field prompt has been implemented effectively (e.g., Leaf, Leaf, et al., 2016; Soluaga et al., 2008). One last prompt we will mention here that is associated with the APM is the multiple alternative prompt. This prompt type involves providing multiple responses or choices, one of which is the desired response. For example, when teaching the learner to expressively identify superheroes, the interventionist might hold up a picture of Batman and ask “Who is it? Superman, Batman, or Green Lantern?” and wait for the learner to respond. The interventionist should randomize when the correct target appears within the list of multiple choices. The interventionist might start with distractors the learner already knows and then fade to unknown distractors. This way the learner might learn from exclusion (McIlvane & Stoddard, 1981; Wilkinson et al., 2009). Multiple alternative prompts are commonly used in combination with other prompt types (e.g., verbal, modeling). A variation on the multiple alternative prompt is the incorrect alternative prompt. In this case, the interventionist proposes an answer that is not actually

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correct but can lead the learner to come up with the answer on their own. For example, if the interventionist is targeting associations they might show a picture of a shoe and ask, “What do you do with this?” followed by the incorrect alternative, “Do you wear it on your head?” which increases the likelihood of a response of the desired association type (i.e., clothing item associated with body part). Incorrect alternative and multiple alternative prompts are conceptualized in the APM as “thinking” prompts because the learner is required to listen to possible choices, think about what they may know or not know from the list of options, and respond with their best answer. This differs from other prompts such as a full verbal prompt in which the learner only needs to echo what the interventionist has previously said. Leaf, Townley-Cochran, et al. (2016) compared model prompts to multiple alternative prompts to teach three children diagnosed with ASD expressive labels. Leaf, Townley-Cochran, and colleagues taught the participants a variety of expressive labels including tools, objects, cartoon characters, and sports teams. A most-to-least prompting system was used within both teaching conditions. In the model prompt condition, the prompting hierarchy included a full verbal prompt, then a partial verbal prompt, and then no prompt. In the multiple alternative prompt condition, the prompting hierarchy included a list of multiple alternatives with known distractors, then a list of multiple alternatives with unknown distractors, and then no prompt. The results showed that both prompt types were effective, but the multiple alternative prompts resulted in better maintenance for the participants included in the study. Thus, Leaf, Townley-Cochran, and colleagues’ results indicated that the use of multiple alternative prompts could be an appropriate prompting strategy for some learners diagnosed with ASD.

Prompting systems Prompt types are commonly arranged into prompting systems, which are rules/guidelines of when to provide prompts, when to fade prompts and what prompt types to implement. Currently, there are numerous prompting systems (e.g., least to most prompting, no-no-prompt, most-to-least prompting, progressive time delay) that have been empirically evaluated and clinically implemented in the field of applied behavior analysis (ABA). Within the APM, interventionists are not tied to a specific prompting system. They understand the principles underlying the evidence-based prompting systems we describe here and select prompting methods to be as

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efficient as possible with a specific child learning a specific skill. This approach is known as flexible prompt fading (Cihon et al., 2020; Leaf et al., 2014, 2019; Leaf, Leaf, et al., 2016; Soluaga et al., 2008). We will first describe some of the most widely used prompting systems, and then describe in detail flexible prompt fading, elements it shares with conventional approaches, and how it differs from them.

Common conventional prompting systems Simultaneous prompting One prompting system that can be used in behavioral intervention is simultaneous prompting (e.g., Leaf et al., 2010). Simultaneous prompting is a prompting system that is intended to be near-errorless (i.e., minimizing learner errors). Within this prompting system, only one prompt type is provided (i.e., a controlling prompt), which is implemented during every trial and is not faded, it is simply removed. Therefore, when using simultaneous prompting, every teaching trial is a prompted trial, and it is only during probes that the learner has the opportunity to respond independently. Prior to implementing simultaneous prompting, the interventionist should complete a controlling prompt assessment. During a controlling prompt assessment, the interventionist evaluates the effectiveness of different prompt types with unknown targets. Often symbols or unfamiliar letters (e.g., from a language the learner does not speak) are used as targets to ensure that the learner has no prior history with the targets. This is important to ensure that the learner’s correct or incorrect responding is solely based on the prompt type, not a previous learning history. The prompt type that results in 100% correct responding and is the least assistive is then used as the controlling prompt during teaching sessions. When using simultaneous prompting, trials are divided into probe and teaching trials. A teaching session starts with probe trials, which are unprompted opportunities for the learner to engage in the targeted behavior. A probe trial starts with the interventionist providing an instruction, a short period of time for the learner to respond (e.g., 5 s), and then feedback from the interventionist. When the learner responds correctly on 80%–100% of probe trials, the targeted skill is considered mastered. After a series of probe trials, the interventionist implements teaching trials. A teaching trial starts with the interventionist providing an instruction, immediately followed (i.e., 0 s delay) by the controlling prompt, an opportunity for the learner to respond, and then feedback. There are several studies that have evaluated the effects of simultaneous prompting for teaching a variety of skills, including handwashing

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(Parrott et al., 2000), names of relatives (Akmanoglu-Uludag & Batu, 2005), identifying numbers (Akmanoglu & Batu, 2004), leisure skills (Kurt & Tekin-Iftar, 2008), and self-help skills (Sewell et al., 1998). Morse and Schuster (2004) reviewed 18 studies that used simultaneous prompting. The review encompassed results from 70 participants, and found simultaneous prompting was effective across various instructional formats (e.g., one-to-one, small group, and large group), and a variety of behaviors (e.g., self-help, language skills, vocational tasks). The review also found some studies that compared the effectiveness of simultaneous prompting with other prompting systems. For example, Schuster et al. (1992) compared simultaneous prompting to constant time delay (described below) with four children diagnosed with intellectual disabilities. Schuster and colleagues used a verbal model as the controlling prompt and taught the participants sight words. The results demonstrated that both prompting systems were effective, but simultaneous prompting was more efficient. Constant time delay Another prompting system that is commonly implemented in conventional behavioral intervention is constant time delay (e.g., Chazin & Ledford, 2021). Constant time delay is a prompting system that involves fading prompts using a time delay. Like simultaneous prompting, only a controlling prompt is used in constant time delay. Within this prompting system, there are only two periods of time in which a prompt is provided: a 0 s delay and a specified short delay, typically ranging from 2 to 5 s following the instruction. Prior to implementing constant time delay, the interventionist should conduct a controlling prompt assessment (as described previously). Also, since the prompting system requires the learner to wait and not respond during the specified delay if they do not know the correct answer, it may require the interventionist to train a waiting response (see Leaf & McEachin, 1999; Soluaga et al., 2008). Constant time delay requires beginning with a block of teaching trials in which the interventionist provides the controlling prompt with a 0 s delay. Once the learner reaches a predetermined success criterion, the interventionist then moves to a block of teaching trials in which the learner can respond independently or wait for the predetermined period of time prior to the interventionist providing the controlling prompt. If the learner responds correctly with a 0 s delay or after the longer delay, then reinforcement is provided. It is highly recommended that independent responses result in higher quality/quantity/duration of reinforcement as opposed to prompted responses. If the learner responds incorrectly, then

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the interventionist provides corrective feedback and should remind the learner if they do not know the answer they should wait for help. If the learner responds incorrectly across multiple teaching trials, the interventionist may need to reteach a wait response. Additionally, the interventionist would return to the 0 s delay. Several studies have evaluated the effects of constant time delay for teaching various skills such as sight words (Gast et al., 1988), doing laundry (Miller & Test, 1989), sports skills (e.g., Zhang et al., 1995), and aquatic skills (e.g., Yilmaz et al., 2005). Walker (2008) conducted a review of the literature using constant time delay and progressive time delay (described below). Walker found 10 studies that evaluated constant time delay across 34 participants and various instructional formats (e.g., one-to-one, small group, large group) to teach a variety of behaviors (e.g., self-help, language skills, vocational tasks). Overall, constant time delay was found to be an effective prompting system for teaching a variety of skills.

Progressive time delay Another prompting system that is a variation of constant time delay is progressive time delay (e.g., Francis et al., 2020). Like constant time delay, progressive time delay is also a prompting system that fades prompts using a time delay. Unlike constant time delay, which only has two delay options (e.g., 0 and 2 s), progressive time delay fades the prompt across multiple time delays (e.g., 0, 1, 3, 5, and 7 s). Like simultaneous prompting and constant time delay, only a controlling prompt is used, and the prompt type provided never changes. Prior to implementing progressive time delay, the interventionist should conduct a controlling prompt assessment (described above) and ensure that the learner can wait for the provision of a prompt. Progressive time delay requires beginning with a block of teaching trials in which the teacher provides the controlling prompt with a 0 s delay. Once the learner reaches a predetermined criterion of correct responding at the 0 s delay, the interventionist then moves to a block of teaching trials in which the prompt is delayed by a specified time (e.g., 1 or 2 s). At this level, the learner can respond independently or wait for the interventionist to provide the controlling prompt. The duration of time before the controlling prompt is provided is increased in a predetermined sequence as each success criterion is met. If the learner begins to respond incorrectly, the interventionist may move down the time hierarchy and provide the controlling prompt earlier

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or teach the learner to wait for longer durations until the controlling prompt is provided. There have been several studies that have evaluated the effects of progressive time delay for teaching various skills such as sight words (Klaus et al., 2019), self-instruction (Smith et al., 2016), leisure skills (Carlile et al., 2013), imitation (Sweeney et al., 2018), and communicative gestures (Duker et al., 1997). In the aforementioned review, Walker (2008) found 12 studies that used progressive time delay. In this review, 31 participants were taught a variety of skills across multiple instructional formats. Like the results found using constant time delay procedures, progressive timedelay was also found to be an effective prompting system.

Least-to-most prompting Least-to-most prompting, sometimes referred to as system of least prompts, is a hierarchical prompting system in which the interventionist implements multiple prompt types (e.g., gestures, models, physical assistance) arranged from least to most assistive (Gil et al., 2019). This system is designed to minimize the delivery of unneeded prompts. The interventionist changes their prompt type and moves through the hierarchy based on the performance of the learner (Gil et al., 2019). To use least-to-most prompting, the interventionist must first identify and create a hierarchy of prompt types arranged from least to most assistive for the learner. Least-to-most prompting starts with the interventionist providing an initial instruction to the learner (e.g., “Touch the ball.”) without the provision of a prompt (i.e., least assistive). If the learner responds correctly (e.g., touching the ball), then reinforcement is provided, and the next trial is issued. If the learner responds incorrectly or does not respond to the instruction, then the next least assistive prompt, as determined by the prompt hierarchy, is provided on the next trial. If the learner then responds correctly, the interventionist provides reinforcement; if the learner responds incorrectly or does not respond to the instruction, then the next most assistive prompt is provided. This cycle repeats itself until the learner engages in a correct response or the interventionist implements the most assistive prompt (i.e., controlling prompt). Several studies have demonstrated the effectiveness of least-to most prompting for teaching various skills such as augmentative communication (Finke et al., 2017), language development (Humphreys et al., 2013), grocery shopping (Gil et al., 2019), and functional communication (Nepo et al., 2017).

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Most-to-least prompting Most-to-least prompting, otherwise known as system of decreasing assistance, is another hierarchical prompting system that uses multiple prompt types (Foran-Conn et al., 2021). Most-to-least prompting also involves the interventionist determining a hierarchy of prompt types prior to instruction, but in this system, prompts are arranged from the most to the least assistive prompt. This system is designed to minimize errors during skill acquisition. Most-to-least prompting starts with the interventionist providing an instruction followed immediately by the most assistive prompt necessary to produce a correct response (i.e., the controlling prompt). Gradually, over successive teaching trials, the interventionist fades the controlling prompt so that less assistive prompt types are used. Thus, over successive teaching trials, prompts are faded until the learner responds independently correct. There have been several studies that have evaluated the effects of mostto-least prompting for teaching various skills such as swimming (Yilmaz et al., 2010), laundry skills (Miller & Test, 1989), and receptive labels (Leaf, Leaf, et al., 2016). Libby et al. (2008) compared a most-to-least prompting system to a least-to-most prompting system for five individuals diagnosed with ASD. Libby et al. taught the participants to build Lego structures and the results showed that both prompting systems were effective. In another example, Fentress and Lerman (2012) compared most-to-least prompting to no-no-prompting (see below) to teach various skills to four children diagnosed with ASD. The results demonstrated that most-to-least prompting was effective for all participants. Although no-no-prompting produced more rapid mastery, maintenance was better with most-to-least prompting. No-no-prompting No-no-prompting (sometimes referred to as wrong-wrong-prompt) is a system designed to promote learning from errors. It involves the interventionist delivering an instruction followed by a period during which the learner has the opportunity to respond independently (Leaf et al., 2010). If the learner responds correctly, the interventionist provides reinforcement. If the learner responds incorrectly, the interventionist provides corrective feedback (e.g., “No”) and reissues the instruction. The learner then has an immediate second opportunity to respond independently with the same contingent consequences. If the second trial results in the learner making another error, the interventionist then provides a third trial for the same target. On this third trial, the interventionist issues the instruction and then

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immediately provides a controlling prompt. Since a controlling prompt is provided, the learner should respond correctly, and then reinforcement would be provided. No-no-prompting was first developed for a two-choice discrimination task in which the learners could learn from exclusion by hearing the feedback “no” if the response was incorrect. When using no-no-prompt, the learner has an opportunity to respond independently on the first trial. If the learner responds incorrectly then the feedback (e.g., “No”) should inform them that their response was incorrect, indirectly indicating that the other stimulus or response was correct. Therefore, on the next trial targeting the same response the learner should have a higher likelihood of responding correctly based on the previous feedback. If, however, the learner still responds incorrectly then the interventionist would provide the controlling prompt. Given that the rationale for no-no-prompt is to allow the learner to make errors as long as they are changing their response based on feedback, it is worth noting that a logical extension to a threechoice discrimination would be no-no-no-prompt. Although no-no-prompt was developed for two choice receptive discrimination training, researchers have demonstrated it to be effective in other formats, such as learning expressive labels (Leaf et al., 2011). Although no-no-prompt has been implemented clinically for years, there remains limited empirical research. Leaf et al. (2010) compared no-no-prompt to simultaneous prompting to teach various receptive tasks in a two-choice discrimination task with four individuals diagnosed with ASD. The results showed that no-no-prompting was effective in teaching all participants all targeted skills, whereas simultaneous prompting was ineffective for the majority of skills taught. There have been at least two followup studies on no-no-prompt. Leaf et al. (2011) showed that no-no-prompt could be effective in teaching individuals diagnosed with ASD an expressive label task in a small group instructional format. Fentress and Lerman (2012) also demonstrated that no-no-prompt was just as effective as most-to-least prompting. Stimulus fading Stimulus fading can be defined as “gradually shifting control from some dominant stimulus element to a different and criterion stimulus” (Etzel & LeBlanc, 1979, p. 369). When using stimulus fading, the interventionist gradually changes a noncriterion related dimension of the stimulus until the terminal stimulus is presented. For example, when teaching letter

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discrimination (e.g., “F” vs “E”), the interventionist might highlight the bottom line of the “E” with a bright color and gradually fade this coloring. In this example, none of the critical dimensions are changed but, rather, highlighted and then the highlighting is faded so that the student responding comes under control of the desired terminal stimulus. Stimulus fading has been used to teach a variety of behaviors including discrimination tasks (Rincover, 1978), identifying colors (e.g., Luiselli & Donellon, 1980), and food refusal (Freeman & Piazza, 1998). Stimulus shaping A procedure that is like stimulus fading is stimulus shaping. Stimulus shaping is when the interventionist changes the topography of the stimulus so that “the initial stimulus does not resemble the final or criterion-level stimulus on any dimension” (Etzel & LeBlanc, 1979, p. 370). For example, when teaching the letter “F” the interventionist might initially draw a picture of a frog (for the letter “F”) and gradually fade that picture over trials until the picture of the frog turns into the letter “F.” Both stimulus shaping and stimulus prompting are examples of within-stimulus prompting, where the prompt is embedded in the discriminative stimulus. When such a prompt is available, it may have the advantage that the learner’s attention is directed to the desired controlling stimulus from the outset, rather than to an external (and ultimately irrelevant) stimulus such as a pointing gesture. However, the disadvantage is that a within stimulus prompt is not by itself a controlling prompt and may therefore require the temporary use of an additional prompt to prevent errors.

Flexible prompt fading: The APM prompting system Within the APM, interventionists implement flexible prompt fading (Leaf, Leaf, et al., 2016). With flexible prompt fading, the interventionist makes in-the-moment assessment and decisions using clinical judgment regarding: (a) if a prompt should be provided, (b) when a prompt should be faded, and (c) which prompt type should be provided. Therefore, within this prompting system, an interventionist can implement any prompt type and can fade or increase the level of prompting at their discretion. These decisions are based on several important guidelines that are aimed at making instruction responsive to a broad constellation of variables that impact a learner’s progress. First, the goal when using flexible prompt fading is to ensure that the learner is responding correctly at a high rate, but still allow opportunities to

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learn from mistakes. The general recommendation is to aim for 80% correct responding, whether it is independent correct responding or prompted correct responding. This is critical for the learner to be successful and come in frequent contact with reinforcement. However, the optimal percent correct varies across learners and contexts, and should be thought of as a range that often varies from 75% to 90% and there are circumstances where the range could be even larger. Second, an interventionist can use any prompt type well suited for the learner and the target behavior. However, when the interventionist selects a prompt type, they should select the least assistive prompt they believe is necessary to ensure the learner will be successful. Third, fade all prompts as quickly as possible so that the learner is engaging in the target behavior independently under the desired stimulus control. When implementing flexible prompt fading, the interventionist’s behavior changes based on the learner’s responding and the interventionist is constantly assessing whether to prompt or not to prompt and what type of prompt to provide. This should be done based on careful observation of the learner’s behavior which informs clinical judgment and application of the guidelines stated above. Variables the interventionist should assess include the likelihood of the learner responding correctly or incorrectly on the next teaching trial weighed against the benefit or detriment that would result from an error. The likelihood of correct or incorrect responding could be based on multiple factors (e.g., recent history of errors, past performance, attending, engagement in challenging behavior, length of session). The interventionist is also considering what has been the impact of errors and corrective feedback on the learner’s recent and historical performance. For example, what is the likelihood that the learner will learn from a mistake vs become excessively frustrated at another failed trial? If the interventionist determines that the learner is likely to respond correctly on the next trial, then no prompt should be provided. If the interventionist determines that the learner is likely to respond incorrectly, then they first must determine if it is critical for the learner to respond correctly or not. If they determine that it is critical for the learner to experience at least some reinforcement, then the interventionist must determine the least assistive prompt likely to result in a correct response. Even when effort is suboptimal, some reinforcement may be necessary to prevent further worsening of behavior. Flexible prompt fading has been implemented clinically for decades with many individuals diagnosed with ASD. The prompting system was first implemented and described as part of the UCLA Young Autism Project

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(Lovaas, 1987; Lovaas et al., 1981) and later described in various curriculum books (e.g., Leaf & McEachin, 1999). However, it was only recently that flexible prompt fading has been empirically evaluated and published in the behavior analytic literature. The first empirical evaluation of flexible prompt fading was conducted by Soluaga et al. (2008). In this study, the researchers compared flexible prompt fading to a time delay prompting system for five individuals diagnosed with ASD. Soluaga and colleagues taught the participants different academic tasks (e.g., sight words, math facts). In the time delay condition, they only used a singular controlling prompt for each of the participants. In the flexible prompt fading condition, they used five different prompt types (i.e., reduction of the field, positional, model, gestural, physical) and the prompt types were used and faded at the researcher’s discretion. Soluaga and colleagues used a parallel treatment design to compare the two prompting procedures. The results indicated that both prompting systems were effective and there were idiosyncratic results in terms of efficiency across the prompting systems. One result of this study was the addition of time delay prompting methods to interventionists’ repertoire of prompt types used within flexible prompt fading, which is indicative of how the APM is progressive. Leaf et al. (2014) conducted a follow-up study on flexible prompt fading. In this study, Leaf and colleagues compared flexible prompt fading to error correction with four individuals diagnosed with ASD. Each participant was taught to expressively label 12 cartoon characters. Six labels were taught with flexible prompt fading and the other six were taught using error correction. Unlike the previous study, Leaf and colleagues were allowed to use any prompt type as part of flexible prompt fading and were able to determine when to prompt and how quickly to fade prompts using their discretion. The results indicated that both prompting procedures were effective, but flexible prompt fading was more efficient than error correction. Leaf, Leaf, et al. (2016) conducted another study comparing flexible prompt fading to most-to-least prompting with four individuals diagnosed with ASD. Each participant was taught to expressively label 12 pictures (i.e., sports teams, comic book characters, professions, places, Star Wars characters, or actions). Six pictures were taught with flexible prompt fading and six pictures were taught with most-to-least prompting. The most-to-least prompting consisted of a three-level hierarchy and in the flexible prompt fading condition Leaf, Leaf, and colleagues used clinical judgment to determine the prompt type to use, when to use a prompt, and how quickly to fade

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prompts. Like the previous studies, both prompting systems were effective. However, once again, flexible prompt fading was more efficient for three of the four participants and resulted in higher independent correct responding during teaching. More recently, Leaf et al. (2019) compared flexible prompt fading to no-no-prompting with four children diagnosed with ASD. Leaf and colleagues taught the participants to expressively label 10 pictures of athletes in the flexible prompt fading condition and 10 pictures of athletes in the no-no-prompt condition. The results indicated that both prompting procedures were effective. The results also demonstrated that flexible prompt fading resulted in a higher percentage of correct responding during teaching trials, but no-no-prompt was more preferred by the learners. Finally, the most recent evaluation of flexible prompt fading was conducted by Cihon and colleagues (2020). Unlike previous studies, which used a single subject design, this study used a randomized control trial. The study included 27 participants, all of whom were diagnosed with ASD. The participants were randomly placed into one of three prompting conditions: (a) constant time delay, (b) most-to-least, or (c) flexible prompt fading. Within each condition, the participants were taught to expressively label six pictures of Batman characters using the predetermined prompting procedure. Several measures were used throughout the study: (a) correct responding prior to teaching and following teaching using pre- and posttest measures, (b) generalization as assessed during trials where the participants were presented with different (i.e., untaught) pictures of the characters, (c) the number of sets mastered across the three prompting conditions, (d) the efficiency of the three prompting conditions, and (e) participant responding during teaching sessions in which the assigned prompting system was used. Cihon and colleagues (2020) executed a variety of statistical analyses across the various measures. First, the researchers showed that there was no statistically significant difference for the participants in terms of age, and scores on Expressive One Word Picture Vocabulary Test (Martin & Brownell, 2011), Peabody Picture Vocabulary Test (Dunn & Dunn, 2007), and Vineland Adaptive Behavior Scales (Sparrow et al., 2016). This was important so that any differences in responding were attributed to the teaching conditions and not participant demographic differences. Second, no statistically significant difference was found in terms of responding prior to teaching as all participants responded incorrectly on all pretest probes. Third, no statistically significant difference was found in terms of responding

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following teaching, as the average correct responding on posttests was 85%, 81%, and 83% for the most-to-least, constant time delay, and flexible prompt fading condition, respectively. Fourth, no statistically significant difference was found in terms of participant responding during generalization probes prior to teaching as all participants responded incorrectly on all probe trials. Fifth, no statistically significant difference was found in terms of responding to generalization targets following teaching, as the average correct responding on probes was 60%, 60%, and 40% for the most-to-least, constant time delay, and flexible prompt fading condition, respectively. Cihon and colleagues (2020) found that the mastery criterion was reached for 88.8%, 81.4%, and 88.8% of the sets across participants for the most-to-least, constant time delay, and flexible prompt fading condition, respectively. Flexible prompt fading required fewer teaching sessions for the participants to reach the mastery criterion, but this was not found to be statistically significant. Finally, participant independent correct responding during teaching sessions was at 57%, 58%, and 78% for most-to-least, constant time delay, and flexible prompt fading, respectively. The differences seen between the conditions were found to be statistically significant. In sum, the results of this study demonstrated that all three prompting systems were effective; however, flexible prompt fading has an advantage over the other two prompting systems in terms of efficiency and participant independent correct responding during teaching sessions.

Summary This research discussed within this chapter, taken collectively, indicates that flexible prompt fading is an effective way to teach learners diagnosed with ASD. Furthermore, it has advantages over conventional prompting systems (e.g., no-no-prompt, constant time delay, most-to-least) in that it can result in more independent correct responding during teaching and is often found to be more efficient. The results of the empirical research mirror what we have found for over 40 years of implementing flexible prompt fading, namely that it is a highly effective and efficient procedure.

References Akmanoglu, N., & Batu, S. (2004). Teaching pointing to numerals to individuals with autism using simultaneous prompting. Education and Training in Developmental Disabilities, 39(4), 326–336.

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Akmanoglu-Uludag, N., & Batu, S. (2005). Teaching naming relatives to individuals with autism using simultaneous prompting. Education and Training in Developmental Disabilities, 40(4), 401–410. Carlile, K. A., Reeve, S. A., Reeve, K. F., & DeBar, R. M. (2013). Using activity schedules on the iPod touch to teach leisure skills to children with autism. Education and Treatment of Children, 36(2), 33–57. https://doi.org/10.1353/etc.2013.0015. Chazin, K. T., & Ledford, J. R. (2021). Constant time delay and system of least prompts: Efficiency and child preference. Journal of Behavioral Education, 30(4), 684–707. https://doi.org/10.1007/s10864-020-09396-0. Cihon, J. H., Ferguson, J. L., Leaf, J. B., Milne, C. M., Leaf, R., & McEachin, J. (2020). A randomized clinical trial of three prompting systems to teach tact relations. Journal of Applied Behavior Analysis, 53(2), 727–743. https://doi.org/10.1002/jaba.617. Duker, P. C., van Deursen, W., de Wit, M., & Palmen, A. (1997). Establishing a receptive repertoire of communicative gestures with individuals who are profoundly mentally retarded. Education and Training in Mental Retardation and Developmental Disabilities, 32(4), 357–361. Dunn, L. M., & Dunn, D. M. (2007). Peabody picture vocabulary test (4th ed.). APA PsycTests. Etzel, B. C., & LeBlanc, J. M. (1979). The simplest treatment alternative: The law of parsimony applied to choosing appropriate instructional control and errorless-learning procedures for the difficult-to-teach child. Journal of Autism and Developmental Disorders, 9, 361–382. https://doi.org/10.1007/BF01531445. Fentress, G. M., & Lerman, D. C. (2012). A comparison of two prompting procedures for teaching basic skills to children with autism. Research in Autism Spectrum Disorders, 6(3), 1083–1090. https://doi.org/10.1016/j.rasd.2012.02.006. Finke, E. H., Davis, J. M., Benedict, M., Goga, L., Kelly, J., Palumbo, L., Peart, T., & Waters, S. (2017). Effects of a least-to-most prompting procedure on multisymbol message production in children with autism spectrum disorder who use augmentative and alternative communication. American Journal of Speech-Language Pathology, 26(1), 81–98. https://doi.org/10.1044/2016_AJSLP-14-0187. Foran-Conn, D., Hoerger, M., Kelly, E., Cross, R., Jones, S., Walley, H., & Firth, L. (2021). A comparison of most to least prompting, no-no prompting and responsive prompt delay procedures. Behavioral Interventions, 36(4), 1024–1041. https://doi.org/10.1002/ bin.1808. Francis, R., Winchester, C., Barton, E. E., Ledford, J. R., & Velez, M. (2020). Using progressive time delay to increase levels of peer imitation during play with preschoolers with disabilities. American Journal on Intellectual and Developmental Disabilities, 125(3), 186–199. https://doi.org/10.1352/1944-7558-125.3.186. Freeman, K. A., & Piazza, C. C. (1998). Combining stimulus fading, reinforcement, and extinction to treat food refusal. Journal of Applied Behavior Analysis, 31(4), 691–694. Win 1998 https://doi.org/10.1901/jaba.1998.31-691. Gast, D. L., Ault, M. J., Wolery, M., & Doyle, P. M. (1988). Comparison of constant time delay and the system of least prompts in teaching sight word reading to students with moderate retardation. Education and Training in Mental Retardation, 23(2), 117–128. Gil, V., Bennett, K. D., & Barbetta, P. M. (2019). Teaching young adults with intellectual disability grocery shopping skills in a community setting using least-to-most prompting. Behavior Analysis in Practice, 12(3), 649–653. https://doi.org/10.1007/s40617-01900340-x. Grow, L., & LeBlanc, L. (2013). Teaching receptive language skills: Recommendations for instructors. Behavior Analysis in Practice, 6(1), 56–75. https://doi.org/10.1007/ BF03391791. Humphreys, T., Polick, A. S., Howk, L. L., Thaxton, J. R., & Ivancic, A. P. (2013). An evaluation of repeating the discriminative stimulus when using least-to-most prompting

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to teach intraverbal behavior to children with autism. Journal of Applied Behavior Analysis, 46(2), 534–538. https://doi.org/10.1002/jaba.43v. Klaus, S., Hixson, M. D., Drevon, D. D., & Nutkins, C. (2019). A comparison of prompting methods to teach sight words to students with autism spectrum disorder. Behavioral Interventions, 34(3), 352–365. https://doi.org/10.1002/bin.1667. Kurt, O., & Tekin-Iftar, E. (2008). A comparison of constant time delay and simultaneous prompting within embedded instruction on teaching leisure skills to children with autism. Topics in Early Childhood Special Education, 28(1), 53–64. https://doi.org/ 10.1177/0271121408316046. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Leaf, R., & McEachin, J. (2019). Comparing no-no prompt to flexible prompt fading to teach expressive labels to individuals diagnosed with autism spectrum disorder. Education and Training in Autism and Developmental Disabilities, 54(3), 274–287. Leaf, J. B., Cihon, J. H., Townley-Cochran, D., Miller, K., Leaf, R., McEachin, J., & Taubman, M. (2016). An evaluation of positional prompts for teaching receptive identification to individuals diagnosed with autism spectrum disorder. Behavior Analysis in Practice, 9(4), 349–363. https://doi.org/10.1007/s40617-016-0146-8. Leaf, J. B., Leaf, J. A., Alcalay, A., Kassardjian, A., Tsuji, K., Dale, S., Ravid, D., Taubman, M., McEachin, J., & Leaf, R. (2016). Comparison of most-to-least prompting to flexible prompt fading for children with autism spectrum disorder. Exceptionality, 24(2), 109–122. https://doi.org/10.1080/09362835.2015.1064419. Leaf, J. B., Leaf, R., Taubman, M., McEachin, J., & Delmolino, L. (2014). Comparison of flexible prompt fading to error correction for children with autism spectrum disorder. Journal of Developmental and Physical Disabilities, 26(2), 203–224. https://doi.org/ 10.1007/s10882-013-9354-0. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, J. B., Oppenheim-Leaf, M. L., Dotson, W. H., Johnson, V. A., Courtemanche, A. B., Sheldon, J. B., & Sherman, J. A. (2011). Effects of no-no prompting on teaching expressive labeling of facial expressions to children with and without a pervasive developmental disorder. Education and Training in Autism and Developmental Disabilities, 46(2), 186–203. Leaf, J. B., Sheldon, J. B., & Sherman, J. A. (2010). Comparison of simultaneous prompting and no-no prompting in two-choice discrimination learning with children with autism. Journal of Applied Behavior Analysis, 43(2), 215–228. https://doi.org/10.1901/ jaba.2010.43-215. Leaf, J. B., Townley-Cochran, D., Mitchell, E., Milne, C., Alcalay, A., Leaf, J., Leaf, R., Taubman, M., McEachin, J., & Oppenheim-Leaf, M. L. (2016). Evaluation of multiple-alternative prompts during tact training. Journal of Applied Behavior Analysis, 49(2), 399–404. https://doi.org/10.1002/jaba.289. Libby, M. E., Weiss, J. S., Bancroft, S., & Ahearn, W. H. (2008). A comparison of most-toleast and least-to-most prompting on the acquisition of solitary play skills. Behavior Analysis in Practice, 1(1), 37–43. https://doi.org/10.1007/BF03391719. Lovaas, O. I. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55(1), 3–9. https://doi.org/10.1037/0022-006X.55.1.3. Lovaas, O. I. (2003). Teaching individuals with developmental delays: Basic intervention techniques. PRO-ED. Lovaas, O. I., Ackerman, A., Alexander, D., Firestone, P., Perkins, J., & Young, D. (1981). Teaching developmentally disabled children: The ME book. Austin, TX: Pro-Ed, Inc. Luiselli, J. K., & Donellon, S. (1980). Use of a visual stimulus fading procedure to teach color naming to an autistic child. Journal of Behavior Therapy and Experimental Psychiatry, 11(1), 73–76. https://doi.org/10.1016/0005-7916(80)90057-9.

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Martin, N. A., & Brownell, R. (2011). Expressive one-word picture vocabulary test (4th ed.). Pro-Ed. McIlvane, W. J., & Stoddard, T. (1981). Acquisition of matching-to-sample performances in severe retardation: Learning by exclusion. Journal of Mental Deficiency Research, 25(1), 33–48. Miller, U. C., & Test, D. W. (1989). A comparison of constant time delay and most-to-least prompting in teaching laundry skills to students with moderate retardation. Education and Training in Mental Retardation, 24(4), 363–370. Morse, T. E., & Schuster, J. W. (2004). Simultaneous prompting: A review of the literature. Education and Training in Developmental Disabilities, 39(2), 153–168. Nepo, K., Tincani, M., Axelrod, S., & Meszaros, L. (2017). iPod Touch® to increase functional communication of adults with autism spectrum disorder and significant intellectual disability. Focus on Autism and Other Developmental Disabilities, 32(3), 209–217. https:// doi.org/10.1177/1088357615612752. Parrott, K. A., Schuster, J. W., Collins, B. C., & Gassaway, L. J. (2000). Simultaneous prompting and instructive feedback when teaching chained tasks. Journal of Behavioral Education, 10(1), 3–19. https://doi.org/10.1023/A:1016639721684. Rincover, A. (1978). Variables affecting stimulus fading and discriminative responding in psychotic children. Journal of Abnormal Psychology, 87(5), 541–553. https://doi.org/ 10.1037/0021-843X.87.5.541. Schuster, J. W., Griffen, A. K., & Wolery, M. (1992). Comparison of simultaneous prompting and constant time delay procedures in teaching sight words to elementary students with moderate mental retardation. Journal of Behavioral Education, 2(3), 305–325. https:// doi.org/10.1007/BF00948820. Sewell, T. J., Collins, B. C., Hemmeter, M. L., & Schuster, J. W. (1998). Using simultaneous prompting within an activity-based format to teach dressing skills to preschoolers with developmental delays. Journal of Early Intervention, 21(2), 132–145. https://doi.org/ 10.1177/105381519802100206. Smith, K. A., Ayres, K. A., Alexander, J., Ledford, J. R., Shepley, C., & Shepley, S. B. (2016). Initiation and generalization of self-instructional skills in adolescents with autism and intellectual disability. Journal of Autism and Developmental Disorders, 46(4), 1196–1209. https://doi.org/10.1007/s10803-015-2654-8. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j.rasd.2008.03.005. Sparrow, S. S., Cicchetti, D. V., & Saulnier, C. A. (2016). Vineland adaptive behavior scales (3rd ed.). Pearson. Sweeney, E., Barton, E. E., & Ledford, J. R. (2018). Using progressive time delay to increase levels of peer imitation during sculpting play. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-018-3638-2. Advance online publication. Walker, G. (2008). Constant and progressive time delay procedures for teaching children with autism: A literature review. Journal of Autism and Developmental Disorders, 38(2), 261–275. https://doi.org/10.1007/s10803-007-0390-4. Wilkinson, K. M., Rosenquist, C., & McIlvane, W. J. (2009). Exclusion learning and emergent symbolic category formation in individuals with severe language impairments and intellectual disabilities. The Psychological Record, 59(2), 187–206. https://doi.org/ 10.1007/BF03395658. Wolery, M., Ault, M. J., & Doyle, P. (1992). Teaching students with moderate to severe disabilities: Use of response prompting strategies. Longman Pub Group. Yilmaz, I_ ., Birkan, B., Konukman, F., & Erkan, M. (2005). Using a constant time delay procedure to teach aquatic play skills to children with autism. Education and Training in Developmental Disabilities, 40(2), 171–182.

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Yilmaz, I¨., Konukman, F., Birkan, B., & Yanardag, M. (2010). Effects of most to least prompting on teaching simple progression swimming skill for children with autism. Education and Training in Autism and Developmental Disabilities, 45(3), 440–448. Zhang, J., Gast, D., Horvat, M., & Dattilo, J. (1995). The effectiveness of a constant time delay procedure on teaching lifetime sport skills to adolescents with severe to profound intellectual disabilities. Education and Training in Mental Retardation and Developmental Disabilities, 30(1), 51–64.

CHAPTER 12

Discrete trial teaching Contents Components of DTT Instructional format Field size Placement and rotation of stimuli Trial order The discriminative stimulus Prompts Learner’s response Feedback Instructive feedback Intertrial interval Mass trialing vs interspersal Simple-to-conditional or conditional only Summary References

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Discrete trial teaching (DTT) is one of the most implemented teaching methods used within interventions for children diagnosed with autism spectrum disorder (ASD; Ferguson et al., 2020; Gutierrez et al., 2009; Kurt, 2011; Leaf et al., 2013). DTT consists of implementing a series of trials within a teaching session and consists of three primary components: (a) a discriminative stimulus (e.g., instruction) provided or arranged by the interventionist, (b) a response by the learner, and (c) a contingent consequence provided by the interventionist (i.e., reinforcement or corrective feedback). If the learner responds correctly (i.e., the response corresponds to the instruction), the interventionist provides a reinforcing consequence. If the learner responds incorrectly (i.e., the response does not correspond to the instruction), the interventionist does not provide reinforcement and may provide corrective feedback or other punishing consequence. Within a discrete trial, an optional and commonly used fourth component is the provision of a prompt (see Chapter 11). DTT has been used to teach a variety of skills, including, but not limited to, receptive labels (e.g., DiGennaro Reed et al., 2011), expressive labels (e.g., Conallen & Reed, 2016), question A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00018-0

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asking (e.g., Ingvarsson & Hollobaugh, 2010), play skills (e.g., NuzzoloGomez et al., 2002), and social skills (e.g., Shillingsburg et al., 2014). Professionals have described DTT in experimental studies (e.g., Taubman et al., 2013), books (e.g., Leaf & McEachin, 1999), commentaries (e.g., Ghezzi, 2007; Smith, 2001), and book chapters (e.g., Lerman et al., 2016). Effective swim instructors, baseball coaches, and university professors use DTT although they may not be cognizant of the principles of applied behavior analysis (ABA). DTT may appear to be a simple procedure, but there is a multitude of decisions that an interventionist must make throughout the teaching process, making it a more complex teaching procedure than it appears.

Components of DTT Instructional format Although DTT is commonly associated with one-to-one teaching (Leaf et al., 2013), it can and should be implemented within a group instructional format for learners who demonstrate the prerequisite skills to learn in a group. Within the Autism Partnership Method (APM), learners typically receive what has been termed a progressive approach to DTT (Leaf, Cihon, et al., 2016) in one-to-one and group instructional formats. One goal of quality behavioral intervention should be to teach learners the prerequisite and learning-how-to-learn skills (see Chapter 24) so they can learn in a group instructional format. This is especially important as children grow older, and the classroom becomes the most readily available environment for learning. Thus, within the APM method, group DTT is commonly implemented early in intervention, including with young learners. One-to-one instructional format When implementing DTT in a one-to-one instructional format, there are two primary ways that the interventionist can implement a discrete trial. First, the interventionist could implement DTT in a structured manner with limited distractions to increase the likelihood the learner focuses their attention on the targeted skill (Sigafoos et al., 2019). A second option is that the interventionist could embed instructions into an activity or game (Cheung et al., 2022) using naturalistic teaching methods. In a progressive approach to behavioral intervention, the child should be learning in the most natural environment possible. There has been an abundance of research showing that DTT is effective in a one-to-one instructional format

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(e.g., Geiger et al., 2012; Leaf et al., 2010; Leaf, Alcalay, et al., 2016) and it is identified as evidence-based practice as a part of the comprehensive behavioral intervention (e.g., National Autism Center, 2015). Group instructional format When implementing group instruction, there are several ways that an interventionist might use DTT. One way is to use sequential trials (Leaf, Milne, et al., 2020). A sequential trial is when the interventionist provides instruction to each learner individually in a sequential order from learner to learner. For example, if there was a group of four students, the interventionist might start with a trial of the first student, then the second, then the third, and then finally the fourth student. This can be done in a true sequential order like in the previous example or in a random sequential order (e.g., student 2, then 3, then 1, then 4). A child could receive more than one trial before the interventionist moves to the next student. Also, the interventionist should ensure that the learner who needs the highest rate of opportunity for active responding (e.g., because of limited attending skills) receives a proportionately higher share of the trials. Within a group instructional format, an interventionist can also implement choral discrete trials (Leaf, Milne, et al., 2020). When implementing choral discrete trials, the interventionist provides instruction with the expectation that all learners in the group would respond simultaneously. For example, if teaching a group of students to expressively label sight words, the interventionist would show the sight word to all members of the group, provide an instruction (e.g., Everyone, what does this word say?), and then have all learners respond simultaneously. An advantage of choral responding is every learner gets the maximum number of active learning opportunities. A third type of discrete trial that can be implemented in a group setting is an overlapping trial, in which one learner’s response sets the occasion for another learner’s response (Leaf, Milne, et al., 2020). For example, an interventionist might ask one learner to retrieve something from across the room and then asks another a question before closing the first trial. Research has evaluated the effects of group DTT on autistic children (Leaf et al., 2013) as well as compared one-to-one DTT to group DTT (Leaf et al., 2013). For example, Ledford et al. (2008) evaluated DTT implemented in a small group instructional format (i.e., a dyad of students) to teach sight words to children ages 5–8 years old. The main purpose of the study was for the participants to learn new sight words through observational learning in the group setting. Ledford and colleagues used a constant-time delay prompting

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procedure as a component of group DTT. The results were positive in that the majority of the participants learned 100% of targets taught to their peers, showing a benefit of group instruction compared to one-on-one. Leaf et al. (2013) compared group DTT to one-to one DTT for six children diagnosed with ASD. Participants were randomly divided into two groups of three children. The researchers taught participants to expressively label pictures, job functions, inferences, and materials needed for play. The stimuli used were divided into sets so that some targets were only taught directly in one-to-one instruction and the other targets were directly taught in group instruction format. For the targets taught in group instruction, opportunities for observational learning also occurred (i.e., skills could be learned by observing instruction to another group member). The participants in this study acquired the targeted skills in both instructional formats, demonstrating that DTT was an effective procedure regardless of being implemented in a one-to-one vs group format. Second, Leaf and colleagues (2013) found that during group DTT instruction, the participants also learned the targets that they were not directly taught. This study demonstrates that when DTT is implemented in a group format, additional learning can occur without any additional direct teaching. One goal within the APM is to teach clients how to learn in a group setting as soon as possible. Before a learner can acquire new skills in a group instructional format, there are a few variables that an interventionist must take into consideration. First, the learner should already have a variety of items that function as reinforcers. If reinforcers are limited, it may be more important to work on conditioning and developing reinforcers to keep motivation high and avoid satiation throughout teaching. Second, the learner should refrain from engaging in behaviors that would interfere with the learning of their group mates. This could include talking out, getting up from the group, making silly sounds, or engaging in vocal or motor stereotypy that is distracting to other members of the group. Finally, a learner should demonstrate a variety of learning-how-to-learn behaviors (e.g., waiting, attending, understanding contingencies, responding to prompts, sitting appropriately). Learning-how-to-learn behaviors (see Chapter 24) are essential for a learner to successfully learn in a group environment. If these prerequisite skills are not in a learner’s repertoire, then they would first need to be taught before group DTT is appropriate for that learner. Ultimately, an interventionist should make individualized decisions if their learner is ready for group instruction.

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Field size When using DTT to teach skills such as receptive labels, sorting, or matching, an interventionist must determine the number of stimuli to place in the array of choices. For example, if teaching a learner to receptively identify pictures of comic book characters (e.g., Ironman, Batman, Spiderman), the array should include at least two pictures (i.e., Spiderman and Batman), but could it be three pictures (i.e., Ironman, Batman, Spiderman), or even more? Additional considerations may include increasing the size of the array to also include pictures of known comic book characters. Some researchers have proposed best-practice recommendations for determining the size of an array (also known as field size). For example, Green (2001) stated that “for most purposes, it is preferable to have at least three comparisons on every trial” (p. 76). Grow and LeBlanc (2013) further recommended, “A good rule of thumb is to include at least three new targets at the start of training to reduce the likelihood of reinforcing correct responses occurring under faulty stimulus control (e.g., position biases)” (p. 63). Within the APM, the determination of field size depends on a variety of variables for each learner. One variable to consider is whether high levels of chance correct responding (i.e., lucky guesses) would be acceptable in the absence of prompting from the interventionist. For example, if implementing a matching program with a field of two, there is a 50% chance the learner could respond correctly without actually knowing the correct response. When the field size is increased to three, there is a 33% chance the learner will guess correctly on one trial, and only 11% chance of correctly guessing on two consecutive trials. Alternatively, the field size can be decreased to a field of one and ensure the learner will respond correctly. For example, if targeting the behavior of picking up a card and handing it to the interventionist without bending the card, it would make sense to have only one card on the table, to remove the challenge of having to simultaneously make a correct choice of which card to pick up. Another variable to consider is the learner’s attending and scanning skills. If the learner has a more advanced scanning repertoire, then a larger field size may be more appropriate. Finally, the interventionist must determine how difficult the skill is for the learner. If the task involves fine discriminations (e.g., sequencing pictures) then a smaller field size might be justified. Wechsung et al. (2023) compared the acquisition of targets in a field size of two compared to a field size of three when using DTT. In this study, Wechsung and colleagues taught three autistic children to receptively label

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pictures of comic book characters. In the field size of three condition, there were two novel targets and one mastered target in the array. In the field size of two, both targets were novel. Therefore, it was not determined what would happen if all targets were novel in the larger field of three. Additionally, due to COVID-19 all sessions were conducted via telehealth using the Zoom Communications platform. The results of this study showed that participants reached the mastery criterion for all targets regardless of field size. Additionally, the efficiency of learning between the two conditions was idiosyncratic across the three participants. Thus, no real difference was found between the two conditions. This, however, was one of the first studies of its kind and more research is needed to determine how learning is affected when various field sizes are used during DTT.

Placement and rotation of stimuli Another decision that interventionists must make is the placement of stimuli when using DTT to teach skills that require a stimulus array. One common conventional approach is to counterbalance the placement and rotation of stimuli in an array, so that each targeted stimulus is placed in each location and equal number of times and rotated in a specific way (Grow & LeBlanc, 2013). Within the APM, however, an interventionist uses in-the-moment assessment to make decisions about the placement of stimuli in an array and when to rotate the stimuli. Interventionists are not provided with rules regarding placement and rotation. Rather, an interventionist makes in-the-moment decisions based on several considerations. For example, if a learner is showing a location bias (e.g., selects only the stimulus on the left side), then an interventionist would use this assessment to inform their decision for placement by avoiding placing a stimulus on that side as to not inadvertently provide intermittent reinforcement. Additionally, the interventionist must analyze the learner’s past responding. For example, an interventionist might switch the placement of the target stimulus if the learner was correctly responding on consecutive trials, or the interventionist might not move or rotate the stimuli too quickly if a learner has challenges related to attending. Additionally, interventionists must ensure that stimuli placement does not lead to arbitrary response patterns based on location of targets. Leaf et al. (2018) evaluated the placement and rotation of stimuli in a field of three during a receptive label task for five individuals diagnosed with ASD. In this study, Leaf and colleagues compared counterbalancing the

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rotation and placement to in-the-moment assessment of placement (described previously), to a fixed placement of stimuli. Leaf and colleagues found that the results were idiosyncratic across participants and sets in terms of effectiveness and efficiency of each condition. Thus, the results indicated that the rotation and placement of stimuli did not impact the learning of the individuals in the study. Therefore, the placement and rotation of the stimulus array should be based on the learner, not determined a priori. There are three other DTT procedural details that are notable for lack of consensus among practitioners. Going back to the days of the UCLA Young Autism Project, it was sometimes advocated to briefly remove all stimuli (or cover up the stimulus array) prior to starting a new trial. This can be observed in training videos disseminated by the project (Lovaas et al., 1981) and is still commonly practiced today. The main rationale for this procedural detail is to maintain discreteness and separation of trials. There is no research demonstrating that this is necessary but abundant evidence that both methods work. A second point of disagreement is whether the verbal component of the discriminative stimulus (i.e., the instruction) should be delivered with the field in view or out of view of the learner. Again, both variations have been demonstrated as effective, but there is no empirical basis for claiming that one approach is superior to the other. Finally, related to the timing of the presentation of the field, some practitioners require a specific observing response from the learner prior to revealing the stimulus array. An observing response is an affirmative indication that the learner is oriented to the learning task such as tapping on the shield that is covering the stimulus array. Within the APM, the observing response is considered a vital component of the learning process, but hiding the stimulus array is not the only way to achieve this. An alternative is to simply withhold the second component of the two-part discriminative stimulus until an observing response occurs. For example, in a receptive learning task, the field remains in place and the interventionist waits for the learner to either look at the stimulus array or to glance at the interventionist to trigger delivery of the verbal instruction. In effect, the interventionist is teaching the learner to not only be ready to learn, but to indicate that they are ready. The removal of stimuli between trials or rearrangement of stimuli is not inherently necessary.

Trial order When implementing consecutive discrete trials, another decision that needs to be made is the order of trials for targeted skills within a teaching session.

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Like the placement of stimuli, in the conventional model the recommendation for trial order is counterbalanced and is commonly outlined on a datasheet prior to the teaching session (e.g., Grow & LeBlanc, 2013). In the APM, the trial order is not predetermined ahead of time; rather, the interventionist makes in-the-moment decisions on the order that targeted skills are presented. The interventionist could conduct several trials with each targeting a different response, or conduct several trials each targeting the same response. The interventionist could implement only novel targets or intersperse maintenance and novel targets in skill acquisition. Like the placement of stimuli, the interventionist is making these in-the-moment decisions based on their clinical judgment. If a learner is struggling learning new skills and needs to contact reinforcement more frequently, it may be best to intersperse maintenance targets or continue with the same target to provide repeated exposure to the target response. If the learner is struggling to learn a singular target, the interventionist might continue with that target for more trials. Wong et al. (2020) compared a predetermined trial order vs a trial order determined in the moment to teach three participants diagnosed with ASD to receptively identify pictures of different cartoon/comic book characters. There were three conditions in this study, all of which implemented teaching in blocks of nine trials. The first was a predetermined condition in which the interventionist implemented a fully counterbalanced trial order and location of the stimuli (i.e., left side, middle, or right side) that was determined prior to the teaching session. The second condition was a constrained condition in which the interventionist implemented a counterbalanced stimulus placement that was determined in advance but had discretion over the sequencing of target stimuli as long as every target stimulus was targeted three times within each teaching session. The final condition was unconstrained, allowing the interventionist full discretion over stimulus placement, trial order, and how many trials to allocate to each targeted stimulus. The results indicated that the unconstrained condition was more efficient across the three participants, demonstrating how clinical judgment can be used to increase the efficiency of teaching and maximize rate of acquisition.

The discriminative stimulus Each trial within DTT begins with providing a discriminative stimulus. This is often an instruction, presenting an item/stimulus, or a combination of an

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instruction and the presentation of an item/stimulus. Within a conventional approach, there are numerous guidelines related to providing an instruction, most of which would be considered protocol-driven, simple, and unvarying (e.g., Ghezzi, 2007;Green, 2001; Grow & LeBlanc, 2013). One common recommendation is for the interventionist to use the simplest form of language possible for the instruction (Green, 2001; Grow & LeBlanc, 2013). For example, instead of saying “Find the alligator,” saying “Alligator.” Within the APM, instead of protocols we have guidelines with respect to instructions. Instruction complexity falls on a continuum. On one end of this continuum are simple instructions (e.g., “Ball”) and on the other end are complex instructions (e.g., “Hey, can you find the ball for me?”). The complexity of the instruction may vary from learner to learner, program to program, or trial to trial, with the aim of varying instructions as soon as possible (Leaf, Cihon, et al., 2016). Providing varied instructions can help prevent restricted stimulus control (e.g., only responding when a specifically worded instruction is provided). Varied instructions can also provide the learner with multiple exemplars, which promotes generalization (Stokes & Baer, 1977), can reduce learner boredom (Leaf & McEachin, 1999), and more closely resembles instructions provided within natural teaching environments (e.g., classroom). The instruction provided by the interventionist should be based on several variables that are assessed in-the-moment and based on clinical judgment. These variables include, but are not limited to, the learner’s previous history with the program or the task, current receptive language/listener skills, correct trials with a specific instruction, attending, novelty of the task, and difficulty of the task. Another common recommendation of conventional DTT is to avoid varying the instructions for a given target (e.g., Grow & LeBlanc, 2013). For example, saying “Touch Ball” on every discrete trial as opposed to varying between “Touch the ball,” “Now find the ball,” “Where’s the ball” and “How about the ball” across trials. As with the differing opinions on the complexity of instruction, there are differing opinions about varying instructions; some professionals have put forth that the instruction should be the same from trial to trial (e.g., Ghezzi, 2007) while others say that the instruction could vary from trial to trial (e.g., Leaf & McEachin, 1999). Within the APM, the goal is to vary instructions from trial to trial as quickly as possible. Whether and when to vary instructions is based on several learner and environmental considerations. One consideration is how the learner responds to more complex instructions (described previously).

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If acquisition is not slowed by a more natural level of wordiness, the learner may be ready for varied instructions. However, if it has been determined that, currently, simple instructions are best for the learner, varied instructions may not be ideal. Another consideration is if generalization is a goal of the program. Varying the instruction in the early stages of learning may lead to slower acquisition, but more robust learning in terms of generalizability and maintenance. Ultimately, the interventionist should work toward providing varied instructions. Aljohani et al. (2023) compared the provision of a singular instruction to providing varied instructions to teach expressive labels for three children diagnosed with ASD. In this study, the first condition was a single instruction condition where the researcher implemented the same instruction (e.g., “Who is it”) on every single teaching trial. In the second condition, the researcher varied the instruction (e.g., “What is his name,” “Who is it,” or “Tell me his name?”) across the teaching trials. The number of different instructions ranged from 5 to 16 per session in the varied instruction condition. The results indicated that both singular instruction and varied instructions resulted in participants reaching mastery criterion on all skills with idiosyncratic differences in terms of efficiency across participants. However, the varied condition was slightly more efficient for most of the participants. The advantage of varying instructions during acquisition may be even more apparent when evaluating generalization, which future research should examine. Besides using natural language as early as possible, the APM also aims to ensure that children respond to a natural tone of voice and volume when receiving instructions. A common error in implementing DTT is to over rely on a loud, commanding tone of voice when delivering verbal discriminative stimuli. While it may initially generate heightened responsiveness to instructions, it potentially forms an unwanted discrimination (i.e., that requests made in an everyday conversational tone of voice become stimuli-delta). Said differently, during DTT, learners should access reinforcement for responding to instructions that are delivered in the same manner as they will encounter in the rest of the world.

Prompts Although not a mandatory component, prompting is commonly used in the implementation of DTT. As discussed in the prompting chapter, in the APM, interventionists implement flexible prompt fading (Cihon et al.,

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2020; Leaf et al., 2014, 2019; Leaf, Leaf, et al., 2016; Soluaga et al., 2008). Within this instructional format, the interventionist has the flexibility to implement any prompt type and fade prompts based on their clinical judgment. There are three general guidelines when using flexible prompt fading while implementing DTT. First, the timing of the prompt should occur prior to the learner’s response. As such, the interventionist would implement the prompt simultaneously with the instruction or immediately following the instruction. Second, the goal is for the learner to respond correctly independently or with the provision of a prompt on at least 80% of trials. This goal is important to ensure a high level of success and, more importantly, so that the learner accesses a sufficiently rich schedule of reinforcement. Third, the goal when prompting is to provide the least assistive prompt necessary. This is done to ensure that the interventionist is not over prompting, which may lead to prompt dependency from the learner and slow down attainment of mastery. At the start of each trial, the interventionist should ask themselves “Is the learner going to respond correctly on the next trial?” If the answer is “yes,” then the interventionist should not provide a prompt. If the answer is “no,” then the interventionist should ask themselves how important it is for the learner to get the next trial correct. If it is imperative that the learner responds correctly on the next trial, the interventionist should provide the least assistive, yet effective, prompt. If the answer is that it is not imperative that the learner responds correctly on the next trial (e.g., the learner is changing their behavior based on feedback), then the interventionist should not provide a prompt. There have been numerous studies that have shown the effectiveness of flexible prompt fading (Cihon et al., 2020; Leaf et al., 2014, 2019; Leaf, Leaf, et al., 2016; Soluaga et al., 2008), which have been reviewed in Chapter 11.

Learner’s response Following the instruction and/or the provision of a prompt, the next step in DTT is the response from the learner. There are multiple ways that the learner can respond, but learner responding is commonly categorized across six different responses within DTT. First, the learner could engage in a correct response. A correct response is when the learner provides a response that corresponds to the instruction without the use of prompts. Second, the learner could engage in an incorrect response. An incorrect response is when the learner provides a response that does not correspond with the instruction

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without the use of prompts. Third, the learner could engage in a prompted correct response. A prompted correct response is when the learner provides a response that corresponds with the instruction after a prompt has been provided. Fourth, the learner could engage in a prompted incorrect response. A prompted incorrect response is when the learner provides a response that does not correspond with the instruction after a prompt was provided. Note that this can only happen when the prompt level was insufficient, which may or may not reflect an error in the judgment of the interventionist. Fifth, the learner could engage in no response. No response is when the learner does not provide any response to the instruction and/or prompt, any response that occurs after the target duration, or any responses that do not fall within the other categories. The sixth type of response a learner could engage in is an off-task response. An off-task response is when the learner engages in some form of undesired behavior (e.g., stereotypic behavior, fidgeting) that interferes with learning.

Feedback The final step of DTT is feedback provided by the interventionist. Typically, if the learner engages in a correct response or a correct prompted response, the interventionist provides a consequence in the form of feedback and other types of reinforcement. If the learner engages in an incorrect response, incorrect prompted response, no-response, or off-task response, the interventionist does not provide reinforcement and may also provide corrective feedback. The type of corrective feedback could vary and can be, but is not limited to, informative feedback (e.g., “No, this is a [correct response]”), a verbal reprimand (e.g., “Don’t grab.”), loss of privileges (e.g., missing out on recess), removal of tokens, or moving down on a level system. In the APM, consequences (i.e., reinforcement or corrective feedback) are provided on a continuum, where the strength of the consequence corresponds to the quality of the response. For example, a slow but correct response may receive moderate praise, and a quick correct response would receive warmer praise plus a token. During some discrete trials, the interventionist may only provide feedback based on the presence or absence of challenging behavior. When an interventionist does this, it is often because they are prioritizing effort and sustained attention over merely being correct. If a trial contains both undesired behavior and a correct response, this poses a dilemma for the interventionist. If they punish the undesired behavior, the punishment impacts not

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only the undesired behavior, but also impacts all behavior that occurred during the trial, including the correct response. Similarly, if they reinforce the correct response, they are simultaneously reinforcing undesired behavior. While some students might understand compound feedback like “yes that’s correct, but you are fidgeting too much,” the cleanest way to handle the occurrence of undesired behavior during a trial is to stop the trial as soon as off-task behavior occurs and provide the appropriate consequence for the off-task behavior. In effect, the opportunity to respond is removed contingent on the occurrence of off-task behavior and task responses are only allowed when the interventionist is satisfied with the overall behavior that is being displayed. Conversely, during some discrete trials, the interventionist might only provide feedback if the learner’s response corresponds with the instruction or prompt. During these trials, the interventionist is not as concerned with challenging behavior, but more on the correct or incorrect responding of the learner. Finally, during some trials the interventionist might provide feedback based on both challenging behavior and correct responding. The interventionist’s decisions on what behaviors to reinforce should occur in-the-moment and based on their clinical judgment due to factors such as how new the skill is to the learner, the rates of aberrant behavior, and the type of task. Another consideration when providing feedback during DTT is what criteria to use for evaluating the reinforcer-worthiness of the learner’s behavior. There are multiple dimensions to every response and some aspects of a response might warrant higher priority than others. For example, an interventionist might provide more or higher quality reinforcers for responding with reduced assistance. Or they may choose to differentially reinforce higher quality responses (e.g., clear articulation, novel responses). When four consecutive correct responses have occurred (even if they are a bit latent), an interventionist might provide a higher level of reinforcement for a learner who has a history of not sustaining on-task behavior. The interventionist must use clinical judgment to balance competing and continually shifting priorities.

Instructive feedback One component of feedback that deserves consideration in its own right is instructive feedback. Instructive feedback is when the interventionist provides the learner with additional information alongside the reinforcement or the corrective feedback. For example, if teaching a learner to expressively label

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superheroes, a trial might start with holding up a picture of Superman and asking, “Who is this?”. If the learner says “Superman” the interventionist might say “That is right, and he can fly.” If the learner says “Batman” the interventionist might say “That is not right. This is Superman and he can fly.” In both instances, the instructive feedback provides the learner with additional information about the target (e.g., “he can fly”). In the days of the UCLA Young Autism Project, feedback during DTT was used solely to address the response of the learner. It was not until more recently that the work of researchers such as Reichow and Wolery (2011) demonstrated the utility of instructive feedback during discrete trial instruction with autistic children and the strategy was incorporated into the APM. It allows sessions to become more efficient by producing additional free learning without extending instruction time. Leaf et al. (2017) evaluated the effects of instructive feedback for teaching six children diagnosed with ASD to expressively label comic book characters and athletes. The six participants were divided into two groups of three children and each participant was taught their respective expressive labels using DTT in a group instructional format. Participants were directly taught to expressively label either comic book characters or athletes and were provided with their superpower or what team they played for as part of the instructive feedback. Additionally, participants had the opportunity to observationally learn comic book characters or athletes and their superpowers and/or teams that were taught to their peers in the group. The results showed that participants: (a) learned the targets directly taught to them, (b) learned the information about the targeted stimulus through instructive feedback, (c) learned targets through observational learning, and (d) observationally learned information about targets through instructive feedback. Thus, these results showed that instructive feedback can be beneficial in teaching individuals diagnosed with ASD. Ferguson et al. (2020) were one of the first researchers to evaluate DTT via telehealth during the COVID-19 pandemic. Specifically, Ferguson and colleagues evaluated the effects of instructive feedback as part of DTT during telehealth sessions. The researchers evaluated if participants could learn to correctly label pictures of comic book characters and if they could learn their corresponding superpowers when provided as instructive feedback. Additionally, DTT was conducted in a dyad arrangement via telehealth so the researchers evaluated if participants also acquired their learning partner’s targeted superheroes and the corresponding powers taught via instructive feedback. The results indicated that all participants learned

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the superheroes directly taught to them and all superpowers taught through instructive feedback. Finally, five out of the six participants observationally learned the comic book characters and powers taught to their peers. Another important consideration when providing feedback is the use of error correction. Within the APM, researchers have compared using error correction to other prompting systems when implementing DTT (e.g., Leaf, Alcalay, et al., 2016; Leaf, Cihon, et al., 2020). For example, Leaf et al. (2014) compared most-to-least prompting to error correction when teaching two children diagnosed with ASD to expressively label pictures of comic book or Muppet characters. The researchers implemented both conditions in a one-to-one instructional format. Using an adapted alternating treatment design, the finding of this study was that both conditions were effective, but participants reached the mastery criterion on more sets in the error correction condition. Leaf, Alcalay, et al. (2016) conducted a follow up study when they compared the same two conditions (i.e., most-to-least and error correction), but for teaching two children to receptively label jobs, places, actions, or cartoon characters. Once again, Leaf, Alcalay, and colleagues used an adapted alternating treatment design and found that both conditions were effective, but participants reached mastery criterion on more sets in the error correction condition. Leaf, Cihon, et al. (2020) conducted a randomized clinical trial to compare error correction to errorless learning for 28 individuals diagnosed with ASD. The 28 participants were randomly divided into two groups. The participants who were assigned to the errorless learning condition received most-to-least prompting to minimize errors and following an incorrect response the researcher provided simple feedback (e.g., “No”). In the error correction condition, no attempt was made to prevent errors and no proactive prompting was used, only corrective feedback (e.g., “No, it is Daredevil”) following errors. Positive reinforcement for correct responding was used in the same manner for both conditions and the participants were taught to expressively label comic book characters. Leaf, Cihon, and colleagues utilized a pre-posttest group design to evaluate the differences and the results showed that participants in the error correction condition responded significantly better than participants in the errorless condition during postprobes. Additionally, participants displayed more aberrant behavior in the errorless learning condition as opposed to the error correction condition.

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Intertrial interval The intertrial interval is a pause that separates the end of one trial from the beginning of the next. The intertrial interval serves many purposes. The pause helps differentiate statements that constitute feedback for a response that just occurred from any statement that will be used as part of the discriminative stimulus (i.e., instruction) for the next trial. It allows both the instructor and the learner a moment to process the outcome of a trial. It can also provide a few seconds to set up materials for the next trial and to reflect on which target to present next and what prompt, if any, to use. The length of the pause determines the pace of instruction. The optimal duration varies for each learner and learning context and will also vary from trial to trial. For some learners, a more rapid (but not rushed) pace has the effect of making it more difficult to engage in off-task behavior because they are fully occupied keeping up with instruction. A fully rapid pace helps build fluent responding as the learner progresses toward mastery of targets. A longer pause can provide the opportunity for the learner to practice shifting attention back to the instructor and resist the temptation to engage in stereotypic behavior. Varying the intertrial interval can ensure that a learner does not attempt to anticipate the next instruction. An unexpected break in the rhythm of the trials can serve as a motivating operation for checking in with the interventionist and heighten the motivation for continuing instruction. There are all variables that the interventionist is analyzing trial by trial to determine the just-right duration of each intertrial interval.

Mass trialing vs interspersal Another component that interventionists must consider is how to optimize learning by providing the just-right amount of target interspersal. This is best understood by first describing mass trialing, which is equivalent to zero interspersal. Mass trialing involves presenting consecutive trials of the same target. This method is intended to provide opportunities to intensively practice a skill and is described in The Me Book (Lovaas et al., 1981). For example, an interventionist might have the learner imitate the action of clapping their hands on eight consecutive trials. Interspersal involves inserting trials of one or more additional target responses within the series of trials (see Henrickson et al., 2015; Volkert et al., 2008). For example, an interventionist might have the learner imitate the action of clapping their hands two or three times, then practice waving bye a few times, then switch back to clapping. The degree of interspersal can vary with as few as two targets occurring with a trial block,

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to targeting a number of different skills within the trial block and each one occurring only once. All or some of the interspersed items could be additional acquisition targets or they could all be mastered targets. Within the field of ABA there have been several discussions and evaluations on the use of mass-trialing vs task interspersal (e.g., Benavides & Poulson, 2009; Charlop et al., 1992; Chong & Carr, 2005; Dunlap, 1984; Dunlap & Koegel, 1980; Thiessen et al., 2009). In addition to these studies, researchers have also conducted comparison studies (e.g., Grow et al., 2011; Henrickson et al., 2015; Volkert et al., 2008). For example, Henrickson and colleagues (2015) compared mass trialing to task interspersal for three participants diagnosed with ASD. The results showed that mass trialing resulted in better skill acquisition and lower levels of challenging behavior but task interspersal resulted in higher levels of maintenance. Taken together, the research on task interspersal and mass trialing is inconclusive in determining which way is superior in teaching (Chong & Carr, 2005). However, some conventional practice guidelines caution about prolonged trial blocks of only a single target (e.g., Grow et al., 2011) because they may inadvertently promote perseverating on a response and not attending to the discriminative stimulus, which is a legitimate concern. However, the proposed remedy of never presenting the same target consecutively is too extreme because it precludes the use of repetition which can be beneficial to learners, if used judiciously. Interventionists should be mindful that there is a very broad range of interspersal possibilities, not just the endpoints of zero (i.e., mass trialing) and infinity (i.e., never presenting the same target consecutively). Within the APM, interventionists select the appropriate degree of interspersal based on the needs of the individual learner. If a learner needs more intensive teaching on a particular program or if a learner is struggling with acquiring a skill, then an interventionist might elect to employ a higher level of repetition. If a learner is mastering targets quickly and not engaging in interfering behavior, then the interventionist might implement a higher level of task interspersal. For most learners, the just-right approach will be a combination of task interspersal and repetition within any given session. In other words, very rarely, if ever, does an interventionist completely use task interspersal or completely implement mass trialing in a teaching session of 1 h or longer.

Simple-to-conditional or conditional only Another consideration for an interventionist is how to teach conditional discriminations. One method to teach discrimination is known as a simple-to-

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conditional method (Lovaas et al., 1981). In a simple-to-conditional method, each item to be taught is first presented as a simple discrimination (i.e., with no distractors; see Chapter 4) before placing two targets in the same field. Table 1 highlights how this procedure may be done for teaching a learner to receptively label pictures of cat, dog, and duck. This process is highly systematic, highly time consuming, and very protocol driven. In contrast, another way to teach learners is a procedure known as the conditional-only method (Grow et al., 2011). In this method, the interventionist jumps to the final step of the simple-to-conditional discrimination during initial teaching. In other words, the interventionist starts teaching the discriminations from a field of three in the very beginning of teaching. Grow et al. (2011) compared the simple-to-conditional method to the conditional only discrimination with three children diagnosed with ASD. Participants were taught receptive labels (e.g., animals, letters). The results indicated that the conditional only method was the more efficient form of teaching and resulted in fewer errors. Within the APM, teaching starts most often with a conditional only method as logistically it makes more sense to start teaching a discrimination initially. However, if a learner is struggling or if demonstrate low levels of attending/scanning, then the simple conditional only method may be appropriate.

Table 1 Example of simple conditional discrimination training. Step

Target goal

1 2 3

Receptively labels picture of a cat (only a picture of a cat being shown) Receptively labels picture of a dog (only a picture of a dog being shown) Receptively labels pictures of a cat (with both a picture of a cat and a picture of a dog shown) Receptively labels pictures of a dog (with both a picture of a cat and a picture of a dog shown) Receptively labels pictures of a cat and dog (with both a picture of a cat and a picture of a dog shown) Receptively labels picture of a duck (only a picture of a duck being shown) Receptively labels pictures of a duck and cat (with both a picture of a cat and a picture of a duck shown) Receptively labels pictures of a duck and dog (with both a picture of a dog and a picture of a duck shown) Receptively labels pictures of a duck, dog, and cat (with both a picture of a cat, dog and a picture of a duck shown)

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Summary DTT is a procedure with a substantial amount of research to show its effectiveness (Cihon et al., 2020; Leaf et al., 2014, 2019; Leaf, Leaf, et al., 2016; Soluaga et al., 2008). As such, it is considered an evidence-based practice. There are many procedural variations in widespread use that have an extensive body of research to demonstrate effectiveness. However, within the APM, the emphasis is on efficiency and that requires head-to-head comparison of procedural variations. It is not sufficient to merely know that an approach works. When conclusive evidence about the relative efficiency of competing approaches is not available, interventionists should be well versed on the rationales underlying best-practice guidelines and should be trained to analyze in-the-moment which method is working best for the learner in front of them and the specific skill being taught. When interventionists implement procedures with flexibility, clinical judgment, and in-the-moment decision making, it can result in the most efficacious and efficient learning.

References Aljohani, W. A., Ferguson, J. L., Cihon, J. H., Ross, R. K., Weiss, M. J., & Leaf, J. B. (2023). Comparison of single instruction and varied instructions to teach expressive labels via direct telehealth for children with autism spectrum disorder. Journal of Developmental and Physical Disabilities. https://doi.org/10.1007/s10882-023-09921-9 (Advance online publication). Benavides, C. A., & Poulson, C. L. (2009). Task interspersal and performance of matching tasks by preschooler with autism. Research in Autism Spectrum Disorders, 3(3), 619–629. https:// doi.org/10.1016/j.rasd.2008.12.001. Charlop, M. H., Kurtz, P. H., & Milstein, J. P. (1992). Too much reinforcement, too little behavior: Assessing task interspersal procedures in conjunction with different reinforcement schedules with autistic children. Journal of Applied Behavior Analysis, 25(4), 795–808. https:// doi.org/10.1901/jaba.1992.25-795. Cheung, Y., Lai, C. O. Y., Cihon, J. H., Leaf, J. B., & Mountjoy, T. (2022). Establishing requesting with children diagnosed with autism using embedded instruction in the context of academic activities. Journal of Behavioral Education, 31, 265–280. https://doi.org/ 10.1007/s10864-020-09397-z. Chong, I. M., & Carr, J. E. (2005). An investigation of the potentially adverse effects of task interspersal. Behavioral Interventions, 20(4), 285–300. https://doi.org/10.1002/bin.202. Cihon, J. H., Ferguson, J. L., Leaf, J. B., Milne, C. M., Leaf, R., & McEachin, J. (2020). A randomized clinical trial of three prompting systems to teach tact relations. Journal of Applied Behavior Analysis, 53(2), 727–743. https://doi.org/10.1002/jaba.617. Conallen, K., & Reed, P. (2016). A teaching procedure to help children with autistic spectrum disorder to label emotions. Research in Autism Spectrum Disorders, 23, 63–72. https:// doi.org/10.1016/j.rasd.2015.11.006.

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DiGennaro Reed, F. D., Reed, D. D., Baez, C. N., & Maguire, H. (2011). A parametric analysis of errors of commission during discrete-trial training. Journal of Applied Behavior Analysis, 44(3), 611–615. https://doi.org/10.1901/jaba.2011.44-611. Dunlap, G. (1984). The influence of task variation and maintenance tasks on the learning and affect of autistic children. Journal of Experimental Child Psychology, 37(1), 41–64. https:// doi.org/10.1016/0022-0965(84)90057-2. Dunlap, G., & Koegel, R. L. (1980). Motivating autistic children through stimulus variation. Journal of Applied Behavior Analysis, 13(4), 619–627. https://doi.org/10.1901/ jaba.1980.13-619. Ferguson, J. L., Majeski, M. J., McEachin, J., Leaf, R., Cihon, J. H., & Leaf, J. B. (2020). Evaluating discrete trial teaching with instructive feedback delivered in a dyad arrangement via telehealth. Journal of Applied Behavior Analysis, 53(4), 1876–1888. https://doi. org/10.1002/jaba.773. Geiger, K. B., Carr, J. E., LeBlanc, L. A., Hanney, N. M., Polick, A. S., & Heinicke, M. R. (2012). Teaching receptive discriminations to children with autism: A comparison of traditional and embedded discrete trial training. Behavior Analysis in Practice, 5(2), 49–59. https://doi.org/10.1007/BF03391823. Ghezzi, P. M. (2007). Discrete trials teaching. Psychology in the Schools, 44(7), 667–679. https:// doi.org/10.1002/pits.20256. Green, G. (2001). Behavior analytic instruction for learners with autism: Advances in stimulus control technology. Focus on Autism and Other Developmental Disabilities, 16(5), 72–85. https://doi.org/10.1177/10883576101600203. Grow, L. L., Carr, J. E., Kodak, T. M., Jostad, C. M., & Kisamore, A. N. (2011). A comparison of methods for teaching receptive labeling to children with autism spectrum disorders. Journal of Applied Behavior Analysis, 44(3), 475–498. https://doi.org/ 10.1901/jaba.2011.44-475. Grow, L., & LeBlanc, L. (2013). Teaching receptive language skills: Recommendations for instructors. Behavior Analysis in Practice, 6(1), 56–75. https://doi.org/10.1007/ BF03391791. Gutierrez, A., Jr., Hale, M. N., O’Brien, H. A., Fischer, A. J., Durocher, J. S., & Alessandri, M. (2009). Evaluating the effectiveness of two commonly used discrete trial procedures for teaching receptive discrimination to young children with autism spectrum disorders. Research in Autism Spectrum Disorders, 3(3), 630–638. https://doi.org/ 10.1016/j.rasd.2008.12.005. Henrickson, M. L., Rapp, J. T., & Ashbeck, H. A. (2015). Teaching with massed versus interspersed trials: Effects on acquisition, maintenance, and problem behavior. Behavioral Interventions, 30(1), 36–50. https://doi.org/10.1002/bin.1396. Ingvarsson, E. T., & Hollobaugh, T. (2010). Acquisition of intraverbal behavior: Teaching children with autism to mand for answers to questions. Journal of Applied Behavior Analysis, 43(1), 1–17. https://doi.org/10.1901/jaba.2010.43-1. Kurt, O. (2011). A comparison of discrete trial teaching with and without gestures/signs in teaching receptive language skills to children with autism. Educational Sciences: Theory & Practice, 11(3), 1436–1444. Leaf, J. B., Alcalay, A., Leaf, J. A., Tsuji, K., Kassardjian, A., Dale, S., McEachin, J., Taubman, M., & Leaf, R. (2016). Comparison of most-to-least to error correction for teaching receptive labelling for two children diagnosed with autism. Journal of Research in Special Educational Needs, 16(4), 217–225. https://doi.org/10.1111/1471-3802.12067. Leaf, J. B., Cihon, J. H., Alcalay, A., Mitchell, E., Townley-Cochran, D., Miller, K., Leaf, R., Taubman, M., & McEachin, J. (2017). Instructive feedback embedded within group instruction for children diagnosed with autism spectrum disorder. Journal of Applied Behavior Analysis, 50(2), 304–316. https://doi.org/10.1002/jaba.375.

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Leaf, J. B., Cihon, J. H., Ferguson, J. L., Leaf, R., & McEachin, J. (2019). Comparing no-no prompt to flexible prompt fading to teach expressive labels to individuals diagnosed with autism spectrum disorder. Education and Training in Autism and Developmental Disabilities, 54(3), 274–287. Leaf, J. B., Cihon, J. H., Ferguson, J. L., McEachin, J., Leaf, R., & Taubman, M. (2018). Evaluating three methods of stimulus rotation when teaching receptive labels. Behavior Analysis in Practice, 11(4), 334–349. https://doi.org/10.1007/s40617-018-0249-5. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Milne, C., Leaf, R., & McEachin, J. (2020). Comparing error correction to errorless learning: A randomized clinical trial. The Analysis of Verbal Behavior, 36(1), 1–20. https://doi.org/10.1007/s40616-019-00124-y. Leaf, J. B., Cihon, J. H., Leaf, R., McEachin, J., & Taubman, M. (2016). A progressive approach to discrete trial teaching: Some current guidelines. International Electronic Journal of Elementary Education, 9(2), 361–372. Leaf, J. B., Leaf, J. A., Alcalay, A., Kassardjian, A., Tsuji, K., Dale, S., Ravid, D., Taubman, M., McEachin, J., & Leaf, R. (2016). Comparison of most-to-least prompting to flexible prompt fading for children with autism spectrum disorder. Exceptionality, 24(2), 109–122. https://doi.org/10.1080/09362835.2015.1064419. Leaf, J. B., Leaf, R., Taubman, M., McEachin, J., & Delmolino, L. (2014). Comparison of flexible prompt fading to error correction for children with autism spectrum disorder. Journal of Developmental and Physical Disabilities, 26(2), 203–224. https://doi.org/ 10.1007/s10882-013-9354-0. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., OppenheimLeaf, M. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The Autism Partnership Method: Social skills groups. DRL Books. Leaf, J. B., Sheldon, J. B., & Sherman, J. A. (2010). Comparison of simultaneous prompting and no-no prompting in two-choice discrimination learning with children with autism. Journal of Applied Behavior Analysis, 43, 215–228. https://doi.org/10.1901/jaba. 2010.43-215. Leaf, J. B., Tsuji, K. H., Lentell, A. E., Dale, S. E., Kassardjian, A., Taubman, M., McEachin, J., Leaf, R., & Oppenheim-Leaf, M. L. (2013). A comparison of discrete trial teaching implemented in a one-to-one instructional format and in a group instructional format. Behavioral Interventions, 28(1), 82–106. https://doi.org/10.1002/bin.1357. Ledford, J. R., Gast, D. L., Luscre, D., & Ayres, K. M. (2008). Observational and incidental learning by children with autism during small group instruction. Journal of Autism and Developmental Disorders, 38(1), 86–103. https://doi.org/10.1007/s10803-007-0363-7. Lerman, D. C., Valentino, A. L., & Leblanc, L. A. (2016). Discrete trial training. In R. Lang, T. B. Hancock, & N. N. Singh (Eds.), Early intervention for young children with autism spectrum disorder (pp. 47–83). Springer International Publishing. Lovaas, O. I., Ackerman, A., Alexander, D., Firestone, P., Perkins, J., & Young, D. (1981). Teaching developmentally disabled children: The ME book. Austin, TX: Pro-Ed, Inc. National Autism Center. (2015). Findings and conclusions: National standards project, phase 2. Author. Nuzzolo-Gomez, R., Leonard, M. A., Ortiz, E., Rivera, C. M., & Greer, R. D. (2002). Teaching children with autism to prefer books or toys over stereotypy or passivity. Journal of Positive Behavior Interventions, 4(2), 80–87. https://doi.org/10.1177/109830070200400203. Reichow, B., & Wolery, M. (2011). Comparison of progressive prompt delay with and without instructive feedback. Journal of Applied Behavior Analysis, 44(2), 327–340. https://doi. org/10.1901/jaba.2011.44-327. Shillingsburg, M. A., Bowen, C. N., & Shapiro, S. K. (2014). Increasing social approach and decreasing social avoidance in children with autism spectrum disorder during discrete

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trial training. Research in Autism Spectrum Disorders, 8(11), 1443–1453. https://doi.org/ 10.1016/j.rasd.2014.07.013. Sigafoos, J., Carnett, A., O’Reilly, M. F., & Lancioni, G. E. (2019). Discrete trial training: A structured learning approach for children with ASD. In S. G. Little, & A. Akin-Little (Eds.), Behavioral interventions in schools: Evidence-based positive strategies (pp. 227–243). American Psychological Association. https://doi.org/10.1037/0000126-013. Smith, T. (2001). Discrete trial training in the treatment of autism. Focus on Autism and Other Developmental Disabilities, 16(2), 86–92. https://doi.org/10.1177/10883576101600204. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j.rasd.2008.03.005. Stokes, T., & Baer, D. (1977). An implicit technology of generalization. Journal of Applied Behavior Analysis, 10(2), 349–367. https://doi.org/10.1901/jaba.1977.10-349. Taubman, M. T., Leaf, R. B., McEachin, J. J., Papovich, S., & Leaf, J. B. (2013). A comparison of data collection techniques used with discrete trial teaching. Research in Autism Spectrum Disorders, 7(9), 1026–1034. https://doi.org/10.1016/j.rasd.2013.05.002. Thiessen, C., Fazzio, D., Arnal, L., Martin, G. L., Yu, C. T., & Keilback, L. (2009). Evaluation of a self-instructional manual for conducting discrete-trials teaching with children with autism. Behavior Modification, 33(3), 360–373. https://doi.org/10.1177/0145445508 327443. Volkert, V. M., Lerman, D. C., Trosclair, N., Addiosn, L., & Kodak, T. (2008). An exploratory analysis of task-interspersal procedures while teaching object labels to children with autism. Journal of Applied Behavior Analysis, 41(3), 335–350. https://doi.org/10.1901/ jaba.2008.41-335. Wechsung, N. B., Leaf, J. B., Ferguson, J. L., Cihon, J. H., Milne, C., & Eddington, K. (2023). Comparing a field of two to a field of three within discrete trial teaching. Education and Training in Autism and Developmental Disabilities, 58(2), 222–234. Wong, E., Ferguson, J. L., Milne, C. M., Cihon, J. H., Leaf, J. B., McEachin, J., Leaf, R., Schulze, K., & Rudrud, E. (2020). Evaluating three methods of the presentation of target stimuli when teaching receptive labels. Behavioral Interventions, 35(4), 542–559. https:// doi.org/10.1002/bin.1744.

CHAPTER 13

Naturalistic instruction Contents Incidental teaching Embedded instructions Summary References

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Naturalistic instructions are procedures in which the interventionist captures and takes advantage of naturally occurring opportunities to teach skills in the context of a learner’s daily routine and preferred activities (Ala’i-Rosales et al., 2017). The interventionist arranges stimuli in the learner’s natural environment to serve as instructional materials. An example would be teaching colors in the context of playing with cars. The activities themselves (e.g., playing with cars) also serve as the reinforcers (e.g., making a car go down a ramp contingent upon the learner labeling the color of the car) as opposed to using additional noncontextualized stimuli to serve as reinforcement (e.g., token, candy). The instructional methods that fall under the umbrella of naturalistic instruction are learner initiated. That is, the interventionist arranges the environment to entice interaction between the learner and the environment, and the interventionist waits for the learner to initiate before capturing and expanding upon the learner’s initiation. This is in opposition to interventionist-led instruction (e.g., discrete trial teaching, teaching interaction procedure) in which instructions and discriminative stimuli are arranged and initiated by the interventionist. It should be noted, however, that this does not mean that the learner would be inherently less interested in interventionist-led instruction. A well-designed discrete trial also includes effective reinforcers that are selected based on learner interest. The biggest difference is that in discrete trial teaching, the interventionist has more options for when the instruction occurs and a better ability to closely space opportunities to practice a skill in a manner that produces fluent responding. Today, there are numerous procedures that fall under the umbrella of naturalistic interventions. These interventions include: (a) natural language paradigm (e.g., Koegel et al., 1987), (b) mand-model procedures A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00025-8

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(e.g., Hawkins & Schuster, 2007), (c) incidental teaching (Hart & Risley, 1975), (d) pivotal response training (e.g., Koegel et al., 2003), (e) activity-based instruction (e.g., Bricker & Cripe, 1992), and (f ) embedded instruction (e.g., Snyder et al., 2013). All these procedures have numerous peer-reviewed studies demonstrating their effectiveness and have been identified as evidence-based practices in various reports (e.g., National Autism Center, 2015). In the Autism Partnership Method (APM), incidental teaching and embedded instructions are the most frequently used forms of naturalistic instruction procedures. As such, in this chapter we focus on those two variations of these procedures.

Incidental teaching One form of naturalistic instruction is incidental teaching. Incidental teaching is known as a child-led procedure because the learner initiates the instruction. Incidental teaching is a procedure in which the interventionist uses naturally occurring opportunities or arranges opportunities in the learner’s natural environment to capture teachable moments, often with a focus on communication (Haring, 1992; Hart & Risley, 1968). Hart and Risley (1975) defined incidental teaching as “the interaction between an adult and a single child, which arises naturally in an unstructured situation, which is used by the adult to transmit information or give the child practice in developing a skill” (p. 411). The first component of incidental teaching is arranging the environment. The environment should be arranged in a way that enriches it with activities and stimuli that the learner prefers. Further, the environment should be arranged in such a way that the learner does not have free access to preferred items/activities, but, rather, must initiate to access the item or activity. For example, if the learner wants to play a game with a marble maze, the interventionist may arrange the environment to include a set up marble maze but put the marbles out of reach of the learner. The second component is the teaching incident in which the learner makes an initiation. When a learner makes this initiation, it is an indication that they want to engage with that item/activity. For example, the learner may reach for the marbles, request a marble, or make a vocal approximation. The third component is elaboration. In elaboration, the interventionist targets an expansion of the learner’s initial response. For example, if the learner just reached for the marbles, the interventionist could model saying “marbles” and wait for the learner to echo or provide an approximation to the model. If the child’s initial request

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was “Marble,” the intervention would model a more elaborate phrase such as, “Can I have a marble?” or “Give me marble, please.” The final step is for the interventionist to provide response-specific reinforcement. For example, providing a marble to the learner and then the learner placing the marble in the marble maze to watch it go down. Ala’i-Rosales et al. (2017) provided some key recommendations for interventionists when implementing incidental teaching. First, the interventionist must constantly observe and analyze the learner’s behavior. As the learner progresses, the interventionist adjusts their expectations for the learner to require a more complex and diverse response. Second, the interventionist must consider the “little picture” and “big picture.” In other words, the interventionist needs to know the benefits of teaching the targeted behavior in the short and long term. Finally, Ala’i-Rosales and colleagues provided one of the most important recommendations, happy progress. Happy progress was defined as “the arrangement of positive reinforcement contingencies, clearly signaled by the learner’s happy and uncoerced initiations, consequated by natural, response specific reinforcers, and occurring in the context of progressively more complex competence across behaviors, social partners, and situations over time” (Ala’i-Rosales et al., 2017, p. 182). This approach ensures that learning is an enjoyable experience shared by the learner and interventionist. Betty Hart and Todd Risley were the first to evaluate the effectiveness of incidental teaching in a series of studies conducted at the University of Kansas. Hart and Risley (1968) demonstrated that children were unable to generalize requesting when taught with traditional instruction. However, when incidental teaching was implemented, requesting generalized to different contexts. Hart and Risley (1975) implemented incidental teaching to increase the frequency of language and range of vocabulary for 11 preschool children. The results showed a substantial increase in the unprompted use of compound sentences and requests across the child participants. McGee et al. (1992) evaluated the effects of incidental teaching to improve social behavior for a child diagnosed with autism spectrum disorder (ASD). McGee and colleagues used peer tutors to implement the incidental teaching procedure. The results demonstrated that there was an increase in reciprocal peer interactions across participants. Additionally, peer-tutors rated the individual diagnosed with autism as more likable after the intervention. McGee and Daly (2007) used incidental teaching and stimulus fading to teach three children diagnosed with autism to increase social responses. All three participants’ social initiations increased and generalized to additional

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contexts. In addition to the aforementioned studies, there has been a plethora of research on the effectiveness of incidental teaching. Researchers have demonstrated that incidental teaching to be effective in teaching conversation skills (e.g., Hart & Risley, 1975), play skills (e.g., Wong et al., 2007), complex language (e.g., Hart & Risley, 1978), social skills (e.g., McGee et al., 1992), receptive labels (e.g., McGee et al., 1983), and early reading skills (e.g., McGee et al., 1986). The most common form of incidental teaching implemented within the APM is what we call “communication temptations” (see Leaf & McEachin, 1999, p. 199). Communication temptations consist of arranging situations for a learner to communicate their desires. For example, an interventionist might begin by blowing bubbles. Then, the interventionist holds bubbles near their mouth and waits for the learner to say “bubbles.” Once the learner makes the request or an approximation, the interventionist blows the bubbles. As the learner continues to be successful, the interventionist would then target increasing the complexity of the learner’s requests (e.g., saying “Big bubbles”). Leaf et al. (2012) described phases within a communication temptation including: (a) developing the contingency between vocalizations and reinforcers, (b) shaping word approximations, and (c) expanding the length of the utterances. A variation of communication temptations that are implemented as part of the APM is referred to as social temptations. Social temptations are arranged in a similar manner, but the goal is for the learner to initiate a bid for social attention. For example, an interventionist might begin by doing spaghetti arms with a learner (e.g., holding the learner’s hands and shaking their arms up and down like spaghetti noodles), and then pausing to wait for the learner to say “Again!” Once the learner makes the social initiation or an approximation, the interventionist does spaghetti arms. As the learner continues to be successful, the interventionist would then target increasing the complexity of the learner’s requests (e.g., saying, “Do at again, faster!”). Besides increasing the use of language, social temptations can be used to promote other forms of social behavior. An interventionist could pause in the middle of tossing a child up in the air or swinging them around in a circle and wait for them to look toward the adult before resuming the activity. Or after setting the child down, the interventionist could wait for them to reach their arms up before picking them up again. Such activities have the added benefit of paring enjoyment with the participation of another person.

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Embedded instructions Another naturalistic instruction procedure used in the APM is embedded instruction. Embedded instruction involves inserting learning opportunities into a learner’s normal routine and/or play activities (Neef et al., 1984; Sigafoos et al., 2009). For example, a game that is played in the APM is called “Fruit Salad.” Within this game, the interventionist separates a group of learners into two lines and assigns each learner a different fruit (e.g., banana, strawberry, apple). The interventionist then calls a fruit (e.g., “apple”) and the two learners that are assigned to the fruit go and high-five each other. Within this game, there are multiple types of embedded instructions (e.g., conditional instructions, waiting, social interaction) that are targeted through this preferred activity. Here again we see the benefit in the pairing of enjoyment with the participation of others, potentially heightening social interest. And because this game often evokes a lot of excitement with all the learners playing together, it provides the opportunity to target excitement regulation. Like incidental teaching, there is a plethora of research supporting the effects of embedded instruction (Snyder et al., 2015). Neef et al. (1984) compared embedded instruction to discrete trial teaching. In this study, there were four individuals diagnosed with ASD. The main dependent variable was the participants accurately responding to yes/no questions. Neef and colleagues used a multiple baseline design and the results indicated that participants acquired the skills taught with embedded instructions. Sigafoos et al. (2009) also compared discrete trial teaching to embedded instruction to decrease self-injury and increase pro-social with a 12-year-old boy diagnosed with ASD. The results indicated that embedded instruction was more effective in decreasing self-injury and increasing correct responding. Cheung et al. (2022) evaluated the effects of embedded instruction to increase requesting with three participants diagnosed with ASD. Cheung and colleagues embedded requesting in the context of an academic task. The results showed that the participants learned the embedded target as well as the academic target. In the APM, interventionists commonly use embedded instructions as part of a systematic approach to intensive behavioral intervention. Rather than viewing “naturalistic” teaching as a polar opposite of discrete trial teaching, we conceptualize the approaches as falling along a continuum of structure. A child’s intervention program moves up and down that continuum depending on the needs of the learner and the nature of the skill

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being taught. When it is necessary to teach in a more structured manner to bring about the acquisition of certain skills, the teaching continues to evolve in a more naturalistic direction to ensure that the new behavior comes under the control of naturally occurring stimuli and contexts. Often there is a blend of discrete trial teaching and naturalistic teaching where specific skills are inserted into a variety of activities. Interventionists are unconstrained during teaching and will ensure that when an incidental opportunity to practice (or newly learn) a skill arises they capture it, and there is also sufficient repetition using elements of discrete trial teaching to produce a meaningful and enduring change in the learner’s behavior. Leaf et al. (2020) described a variety of social games that have been implemented in social skills groups and that could be implemented in one-toone instructional formats. These games included: (a) slapjack; (b) fruit salad; (c) I like you, but I just can’t smile; (d) Did you see that?; and the sleeping game. There are numerous advantages of teaching skills through embedding instruction within game or play activities. For one, it can make the activity more fun for the learner. Second, it is a more natural way of providing instruction. Third, it can be more engaging for the learner. Fourth, an interventionist can target multiple behaviors simultaneously. Finally, it may lead to better generalization.

Summary Within the APM, a variety of procedures are implemented as part of comprehensive intervention and naturalistic intervention procedures have an important role in high-quality intervention. It is important to note that even in the naturalistic intervention described in this chapter and the other naturalistic intervention procedures (e.g., mand-model), teaching instances still resemble those of discrete trial teaching. That is, the environment is arranged with discriminative stimuli, the learner engages in a response, and the interventionist provides reinforcement. So, while some may advocate for the use of naturalistic instructions or discrete trial teaching, both procedures are very similar. Finally, it is important to note that within the APM, intervention consists of a combination of interventionistdirected and child-led instruction. It is never one or the other in any given session; rather, the interventionist has to find the correct balance between the two. This will change from session to session and hour to hour based on the learner’s behavior.

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References Ala’i-Rosales, S., Toussaint, K. A., & McGee, G. G. (2017). Incidental teaching: Happy progress. In J. B. Leaf (Ed.), Handbook of social skills and autism spectrum disorder (pp. 171–185). https://doi.org/10.1007/978-3-319-62995-7_11. Bricker, D., & Cripe, J. (1992). An activity-based approach to early intervention. Brookes. Cheung, Y., Lai, C. O. Y., Cihon, J. H., Leaf, J. B., & Mountjoy, T. (2022). Establishing requesting with children diagnosed with autism using embedded instruction in the context of academic activities. Journal of Behavioral Education, 31, 265–280. https://doi.org/ 10.1007/s10864-020-09397-z. Haring, T. G. (1992). The context of social competence: Relations, relationships, and generalization. In S. L. Odom, S. R. McConnell, & M. A. McEvoy (Eds.), Social competence of young children with disabilities: Issues and strategies for intervention Brookes Publishing. Hart, B., & Risley, T. R. (1968). Establishing use of descriptive adjectives in the spontaneous speech of disadvantaged preschool children. Journal of Applied Behavior Analysis, 1(2), 109–120. https://doi.org/10.1901/jaba.1968.1-109. Hart, B., & Risley, T. R. (1975). Incidental teaching of language in the preschool. Journal of Applied Behavior Analysis, 8(4), 411–420. https://doi.org/10.1901/jaba.1975.8-411. Hart, B., & Risley, T. R. (1978). Promoting productive language through incidental teaching. Education and Urban Society, 10(4), 407–429. https://doi.org/ 10.1177/001312457801000402. Hawkins, S. R., & Schuster, J. W. (2007). Using a mand-model procedure to teach preschool children initial speech sounds. Journal of Developmental and Physical Disabilities, 19, 65–80. https://doi.org/10.1007/s10882-006-9032-6. Koegel, R. L., Koegel, L. K., & Brookman, L. I. (2003). Empirically supported pivotal response interventions for children with autism. In A. E. Kazdin (Ed.), Evidence-based psychotherapies for children and adolescents (pp. 341–357). Guilford Press. Koegel, R. L., O’Dell, M. C., & Koegel, L. K. (1987). A natural language teaching paradigm for nonverbal autistic children. Journal of Autism and Developmental Disabilities, 17, 187–200. https://doi.org/10.1007/BF01495055. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, R., McEachin, J., & Mountjoy, T. (2012). A work in progress: Video series. Autism Partnership. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., OppenheimLeaf, M. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The autism partnership method: Social skills groups. DRL Books. McGee, G. G., Almeida, M. C., Sulzer-Azaroff, B., & Feldman, R. S. (1992). Promoting reciprocal interactions via peer incidental teaching. Journal of Applied Behavior Analysis, 25(1), 117–126. https://doi.org/10.1901/jaba.1992.25-117. McGee, G. G., & Daly, T. (2007). Incidental teaching of age-appropriate social phrases to children with autism. Research and Practice for Persons with Severe Disabilities, 32(2), 112–123. https://doi.org/10.2511/rpsd.32.2.112. McGee, G. G., Krantz, P. J., Mason, D., & McClannahan, L. E. (1983). A modified incidental-teaching procedure for autistic youth: Acquisition and generalization of receptive object labels. Journal of Applied Behavior Analysis, 16(3), 329–338. https:// doi.org/10.1901/jaba.1983.16-329. McGee, G. G., Krantz, P. J., & McClannahan, L. E. (1986). An extension of incidental teaching procedures to reading instruction for autistic children. Journal of Applied Behavior Analysis, 19(2), 147–157. https://doi.org/10.1901/jaba.1986.19-147. National Autism Center. (2015). Findings and conclusions: National standards project, phase 2. NAC.

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Neef, N. A., Walters, J., & Egel, A. L. (1984). Establishing generative yes/no responses in developmentally disabled children. Journal of Applied Behavior Analysis, 17(4), 453–460. https://doi.org/10.1901/jaba.1984.17-453. Sigafoos, J., O’Reilly, M., Ma, C. H., Edrisinha, C., Cannella, H., & Lancioni, G. E. (2009). Effects of embedded instruction versus discrete-trial training on self-injury, correct responding, and mood in a child with autism. Journal of Intellectual and Developmental Disabilities, 31(4), 196–203. https://doi.org/10.1080/13668250600999160. Snyder, P., Hemmeter, M. L., McLean, M. E., Sandall, S., & McLaughlin, T. (2013). Embedded instruction to support early learning in response-to-intervention frameworks. In V. Buysse, & E. Peisner-Feinberg (Eds.), Handbook of response-to-intervention in early childhood (pp. 283–298). Brookes. Snyder, P. A., Rakap, S., Hemmeter, M. L., McLaughlin, T. W., Sandall, S., & McLean, M. E. (2015). Naturalistic instructional approaches to early learning: A systematic review. Journal of Early Intervention, 37(1), 69–97. https://doi.org/ 10.1177/1053815115595461. Wong, C. S., Kasari, C., Freeman, S., & Paparella, T. (2007). The acquisition and generalization of joint attention and symbolic play skills in young children with autism. Research and Practice for Persons with Severe Disabilities, 32(2), 101–109. https://doi.org/10.2511/ rpsd.32.2.101.

CHAPTER 14

The teaching interaction procedure Contents Overview Components of the TIP Promoting generalization Other considerations Teaching interaction procedure research Summary References

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Overview Within the Autism Partnership Method (APM), the teaching interaction procedure (TIP) is a commonly implemented procedure to teach meaningful pro-social behaviors (e.g., Dotson et al., 2010; Ferguson et al., 2013; Leaf et al., 2009; Ng et al., 2016; Peters et al., 2016). The TIP is a multicomponent and interactive teaching procedure between the learner and the interventionist. There are six steps in the TIP. The interventionist first labels and describes the skill being targeted within a teaching session. The interventionist then provides a meaningful rationale or has the learner provide a meaningful rationale for why the targeted skill is important. Third, the interventionist breaks the targeted skill into smaller steps. Fourth, the interventionist provides a demonstration of the targeted skill. The interventionist then role-plays the targeted skill with the learner. The sixth step is the provision of feedback (e.g., reinforcement or corrective feedback), which also occurs throughout the entire procedure. Each of these steps is discussed in detail in the following section. It should be noted, however, that while each of these steps is part of the TIP, the interventionist has the flexibility to alter the order of the steps or omit steps when necessary.

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Components of the TIP Label and identify The first step of the TIP is for the interventionist to label and define the skill being taught. This typically involves the interventionist labeling the targeted skill and identifying periods of time that the learner should and should not display the skill. This is followed by having the learner restate what skill is being taught and when to display the skill. This is an important step to highlight the natural environmental cues for when the learner should display the skill. For example, when targeting changing the conversation when others are bored, the interventionist would highlight the cues for when to display this skill (e.g., what are the facial expressions, body language, physical or verbal behaviors of conversational partner that signal they are bored with the conversation). When the learner correctly states the skill being targeted and the cues, they are provided reinforcement. When they respond incorrectly, feedback is provided, and another opportunity is provided for the learner to respond correctly. During this first step of the TIP, the interventionist should use clear and concise language that is developmentally appropriate for the learner. Rationales The second component of the TIP is the provision of a meaningful rationale. A rationale is a reason why the learner should engage in the targeted behavior. A rationale usually takes the form of an if-then statement and clearly defines the benefits for the learner to engage in the targeted skill. There are three primary reasons for providing a meaningful rationale. First, it provides the learner with a reason why they should engage in the targeted skill. Second, the rationale can become a self-reminder and a source of motivation for the learner to engage in the targeted skill within the naturalistic setting. Third, if done correctly, rationales can help the interventionist fade supplemental reinforcers, such as tokens, because the successful demonstration of the targeted skill will become naturally reinforcing. However, to accomplish this, the rationale must be meaningful. For example, “If you play with your friends at school, then they might invite you to their house to play.” Meaningful rationales are ones that are important to the learner and based on their preferences. As such, a meaningful rationale must be individualized to the learner and should motivate the learner to demonstrate the targeted skill. The interventionist should avoid blanket or “adult” rationales, as these are not likely to be meaningful to the learner. A blanket rationale is a

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statement that could apply to any pro-social behavior. For example, if the interventionist says that the learner should engage in a behavior because it is “nice,” “cool,” or “good to do.” An adult rationale is one where the rationale is important to the adult interventionist but not important to the learner. For example, “so you don’t get in trouble” or “because I told you so.” Finally, the rationale should not be unrealistic. An unrealistic rationale is one that is unlikely to come to fruition. For example, “If you play with your friends at recess, you will become captain of the football team.” Prior to the teaching session, the interventionist should identify as many meaningful rationales as possible. During the initial teaching sessions, the interventionist might state a few rationales and have the learner repeat the rationales or might state a few rationales and have the learner come up with additional rationales. Regardless of how the rationales are brought up, the interventionist should introduce as many rationales as necessary. After the first session, the learner should develop their own rationales or choose one of the previously identified meaningful rationales. Additionally, it is important for the interventionist to discuss situations that the learner encounters in which they contact naturally occurring consequences based on their behavior which may strengthen the rationale. When doing so, the interventionist can bring attention to the rationale in-the-moment. For example, if a learner was working on “matching the mood” (i.e., engaging in behavior similar to those around them such as talking at the same volume as others) and not acting too silly, an interventionist may set up scenarios that are similar to the ones in which the learner has not matched the mood in the past. If the learner refrains from going over the top and matches the mood and their friends continue to play with them, then the interventionist can bring up the rationale (e.g., “See, when you matched the mood, your friends kept playing with you!”). Conversely, if the learner does not match the mood and their friends leave the play area then the interventionist can bring up the rationale (e.g., “See, when you did not match the mood, your friends left to play with someone else.”). Setting up these situations and tying the rationale used in the TIP can strengthen the rationale and social motivation to engage in the targeted skill. Description A description of the targeted skill is the third component of the TIP. The description outlines a task analysis of the targeted skill. On this step, the interventionist describes the component behaviors that a learner needs to engage in to display the targeted skill correctly. The number of component

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behaviors that are described to the learner is dependent on numerous factors such as the learner’s receptive language (comprehension), expressive language, and cognitive level. Thus, prior to teaching the interventionist must be well prepared. During the initial teaching session, the interventionist will typically state each of the component behaviors and have the learner repeat each of the steps. As teaching progresses, the interventionist may have the learner state each of the component behaviors independently. Each of the component behaviors can allow for the interventionist and the learner to role-play the specific component. For example, if one of the steps is to look at a peer, the interventionist might implement discrimination training (i.e., appropriate versus inappropriate eye contact). Demonstration The fourth step of the TIP is the demonstration. In this step, the interventionist demonstrates the targeted skill the correct and incorrect way. It should be noted that the labels used for the correct and incorrect way to display the targeted skill should be individualized for the learner (e.g., cool and not cool, correct and incorrect, right and wrong, appropriate and inappropriate). During correct demonstrations, the interventionist displays all steps of the targeted skill correctly. During incorrect demonstrations, the interventionist incorrectly displays or omits steps that the learner is displaying incorrectly or omitting in the relevant social contexts. During demonstrations, the interventionist should provide a cue that a demonstration is going to occur (e.g., “Action!”). Every effort should be taken to ensure demonstrations resemble the natural environment as closely as possible, including the same contexts that set the occasion to display the skill. Once the demonstration concludes, the interventionist provides a cue that the demonstration is complete (e.g., “Cut!”). At this point, the interventionist asks the learner to label the demonstration as correct or incorrect and provide feedback based on the learner’s response. The interventionist should also ask why the demonstration was correct or incorrect followed by feedback based on the learner’s response. This sequence continues until the interventionist has completed all demonstrations. Demonstrations can occur in a one-to-one instructional format or within group instruction. Depending on whether the demonstration is done in a group or one-to-one, this may change how the demonstration is completed. If done in a group, the learner can watch the demonstration while the interventionist and other members of the group demonstrate the targeted skill.

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If done in a one-to-one format, then the learner may have to act as a peer while the interventionist demonstrates the target skill. Role-play The fifth component of the TIP is the learner role-playing the targeted behavior with the interventionist. Role-playing might be one of the most important components of the TIP as it allows the learner to practice displaying the targeted skill correctly and contact reinforcement or feedback. During role-plays, the interventionist provides a cue that it is the learner’s turn to practice the skill (e.g., “Ok it is your turn to practice!”). The interventionist should then arrange a situation that evokes the targeted skill. Once the roleplay is complete, the interventionist should provide a cue that the role-play has ended (e.g., “Pause!”). Next, the interventionist and the learner should discuss if the role-play was done correctly or incorrectly and why the roleplay was correct or incorrect. If the learner role-played correctly, then the interventionist should provide reinforcement. If the learner role-played incorrectly, the interventionist should provide corrective feedback and provide the learner with another opportunity to role-play correctly. The interventionist should continue role-play opportunities until the learner displays the skill correctly. After multiple role-plays, if the learner does not display the skill correctly, the interventionist should reevaluate the teaching strategy and make any changes necessary (e.g., smaller component behaviors, more intrusive/assistive prompts, richer schedule of reinforcement). When conducting role-plays, it is imperative that the interventionist arranges the situation as naturally as possible to help ensure that the practice situation will be as close to the natural environment as possible, thus increasing the likelihood of generalization. Additionally, the interventionist should use multiple exemplars within role-plays. The interventionist should only have the learner role-play the skill the correct way (as opposed to the demonstration in which the interventionist provides correct and incorrect demonstrations), so the learner is only practicing the correct skill and receiving reinforcement or feedback contingent on that skill. Finally, across teaching sessions, the interventionist should increase the complexity and difficulty of the scenarios within the role-plays to help ensure generalization to the relevant social contexts. Feedback The final component of the TIP is feedback from the interventionist to the learner. Feedback should be provided throughout the entire procedure and

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includes contingent praise and corrective feedback according to the learner’s responses. During the didactic portion of the TIP (i.e., labeling, rationales, description, demonstration), reinforcement is provided for answering questions correctly, participating, and providing information about the targeted skill independently. Conversely, corrective feedback is provided for answering questions incorrectly, not participating, or not providing relevant/accurate information about the targeted skill. During the role-playing component, reinforcement is provided for displaying the skill correctly and answering questions correctly about the role-play. Corrective feedback is provided for incorrect demonstration or not answering questions correctly.

Promoting generalization There are several ways an interventionist can promote generalization of skills taught using the TIP. First, interventionists should ensure that multiple staff are implementing the TIP. Second, interventionists should implement the TIP in different places and at different times across teaching sessions. Third, the interventionist should gradually increase the provocativeness of the scenarios during the TIP, especially the role-play component. For example, when working on sharing, an interventionist might start with having the learner practice with a low preferred item and then, across sessions, increase to a more preferred item. Fourth, an interventionist could decrease the predictability of the role-play. This could be done by increasing the delay between the didactic portion of the TIP and role-play opportunities. For example, the interventionist might start by doing the role-play component immediately following didactic teaching and then, across sessions, increase the time-delay for when the role-play is conducted. In addition, the interventionist can reduce the external cues that a role-play is occurring, and instead provide probes or natural opportunities to practice based on natural cues. For example, following the didactic portion of the TIP, the interventionist may prime the learner they will have an opportunity to practice at some point later in the session and to be on the lookout for cues that signal it is time to display the skill. Ultimately, the interventionist will inform the learner they should be ready to engage in the skill at any time throughout the session and discretely arrange situations for them to display the targeted skill. A final way to promote generalization is to decrease the amount and frequency of reinforcement provided within the TIP.

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Other considerations There are several factors that must be considered to help ensure the TIP is implemented with a high degree of quality and fidelity. First, the TIP is highly conversational and, as such, it requires the learner to have an extensive receptive language repertoire and comprehension skills. To date, there has not been sufficient research to determine the exact prerequisite language skills necessary for a learner to be successful with the TIP. However, from our clinical experience, learners are most successful with the TIP when they demonstrate fairly strong receptive language understanding (comprehension) and basic conversational skills. Second, as with any procedure, the TIP must be tailored to the individual learner. As such, for some learners, the interventionist can use complex or more language while for others the interventionist would use simplified or less language (Ng et al., 2016). Other modifications can include using pictures to represent the steps and/or rationales (Ng et al., 2016), using videos for demonstrations, and omitting demonstrating the target behavior the incorrect way. Third, it is also imperative for the interventionist make the TIP as natural as possible. This can be done by using natural language, implementing the TIP in the learner’s everyday environment, and providing demonstrations and role plays that are similar to situations that the learner is facing in their everyday life. Fourth, the interventionist should make the TIP fun. This means being creative in terms of the reinforcement being used as well as the role-plays. The interventionist must also determine if the TIP will be more effective in a one-to-one or group instructional format. One benefit of implementing the TIP in a group instructional format is that other learners can assist in the demonstration and role-play (Leaf et al., 2012). Additionally, those learners who answer questions or respond better in role-plays can serve as models for those who are struggling to develop the skill. Finally, the interventionist should consider how data are going to be collected on skill acquisition and the fidelity of the implementation of TIP. Frequently within the APM, we use task analysis data (see Figs. 1 and 2) to track the learner’s progress. We also use task analysis data (see Fig. 3) to track the fidelity of the interventionist’s implementation of the TIP.

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Skill: CHEERING UP A FRIEND Date:

Learner:

Role-Play/Natural Probe

Step Behavior

Response

1

Face the person

Correct Incorrect

2

Ask a general question if the other person is okay

Correct Incorrect

3

Make a statement of concern

Correct Incorrect

4

Ask if there is anything that they can do to make them feel better

Correct Incorrect

5

Complete the action that was requested

Correct Incorrect

Fig. 1 Example of task analysis data sheet for a learner.

Skill: Date: Step

Learner: Behavior

Role-Play/Natural Probe Response

1

Correct Incorrect

2

Correct Incorrect

3

Correct Incorrect

4

Correct Incorrect

5

Correct Incorrect

6

Correct Incorrect

7

Correct Incorrect

8

Correct Incorrect

9

Correct Incorrect

10

Correct Incorrect

11

Correct Incorrect

12

Correct Incorrect

13

Correct Incorrect

14

Correct Incorrect

15

Correct Incorrect

Fig. 2 Blank task analysis data sheet for a learner.

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Teaching Interaction Procedure Interventionist Date Name of Child

Steps 1 2 3 4 5 6 7 8 9 10 11 12

Teacher Behavior to Be Displayed Provide the label of the targeted behavior Provide a meaningful rationale for the behavior Break the skill down into smaller behavioral components Provide at least 3 opportunities for the student to respond from step 1 to 3 Provide at least one appropriate demonstration Provide at least one inappropriate demonstration Have the learner rate the demonstration Have the learner provide reasons why the demonstration was appropriate or inappropriate Provide an opportunity for the student to role-play the behavior Have the student role-play until they displayed 100% of the skills correctly Provide specific feedback after each role-play Provide feedback throughout the entire teaching interaction procedure

Total Percentage

Response Correct Incorrect Correct Incorrect Correct Incorrect Correct Incorrect Correct Correct Correct Correct

Incorrect Incorrect Incorrect Incorrect

Correct Incorrect Correct Incorrect Correct Incorrect Correct Incorrect /12 %

Fig. 3 Treatment fidelity data sheet for the teaching interaction procedure.

Teaching interaction procedure research The TIP was first developed by Montrose Wolf and his students as part of the Teaching Family Model and Achievement Place (Kirigin et al., 1982; Phillips, 1968; Wolf et al., 1976). Phillips (1968) first described the TIP in a series of studies demonstrating the effectiveness of the TIP and the Teaching Family Model (Kirigin et al., 1982; Phillips, 1968; Wolf et al., 1976). Minkin et al. (1976) used the TIP to successfully teach conversational skills to the four delinquent and predelinquent youths. Researchers and professionals started disseminating the TIP through the publication of manuals including Effective Skills for Child-care Workers: A Training Manual from Boys Town (Dowd et al., 1994), and The ASSET Manual (Hazel et al., 1983). While professionals were expanding the dissemination of the TIP to predelinquent and delinquent youth, others began to use the procedure with individuals diagnosed with ASD. The procedure was first implemented with individuals diagnosed with autism as part of the UCLA Young Autism Project (Lovaas, 1987). In 1994, it began to be used

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at Autism Partnership and has been implemented clinically ever since (Taubman et al., 2011). Leaf et al. (2009) were the first to empirically evaluate the effectiveness of the TIP as it relates to individuals diagnosed with ASD. In this study, Leaf and colleagues evaluated the TIP combined with a token economy to teach various social behaviors (e.g., staying with a peer, selecting the same peer, giving compliments). All TIP sessions were implemented in a one-to-one instructional format. Confederate peers were used to evaluate if the participants displayed the targeted behaviors correctly. The results showed that the TIP was effective in teaching all targeted skills to the three participants in the study. Leaf et al. (2010) and Dotson et al. (2010) expanded upon Leaf et al. (2009) by evaluating the TIP implemented in a group instructional format. Leaf et al. (2010) evaluated the TIP for young children diagnosed with ASD (i.e., 4–6 years old) and Dotson et al. (2010) evaluated the TIP for adolescents diagnosed with ASD (i.e., 13–18 years old). Leaf et al. (2010) taught various social behaviors (e.g., showing appreciation, giving a compliment, displaying empathy) while Dotson and colleagues taught conversational skills. The results of both studies showed that the TIP was effective in teaching the participants the targeted skills. The results of Leaf et al. (2010) showed that all participants learned the targeted skills which maintained during an 8-week follow-up, while the results of Dotson et al. (2010) demonstrated that four out of the five participants reached the mastery criterion. The next two studies were conducted by Oppenheim-Leaf, Leaf, and Call (2012) and Oppenheim-Leaf, Leaf, Dozier, et al. (2012). Oppenheim-Leaf, Leaf, and Call evaluated the effectiveness of the TIP to teach two young children how to play board games (i.e., Go Fish, Uno, and Yahtzee Junior). Both participants mastered playing the three games which also generalized to different contexts. Oppenheim-Leaf, Leaf, Dozier, and colleagues evaluated the use of the TIP to teach children how to better interact with their siblings diagnosed with ASD. The skills that were targeted included inviting their sibling to play, asking to share with their sibling, providing play instructions to their sibling, and choosing an activity. Results showed that the TIP was effective in teaching the three participants the targeted skills. Leaf et al. (2012) compared the TIP to Social Stories with six children diagnosed with ASD ranging from 5 to 13 years old. Each participant was taught six social skills—three randomly assigned to the TIP condition and three randomly assigned to the Social Stories condition. All skills were

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taught in a one-to-one instructional format. The results indicated that the TIP was more effective than Social Stories and resulted in better generalization and maintenance for all six participants. Kassardjian et al. (2013) further researched the TIP by examining how well four participants generalized the skills taught using the TIP to a more natural environment. Kassardjian and colleagues taught participants in a oneto-one instructional format but used in-the-moment assessment and clinical judgment of when to make modifications to TIP. There were four stages to promote generalization in this study: (a) priming with tangible reinforcement, (b) priming without tangible reinforcement, (c) social praise without priming, and (d) no reinforcement/priming. The results demonstrated that all four participants learned the targeted skills that also generalized to more natural settings. Ferguson et al. (2013) taught sportsmanship skills during video games to six children diagnosed with ASD. Ferguson and colleagues evaluated the TIP in a group instructional format. The results showed that the TIP was effective in teaching sportsmanship and that the skills generalized to other environments. This study was important because it was the first study to evaluate the TIP for individuals diagnosed with ASD outside of researchers from The University of Kansas and Autism Partnership. This study strengthened the evidence-base for the TIP and demonstrated the replicability of the procedures across clinicians and researchers. Kassardjian et al. (2014) extended and replicated Leaf et al.’s (2012) findings by comparing the TIP to Social Stories for three individuals diagnosed with ASD. The study expanded upon the previous work by Leaf et al. (2012) by comparing the two procedures in a group instructional format. In this study, one skill was taught with TIP, one skill was taught with Social Stories, and one social behavior was assigned to a control condition (i.e., no teaching). The results showed that the TIP was effective for all three participants, while Social Stories was ineffective for all three participants. Furthermore, the participants showed more improvement in the control condition than the Social Stories condition. Thus, these results demonstrated that the TIP was more effective than other commonly implemented procedures that do not meet the standard for being evidence-based and therefore are not used in the APM. Peters et al. (2016) conducted a study evaluating the TIP with four participants (ages 8–10 years old). The study was conducted in a school setting and all sessions occurred in the classroom. The skills that were taught consisted of asking for help from an adult, joining activities that are already

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started, ignoring classmates when they are distracting, and responding appropriately when a game is changed. The results showed that all four participants learned the targeted skill which also maintained over time. Thus, once again showing that the TIP was effective when implemented by interventionists who were not trained from Autism Partnership, showing the procedure has a great deal of generality of who can effectively implement the procedure. Ng et al. (2016) expanded the previous research on the TIP by evaluating a modified version of the TIP for four individuals diagnosed with ASD. All participants in this study had IQ scores under 75 and, at the time, would be considered learners requiring very substantial support. This differed from the assessment scores of participants in previous research on the TIP. The modifications included demonstrations for the rationales, using picture prompts for identifying when to display the targeted skill, picture prompts for the component behaviors, and only providing correct demonstrations. The results showed that the TIP was effective in teaching the targeted skills to all participants. This showed that the TIP can be effective not only for children diagnosed with ASD with higher IQs and age-typical language, but also for those with developmentally lower IQ scores and atypical language.

Summary Based on the current state of the research and clinical practice, the TIP meets the standards to be classified as an evidence-based practice (APA Presidential Task Force on Evidence-Based Practice, 2006). As such, it can be a valuable intervention to implement with autistic individuals. When the TIP is implemented with a high degree of quality and fidelity, it can result in meaningful outcomes for autistic individuals.

References American Psychological Association, Presidential Task Force on Evidence-Based Practice. (2006). Evidence-based practice in psychology. American Psychologist, 61(4), 271–285. https://doi.org/10.1037/0003-066X.61.4.271. Dotson, W. H., Leaf, J. B., Sheldon, J. B., & Sherman, J. A. (2010). Group teaching of conversational skills to adolescents on the autism spectrum. Research in Autism Spectrum, 4(2), 199–209. https://doi.org/10.1016/j.rasd.2009.09.005. Dowd, T., Czyz, J. D., O’Kane, S. E., & Elofson, A. (1994). Effective skills for child-care workers: A training manual from boys town. The Boys Town Press.

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Ferguson, B. R., Gillis, J. M., & Sevlever, M. (2013). A brief group intervention using video games to teach sportsmanship skills to children with autism spectrum disorders. Child and Family Behavior Therapy, 35(4), 293–306. https://doi.org/10.1080/07317107.2013.846648. Hazel, J. S., Schumaker, J. B., Sherman, J. A., & Sheldon-Wildgen, J. A. (1983). Social skills training with court-adjusted youths. In C. LeCroy, & J. Beker (Eds.), Social skills training for children and youth (pp. 117–137). Haworth Press. Kassardjian, A., Leaf, J. B., Ravid, D., Leaf, J. A., Alcalay, A., Dale, S., Tsuji, K., Taubman, M., Leaf, R., McEachin, J., & Oppenheim-Leaf, M. L. (2014). Comparing the teaching interaction procedure to social stories: A replication study. Journal of Autism and Developmental Disorders, 44(9), 2329–2340. https://doi.org/10.1007/s10803-0142103-0. Kassardjian, A., Taubman, M., Rudrud, E., Leaf, J. B., Edwards, A., McEachin, J., Leaf, R., & Schulze, K. (2013). Utilizing teaching interactions to facilitate social skills in the natural environment. Education and Training in Autism and Developmental Disabilities, 48(2), 245–257. Kirigin, K. A., Braukmann, C. J., Atwater, J. D., & Wolf, M. M. (1982). An evaluation of teaching-family (achievement place) group homes for juvenile offenders. Journal of Applied Behavior Analysis, 15(1), 1–16. https://doi.org/10.1901/jaba.1982.15-1. Leaf, J. B., Dotson, W. H., Oppenheim, M. L., Sheldon, J. B., & Sherman, J. A. (2010). The effectiveness of a group teaching interaction procedure for teaching social skills to young children with a pervasive developmental disorder. Research in Autism Spectrum Disorders, 4(2), 186–198. https://doi.org/10.1016/j.rasd.2009.09.003. Leaf, J. B., Oppenheim-Leaf, M. L., Call, N. A., Sheldon, J. B., Sherman, J. A., Taubman, M., McEachin, J., Dayharsh, J., & Leaf, R. (2012). Comparing the teaching interaction procedure to social stories for people with autism. Journal of Applied Behavior Analysis, 45(2), 281–298. https://doi.org/10.1901/jaba.2012.45-281. Leaf, J. B., Taubman, M., Bloomfield, S., Palos-Rafuse, L., Leaf, R., McEachin, J., & Oppenheim, M. L. (2009). Increasing social skills and pro-social behavior for three children diagnosed with autism through the use of a teaching package. Research in Autism Spectrum Disorders, 3(1), 275–289. https://doi.org/10.1016/j.rasd.2008.07.003. Lovaas, O. I. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55(1), 3–9. https://doi.org/10.1037/0022-006X.55.1.3. Minkin, N., Braukmann, C. J., Minkin, B. L., Timbers, G. D., Timbers, B. J., Fixsen, D. L., Phillips, E. L., & Wolf, M. M. (1976). The social validation and training of conversational skills. Journal of Applied Behavior Analysis, 9(2), 127–139. https://doi.org/ 10.1901/jaba.1976.9-127. Ng, A. H. S., Schulze, K., Rudrud, E., & Leaf, J. B. (2016). Using the teaching interactions procedure to teach social skills to children with autism and intellectual disability. American Journal on Intellectual and Developmental Disabilities, 121(6), 501–519. https://doi.org/ 10.1352/1944-7558-121.6.501. Oppenheim-Leaf, M. L., Leaf, J. B., & Call, N. A. (2012). Teaching board games to two children with an autism spectrum disorder. Journal of Developmental and Physical Disabilities, 24, 347–358. https://doi.org/10.1007/s10882-012-9274-4. Oppenheim-Leaf, M. L., Leaf, J. B., Dozier, C., Sheldon, J. B., & Sherman, J. A. (2012). Teaching typically developing children to promote social play with their siblings with autism. Research in Autism Spectrum Disorders, 6(2), 777–791. https://doi.org/10.1016/ j.rasd.2011.10.010. Peters, B., Tullis, C. A., & Gallagher, P. A. (2016). Effects of a group teaching interaction procedure on the social skills of students with autism spectrum disorders. Education and Training in Autism and Developmental Disabilities, 51(4), 421–433.

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Phillips, E. L. (1968). Achievement place: Token reinforcement procedures in a home-style rehabilitation setting for “pre-delinquent” boys. Journal of Applied Behavior Analysis, 1(3), 213–223. https://doi.org/10.1901/jaba.1968.1-213. Taubman, M., Leaf, R., & McEachin, J. (2011). Crafting connections: Contemporary applied behavior analysis for enriching the social lives of persons with autism spectrum disorder. DRL. Wolf, M. M., Phillips, E. L., Fixsen, D. L., Braukmann, C. J., Kirigin, K. A., Willner, A. G., & Schumaker, J. (1976). Achievement place: The teaching-family model. Child Care Quarterly, 5(2), 92–103. https://doi.org/10.1007/BF01555232.

CHAPTER 15

Cool versus Not Cool procedure Contents Steps of the CNC procedure Labeling Modeling/demonstrations Role-play Misuses of the CNC procedure History and research Summary References

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The Cool versus Not Cool (CNC) procedure (Leaf et al., 2012) is a teaching procedure that is commonly implemented within the Autism Partnership Method (APM) to develop prosocial behaviors and reduce undesired behaviors for children diagnosed with autism spectrum disorder (ASD). It is also one of the most widely disseminated procedures within the APM. The CNC procedure is a social discrimination program used to help teach learners to discriminate between desired and undesired behaviors. However, the purpose of the procedure is not only to have the learner discriminate but also to provide the learner with opportunities to practice the desired behavior. The CNC procedure consists of five main components: (a) labeling the desired targeted skill, (b) the interventionist demonstrating the desired way to engage in the targeted skill and the undesired way to engage in the targeted skill (e.g., the “cool” and “not cool” behaviors), (c) the learner responding to questions about the demonstrations, (d) the learner role-playing the desired way to engage in the targeted skill, and (e) the interventionist providing reinforcement or feedback for learner responding and role-play.

Steps of the CNC procedure Labeling The CNC procedure starts with the interventionist labeling the targeted skill. For example, if the target skill is for the learner to share toys with A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00014-3

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friends, the interventionist might say, “Today, we are going to practice sharing.” After the interventionist labels the skill, they will ask the learner to restate what is being taught. If the learner responds correctly, the interventionist provides access to reinforcement and moves to the next step. If the learner responds incorrectly, the interventionist provides corrective feedback. At this point, the interventionist could restate the targeted skill and give the learner a chance to independently respond or prompt the correct response.

Modeling/demonstrations The second step of the CNC procedure is the interventionist modeling the target skill for the learner. Within this component, the interventionist models the targeted skill the desired way (e.g., cool, good idea) and undesired way (e.g., not cool, not so good). Modeling the skill correctly allows the learner to observe what behaviors they should be engaging in and how the behavior should look. We believe that it is equally important to model the skill the incorrect way, as it provides the learner with an opportunity to see how they are currently engaging in the skill, what behaviors or steps they are omitting, or what behaviors they are doing inappropriately. The first step in modeling is the interventionist informing the learner that they are going to watch the model (e.g., “Billy, now you are going to watch me share and tell me if I’m doing it the cool or not cool way.”). Next, the interventionist provides a cue that the model is going to start (e.g., “Ready, set, action!”). The interventionist then models the skill correctly or incorrectly. If the interventionist is demonstrating the skill the correct way, it is imperative that they display all the steps of the target skill correctly. If the interventionist is demonstrating the skill the incorrect way, the interventionist should display a step incorrectly or omit a step. Ideally, the incorrect model closely aligns with the way the learner is currently engaging in the target skill. In the initial stage of teaching, it can help learners successfully discriminate the not cool version of behavior if the model exaggerates the inappropriateness of the behavior. As the learner progresses, the inappropriateness can be toned down to more typical and more subtle examples of inappropriate behavior. After the interventionist models the skill, they should indicate that the model has concluded (e.g., “Cut.”). Next, the interventionist should ask the learner to label if the model was correct or incorrect. The interventionist should provide access to reinforcement for correct responses or corrective

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feedback for incorrect responses. The interventionist will then ask the learner to provide reasons why the model was correct or incorrect. During this portion, the learner will identify what steps the interventionist did correctly, what steps the interventionist did incorrectly, and/or what steps the interventionist omitted. The interventionist should then provide access to reinforcement for correct reasons or corrective feedback for incorrect reasons. The interventionist continues this process until a sufficient number of models have been provided. It is not always necessary that the learner give a detailed explanation when the demonstration is correct. There are endless possible reasons for saying that it was correct (e.g., “because you didn’t …” and then name any number of possible errors that did not occur). It is much easier to justify the answer when the demonstration was the incorrect version of the social behavior. The ultimate goal is for the learner to attain a generalized, instinctive sense of what is typically expected social behavior, rather than be dependent on having learned specific criteria for specific situations. There are seven general guidelines the interventionist should consider when implementing the model step of the CNC procedure. First, it is important that incorrect demonstrations closely align with what the learner is not doing or doing incorrectly in the natural setting. The purpose of the incorrect demonstration is to help the learner identify what behaviors they are engaging in incorrectly. If an interventionist decides what behavioral steps to engage in or chooses behavioral steps that do not correspond with the learners’ behavior, then the importance of the incorrect demonstration is minimized. To determine what steps to display incorrectly, the interventionist should observe the learner in the settings where they typically have opportunities to engage in the target behavior. Additionally, the interventionist could implement a naturalistic probe prior to implementing the CNC procedure. A naturalistic probe is an opportunity for the learner to display the targeted skill without supplemental reinforcement, corrective feedback, prompting, or priming. During this naturalistic probe, the interventionist engages in a behavior that sets the occasion for the learner to display the targeted behavior. For example, if the interventionist was working on sharing, the interventionist might have a peer ask the learner if they can see the learner’s toy. The interventionist would then observe what the learner did correctly and incorrectly. A second recommendation is that the interventionist should provide multiple models and scenarios during the demonstration. The interventionist should arrange different situations in which they display the targeted skill

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the correct and incorrect way. Providing multiple examples increases the likelihood of generalization of the targeted skill. A third guideline is to rotate the order of the demonstrations and use in-the-moment assessment and clinical judgment regarding which way to model. The interventionist can determine if it is more important for the learner to observe a correct or an incorrect demonstration first. Relatedly, a fourth guideline is there does not need to be an equivalent number of correct and incorrect demonstrations. Rather, the interventionist can decide what the emphasis should be during any given teaching session. Fifth, an interventionist does not need to only use the words “cool” and “not cool” when doing the demonstration and/or role-play. Rather, the interventionist should use whatever language is appropriate, taking into consideration the learner’s culture and geographic location. For example, demonstrations could be labeled as “appropriate” or “inappropriate” if the learner is older or “fire” or “lame” if the learner is younger. Ultimately, the language used should closely align with the language used in the learner’s typical verbal community. It is important that whatever language is used is clearly attached to the behavior and not expressed as a judgment of the person. The interventionist is not saying that the behavior is right or wrong, just trying to teach the child how the behavior would be perceived by others (e.g., many people would see that behavior as not cool and that might affect the opportunities that are made available to you). The sixth recommendation relates to how the interventionist arranges the model. If the CNC procedure is implemented with only the learner and the interventionist (i.e., one-to-one instruction), the interventionist should play the role of the learner and the learner plays the role of a different person in the learner’s environment (e.g., friend, teacher, sibling, peer). Thus, during the demonstration, the learner partakes in the demonstration and simultaneously observes the interventionist to determine if the demonstration was correct or incorrect and why. If the CNC procedure is implemented with multiple learners (e.g., dyad or group instruction), then typically the interventionist is the one demonstrating the skill, one of the learners is part of the demonstration (e.g., pretending to be a peer), and the rest of the learners watch the demonstration. If possible, it is preferred that the learner is not a participant in the model, so that they can fully attend to the model. If possible, the interventionist should use an additional adult or confederate peer during the model. Regardless of the instructional format, it is important for the interventionist to remind the learner whom they should be watching throughout the model (e.g., “Remember to watch me and see if I do it the cool or not cool way.”).

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The final guideline is for the interventionist to be aware that some target skills may result in emotional responding. Working on skills such as bullying/teasing, talking with your crush, being a good loser, or asking someone out on a date may be embarrassing or difficult for the learner. This may be a result of the learner knowing they are not good at the skill, or it is a skill that may be hard to display in the natural setting. As such, an interventionist should be clinically sensitive when working on such skills. One way to do so is by reassuring the learner that it is difficult to work on these skills, but it is important for them overall. A second way is for the interventionist to not be too harsh with corrective feedback. An interventionist might also provide more reinforcement than usual on these difficult skills. A third option is to not start with mirroring the full version of the behavior that occurs in the natural environment, but rather slowly have the models become more representative of what occurs in the natural environment over time, in effect desensitizing them to the emotional response they experience from observing the inappropriate behavior being modeled. Finally, a strong emotional response to behavior being modeled is indicative of the need to provide stress management skills as part of a comprehensive intervention plan.

Role-play The final component of CNC is having the learner role-play the targeted skill. During role-plays, the learner should only role-play the skill the correct way, so they contact reinforcement for correct demonstrations and the skill is more likely to generalize to the natural environment. The interventionist should start by informing the learner it is time to practice (e.g., “Ok. Now it is your turn to practice sharing the cool way.”) and provide a cue that the role-play is going to start (e.g., “Ready, set, action!”). Next, the interventionist engages in behavior that sets the occasion for the learner to display the target skill. When the role-play has concluded, the interventionist should indicate that the role-play is over (e.g., “Cut.”). Next, the interventionist should ask the learner if they role-played correctly or incorrectly. The interventionist then provides reinforcement for a correct discrimination or corrective feedback for an incorrect discrimination. The interventionist should then ask the learner to provide reasons why the role-play was correct or incorrect. The learner should identify steps they did correctly, steps they did incorrectly, and any steps they may have omitted. The interventionist should then provide reinforcement for correct reasons or corrective

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feedback for incorrect reasons. If the learner role-played the targeted skill incorrectly, the interventionist should have the learner practice again until they display the targeted skill correctly. After two or more role-plays during which the learner does not display the targeted skill correctly, the interventionist can implement flexible prompt fading (e.g., Cihon et al., 2019; Soluaga et al., 2008) to ensure that the learner displays the targeted behavior correctly. Like the demonstration, it is also important for there to be multiple exemplars during role-play. The interventionist should arrange different situations for the learner to display the skill correctly. Thus, providing the learner with opportunities to practice the targeted skill in different situations, all of which can help promote generalization.

Misuses of the CNC procedure One of the most common misuses of the CNC procedure is that the interventionist does not model the skill or have the learner role-play the skill. In doing so, the interventionist simply is having the learner state desired and undesired behavior. For example, an interventionist may ask the learner, “Is it cool or not cool to share?” and the learner responds “cool.” Active learning is necessary to change behavior. This means arranging a situation to have the learner observe sharing the “cool” and “not cool” way and practicing sharing during role-play. When the procedure is just verbally answering questions, it is missing essential components (i.e., demonstration and role playing) of the CNC procedure. A second common misuse is only using the words “cool” or “not cool” as opposed to terms that are relevant and meaningful to the learner. For example, using “wicked” or “not wicked” when running social skills groups in the East Coast region of the United States, “rad” or “lame,” or characters from a favorite show or movie (e.g., the Avengers or Thanos way) to help the learner identify the discrimination between the demonstrations. It is important for interventionists to adjust language based on the learner’s culture, age, geographical norms, and interests. A third misconception is that the CNC procedure is attempts to change the learner’s thought process as opposed to observable behavior. Unlike social cognition programs (e.g., Social Thinking; Leaf, Kassardjian, et al., 2016) which are concerned with changing thought processes, the CNC procedure was developed to change observable behavior. Finally, another misuse of the procedure is that the interventionist only uses the procedure as a

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way to provide corrective feedback. For example, only saying “that is not cool” when a learner engages in an undesired behavior as opposed to engaging in proactive teaching and focus more on positive reinforcement to shape prosocial behavior.

History and research The CNC procedure was first introduced as a clinical procedure in 1994 by Rick Schroder, one of the first staff members at Autism Partnership along with Michael Williams who co-led social skills groups. The procedure was used to teach adolescent males a variety of social behaviors. Subsequently, it has been used to teach hundreds of children a variety of prosocial behaviors (e.g., social behavior, language, replacement skills, academic skills) as well as to decrease aberrant behaviors (e.g., stereotypy, aggression, selfinjury). The CNC procedure has also been disseminated in curriculum books (Taubman et al., 2011) and book chapters (Creem et al., 2022). It was not until 2012 that the first empirical study was conducted to evaluate the procedure with autistic children. Leaf et al. (2012) were the first to empirically evaluate the CNC procedure to teach a variety of skills including: (a) interrupting, (b) changing the game, (c) appropriate greetings, (d) joint attention, (e) changing the conversation, (f ) abduction prevention, and (g) eye contact with three individuals diagnosed with ASD. Leaf and colleagues first implemented the CNC procedure without role-playing. If a participant was unable to reach the mastery criterion within 10 sessions, then the researchers added the role-play component. The results showed that the participants reached the mastery criterion on 50% of targeted skills without the need for role-play. With the addition of the role-play component, the participants reached the mastery criterion on additional 37.5% of targeted skills. Thus, overall participants reached the mastery criterion on 87.5% of the targeted skills. Leaf et al. (2015) evaluated the CNC procedure to teach social interaction skills for three individuals diagnosed with ASD. Each participant was taught one social skill (i.e., compromising, sharing, assertiveness), all of which fell under the domain of social interaction within the social taxonomy as described by Taubman et al. (2011). In this study, Leaf and colleagues implemented the CNC procedure using modeling and role-play for every skill. Leaf and colleagues used a multiple baseline design across participants and the results demonstrated that all participants reached the mastery

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criterion within eight sessions (range, three to eight sessions). Furthermore, all participants maintained the targeted skill following intervention. Leaf, Taubman, et al. (2016) expanded upon the results of Leaf et al. (2015) by evaluating the CNC procedure to teach three children diagnosed with ASD social communication skills. In this study, each participant was taught one social skill (i.e., providing verbal support, chatting, interrupting). All these skills fell under the domain of social communication as described by the social taxonomy outlined by Taubman et al. (2011). Like the previous study, Leaf, Taubman, and colleagues incorporated modeling and role-play during all teaching sessions. The results demonstrated that all participants reached the mastery criterion. However, maintenance dipped for two of the participants and was variable for a third. Therefore, the researchers implemented a booster teaching session which resulted in the participants displaying the targeted skills at high levels. Leaf, Mitchell, et al. (2016) compared the CNC procedure to Social Stories for one child diagnosed with ASD. The researchers taught losing graciously, empathy, and changing the game when someone is bored using the CNC procedure and interrupting appropriately, stopping to talk, and sportsmanship using Social Stories. The CNC procedure involved modeling and role-play during every teaching session. The Social Story procedure involved implementing a basic social story (Gray & Garand, 1993) with added comprehension questions. Leaf, Mitchell, and colleagues used an adapted alternating treatments design to evaluate the effectiveness of the two procedures. The results indicated that the participant reached the mastery criterion on all three skills taught with the CNC procedure and none of the skills taught with Social Stories. Furthermore, the participant showed very little improvement from baseline to intervention for skills assigned to the Social Story condition. Thus, the results showed that a procedure as part of the APM was far more effective than a commonly used procedure (i.e., Social Stories) to teach social skills for individuals diagnosed with ASD. Au et al. (2016) evaluated the CNC procedure for individuals diagnosed with ASD in a small group format. This study expanded upon the previous research on the CNC procedure in three ways. First, it was the first study to evaluate the CNC procedure in a group instructional format. Second, it was the first study that was conducted internationally (i.e., Hong Kong) on the use of the CNC procedure. Finally, this study attempted a component analysis by starting with only modeling, followed by adding the role-play, and then role-play plus feedback if needed. Each participant had 10 sessions to reach the mastery criterion for the targeted skills with modeling only. If after

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10 sessions, the participant had not reached the mastery criterion with modeling only then role-playing was added to the intervention. If after another 10 sessions the participants did not reach the mastery criterion, then feedback was provided. Au and colleagues taught participants to invite peers to play, comment on toys, and gain a peer’s attention. Au and colleagues evaluated the effectiveness of the CNC procedure using a multiple baseline design. Participants reached the mastery criterion on 67% of the skills with modeling only and reached the mastery criterion on the remaining 33% of the skills with modeling, role-play, and feedback. Thus, showing that some skills did not require role-playing while others did for the participants to reach the mastery criterion. Milne et al. (2017) and Leaf, Leaf, et al. (2016) further expanded on the CNC procedure as it relates to implementing the CNC procedure in a group instructional format. Both studies were also a part of a large randomized clinical trial study that evaluated the effectiveness of behaviorally based social skills groups (i.e., Leaf et al., 2017). Milne and colleagues targeted peer to peer communication and joint attention using the CNC procedure. Each CNC session consisted of interventionist demonstration and role-play. All but 2 of the 16 participants reached the mastery criterion for joint attention and peer to peer communication. For those participants that did not reach the mastery criterion on joint attention or social communication did show marked improvements from baseline levels. Furthermore, the results did indicate high levels of maintenance for all participants. Leaf, Leaf, and colleagues evaluated the effectiveness of the CNC procedure implemented in a group instructional format to teach eight children how to play interactive games (i.e., fruit salad, the sleeping game, and mouse trap). All sessions consisted of interventionist demonstration and role-play. Leaf, Leaf, and colleagues used a multiple baseline design to evaluate the effectiveness of the CNC procedure. The results demonstrated that seven of the eight participants reached the mastery criterion on all games taught and maintained at high levels. Olcay-Gul and Vuran (2019) were the first researchers outside of Autism Partnership to evaluate the CNC procedure. In this study, Olcay-Gul and Vuran evaluated the CNC procedure to teach three children diagnosed with ASD how to cope with inappropriate requests from peers or adults. The participants’ ages ranged from 8 to 12 years old, marking the oldest participants in any empirical study to date. Olcay-Gul and Vuran used a multiple probe design across participants and the results indicated that the CNC procedure was effective in teaching all participants the targeted skill. Additionally, the

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target skill was maintained at a 10-week follow-up. Furthermore, social validity data revealed that the participants felt positive about the CNC procedure. Thus, this study expanded upon previous research by evaluating the CNC procedure with older participants and taking social validity measures. Most importantly though, this study expanded upon previous research by including researchers outside of Autism Partnership/Autism Partnership Foundation to evaluate the CNC procedure and showing it to be an effective procedure. In 2020, behavioral intervention quickly switched to telehealth due to the devastating effects of COVID-19. Unfortunately, the research on behavioral intervention delivered via this modality was limited at the time. As such, there were no data on the effectiveness of the CNC procedure implemented via telehealth. Cihon et al. (2022), however, were the first to empirically evaluate the effectiveness of the CNC procedure implemented directly via telehealth. Specifically, Cihon and colleagues evaluated the effectiveness of the CNC procedure implemented directly via telehealth to teach three children diagnosed with ASD to change the conversation when their conversation partner was bored. Cihon and colleagues used interventionist demonstration and role-play during all sessions. All three participants reached the mastery criterion within no more than eight sessions. Further, two of the three participants showed marked improvements during a generalization probe with another conversation partner. This study demonstrated that the CNC procedure can be effective even when implemented directly via telehealth adding to the options for interventionists targeting social skills within a virtual environment.

Summary For over 25 years, the CNC procedure has been implemented clinically with thousands of individuals diagnosed with ASD. Clinically, it has been demonstrated to be effective in teaching social skills, language development, school readiness skills, and decreasing undesired behavior. Further, numerous clinical trainings have been conducted to train teachers, paraprofessionals, and caregivers resulting in the CNC procedure being implemented by professionals who would not consider themselves behavior analysts. In the last 10 years, there has been an increasing number of studies that have demonstrated the effectiveness and efficiency of the CNC procedure. Overall, the CNC procedure is an effective teaching procedure which can be used to teach a variety of skills with autistic individuals of all ages.

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Given the effectiveness of the procedure and the relative ease of implementing the procedure, interventionists should feel confident in using the CNC procedure to teach a wide variety of skills to a wide variety of clients.

References Au, A., Mountjoy, T., Leaf, J. B., Leaf, R., Taubman, M., McEachin, J., & Tsuji, K. (2016). Teaching social behaviour to individuals diagnosed with autism spectrum disorder using the cool versus not cool procedure in a small group instructional format. Journal of Intellectual Disability, 2, 115–124. https://doi.org/10.3109/13668250.2016.1149799. Cihon, J. H., Ferguson, J. L., Leaf, J. B., Milne, C., Leaf, R., & McEachin, J. (2019). A randomized clinical study of three prompting systems to teach tact relations. Journal of Applied Behavior Analysis, 53(2), 727–743. https://doi.org/10.1002/jaba.617. Cihon, J. H., Ferguson, J. L., Lee, M., Leaf, J. B., Leaf, R., & McEachin, J. (2022). Evaluating the cool versus not cool procedure via telehealth. Behavior Analysis in Practice, 15(1), 260–268. https://doi.org/10.1007/s40617-021-00553-z. Creem, A., Leaf, J. B., & Oppenheim-Leaf, M. L. (2022). Social behavior and interventions for individuals diagnosed with autism Spectrum disorder. In J. L. Matson, & P. Sturmey (Eds.), Handbook of autism and pervasive developmental disorder. Autism and child psychopathology series. Cham: Springer. https://doi.org/10.1007/978-3-030-88538-0_37. Gray, C. A., & Garand, J. D. (1993). Social stories: Improving responses of students with autism with accurate social information. Focus on Autistic Behavior, 8(1), 1–10. Leaf, J. B., Kassardjian, A., Oppenheim-Leaf, M. L., Cihon, J. H., Taubman, M., Leaf, R., & McEachin, J. (2016). Social thinking®: Science, pseudoscience, or antiscience? Behavior Analysis in Practice, 9(2), 152–157. https://doi.org/10.1007/s40617-016-0108-1. Leaf, J. B., Leaf, J. A., Milne, C., Taubman, M., Oppenheim-Leaf, M., Torress, N., Townley-Cochran, D., Leaf, R., McEachin, J., & Yoder, P. (2017). An evaluation of a behaviorally based social skills group for individuals diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(2), 243–259. https://doi. org/10.1007/s10803-016-2949-4. Leaf, J. A., Leaf, J. B., Milne, C., Townley-Cochran, D., Oppenheim-Leaf, M. L., Cihon, J. H., Taubman, M., McEachin, J., & Leaf, R. (2016). The effects of the cool versus not cool procedure to teach social game play to individuals diagnosed with autism spectrum disorder. Behavior Analysis in Practice, 9(1), 34–49. https://doi.org/10.1007/ s40617-016-0112-5. Leaf, J. B., Mitchell, E., Townley-Cochran, D., McEachin, J., Taubman, M., & Leaf, R. (2016). Comparing social stories™ to cool versus not cool. Education and Treatment of Children, 39(2), 173–186. Leaf, J. B., Taubman, M., Leaf, J., Dale, S., Tsuji, K., Kassardjian, A., Alcalay, A., Milne, C., Mitchell, E., Townley-Cochran, D., Leaf, R., & McEachin, J. (2015). Teaching social interaction skills using cool versus not cool. Child and Family Behavior Therapy, 37(4), 321–334. https://doi.org/10.1080/07317107.2015.11044778. Leaf, J. B., Taubman, M., Milne, C., Dale, S., Leaf, J., Townley-Cochran, D., Tsuji, K., Kassardjian, A., Alcalay, A., Leaf, R., & McEachin, J. (2016). Teaching social communication skills using a cool versus not cool procedure plus role-playing and a social skills taxonomy. Education and Treatment of Children, 39(1), 44–63. Leaf, J. B., Tsuji, K. H., Griggs, B., Edwards, A., Taubman, M., McEachin, J., Leaf, R., & Oppenheim-Leaf, M. L. (2012). Teaching social skills to children with autism using the cool versus not cool procedure. Education and Training in Autism and Developmental Disabilities, 47(2), 165–175.

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Milne, C., Leaf, J. A., Leaf, J. B., Cihon, J. H., Torress, N., Townley-Cochran, D., Taubman, M., Leaf, R., McEachin, J., & Oppenheim-Leaf, M. (2017). Teaching joint attention and peer to peer communication using the cool versus not cool procedure in a large group setting. Journal of Developmental and Physical Disabilities, 29(5), 777–796. https://doi.org/10.1007/s10882-017-9556-y. Olcay-Gul, S., & Vuran, S. (2019). Effectiveness of teaching social skills to individuals with autism spectrum disorder using cool versus not cool. Education and Training in Autism and Developmental Disabilities, 54(2), 132–146. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j. rasd.2008.03.005. Taubman, M., Leaf, R., & McEachin, J. (2011). Crafting connections: Contemporary applied behavior analysis for enriching the social lives of persons with autism spectrum disorder. Different Roads to Learning.

CHAPTER 16

Social skills groups Contents Hallmarks of behaviorally based social skills groups Evidence-based and conceptually systematic Use a variety of teaching strategies Teachable moments As naturalistic as possible Contingency systems Curriculum Peers Caregivers Length Research General overview of research Research on the Autism Partnership Method Summary References

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Behaviorally based social skills groups are a common component of intervention as part of the Autism Partnership Method (APM). The APM defines a behaviorally based social skills group as “three or more learners coming together to learn social behaviors simultaneously using [applied behavior analysis] (ABA) principles” (Leaf, Milne, et al., 2020, p. 23). Behaviorally based social skills groups are implemented for all ages including young children (e.g., 2–3 years old), preschool-aged children, elementary school-aged children, middle school children, and adolescents in high school. Behaviorally based social skills groups can be implemented across all types of learners from those with less developed language skills and higher rates of challenging behavior to those working on complex social skills. Since behaviorally based social skills groups are an important part of the APM, previous books and chapters have been dedicated to describing social skills groups (e.g., Leaf, Cihon, & Ferguson, 2017; Leaf, Milne, et al., 2020; Taubman et al., 2011). As such, this chapter provides only a brief overview of behaviorally based social skills group in the APM. We recommend that consumers of this book access previous works for more comprehensive information. A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00007-6

Copyright © 2024 Elsevier Inc. All rights reserved.

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Hallmarks of behaviorally based social skills groups Evidence-based and conceptually systematic When an interventionist implements a behaviorally based social skills group, a distinguishing feature is that the procedures are empirically supported and would be defined as evidence-based practices. Empirically supported interventions are those interventions that have been experimentally evaluated and published in peer-reviewed journals. Evidence-based practices are defined as practices or interventions that have the best research evidence combined with the interventionist’s training and skills and a client’s input/preferences (American Psychological Association Presidential Task Force on Evidence-Based Practice, 2006; Leaf et al., 2021). Thus, an interventionist must constantly evaluate if the procedures they choose to implement have strong empirical evidence, what their skill level is when implementing a given procedure, and if they are incorporating the client’s preferences prior to implementing a procedure. Therefore, interventions such as fidget spinners (Cihon et al., 2020), weighted vests (Taylor et al., 2017), Social Thinking (Leaf et al., 2018), Rapid Prompting Method (Schlosser et al., 2019), Social Stories (Leaf, Cihon, et al., 2020), or Floortime (Mercer, 2017) should not implemented as a part of behaviorally based social skills groups because they do not have the best research evidence and are often not empirically supported or evidence-based treatments (American Psychological Association Presidential Task Force on EvidenceBased Practice, 2006; Leaf et al., 2021). Additionally, within the context of APM’s behaviorally based social skills groups, interventionists only implement procedures that are conceptually systematic with the principles of ABA (Baer et al., 1968, 1987; Wolf, 1978). For example, shaping, discrete trial teaching, and the teaching interaction procedure are all based on the principles of ABA and, therefore, can be implemented within the context of a behaviorally based social skills group. Given that the APM is one of flexibility and discovery, there are times when an interventionist might create a new procedure that does not have empirical support in peer-reviewed journals and does not meet the criterion of an evidence-based practice. In the history of Autism Partnership/Autism Partnership Foundation, there have been many instances of this occurring, whether it be the Cool versus Not Cool Procedure (Leaf et al., 2012), the magic number token system (Cihon, Ferguson, Milne, et al., 2019), or flexible prompt fading (Soluaga et al., 2008). If a procedure is novel, it does not mean that an interventionist cannot or should not implement the new

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procedure. Rather, they should ensure that some conditions are met. First, they must ensure that the new procedure is conceptually systematic with the principles of behavior analysis. Second, they should ensure that the new procedure is clearly described and operationally defined so that other interventionists can implement the procedure. Third, the interventionist must carefully monitor the fidelity of implementation of the procedure and the effectiveness of the procedure through objective data collection. Finally, the interventionist should always measure if the target behavior is changing in the desired direction and attempt to empirically evaluate the procedure as soon as possible.

Use a variety of teaching strategies Throughout this book, we have described various teaching procedures that can be implemented as part of the APM, such as discrete trial teaching, the Cool versus Not Cool Procedure, the Teaching Interaction Procedure, systematic desensitization, shaping, and incidental teaching. When running a behaviorally based social skills group, an interventionist does not just implement one procedure within a session or across sessions. Rather, the interventionist implements whichever procedures are necessary and effective, which often results in the use of multiple procedures during the course of a group session. Different procedures can be very useful at teaching different skills and the combination of multiple procedures may lead to more meaningful gains for the learner.

Teachable moments One common occurrence within a conventional model of social skills groups is that group meetings are sometimes just opportunities for learners to come within proximity of peers. They are regarded as “friendship groups,” “circle of friends,” or “hang out sessions” as opposed to groups with a heavy focus on direct and indirect social instruction. Within the APM, every moment in the group is a possible teachable moment, with the goal to minimize “downtime” in which no planned learning opportunities occur. This does not mean that the interventionist must directly instruct the learners; rather, it means when direct instruction is not occurring the interventionist should arrange indirect learning opportunities. This takes careful planning of the group to ensure that every activity ocurring will provide the learners with the greatest possible number of social learning opportunities.

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As naturalistic as possible Within the APM, it is imperative that behaviorally based social skills groups are as natural as possible. Interventionists running the group should ensure that the decor and materials (e.g., posters, furniture, books) in the group setting are appropriate for the learners in the group and resemble other age-typical environments the learners would encounter. For example, if a behaviorally based social skills group is designed for high school students, the room should not be decorated with Cocomelon or Paw Patrol. Additionally, the interventionists should ensure the use of age-appropriate instructional materials and reinforcers. Finally, the interventionists should speak as naturally as possible to the learners with whom they are working using language that is age-appropriate for the make-up of the group.

Contingency systems In any behaviorally based social skills group, the interventionist must ensure the use of contingency systems. It is imperative that these contingency systems are put in place proactively and are used consistently and contingently. Within behaviorally based social skills groups, the interventionist will often implement multiple contingency systems, usually simultaneously. Thus, in a behaviorally based social skills group, an interventionist could implement learner-specific contingency systems or they could implement group contingency systems. Historically, interventionists have implemented contingency systems such as direct exchange of stimuli contingent upon a specific behavior (Cooper et al., 2020), time-in ribbons (Foxx & Shapiro, 1978), individualized and group behavioral charts (e.g., Cihon, Ferguson, Leaf, et al., 2019), noncontingent reinforcement (e.g., Carr et al., 2000), and self-monitoring systems (e.g., Holifield et al., 2010).

Curriculum It is important that the social skills taught are meaningful and that the interventionist individualizes the targets to the needs of each of the learners in the social skills group. This means that an interventionist should not assume that one single curriculum program or book will meet all the needs of all the individuals in the group, but rather draws from many curriculum programs and books that have empirical support. Additionally, the interventionist could create their own curricular targets and methods as needed. Further, when selecting curriculum, it is important for the targets to be socially valid. The interventionist should collaborate with the learners in the group and

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their caregivers to decide which goals to target and what goals should be prioritized (Wolf, 1978). This does not mean that the interventionist only selects goals that the learner or caregivers request, but it does mean that relevant consumers should be part of the collaborative process when it comes to goal selection. Behaviorally based social skills groups are not just for teaching and developing social behavior, but an opportunity to develop a wide range of skills. These include improving language and communication skills, play and leisure skills, developing learning-how-to-learn skills, adaptive behaviors, and self-help skills. Additionally, an interventionist should address the presence of any challenging behavior such as aggression, self-injury, pica, elopement, and stereotypic behaviors that interfere with the learning process. Further, an interventionist should always consider the immediate and long-term benefits of teaching a social skill. During group, the interventionist should target multiple skills and curricular goals. Finally, the interventionist should target social skills in relevant contexts to increase the probability of the social skills generalizing to natural settings.

Peers Within the APM, neurotypical same-aged peers are included as part of behaviorally based social skills groups. Peers are an important part of groups because they can serve as excellent models of age-typical social behavior. When including peers, there are several guidelines that should be considered by an interventionist. First, peers in the group should not be interventionists. The goal is not for the peers to become teachers in the group, but rather to be a peer and model for the learners in the group. Second, peers should also have their own goals and contingency systems when they participate in the group. This way, the peers also obtain therapeutic benefits from the group and have opportunities to access reinforcement. Third, the use of siblings as peers in the group is strongly discouraged. Siblings of individuals diagnosed with autism should have their own identity, their own special activities, their own special time, and not feel that their lives completely revolve around their sibling’s life.

Caregivers It is critical that parents and caregivers are included as part of the behaviorally based social skills groups. Interventionists should ensure that they proactively meet with caregivers prior to the group commencing. Interventionists

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should share information regarding procedures, goals, and desired outcomes. Interventionists should also work collaboratively with parents and seek their input prior to the learner participating in the group. Following each group session, interventionists should debrief with caregivers verbally or via a note. It is highly recommended that the social skills group have an open-door policy (e.g., caregivers can come and observe whenever they wish) or at the very least a semiopen-door policy (e.g., caregivers can come observe with prior notice). Having an open-door policy helps increase trust and rapport between the parents and the interventionists. Additionally, interventionists can use these opportunities to model various interventions for parents and caregivers that can be used at home.

Length There is no magic number or set standard for the number of sessions per week or session duration of each social skills group. However, it stands to reason that the more opportunities there are to systematically practice social behavior in a group setting, the more fluent the social behaviors will become, and the learners will likely learn the targeted skills faster. Generally, we recommend that social skills groups are conducted at least twice per week. Further, we recommend that groups last at least 60–90 min depending on the participants’ ages.

Research General overview of research Behaviorally based social skills groups have a plethora of research published in peer-reviewed journals (e.g., Au et al., 2016; Dotson et al., 2010; Gengoux et al., 2021; Kamps et al., 1992; Leaf et al., 2010; Oppenheim-Leaf et al., 2012). Most of the research on behaviorally based social skills groups have been evaluated using single subject research designs. Researchers have also shown behaviorally based social skills groups to be effective using group research design methodology (e.g., Laugeson et al., 2015; Leaf, Leaf, et al., 2017). There are a number of findings from the research literature. First, behaviorally based social skills groups are effective in increasing behavior for participants of a wide range of ages from as young as 3 years old to age 44 (e.g., Howlin & Yates, 1999; Leaf et al., 2010). Second, social skills groups can be effective for a wide range of functioning levels (Au et al., 2016; Dotson et al., 2010; Gengoux et al., 2021; Kamps et al., 1992; Leaf et al.,

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2010; Oppenheim-Leaf et al., 2012). Third, social skills groups are effective in teaching a wide variety of social behaviors such as conversation (Dotson et al., 2010), reading social cues (Leaf, Leaf, et al., 2017), complimenting others (Leaf et al., 2010), and perspective taking (Laugeson et al., 2015). Fourth, a wide variety of procedures can be implemented in the context of a behaviorally based social skills group, including level systems or behavioral charts (e.g., Leaf, Leaf, et al., 2017), self-management strategies (e.g., Cotugno, 2009), video modeling (e.g., Kroeger et al., 2007), and peermediated strategies (e.g., Banda et al., 2010). Kamps et al. (1992) conducted a seminal study on social skills groups. In this study, Kamps and colleagues evaluated social skills groups conducted in a first-grade classroom. Kamps and colleagues used a teaching package based upon the principles of applied behavior analysis. Kamps and colleagues sought to improve a variety of social behaviors including initiating, asking for help, and accepting compliments. Using a multiple baseline design, Kamps and colleagues demonstrated a positive increase in social interactions. The most commonly implemented behaviorally based social skills group to date is the Program for the Education and Enrichment of Relational Skills (PEERS) model (Idris et al., 2020; Laugeson et al., 2014, 2015; Rabin et al., 2018; Shum et al., 2019; Yamada et al., 2020). The PEERS model is a structured program to teach adolescents and adults various social behaviors in a group setting. The research conducted on the PEERS model of social skills groups have consistently shown that the implementation of the PEERS model results in significant increases in social behavior.

Research on the Autism Partnership Method In terms of the APM, there have been numerous single subject designs that have demonstrated the effectiveness of various components used in social skills groups that reflect a progressive approach to teaching (Au et al., 2016; Dotson et al., 2010; Leaf et al., 2010; Oppenheim-Leaf et al., 2012). Research has demonstrated that the teaching interaction procedure, the Cool versus Not Cool procedure, and discrete trial teaching can all be effective in the context of social skills groups (Leaf et al., 2010; Leaf, Leaf, et al., 2017). However, our largest empirical investigation to demonstrate the effectiveness of behaviorally based social skills groups using the APM is known as the “Penguin Study” (Leaf, Leaf et al., 2017). It is called the Penguin Study due to the participants choosing to identify their group as “the Penguins.”

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The goal of the Penguin Study was to evaluate a behaviorally based social skills group to improve the social behavior for several individuals diagnosed with autism that previously would have been referred to as “high functioning” (e.g., higher levels of communication and low levels of behavior). For participants to be included in the study they had to meet several criteria: (a) an independent diagnosis of autism, (b) be between 4 and 7 years of age, (c) had never received services from Autism Partnership, (d) display low levels of stereotypic and challenging behavior, (e) display normal levels of language based upon standardized assessments, (f ) an IQ of 80 or above, and (g) display deficits of social behavior as determined by standardized assessments. Leaf, Leaf et al. (2017) randomly assigned participants to either the treatment group (i.e., the group that received treatment immediately) or a wait list control group (i.e., a group that received treatment after the completion of treatment for the first cohort). In the Penguin Study, there were a total of 15 participants. Eight of these participants were randomly assigned to the treatment group and seven were randomly assigned to the wait-list control group. The average age for participants in the treatment group was 4.07 years and the average age for participants in the wait list control group was 4.10 years. There were no significant differences between the groups in terms of IQ scores, Vineland Adaptive Behavior Composite Scores, Peabody Picture Vocabulary Test scores, or Expressive One Word Vocabulary Picture Vocabulary Test scores. The researchers evaluated improvements in participant behavior using four standardized measures. The Social Skills Improvement System (SSiS) and Social Responsiveness Scale (SRS) were used to assess social functioning. The Walker McConnell was used to measure that social competence and classroom readiness skills. Finally, the Aberrant Behavior Checklist evaluated the presence and levels of challenging behavior. Each of these assessments were completed by three different professionals: (a) a lead researcher, (b) a lead teacher of the social skill group, and (c) a blind evaluator. These assessments were completed at four different periods of time. First, the participants in both groups were evaluated prior to intervention (T1). Next, the participants were evaluated following intervention for the treatment group and prior to intervention for the waitlist control group (T2). Third, the participants were evaluated 16 weeks after intervention for the treatment group and following intervention for the control group (T3). Finally, the participants were evaluated 32 weeks after intervention for the treatment group and 16 weeks following intervention for the wait-list control group. During each observation period, all 15 participants

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were evaluated together during group sessions as well as separately in their individual natural environments (e.g., home, school). The lead interventionists of the social skills group provided intervention how they would typically provide treatment in a clinical setting. Following intervention, Leaf, Leaf et al. (2017) used video recordings to quantify and analyze the procedures implemented and goals targeted. The interventionists did not use any set protocols during group instruction; therefore, interventionists were free to tailor their instruction to the needs of individual participants and the group as a whole. As such, this study represented what naturally occurs during teaching at social skills groups within the APM. Both the treatment group and the wait list control group met for a total of 32 sessions. Each session lasted 2 h for a total of 64 h spent in the group. The group met twice per week. The general schedule of the group was: (a) free play, (b) opening circle, (c) small group where games were taught, (d) large group instruction, (e) outside game instruction, (f ) outside free play, (g) large group instruction, (h) closing circle, and (i) “cash in” (i.e., reinforcement provided contingent on individual behavior in the group). Throughout all these activities, a variety of behaviorally based interventions/procedures were implemented including: (a) shaping, (b) the teaching interaction procedure, (c) discrete trial teaching, (d) incidental teaching, (e) Cool versus Not Cool procedure, and (f ) embedded instructions. Additionally, the researchers used a level system (e.g., Leaf, Leaf et al., 2017), individual token economies (e.g., Cihon, Ferguson, Milne, et al., 2019; Fiske et al., 2015), and noncontingent reinforcement (Carr et al., 2000) as part of the contingency systems. Leaf, Leaf, and colleagues’ (2017) main dependent variable was statistical improvement in social behavior as determined by the four standardized assessments described above. The data from T1 showed that there were no significant differences between the two groups prior to intervention. This is important, as any change in scores could be attributed to the intervention and not to some extraneous variable. The data from T2 showed a significant improvement for the treatment group, no significant improvement for the wait-list control group, and a significant difference between the two groups. This indicated that improvement in social behavior was due to the social skills group and that the participants significantly improved their social behavior when they received this intervention. The data from T3 showed no significant difference for the treatment group from T2 to T3, a significant improvement for the wait-list control

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group, and no significant difference between the two groups. This indicated that the treatment group maintained their gains following a 16-week maintenance period, that the wait list control group improved their social behavior, and that there were no differences between the two groups. The data from T4 showed no significant difference for the treatment group T2 to T4, no significant difference for the wait-list control group from T3 to T4, and no significant difference between the two groups. This indicated that both groups maintained their behavior 32 and 16 weeks after intervention. We also evaluated social validity by giving parents a survey of their satisfaction with improvements, the interventionists, and the procedures. The results showed that the parents were very satisfied with all aspects of the group.

Summary Behaviorally based social skills groups have a plethora of research published in peer-reviewed journals supporting their effectiveness (e.g., Au et al., 2016; Dotson et al., 2010; Gengoux et al., 2021; Kamps et al., 1992; Leaf et al., 2010; Oppenheim-Leaf et al., 2012). The results from the study described in detail here as well as our clinical findings for the past 20 years, align with this research. The implementation of these groups can have lifealtering positive improvements for autistic children and their families and are a core part of the APM.

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Kroeger, K. A., Schultz, J. R., & Newsom, C. (2007). A comparison of two group-delivered social skills programs for young children with autism. Journal of Autism and Developmental Disorders, 37(5), 808–817. https://doi.org/10.1007/s10803-006-0207-x. Laugeson, E. A., Ellingsen, R., Sanderson, J., Tucci, L., & Bates, S. (2014). The ABC’s of teaching social skills to adolescents with autism spectrum disorder in the classroom: The UCLA PEERS® program. Journal of Autism and Developmental Disorders, 44(9), 2244–2256. https://doi.org/10.1007/s10803-014-2108-8. Laugeson, E. A., Gantman, A., Kapp, S. K., Orenski, K., & Ellingsen, R. (2015). A randomized controlled trial to improve social skills in young adults with autism spectrum disorder: The UCLA PEERS® program. Journal of Autism and Developmental Disorders, 45(12), 3978–3989. https://doi.org/10.1007/s10803-015-2504-8. Leaf, J. B., Cihon, J. H., & Ferguson, J. L. (2017). Behaviorally based social skill groups. In F. R. Volkmar (Ed.), Encyclopedia of autism spectrum disorders. Cham: Springer. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Milne, C., Leaf, R., & McEachin, J. (2020). Recommendations for behavior analysts regarding the implementation of Social Stories™ for individuals diagnosed with autism spectrum disorder. Behavioral Interventions, 35(4), 664–679. https://doi.org/10.1002/bin.1736. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Taubman, M., Leaf, R., & McEachin, J. (2018). Social Thinking®, pseudoscientific, not empirically supported, and non-evidence based: A reply to Crooke and Winner. Behavior Analysis in Practice, 11(4), 456–466. https://doi. org/10.1007/s40617-018-0241-0. Leaf, J. B., Dotson, W. H., Oppenheim, M. L., Sheldon, J. B., & Sherman, J. A. (2010). The effectiveness of a group teaching interaction procedure for teaching social skills to young children with a pervasive developmental disorder. Research in Autism Spectrum Disorders, 4(2), 186–198. https://doi.org/10.1016/j.rasd.2009.09.003. Leaf, J. B., Leaf, J. A., Milne, C., Taubman, M., Oppenheim-Leaf, M., Torres, N., TownleyCochran, D., Leaf, R., McEachin, J., & Yoder, P. (2017). An evaluation of a behaviorally based social skills group for individuals diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(2), 243–259. https://doi.org/10.1007/s10803016-2949-4. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The Autism Partnership Method: Social skills groups. Different Roads to Learning. Leaf, J. B., Sato, S. K., Javed, A., Arthur, S. M., Creem, A. N., Cihon, J. H., Ferguson, J. L., & Oppenheim-Leaf, M. L. (2021). The evidence-based practices for children, youth, and young adults with autism report: Concerns and critiques. Behavioral Interventions, 36(2), 457–472. https://doi.org/10.1002/bin.1771. Leaf, J. B., Tsuji, K. H., Griggs, B., Edwards, A., Taubman, M., McEachin, J., Leaf, R., & Oppenheim-Leaf, M. L. (2012). Teaching social skills to children with autism using the cool versus not cool procedure. Education and Training in Autism and Developmental Disabilities, 47(2), 165–175. Mercer, J. (2017). Examining DIR/Floortime™ as a treatment for children with autism spectrum disorders: A review of research and theory. Research on Social Work Practice, 27(5), 625–635. https://doi.org/10.1177/1049731515583062. Oppenheim-Leaf, M. L., Leaf, J. B., & Call, N. A. (2012). Teaching board games to two children with an autism spectrum disorder. Journal of Developmental and Physical Disabilities, 24, 347–358. https://doi.org/10.1007/s10882-012-9274-4. Rabin, S. J., Israel-Yaacov, S., Laugeson, E. A., Mor-Snir, I., & Golan, O. (2018). A randomized controlled trial evaluating the Hebrew adaptation of the PEERS® intervention: Behavioral and questionnaire-based outcomes. Autism Research, 11(8), 1187–1200. https://doi.org/10.1002/aur.1974.

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Schlosser, R. W., Hemsley, B., Shane, H., Todd, J., Lang, R., Lilienfeld, S. O., Trembath, D., Mostert, M., Fong, S., & Odom, S. (2019). Rapid prompting method and autism spectrum disorder: Systematic review exposes lack of evidence. Review Journal of Autism and Developmental Disorders, 6, 403–412. https://doi.org/10.1007/s40489-01900175-w. Shum, K. K.-M., Cho, W. K., Lam, L. M. O., Laugeson, E. A., Wong, W. S., & Law, L. S. K. (2019). Learning how to make friends for Chinese adolescents with autism spectrum disorder: A randomized controlled trial of the Hong Kong Chinese version of the PEERS® intervention. Journal of Autism and Developmental Disorders, 49(2), 527–541. https://doi.org/10.1007/s10803-018-3728-1. Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j. rasd.2008.03.005. Taubman, M., Leaf, R., & McEachin, J. (2011). Crafting connections: Contemporary applied behavior analysis for enriching the social lives of persons with autism spectrum disorder. DRL. Taylor, C. J., Spriggs, A. D., Ault, M. J., Flanagan, S., & Sartini, E. C. (2017). A systematic review of weighted vests with individuals with autism spectrum disorder. Research in Autism Spectrum Disorders, 37, 49–60. https://doi.org/10.1016/j.rasd.2017.03.003. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203. Yamada, T., Miura, Y., Oi, M., Akatsuka, N., Tanaka, K., Tsukidate, N., Yamamoto, T., Okuno, H., Nakanishi, M., Taniike, M., Mohri, I., & Laugeson, E. A. (2020). Examining the treatment efficacy of PEERS in Japan: Improving social skills among adolescents with autism spectrum disorder. Journal of Autism and Developmental Disorders, 50(3), 976–997. https://doi.org/10.1007/s10803-019-04325-1.

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CHAPTER 17

Functional behavior assessment and functional analysis Contents Overview of functional behavior assessment Types of functional analysis Standard functional analysis Brief functional analysis Trial-based functional analysis Latency-based functional analysis Precursor functional analysis Practical functional assessment History of FBA and functional analysis The autism partnership method approach to FBAs and FAs References

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Behavior is lawful and orderly (Skinner, 1953). In other words, behavior is the result of present and past circumstances that can be traced back to the natural environment. When a learner engages in challenging behavior, it does not occur because of their zodiac sign, because of the positioning of the moon, or just randomly out of the blue. Rather, the behavior occurs because of the learner’s interaction with their environment. When a learner is engaging in challenging behavior, it is important for a behavior analyst to identify the reason why the behavior is occurring. This is known as the function of the behavior. A conventional approach to applied behavior analysis (ABA) presumes that behavior happens primarily for either one of the four reasons (Dixon et al., 2012). The first reason is social positive reinforcement, also known as attention. For example, a learner might throw a toy at their sibling to gain their attention. The second reason is social negative reinforcement or to escape from unwanted situations. For example, during nonpreferred circle time, a learner might start to loudly sing theme songs from cartoon shows so that the teacher removes them from the group. The third reason is tangible positive reinforcement or access to preferred items. For example, a learner might start crying in a

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store, so their parents buy them their favorite candy. The final reason is automatic reinforcement. Automatic reinforcement is not mediated by social contingencies in the environment but rather from other reasons such as engaging in the behavior “feels good,” or it eliminates a feeling or stimulus to which only the individual has access (Vollmer, 1994). For example, a person might engage in head banging to alleviate a headache. As previously stated, a behavior analyst using a conventional approach to ABA is likely to contend that every behavior falls into one and only one of these four categories. Within the Autism Partnership Method (APM), we assert that there are additional reasons why a learner may engage in challenging behavior. First, a learner might engage in behavior for control. When a learner engages in a behavior maintained by control, they are not engaging in behavior to gain attention, obtain access to an item, escape an undesired situation, or because it feels good. Rather, they want to control their environment and/or another person. For example, a learner may want to play with blocks but only wants a particular person to give them the blocks in a particular way; otherwise, they will not want to play with the blocks. A second reason a learner might display challenging behavior is that it has been respondently elicited, or in other words, it was triggered by emotional arousal. As we discussed in Chapter 4, respondent behavior is an involuntary response to an antecedent stimulus rather than operantly motivated. For example, a kindergartner may cry on their first day of school because they are sad to be leaving their mom, or a first grader might start asking a lot of questions of their teacher because they are feeling anxious. On a similar note, a learner might engage in challenging behavior for frustration release. For example, an adult male might scream, swear, or slam a door as a way to alleviate their frustration. Thus, within the APM, there is consideration of a broader range of reasons for why behavior occurs compared to a conventional approach.

Overview of functional behavior assessment It is important for behavior analysts to reduce challenging behavior for our learners when it might cause harm to oneself, cause harm to others, interfere with the learning process, and/or reduce their overall quality of life. Often, to reduce challenging behavior, a behavior analyst needs to teach a functionally equivalent alternative behavior. A functional alternative behavior is one that will result in the learner accessing the same consequence that occurs when they engage in the challenging behavior. In other words, if a learner engages

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in yelling to access attention, teaching a functional alternative behavior would involve teaching the learner how to get attention in another way. To do this, a behavior analyst may need to conduct a functional behavioral assessment (FBA). FBAs are a series of methods that are used to determine why a learner is engaging in challenging behavior. In doing so, the behavior analyst observes the behavior that is occurring, the antecedents that occur prior to the behavior, and the consequences that follow the behavior. There are a series of steps that a behavior analyst may take to determine behavioral function. This is often conceptualized as three tiers. The indirect measures, descriptive assessments, and analog or experimental analyses (Parker et al., 2008). The first tier, indirect measures, can include record reviews, questionnaires, interviewing the learner, the learner’s caregivers, the learner’s family members, or other professionals (e.g., teachers, principals, social workers). When conducting an interview, it is important that the behavior analyst does so in a compassionate and caring manner. Asking a series of questions backto-back without taking account of the person’s feelings will not only result in the behavior analyst appearing cold but may also impact the information received. Thus, it is important for the person leading the interview to make statements of compassion (e.g., “That must be difficult”), not interrupt the interviewee, and make sure that they never come across as judgmental. Additionally, it is imperative for the behavior analyst to find out why the person believes the challenging behavior is occurring, what occurs prior to the behavior, what occurs following the behavior, how often the behavior occurs, the situation in which the behavior occurred, and the intensity of that behavior. An indirect assessment can also include questionnaires or assessment forms. There are numerous assessments that can be used to help determine function. These include the Motivational Assessment Scale (MAS; Durand & Crimmins, 1988), the Functional Analysis Screening Tool (FAST; Iwata et al., 2013), the Questions about Behavioral Function (QABF; Matson & Vollmer, 1995), or the Aberrant Behavior Checklist (ABC; Aman & Singh, 1994). Although questionaries can be useful, they should not be the only means of determining function, as researchers have demonstrated that they are not always the most accurate or valid when determining function (e.g., Iwata et al., 2013). Advantages of indirect measures used in an FBA include: (a) ability to obtain information from multiple people/perspectives, (b) record review can show history and help narrow the focus, (c) these methods can be

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conducted in-person or via a distance (Parker et al., 2008). Although there are advantages, there are also several limitations of indirect measures including: (a) records being ambiguous or difficult to interpret, (b) respondents to questionnaires or interviews may have an inaccurate recall, (c) integration of reports may be time-consuming or complex, (d) indirect measures can be subjective, and (e) these measures are not sufficient to determine function (Parker et al., 2008). Further analysis is recommended to more clearly identify the function of behavior and develop an effective treatment. Because of these limitations, a behavior analyst should also conduct tier 2 assessments, or descriptive assessments (Contreras et al., 2022). Descriptive assessments require that a behavior analyst observe the learner engaging in the challenging behavior in their natural environment, document what is occurring before and after the behavior, and determine what environmental factors are present when the challenging behavior occurs. The most commonly used descriptive assessment is Antecedent-Behavior-Consequence (ABC) data collection (Oliver et al., 2015). During ABC data collection, the behavior analyst observes the learner and writes down and describes the antecedents and consequences surrounding the challenging behavior. In doing so, the behavior analyst determines the pattern of environmental events to help determine the function of the behavior. When conducting an ABC observation, it is important to conduct multiple observations, at different periods of time, to help fully capture what is occurring in the person’s natural environment. Advantages of descriptive assessments include: (a) avoiding retrospective recall and subjective bias, (b) good ecological validity, (c) allowing for comparison preintervention and postintervention, and (d) individuals without a behavior analysis background can be trained to use this method rather quickly (Parker et al., 2008). Limitations of descriptive assessments include the lack of systematic and precise control that is found in experimental functional analyses (Parker et al., 2008). The final, and often optional, component of an FBA is a functional analysis (i.e., tier 3 assessment). Functional analysis is any experimental manipulation and empirical demonstration of a cause-and-effect relationship between two variables (Baer et al., 1968). This is done by directly manipulating the learner’s environment. Within an experimental functional analysis for determining the function of challenging behavior, the behavior analyst exposes the learner to a series of different conditions that are each uniquely arranged to test for a corresponding function of behavior (Iwata & Dozier, 2008). For example, in an attention condition, the interventionist would ignore the learner (i.e., withhold attention) by being otherwise engaged in another

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activity (e.g., working on a laptop). If the learner engages in challenging behavior, then the interventionist stops working and provides attention. For the escape condition, the interventionist provides a series of instructions to the learner. If the learner engages in challenging behavior, then the interventionist stops presenting the task demands allowing the learner to escape from the demands. For the tangible condition, the interventionist provides the learner with preferred items. At some point in time, they would withhold the item. When the learner engages in challenging behavior, the interventionist will give the preferred item back to the learner. To test for nonsocially mediated functions of behavior, an “alone” condition is conducted in which the learner is placed in an environment alone, with no items or activities, in a relatively barren environment to see if the challenging behavior occurs. The behavior analyst then would compare the rate/frequency/duration of challenging behavior across the conditions. The condition(s) with the highest rate/frequency/duration of challenging behavior is determined to be the reason (i.e., the function) why the behavior is occurring. Today, there are numerous types of functional analysis that can be used to determine the function.

Types of functional analysis Standard functional analysis The most commonly researched and established functional analysis methodology is the one developed and researched by Iwata et al. (1982). Within this type of functional analysis, the behavior analyst evaluates the four conditions (previously described) with the addition of a control condition. Typically, these types of evaluations are done for numerous sessions across numerous days. This methodology can take up to 15 min to complete a single condition; thus, for one session (i.e., all four or five conditions), it could take 60–75 min to complete (Iwata et al., 1982). Typically, these functional analyses are conducted in an analog setting outside of the learner’s natural environment (Hanley et al., 2003).

Brief functional analysis The brief functional analysis was created as a method to reduce the amount of time it takes to conduct each condition (Northup et al., 1991). In the brief functional analysis, each condition lasts 5–10 min (Northup et al., 1991) and is completed in 90 min or less, thus reducing the total time to complete the

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analysis. Additionally, within the brief functional analysis, the behavior analyst usually only compares two conditions (i.e., a test and a control condition) as opposed to exposing the learner to all available conditions to test for all functions (Iwata & Dozier, 2008) which further reduces the amount of time to complete a functional analysis.

Trial-based functional analysis Another type of functional analysis is a trial-based functional analysis (e.g., Lambert et al., 2012). The trial-based functional analysis was developed to address some of the practical problems associated with standard experimental functional analysis methods. A trial-based functional analysis involves arranging and manipulating antecedents and consequences that occur in the learner’s natural environment (e.g., classroom) so that the trial-based functional analysis can occur throughout the learner’s typical day (Ruiz & Kubina, 2017). In a trial-based functional analysis, a hypothesis of a motivating operation or function of behavior is first established. Then, the hypothesized motivating operation is used to develop the test and control conditions. For example, if the hypothesized function is attention, then there would be a period of time where the interventionist/teacher withholds attention (i.e., the test condition) and a period of time where they provide attention continuously (i.e., the matched control). The length of these test and control conditions is brief, usually around 2 min per condition (Lambert et al., 2012). Within this trial-based functional analysis, the interventionist only allows one instance of the challenging behavior to occur within each condition, before terminating the condition. These types of functional analyses are typically done in the learner’s natural environment and are conducted by individuals with whom the learner typically interacts (Ruiz & Kubina, 2017).

Latency-based functional analysis Another variation of functional analysis is a latency-based functional analysis (Neidert et al., 2013). In this approach, the behavior analyst evaluates all four of the standard functions (i.e., attention, demand, tangible, alone) and a playcontrol condition (Neidert et al., 2013). The interventionist begins a condition and starts a timer. After one occurrence of the challenging behavior, the interventionist stops the condition. The interventionist then records the latency between the start of the condition and the first instance of challenging behavior. The assumption with this functional analysis approach is that

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the condition with shortest latency to challenging behavior is correlated with the function of the behavior. This shares similarities to the trial-based approach, in which only one instance of challenging behavior is necessary in each test condition.

Precursor functional analysis Another type of functional analysis is precursor functional analysis (Smith & Churchill, 2002). This approach to functional analysis of challenging behavior was created to minimize the risk of harm to the learner, especially when the challenging behavior in question is dangerous to the learner (e.g., self-injurious behavior, PICA). Within this approach, the behavior analyst determines which behaviors serve reliably as a precursor to the more severe challenging behavior. For example, a behavior analyst would determine if the learner would throw a toy prior to hitting someone else. Once the precursor behaviors are determined, the interventionist conducts the functional analysis but does not wait for the severe challenging behavior to occur to stop demands, provide attention, or provide a tangible. Instead, when the identified precursor behavior occurs, the demand is stopped, attention is provided, etc.

Practical functional assessment Another variation of the functional analysis, which has grown in popularity is the practical functional assessment (e.g., Ferguson et al., 2020; Rajaraman & Hanley, 2020). This type of functional analysis was created, in part, to address the concerns about longer standard functional analysis and to evaluate behavior that might have multiple functions (i.e., happening for two or more reasons). When implementing a practical functional assessment, the behavior analyst begins by conducting an open-ended interview with a learner’s caregivers or other professionals. The purpose of this open-ended interview is to gather information on what the challenging behavior looks like, identify possible precursor behaviors, and why the behavior may be occurring. The behavior analyst uses this open-ended interview to help create a single test and a control condition. The test condition involves restricting access to the hypothesized reinforcers/function(s) that were identified through the open-ended interview and only providing access to them contingent upon the identified precursor or challenging behaviors. The control condition provides free access to all the identified reinforcers so in this condition no challenging behavior should occur. Thus, the practical functional

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analysis is similar to the precursor functional analysis as the interventionist can reinforce less dangerous behavior. This approach also presumes there are multiple functions of behavior and attempts to capture all of them acting in concert to more closely reflect behavior in real-world context. The practical functional assessment also requires less replications and sessions are generally shorter (e.g., 5 min) as compared to the standard functional assessment, so the entire functional analysis can be completed in around 25 min ( Jessel, 2022).

History of FBA and functional analysis Research on functional behavior assessment and analysis is some of the most robust in the field of applied behavior analysis (ABA; Beavers et al., 2013). Functional analysis was first described by Skinner (1953). In this seminal book, Skinner introduced the term functional analysis writing, “The external variables of which behavior is a function provide for what may be called a causal or functional analysis. We undertake to predict and control the behavior of the individual organism” (p. 35). Skinner (1957) further described how a functional analysis might apply to human behavior: The probability that a verbal response of given form will occur at a given time is the basic datum to be predicted and controlled. It is the ‘dependent variable’ in a functional analysis. The conditions and events to which we turn in order to achieve prediction or control—the ‘independent variables’—must now be considered. (pp. 28–29)

Lovaas et al. (1965) were some of the first researchers to evaluate the predecessor to formal functional analysis. In this study, Lovaas and colleagues conducted a variety of experimental manipulations using social reinforcement and extinction (i.e., stopping the delivery of contingent reinforcement) on a participant’s self-injurious behavior. First, Lovaas and colleagues taught the participant to press a bar and provided reinforcement in the form of social praise and smiling. Then, bar pressing was put on extinction and social praise and attention was withheld. The results demonstrated that the bar pressing behavior decreased when extinction was implemented while the participant’s self-injurious behavior increased. This relationship led Lovaas and colleagues to hypothesize that the participant’s appropriate behavior (e.g., bar pressing) and self-injurious behaviors might share a common reinforcer, hence a common function. Lovaas and colleagues then demonstrated that social reinforcement was maintaining the

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learner’s self-injurious behavior. Thus, one of the first studies in the steps toward a formalized functional analysis. Carr et al. (1976) were the first to evaluate an antecedent functional analysis for self-injurious behavior. In this study, Carr and colleagues had a participant who was: (a) engaging in self-injury, (b) previous interventions involving consequence manipulation were unsuccessful, and (c) self-injury was occurring frequently when demands were placed. Carr and colleagues designed three conditions (i.e., mands, tacts, and free time) where they placed and removed demands. The results demonstrated that self-injury occurred more frequently in the mand condition than in the tact or freetime condition. The most seminal article on functional analysis methodology was conducted by Iwata et al. (1982). The researchers used a multielement design with four different conditions to assess the self-injurious behavior of nine individuals with intellectual and developmental disabilities. These conditions were: (a) a social disapproval condition, (b) an academic demand condition, (c) unstructured play condition, (d) and alone condition. Each condition lasted 15 min and the order of the conditions was randomly decided ahead of time. The results showed that the function of self-injury was different across the participants. Four participants displayed higher rates of self-injury in the alone condition, two in the demand condition, one in the attention condition, and three had unclear results across the four conditions. This study was one of the most impactful on the field of ABA (Beavers et al., 2013; Hanley, 2012; Hanley et al., 2003). This study set the way for countless other studies evaluating the standard functional analysis and the development of other variations of functional analysis methodology (Beavers et al., 2013). For example, Northup et al. (1991) conducted one of the first investigations of brief functional analysis. In this study, Northup and colleagues shortened the duration of the test conditions and paired them with a single control condition. Northup and colleagues identified the function and developed a functionally based equivalent alternative behavior in 90 min or less. Sigafoos and Saggers (1995) were the first to evaluate a trial-based functional analysis in a special education classroom. In this study, the authors start with a 1 min test condition where reinforcers were provided noncontingently. The results showed that the function of the challenging behavior could be determined using this approach. Hanley et al. (2014) were the first to evaluate the practical functional analysis with three children diagnosed with ASD. Hanley and colleagues compared a singular synthesized test

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condition to a control condition and demonstrated that the test condition had higher rates of challenging behavior than the control condition. More importantly, the results yielded a successful intervention that included functional communication training and delay-denial tolerance training. These are just some of the thousands of studies that evaluated standardized functional analysis and variations of functional analysis (Beavers et al., 2013).

The autism partnership method approach to FBAs and FAs Although experimental functional analyses are considered the “gold standard” in determining the function of a person’s behavior, in general clinical practice they are rarely conducted (Ellingson et al., 1999). Notwithstanding some evidence showing the shortcomings of FBA methods compared to more rigorous FA methods, many practitioners find that FBAs are more efficient and good clinical outcomes can be obtained using the more readily obtainable information from FBAs. There are additional compelling reasons for not routinely conducting FAs and within the APM formal experimental functional analyses are rarely conducted. First, within a formal experimental functional analysis, the behavior analyst is deliberately arranging an event to evoke challenging behavior. Even if one used a precursor functional analysis, an interventionist runs the risk of creating a situation in which a learner may be harmed. As such, in everyday clinical settings, formal experimental functional analyses can be unnecessarily risky for many of our clients. Second, formal experimental functional analyses are often conducted in an analog setting in which the interventionist arranges artificial conditions to evoke the challenging behavior. Thus, the formal experimental functional analysis does not represent the conditions the learner experiences in their natural environment. As such, a formal experimental functional analysis may not adequately evaluate the actual function of behavior that is occurring in the natural environment. Third, the function of behavior often changes from moment-to-moment. Challenging behavior can occur for attention 1 day and can occur for escape the next day (or even the next hour). As such, an analysis done a priori may not be a valid, reliable, or an accurate account for why the behavior may occur at any future moment. Therefore, the information provided by a formal experimental functional analysis may not be the most useful for an interventionist in-the-moment. Fourth, behavior seldomly occurs for just one reason (e.g., only for attention) and is commonly multicontrolled or synthesized (e.g., escape from a demand to tangible items with attention). The majority

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of formal experimental functional analysis are used to determine a singular function and may not capture the true reason(s) why the behavior is occurring. Finally, formal experimental functional analyses are often time consuming. Not only are they time consuming in the amount of time it takes to run a session, but they are time consuming in the number of sessions it may take to determine the function. This time may be better spent teaching communication and tolerance skills proactively. Within the APM, we view understanding function as extremely important. However, the APM takes a different approach in determining the function of a learner’s behavior. One of the primary differences is the emphasis on skill building preventatively. In doing so, interventionists should teach learners how to successfully and skillfully navigate the four conditions commonly used in formal experimental functional analyses. Ala’i-Rosales et al. (2019) proposed that behavior analysts teach what they termed the “Big 4.” Thus, intervention should focus on teaching a learner to safely and effectively: (a) communicate their wants, needs, likes and dislikes; (b) gain the attention and affection of others; (c) joyfully engage in activities alone and with others; and (d) cope and tolerate adversity (Ala’i-Rosales et al., 2019). Likewise, within the APM, interventionists would also teach learners how to better control their environment, how to alleviate stress, and how to socially connect with others. Within the APM, we feel it is imperative to conduct interviews with caregivers and other professionals and when possible, talk with the client. Caregivers and other professionals are often the people who have the most contact with our learners and to not include them in the development of a behavioral intervention plan would be detrimental to the learner’s progress. Second, as has been demonstrated by Hanley et al. (2014), the parents or caregivers of a learner are able to accurately describe controlling variables of behavior. When conducting an open-ended interview, the behavior analyst has the flexibility to add questions and adjust questions based on the interviewee’s responses thereby zeroing in on essential details that help elucidate the function of the problem behavior. Finally, it is a perfect time for the behavior analyst to demonstrate compassion and empathy to the caregivers and professionals lived experiences. Perhaps the most important component of a progressive approach to understanding the cause of behavior is the continual assessment of function throughout every moment of a session (e.g., function on the fly; Cihon et al., 2016). Thus, interventionists should conduct in-the-moment assessment of function as opposed to exclusively relying on an a priori functional behavior

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assessment or experimental analysis. Using in-moment assessment the interventionist should attend to the environment, particularly to: (a) the topography of the behavior, (b) what occurred prior to the behavior, (c) the consequences following the behavior, and (d) what any nonverbal behavior that was displayed. The interventionist should also evaluate and compare the current behavior and environment to previous events. This analysis can inform identification of commonalties among occurrences of challenging behavior. Third, the interventionist should evaluate the health of the learner. This would include if there were any current physical health concerns (e.g., stomachaches, headaches, bad night sleep) and emotional health concerns (e.g., parents getting divorced, social isolation, general sadness). This type of analysis can be done through formal ABC data collection charts, notes, informal interviews, or through clinical judgment and analysis. In-the-moment analysis of function should lead to the interventionist adjusting their behavior based on the perceived function at the time. Thus, when challenging behavior occurs the interventionist can change their approach quickly and functionally. When doing so, it is okay for an interventionist to have formed a hypothesis about function that turns out to be incorrect (e.g., assuming it is an attention function when it was an escape function) as long as they learn from their analysis and change their approach based on new information (i.e., probe-and-test model). This type of change is important because it can lead to more responsivity to the learner at the moment. Additionally, by teaching proactively we can alleviate much of the challenging behavior that occurs.

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Cihon, T. M., Cihon, J. H., & Bedient, G. M. (2016). Establishing a common vocabulary of key concepts for the effective implementation of applied behavior analysis. International Electronic Journal of Elementary Education, 9(2), 337–348. Contreras, B. P., Tate, S. A., Morris, S. L., & Kahng, S. (2022). A systematic review of the correspondence between descriptive assessment and functional analysis. Journal of Applied Behavior Analysis. https://doi.org/10.1002/jaba.958. Advance online publication. Dixon, D. R., Vogel, T., & Tarbox, J. (2012). A brief history of functional analysis and applied behavior analysis. In J. Matson (Ed.), Functional assessment for challenging behaviors Springer. https://doi.org/10.1007/978-1-4614-3037-7_2. Durand, V. M., & Crimmins, D. B. (1988). Identifying the variables maintaining selfinjurious behavior. Journal of Autism and Developmental Disorders, 18(1), 99–117. https://doi.org/10.1007/BF02211821. Ellingson, S. A., Miltneberger, R. G., & Long, E. S. (1999). A survey of the use of functional assessment procedures in agencies serving individuals with developmental disabilities. Behavioral Interventions, 14(4), 187–198. https://doi.org/10.1002/(SICI)1099-078X (199910/12)14:43.0.CO;2-A. Ferguson, J. L., Leaf, J. A., Cihon, J. H., Milne, C. M., Leaf, J. B., McEachin, J., & Leaf, R. (2020). Practical functional assessment: A case study replication and extension with a child diagnosed with autism spectrum disorder. Education and Treatment of Children, 43, 171–185. https://doi.org/10.1007/s43494-020-00015-1. Hanley, G. P. (2012). Functional assessment of problem behavior: Dispelling myths, overcoming implementation obstacles, and developing new lore. Behavior Analysis in Practice, 5(1), 54–72. https://doi.org/10.1007/BF03391818. Hanley, G. P., Iwata, B. A., & McCord, B. E. (2003). Functional analysis of problem behavior: A review. Journal of Applied Behavior Analysis, 36(2), 147–185. https://doi.org/ 10.1901/jaba.2003.36-147. Hanley, G. P., Jin, C. S., Vanselow, N. R., & Hanratty, L. A. (2014). Producing meaningful improvements in problem behavior of children with autism via synthesized analyses and treatments. Journal of Applied Behavior Analysis, 47(1), 16–36. https://doi.org/10.1002/ jaba.106. Iwata, B. A., DeLeon, I. G., & Roscoe, E. M. (2013). Reliability and validity of the functional analysis screening tool. Journal of Applied Behavior Analysis, 46(1), 271–284. https:// doi.org/10.1002/jaba.31. Iwata, B. A., Dorsey, M. F., Silfer, K. J., Bauman, K. E., & Richman, G. S. (1982). Toward a functional analysis of self-injury. Analysis and Intervention in Developmental Disabilities, 2(1), 3–20. https://doi.org/10.1016/0270-4684(82)90003-9. Iwata, B. A., & Dozier, C. L. (2008). Clinical application of functional analysis methodology. Behavior Analysis in Practice, 1(1), 3–9. https://doi.org/10.1007/BF03391714. Jessel, J. (2022). Practical functional assessment. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & M. J. Weiss (Eds.), Handbook of applied behavior analysis interventions for autism Springer. https://doi.org/10.1007/978-3-030-96478-8_23. Lambert, J. M., Bloom, S. E., & Irvin, J. (2012). Trial-based functional analysis and functional communication training in an early childhood setting. Journal of Applied Behavior Analysis, 45(3), 579–584. https://doi.org/10.1901/jaba.2012.45-579. Lovaas, O. I., Freitas, G., Gold, V. J., & Kassoria, I. C. (1965). Experimental studies in childhood schizophrenia: Analysis of self-destructive behavior. Journal of Experimental Child Psychology, 2(1), 67–84. https://doi.org/10.1016/0022-0965(65)90016-0. Matson, J. L., & Vollmer, T. R. (1995). Questions about behavioral function. APA PsycTests. Neidert, P. L., Iwata, B. A., Dempsey, C. M., & Thomason-Sassi, J. L. (2013). Latency of response during the functional analysis of elopement. Journal of Applied Behavior Analysis, 46(1), 312–316. https://doi.org/10.1002/jaba.11.

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Northup, J., Wacker, D., Sasso, G., Steege, M., Cigrand, K., Cook, J., & DeRaad, A. (1991). A brief functional analysis of aggressive and alternative behavior in an outclinic setting. Journal of Applied Behavior Analysis, 24(3), 509–522. https://doi.org/10.1901/ jaba.1991/24-509. Oliver, A. C., Pratt, L. A., & Normand, M. P. (2015). A survey of functional behavior assessment methods used by interventionists in practice. Journal of Applied Behavior Analysis, 48(4), 817–829. https://doi.org/10.1002/jaba.256. Parker, T., Waks, A., Leaf, R., & Kennedy, C. (2008). Functionality in behavioral assessment: A new approach. In R. Leaf, M. Taubman, & J. McEachin (Eds.), It’s time for school (pp. 153–171). DRL Books. Rajaraman, A., & Hanley, G. P. (2020). Interview-informed synthesized contingency analysis (IISCA). In F. Volkmar (Ed.), Encyclopedia of autism spectrum disorders Springer. https://doi.org/10.1007/978-1-4614-6435-8_102243-2. Ruiz, S., & Kubina, R. M. (2017). Impact of trial-based functional analysis on challenging behavior and training: A review of the literature. Behavior Analysis: Research and Practice, 17(4), 347–356. https://doi.org/10.1037/bar0000079. Sigafoos, J., & Saggers, E. (1995). A discrete-trial approach to the functional analysis of aggressive behaviour in two boys with autism. Australia and New Zealand Journal of Developmental Disabilities, 20(4), 287–297. Skinner, B. F. (1953). Science and human behavior. Macmillan. Skinner, B. F. (1957). Verbal behavior. Appleton-Century-Crofts. Smith, R. G., & Churchill, R. M. (2002). Identification of environmental determinants of behavior disorders through functional analysis of precursor behaviors. Journal of Applied Behavior Analysis, 35(2), 125–136. https://doi.org/10.1901/jaba.2002.35-125. Vollmer, T. R. (1994). The concept of automatic reinforcement: Implications for behavioral research in developmental disabilities. Research in Developmental Disabilities, 15(3), 187–207. https://doi.org/10.1016/0891-4222(94)90011-6.

CHAPTER 18

Differential reinforcement Contents Differential reinforcement of other behavior Differential reinforcement of alternative behavior Differential reinforcement of incompatible behavior Differential reinforcement of low rates of behavior and differential reinforcement of high rates of behavior Some progressive considerations regarding differential reinforcement Differential or graduated? Ranking putative reinforcers Summary References

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Differential reinforcement is commonly used as a hypernym for procedures used to reinforce one response class while withholding reinforcement for another response class. Differential reinforcement procedures are most commonly known for their use as a reductive procedure for undesired behavior (i.e., decreasing the likelihood of a particular response class). As a reductive procedure, differential reinforcement involves contingent access to reinforcement for behavior other than the undesired behavior or a reduction in the rate of the undesired behavior while withholding reinforcement for the undesired behavior. Differential reinforcement procedures can also be used to increase the likelihood of desired behavior (e.g., differential reinforcement of high rates, shaping). What follows is a brief description and research example for commonly used differential reinforcement procedures.

Differential reinforcement of other behavior Differential reinforcement of other behavior (DRO) refers to a procedure in which access to reinforcement is provided contingent upon the undesired (target) behavior not occurring during a specified interval or at specific moments. Furthermore, reinforcement is withheld for the undesired (target) behavior. Colloquially, a DRO is the delivery of reinforcement for the absence of some behavior (Reynolds, 1961). The effectiveness of DRO A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00009-X

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procedures has been well documented and researched across a wide range of undesired behaviors (e.g., self-injurious behavior, pica, tics) and populations (e.g., typically developing persons, adults with severe intellectual disabilities, nonhuman animals; Jessel & Ingvarsson, 2016). Jessel et al. (2015) evaluated the presumed strengthening effects of the “other behavior” in a DRO procedure across two experiments. Experiment 1 involved measuring other behavior while experiencing changes in reinforcement schedules (i.e., variable ratio to extinction, variable ratio to DRO, and variable ratio to fixed time, each of which are common treatments used to reduce problem behavior). This allowed Jessel et al. to examine if the other behavior increased only when DRO schedules were in effect. The results indicated that the most prominent increase in the rate of other behavior occurred in the DRO condition supporting the notion that the DRO differentially reinforces other behavior while there are subsequent decreases in the targeted undesired behavior. Experiment 2 examined if increases in the other behavior during DRO probes maintained after extended exposure to the condition. The results of Experiment 2 demonstrated that the DRO strengthened the other behavior due to “the contiguous pairing of reinforcers delivered at the end of the interval” ( Jessel et al., 2015, p. 412).

Differential reinforcement of alternative behavior Differential reinforcement of alternative behavior (DRA) refers to a procedure in which access to reinforcement is provided contingent upon a specified desired alternative behavior while withholding reinforcement for the undesired (target) behavior. As a result, the DRA strengthens the alternative (desired) behavior while decreasing the strength of the undesired behavior and still allows the learner to access the same (or higher) level of reinforcement. Functional communication training (FCT) makes use of the DRA. Within FCT a reinforcer is provided contingent upon a desired functional communication response while the same reinforcer is withheld for engaging in undesired problem behavior. DRA procedures, such as FCT, have been well documented as effective at developing and strengthening desired behavior while simultaneously decreasing or weakening undesired problem behavior (MacNaul & Neely, 2018). Kunnavatana et al. (2018) conducted a series of three experiments in which the first two evaluated sensitivities to quality, magnitude, and immediacy of reinforcement. The third experiment examined the effects of a

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DRA procedure without the use of extinction for problem behavior in which the alternative behavior resulted in the parameter of reinforcement to which the participant was most or least sensitive. During one condition (i.e., magnitude manipulation), 90 s of access to reinforcement was available for engaging in the alterative behavior while 15 s of access to reinforcement was available for engaging in the problem behavior (targeted for reduction). In the other condition (i.e., quality manipulation), access to a high-quality reinforcer was available for engaging in the alterative behavior while access to a low-quality reinforcer was available for engaging in the problem behavior (targeted for reduction). The magnitude manipulation condition resulted in a decrease in problem behavior for all three participants, but the alternative behavior was only maintained for one participant. The quality manipulation resulted in a decrease in problem behavior and maintained the alternative behavior for all three participants.

Differential reinforcement of incompatible behavior Differential reinforcement of incompatible behavior (DRI) refers to DRA procedures in which the alternative response is selected because it is not possible to simultaneously engage in the alternative response and the undesired behavior. That is, the alternative response is incompatible with also engaging in the undesired or challenging behaviors. For example, clasping your hands in your lap is incompatible with slapping your ears, sitting in your chair is incompatible with running out of the room, and calmly saying “I want a break” is incompatible with yelling. While DRI procedures, specifically, are less researched than DRO and DRA procedures (Chowdhury & Benson, 2011), the research that does exist has demonstrated DRI procedures to be effective at developing the incompatible alternative response as well as decreasing the undesired problem behavior. Donnelly and Olczak (1990) examined the effectiveness of a DRI procedure to decrease pica, in the form of eating cigarette butts, with three adult participants. The alternative, incompatible behavior in this case was chewing gum. To ensure the safety of the participants, fake cigarette butts were used throughout the experiment. The fake cigarette butts were placed in an ashtray in the middle of the room used for research sessions. The DRI procedure began with admitting the participant into the room, giving them a piece of gum, and providing an instruction to chew the gum, not the cigarette butts. Gum chewing was reinforced with small amounts of decaffeinated coffee for each interval in which pica was not observed and gum

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chewing continued. The initial interval was 5 s and gradually increased in 6 s increments all the way up to 15 min “based on the subjective impression of the experimenter that the subject was earning reinforcement frequently enough at the current interval to indicate success” (Donnelly & Olczak, 1990, p. 88). The results indicated that the DRI with gum chewing was effective for decreasing pica for two of the three participants (the third participant stopped engaging in pica during baseline and was not included in the experimental analysis).

Differential reinforcement of low rates of behavior and differential reinforcement of high rates of behavior Differential reinforcement of low rates of behavior (DRL) refers to procedures in which reinforcement is provided contingent upon responses that are separated by some duration. This could refer to responses separated by a specific duration (i.e., spaced-responding DRL) or a certain number of responses during a specified duration (i.e., full session or interval DRL). DRL procedures are commonly used when a behavior is appropriate, but the rate of that behavior is too high. For example, if a client is raising their hand during class too frequently, a DRL could be used to provide reinforcement contingent upon a certain number of hand raises during a class, or interval, or if hand raises are separated by a specific duration. Differential reinforcement of high rates of behavior (DRH) procedures are similar to DRL procedures in that reinforcement is delivered or provided contingent upon responses that are separated by some duration. The difference with a DRH is the time between responses (i.e., spaced-responding DRH) is decreased or the total number of responses during a specific time (i.e., full session or interval DRH) is increased. DRH procedures are commonly used when a behavior is appropriate, but the rate of that behavior is too low. For example, if a client is eating meals too slowly in order to complete their meal before the end of a lunch period, a DRH could be used to provide reinforcement contingent upon a certain number of bites during lunchtime or an interval during lunch or if bites are separated by a specific duration. Lennox et al. (1987) evaluated the effectiveness of a spaced-responding DRL to reduce the rate of eating with three participants who engaged in rapid eating. The DRL was introduced following a response interruption procedure that was ineffective for the participants at decreasing the rate of rapid eating. The DRL consisted of interrupting any eating response that

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occurred prior to the end of a 15 s interval, which also reset the 15 s interval. Thus, eating was only reinforced following 15 continuous seconds of not attempting to eat. Additionally, an incompatible response of setting the utensil down between bites was prompted. The results demonstrated that the DRL procedure with prompting of an incompatible response was effective at decreasing the rate of eating for all three participants. Generalization to other meals, however, did not occur until the procedures were implemented during those mealtimes as well.

Some progressive considerations regarding differential reinforcement The aforementioned differential reinforcement procedures are common within intervention for autistic individuals. Nonetheless, there are some alterations and considerations for their use within a progressive approach to ABA-based interventions for autistic individuals. These alterations and considerations are provided in the following section. In the spirit of a progressive approach (Leaf et al., 2016), they should not be viewed as rigid replacements for traditional applications of differential reinforcement procedures. These traditional applications of differential reinforcement procedures have been continually documented as effective and should not be dismissed out-of-hand. Thus, these alterations and considerations should be considered additive as opposed to substitutive.

Differential or graduated? Most often in the literature, and within clinical practice, differential reinforcement procedures involve all-or-none contingencies. In these contexts, reinforcement is either delivered or not delivered. For example, with a DRA procedure, reinforcement is delivered contingent upon the alternative behavior and the absence of the behavior targeted for decrease. If the behavior targeted for decrease occurs, reinforcement is not delivered, and the interval is typically reset. While this does constitute differential reinforcement in that reinforcement is delivered in one context but not in the other, an all-or-none contingency is not the only option when using differential reinforcement. Consider the following scenario. Myles is required to complete 100 math problems to then access an iPad for 5 min (i.e., the putative reinforcer). If Myles only completes 50 problems in the targeted duration, the iPad could then be delivered for 2.5 min rather than 5 min. This differs from traditional differential reinforcement procedures in which no

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reinforcement would have been delivered for only completing 50 of the math problems. Viewing differential reinforcement as graduated as opposed to all-ornone may have clinical utility. Graduated reinforcement provides interventionists with more flexibility in providing reinforcement. This may allow interventionists to shape the desired behavior or rate of behavior in the absence of the use of extinction. Using graduated reinforcement, rather than all-or-none, may also help ensure the client contacts reinforcement more frequently. This could decrease the likelihood of completely eliminating responding due to ratio strain or insufficient amounts of reinforcement. Using graduated reinforcement could also provide the interventionist with more possible reinforcers to use. Less potent reinforcers could be used for lower quality responding while more potent reinforcers could be reserved for higher quality responding. This makes graduated reinforcement more closely align with conjugate schedules of reinforcement (Rapp, 2008; Rovee & Rovee, 1969) than commonly used differential reinforcement procedures. Kassardjian et al. (2016) compared the effects of graduated and all-ornone reinforcement contingencies on the rate of sorting with six participants diagnosed with ASD. Two formal paired-stimulus preference assessments (Fisher et al., 1992) were conducted with each of the six participants. The items were ranked from 1 to 10 based on the number of times the item was selected across the two assessments. The two items selected the most across the two assessments were denoted as “A” level reinforcers while the items selected fifth and sixth most often were denoted as “C” level reinforcers. Following establishing baseline performance on a simple sorting task that consisted of sorting three different colors of chips into their respective columns, three conditions were randomly conducted during each session. The control condition consisted of providing an instruction to sort as many chips as they wanted, but there would be no toys. The participant was then given 4 min to sort, after which they were taken back to their typically scheduled clinical session for 10 min. The all-or-none reinforcement condition was similar to the control condition except participants could choose one of the two “A” level reinforcers contingent upon sorting chips at 20% above the baseline average. In the graduated reinforcement condition, participants could access “C” level reinforcers following a 20% increase in sorting above the baseline average or “A” level reinforcers following a 30% increase in sorting above the baseline average. The conditions produced idiosyncratic responding across the six participants. Overall, participants

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with more developed behavioral repertoires sorted more chips in the graduated reinforcement condition when compared to the all-or-none reinforcement condition.

Ranking putative reinforcers One method of using reinforcement from a graduated, or differential, perspective is categorizing reinforcers by client preference or presumed quality. This is similar to Kassardjian et al. (2016) in which the two items selected the most across two formal preference assessments were denoted as “A” level reinforcers and the items selected fifth and sixth most often were denoted as “C” level reinforcers. While Kassardjian et al. used a letter ranking system, any system denotating the ordinal ranking of possible reinforcers will suffice (e.g., numbers 1–5, red/yellow/green, great/good/ok). If the rankings are designed with the interventionist in mind, rankings should be selected in a manner that will be the most effective and useful for the interventionist. If the rankings are designed with the client in mind, rankings should be selected with the client’s preferences in mind and would benefit from including the client in the decisions made about rankings. Kassardjian et al. (2016) used formal preference assessments to develop their rankings that relied on the number of selections across two assessments. Number of selections can be one method to develop an ordinal ranking to use graduated reinforcement but is it not the only method. For example, rankings could be determined by simply observing how a learner allocates their responding in the absence of any restrictions or demands. Some may have heard this referred to as the Premack principle (Premack, 1959, 1965, 1971). The task, activity, or behavior the learner allocates the most time to may be assigned as the highest in the ranking, while the task, activity, or behavior the learner allocates the least time to may be assigned as the lowest in the ranking. While all tasks, activities, or behaviors that fall in-between would be ranked accordingly. Ultimately, there is no one best way to identify and develop a possible reinforcer ranking and the interventionist should select the way that is the most appropriate for the context and client. It is also important to note that rankings do not need to be comprised of different tasks, activities, or items. There are many ways in which the quality of reinforcement could be differentiated, or graduated, across rankings. The duration of access with one item could be used to develop a ranking. For example, longer access to playing a video game could be provided for higher quality responses while shorter access could be provided for lower quality

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responses. The amount or number of an item could also be used to differentiate rankings. For example, providing ten dollars for completing all of one’s homework, five dollars for completing half of one’s homework, and one dollar for completing only one worksheet. Various contextual variables could also be altered to develop a ranking. For example, playing basketball with preferred peers could be provided for higher quality responses while playing basketball with only the interventionist could be provided for lower quality responses. Finally, type or branding could also be used in developing rankings. For example, providing Nabisco Oreo cookies for responding to all appropriate peer initiations, Hydrox cookies for responding to some appropriate peer initiations, and Newman-O wafer cookies for responding to only a few appropriate peer initiations.

Summary Differential reinforcement procedures (e.g., DRO, DRA, DRI, DRL) are common within intervention for autistic individuals. They have been well documented to be effective at simultaneously decreasing the likelihood of undesired behavior and increasing the likelihood of desired, alternative behavior (Cooper et al., 2020). While differential reinforcement procedures commonly involve all-or-none contingencies, these procedures can be altered to involve graduated reinforcement when used within a progressive approach to ABA-based interventions for autistic individuals. Graduated reinforcement involves providing more nuanced differential reinforcement by altering the quality or quantity of reinforcement provided based on the quality of the targeted behavior or skill and can potentially be more efficient in shaping behavior.

References Chowdhury, M., & Benson, B. A. (2011). Use of differential reinforcement to reduce behavior problems in adults with intellectual disabilities: A methodological review. Research in Developmental Disabilities, 32(2), 383–394. https://doi.org/10.1016/j.ridd.2010.11.015. Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Donnelly, D. R., & Olczak, P. V. (1990). The effect of differential reinforcement of incompatible behaviors (dri) on pica for cigarettes in persons with intellectual disability. Behavior Modification, 14(1), 81–96. https://doi.org/10.1177/01454455900141006. Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25(2), 491–498. https://doi. org/10.1901/jaba.1992.25-491.

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Jessel, J., Borrero, J. C., & Becraft, J. L. (2015). Differential reinforcement of other behavior increases untargeted behavior. Journal of Applied Behavior Analysis, 48(2), 402–416. https://doi.org/10.1002/jaba.204. Jessel, J., & Ingvarsson, E. T. (2016). Recent advances in applied research on DRO procedures. Journal of Applied Behavior Analysis, 49(4), 991–995. https://doi.org/10.1002/ jaba.323. Kassardjian, A., Leaf, J. A., Leaf, J. B., Townley-Cochran, D., Alcalay, A., Milne, C., Dale, S., Tsuji, K., Leaf, R., Taubman, M., & McEachin, J. (2016). Evaluation of graduated vs all-or-none contingencies on rate tasks for individuals diagnosed with autism. Education and Training in Autism and Developmental Disabilities, 51(4), 434–446. Kunnavatana, S. S., Bloom, S. E., Samaha, A. L., Slocum, T. A., & Clay, C. J. (2018). Manipulating parameters of reinforcement to reduce problem behavior without extinction. Journal of Applied Behavior Analysis, 51(2), 283–302. https://doi.org/10.1002/jaba.443. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Ala’i-Rosales, S., Ross, R. K., Smith, T., & Weiss, M. J. (2016). Applied behavior analysis is a science and, therefore, progressive. Journal of Autism and Developmental Disorders, 46(2), 720–731. https://doi.org/ 10.1007/s10803-015-2591-6. Lennox, D. B., Miltenberger, R. G., & Donnelly, D. R. (1987). Response interruption and DRL for the reduction of rapid eating. Journal of Applied Behavior Analysis, 20(3), 279–284. https://doi.org/10.1901/jaba.1987.20-279. MacNaul, H. L., & Neely, L. C. (2018). Systematic review of differential reinforcement of alternative behavior without extinction for individuals with autism. Behavior Modification, 42(3), 398–421. https://doi.org/10.1177/0145445517740321. Premack, D. (1959). Toward empirical behavior laws. I. Positive reinforcement. Psychological Review, 66(4), 219–233. https://doi.org/10.1037/h0040891. Premack, D. (1965). Reinforcement theory. In D. Levine (Ed.), Nebraska symposium on motivation (pp. 123–180). University of Nebraska Press. Premack, D. (1971). Catching up with common sense, or two sides of a generalization: Reinforcement and punishment. In R. Blaser (Ed.), The nature of reinforcement (pp. 121–150). Academic Press. Rapp, J. T. (2008). Conjugate reinforcement: A brief review and suggestions for applications to the assessment of automatically reinforced behavior. Behavioral Interventions, 23(2), 113–136. https://doi.org/10.1002/bin.259. Reynolds, G. S. (1961). Behavioral contrast. Journal of the Experimental Analysis of Behavior, 4, 57–71. https://doi.org/10.1901/jeab.1961.4-57. Rovee, C. K., & Rovee, D. T. (1969). Conjugate reinforcement of infant exploratory behavior. Journal of Experimental Child Psychology, 8(1), 33–39. https://doi.org/ 10.1016/0022-0965(69)90025-3.

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CHAPTER 19

Extinction and response cost Contents Misperceptions and clarifications related to extinction Extinction is a schedule of reinforcement Extinction is not ignoring Extinction does not eliminate behavior Extinction bursts appear less prevalent in clinical studies Extinction is not punishment Extinction is a naturally occurring behavioral contingency The conditions under which … Response cost Misperceptions and clarifications related to response cost Response cost is commonly used among society Response cost can be easy to implement Recommendations for practice Do not uncritically avoid using extinction-based procedures and response cost Monitor progress, effects, and misuse Avoid digging too deep of a hole Summary References

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Operant extinction refers to withholding reinforcement that was previously available contingent on a response (or response class) that results in a decreased probability of that response (or response class) occurring in the future. In the context of behavioral interventions for autistic individuals, extinction commonly refers to procedures in which the reinforcer(s) maintaining undesired behavior are identified via a functional behavior assessment and then withheld during the course of intervention for the undesired behavior. Williams (1959) provided one of the first experimental evaluations of the use of extinction with humans. Specifically, Williams reported on the use of extinction to treat the “… tyrant-like tantrum behavior …” (p. 269) of a 21-month-old boy. This behavior occurred when the boy’s parents or aunt would put him to bed, which resulted in the parents or aunt going into the child’s bedroom until he fell asleep. The simple intervention involved A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00022-2

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instructing the parents not to reenter the room following bedtime pleasantries and closing the door after putting him to bed. By the 10th session, the child was no longer engaging in tantrums and was happy and smiling when the parents left his room. Williams also noted that “no unfortunate side- or after-effects of this treatment were observed” (p. 269). The use of extinction-based procedures within behaviorally based interventions has become rather controversial recently, with some advocating for the complete abandonment of extinction-based procedures. The rationales given for the abandonment of extinction-based procedures often do not align with information found within the peer-reviewed experimental literature. These absolutes are also concerning within a field of practice committed, in part, to determining the conditions under which behavior change procedures are more and less effective and should or should not be used. What follows is a brief discussion of some misperceptions and clarifications related to the use of extinction-based procedures.

Misperceptions and clarifications related to extinction Extinction is a schedule of reinforcement Contrary to common usage and criticisms, extinction is actually a schedule of reinforcement. Ferster and Skinner (1957) described and defined extinction as one of the two nonintermittent schedules of reinforcement in which no responses are reinforced. While this reinforcement schedule is zero, from a purely historical and technologic perspective, it is a schedule of reinforcement nonetheless. Skinner (1956) describes his discovery of extinction in a very serendipitous way. In his efforts to minimize the effort required to run experiments with rats, he developed an apparatus that would automatically provide access to food without the experimenter’s involvement. One day, this apparatus got jammed and the food it once provided to the rat was no longer provided. Viola! The extinction curve was discovered!

Extinction is not ignoring Some have mistakenly equated extinction-based procedures with ignoring a person. This is likely a result of the use of extinction-based procedures to address behaviors that are maintained primarily by access to attention. In these instances, when the target behavior occurs, attention is not provided. This is sometimes called planned ignoring. It should be noted that ignoring only constitutes extinction when attention was previously provided at a

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higher rate following the target behavior than at other times. Unfortunately, uninformed application of extinction can sometimes look like ignoring a person (e.g., turning away from the individual) rather than simply not reacting to the behavior. This is not the case in a progressive approach to applied behavior analysis. For behavior that is maintained by social reinforcement, extinction requires no longer providing that social reinforcer when problem behavior occurs. It might mean simply not gasping, not showing indignation, or simply acting as if the behavior had not occurred. This does not mean one is required to turn their back to the person. It is also important to note that extinction-based procedures can be implemented when the reinforcing event is something other than attention (e.g., obtaining a desired item, gaining control over another person’s behavior, escaping from something, escaping to something). Extinction-based procedures weaken the controlling/maintaining contingency, regardless of what comprises that controlling/maintaining contingency.

Extinction does not eliminate behavior It is sometimes assumed that extinction-based procedures result in the complete elimination of the target behavior. For example, if the target behavior is spitting and the maintaining reinforcer is attention in the form of reprimands, then by no longer providing reprimands when spitting occurs, spitting is likely to decrease to near zero levels. It may appear that spitting has been eliminated, but that is not necessarily the case. What has changed is that the probability of spitting has decreased, but it has not been completely eliminated from the person’s behavior repertoire. Therein lies one of the rationales for teaching a functionally related, alternative response. This allows access to the putative reinforcer (e.g., reprimands, or attention, in the previous example) without engaging in the behavior targeted for decrease. A further necessary step is to alter the form of attention that is provided from reprimands to praise.

Extinction bursts appear less prevalent in clinical studies In some circumstances, extinction has resulted in a temporary increase in the rate of the target response prior to a decrease (Fisher et al., 2022; Lerman et al., 1999). This behavioral phenomenon has been referred to as an extinction burst. This effect of extinction has been used as a reason to avoid its use with severe destructive or self-injurious behavior (e.g., head banging). That is, one does not want to increase, even temporarily, the rate of severe

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destructive or self-injurious behavior due to safety reasons. What remains unclear within the research literature is how common extinction bursts really are (Fisher et al., 2022; Lerman et al., 1999; Lerman & Iwata, 1996b). Lerman et al. (1999) examined 41 data sets from 30 participants for response bursts or increases in aggression while being treated for selfinjurious behavior using extinction-based procedures in isolation or in combination with other procedures. The results showed “… that about 40% of cases showed at least one of two side effects (i.e., response bursts or increases in aggression) and that almost 20% of the cases showed both phenomena” and that “both side effects were less likely when extinction was combined with alternative procedures” (Lerman et al., 1999, p. 5). This prevalence rate was much lower than expected when compared to nonhuman basic laboratory studies (Fisher et al., 2022; Lerman et al., 1999). Therefore, it appears that the research, to date, does not support assertions of frequent extinction bursts in clinical settings, especially when extinction-based procedures are combined with alternative procedures. It should be noted, however, that Fisher et al. (2022) hypothesized that this disparity may be the result of applied research participants experiencing greater decreases in reinforcerconsumption time and applied researchers including reinforcerconsumption time in calculations of baseline response rates.

Extinction is not punishment Given that extinction and punishment can have similar effects on behavior (i.e., decrease the overall rate or probability of a response), extinction can often be confused with punishment (Lerman & Iwata, 1996a). While extinction- and punishment-based procedures may have similar effects on behavior, they are very different processes and procedures. As previously stated, extinction is a schedule of reinforcement and its use within procedures involves disrupting, or discontinuing, a previously established reinforcement contingency. The use of punishment as a behavior reduction procedure involves a contingent change (i.e., the removal of a positive reinforcer or the addition of a negative reinforcer) that occurs contingent upon the targeted behavior. As such, extinction and punishment are very different as procedures and principles.

Extinction is a naturally occurring behavioral contingency Similar to other contingencies, such as punishment and positive reinforcement, extinction is a naturally occurring behavioral contingency. Meaning,

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extinction occurs within our lives whether someone else is programming for it or not. For example, many of us have had previous experiences with going to a vending machine, inserting money, making a selection by pressing a button, and obtaining food from the vending machine. There are times when the vending machine malfunctions and does not provide us the item for which we paid, or the vending machine may be out of the particular item we are seeking. It would be odd for us to make calls for ending the use and availability of vending machines. Instead, particularly within a progressive approach to ABA, we teach our clients skills that help them cope with situations like the unyielding vending machine. We may even intentionally arrange situations in which the vending machine fails (i.e., extinction) to teach or practice those skills. Doing so may better prepare our clients for the contingencies they inevitably will encounter—whether they are directly programmed or not.

The conditions under which … The field of behavior analysis has been built upon examining the conditions under which behavior is more or less likely to occur. This has involved research that examines making systematic changes to the environment, or context, and measuring the effects of those changes on the target behavior. This same approach has been, and should continue to be, used to examine the conditions under which various methods and procedures are more and less effective or desired. It may be the case that there are few conditions for some procedures (e.g., exclusionary time-out) and more conditions for others (e.g., token systems). For example, related to the use of extinction-based procedures, several researchers have questioned the use of those procedures to treat food selectivity (e.g., Cihon et al., 2020; Riordan et al., 1980). While it may very well be the case that extinction-based procedures are not recommended for treating specific types of problem behavior (e.g., food selectivity), those procedures may still be necessary in other contexts (e.g., as part of a comprehensive intervention treating attention-maintained problem behavior).

Response cost Response cost has been defined as the contingent removal of previously acquired reinforcing stimuli (Harris, 1985; Kazdin, 1972; Weiner, 1962). As such, while extinction-based procedures and response cost may have similar effects on behavior, the principle responsible for the change is different.

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While withholding reinforcement for a previously reinforced response is the principle responsible for behavior change with extinction, negative punishment (e.g., removing a stimulus contingent on a behavior that decreases the future probability of that behavior) is the principle responsible for change with response cost. For example, removing access to a child’s cellphone or tablet contingent upon undesired behavior is response cost, just like being fined for speeding on the highway. It is important to note that ethics codes for certified behavior analysts require that punishment-based procedures, such as response cost, not be used in isolation or before other alternative approaches are shown to be ineffective or unavailable. Similar to the use of extinction-based procedures within behaviorally based interventions, the use of punishment-based procedures, such as response cost, has been controversial. What follows is a brief discussion of some misperceptions and clarifications related to the use of response cost.

Misperceptions and clarifications related to response cost Response cost is commonly used among society As previously mentioned, response cost is a common practice among many parents (e.g., contingent removal of privileges, technology, etc. for engaging in undesired behavior such as staying out too late, breaking a rule, talking rudely; Bagwell et al., 2022). Therefore, for some families and contexts, the use of response cost has proven to be effective and would be considered a socially valid procedure if parents find it to be a reasonable and fair consequence. In fact, there have been several studies that have evaluated the social validity of the use of response cost (e.g., Borrego et al., 2007; Curtis et al., 2006; Eid et al., 2019; Heffer & Kelley, 1987; Jones et al., 1998; Pisecco et al., 2001) all of which have found response cost to be a socially valid procedure. While some within and outside of the practice field of behavior analysis may call for complete abandonment of the use of response cost, doing so would ignore the preferences of some families and contexts. That said, while some may prefer the use of response cost, it is important to outline all of the possible treatment options and possible effects of those options so that families can make an informed decision related to treatment.

Response cost can be easy to implement Response cost has been found to be an easy procedure to implement (Briesch et al., 2015; DeJager et al., 2020). In fact, in one of the earliest

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studies helping parents deal with the severe problem behavior of a child with autism (Wolf et al., 1963), response cost was selected over the sole use of an extinction-based procedure due to its ease of use in comparison to an extinction-based procedure. More specifically, in this case the researchers were concerned with untrained staff implementing an extinction-based procedure, so response cost was used in combination with extinction. With its ease of implementation, response cost may be a preferred procedure in many contexts (e.g., minimally trained care givers, client preference).

Recommendations for practice The use of extinction-based procedures and response cost have often been fraught with controversy. Some of this controversy may be justified, but, often, the results within the peer-reviewed experimental literature do not support many of the assertions related to the use of extinction-based procedures and response cost. What follows are some general guidelines with respect to the use of extinction-based procedures and response cost. These guidelines should be viewed just as that—guidelines. They are not rules to be rigidly applied. They require the use of clinical judgment and in-themoment assessment. Furthermore, these guidelines should be viewed in conjunction with applicable ethics codes.

Do not uncritically avoid using extinction-based procedures and response cost As with almost any procedure, practitioners should not preclude the use of extinction-based procedures and response cost without a critical analysis for the relevant variables (e.g., client and caregiver preference, desired goals, staff skill set, available alternatives). There very well may be some conditions under which extinction-based procedures and response cost should be avoided (e.g., treating food selectivity; Cihon et al., 2020; Riordan et al., 1980). However, there may also be conditions under which extinctionbased procedures and response cost may be desired. For example, it is likely common within autism interventions that when token systems are used, clinicians may also use response cost in the form of losing tokens for certain challenging or undesired behaviors. This noninvasive response cost procedure is not only supported by the literature (e.g., Bagwell et al., 2022), it is also similar to systems that occur in many of our lives (e.g., earning paychecks and being fined for breaking laws).

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Monitor progress, effects, and misuse As with any behavior analytic procedure, intervention, or approach, it is important to track the progress, effects, and possible misuse of extinctionbased procedures and response cost. This should especially be the case with punishment-based procedures like response cost. Punishment occurs when a response is followed by an event (i.e., stimulus change) that results in a decrease in the probability of similar responses in similar situations. The behavioral effects of a punishment-based procedure, like response cost, should be rather immediate. If the use of response cost does not result in a decreased probability of the targeted response, then response cost is not functioning as punishment. In these cases, response cost should not be continued unless programmatic changes occur. The use of extinction-based procedures should also be monitored for effectiveness and progress. However, given the possibility for an initial increase in the target or related behaviors with the use of extinction-based procedures, progress and effects may be difficult to initially ascertain. Finally, the behavior of the interventionist is also lawful and can be affected by changes in the client’s behavior. For example, if a client’s aggression functions as a punisher for an interventionist and the interventionist uses a procedure that decreases the probability of that highly undesired behavior, the interventionist may be more likely to use that punishment procedure again in the future. As such, misuse of extinctionbased procedures and response cost should be monitored closely. Nevertheless, this phenomenon (i.e., an interventionist more likely to use punishment-based procedures because of their effectiveness) has not been well documented within the behavior analytic literature (Lerman & Vorndran, 2002).

Avoid digging too deep of a hole Response cost involves the contingent removal of previously earned reinforcing stimuli. As a result, response cost may be more likely to be effective when at least some previously earned reinforcing stimuli remains in the client’s possession. If response cost is overused (i.e., all previously earned reinforcing stimuli are removed), then there would be no previously earned reinforcing stimuli to remove contingent upon the targeted behavior for decrease. Said differently, the client may no longer have any motivation to avoid engaging in the behavior(s) targeted for increase because they have nothing left to lose. As a result, response cost should be paired with a schedule of reinforcement rich enough to ensure the client does not dig

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themselves too deep into “debt.” This aligns with ethical codes requiring the use of reinforcement-based procedures in tandem with punishment-based procedures.

Summary This chapter highlights some misconceptions about the use of extinctionbased procedures and response cost as well as some clarifications with respect to these misconceptions. Like many claims that can be found outside of reputable sources, the misconceptions do not always align with what can be found in the peer-reviewed experimental literature. We encourage the reader to contact the literature directly, as well as any relevant ethical codes and client information, prior to making any determinations about using or avoiding extinction-based procedures and response cost.

References Bagwell, A., Barnett, M., & Falcomata, T. S. (2022). Response cost and time-out from reinforcement. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & M. J. Wess (Eds.), Handbook of applied behavior analysis interventions for autism (pp. 479–496). Springer. https://doi.org/ 10.1007/978-3-030-96478-8_25. Borrego, J., Ibanez, E. S., Spendlove, S. J., & Pemberton, J. R. (2007). Treatment acceptability among Mexican American parents. Behavior Therapy, 38(3), 217–227. https://doi. org/10.1016/j.beth.2006.08.007. Briesch, A. M., Briesch, J. M., & Chafouleas, S. M. (2015). Investigating the usability of classroom management strategies among elementary schoolteachers. Journal of Positive Behavior Interventions, 17(1), 5–14. https://doi.org/10.1177/1098300714531827. Cihon, J. H., Weiss, M. J., Ferguson, J. L., Leaf, J. B., Zane, T., & Ross, R. K. (2020). Observational effects on the food preferences of children with autism spectrum disorder. Focus on Autism and Other Developmental Disabilities, 36(1), 25–35. https://doi.org/ 10.1177/1088357620954368. Curtis, D. F., Pisecco, S., Hamilton, R. J., & Moore, D. W. (2006). Teacher perceptions of classroom interventions for children with ADHD: A cross-cultural comparison of teachers in the United States and New Zealand. School Psychology Quarterly, 21(2), 171–196. https://doi.org/10.1521/scpq.2006.21.2.171. DeJager, B., Houlihan, D., Filter, K. J., Mackie, P. F. E., & Klein, L. (2020). Comparing the effectiveness and ease of implementation of token economy, response cost, and a combination condition in rural elementary school classrooms. Journal of Rural Mental Health, 44(1), 39–50. https://doi.org/10.1037/rmh0000123. Eid, A., Jobeir, A., Alhaqbani, O., AlSaud, A., & Fryling, M. J. (2019). Assessment of parental acceptability and preference for behavioral interventions for childhood problem behavior in Saudi Arabia. Child & Family Behavior Therapy, 41(4), 237–241. https://doi.org/ 10.1080/07317107.2019.1659548. Ferster, C. B., & Skinner, B. F. (1957). Schedules of reinforcement. Prentice-Hall. Fisher, W. W., Greer, B. D., Shahan, T. A., & Norris, H. M. (2022). Basic and applied research on extinction bursts. Journal of Applied Behavior Analysis. https://doi.org/ 10.1002/jaba.954. Advanced online publication.

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Harris, K. R. (1985). Definitional, parametric, and procedural considerations in timeout interventions and research. Exceptional Children, 51(4), 279–288. Heffer, R. W., & Kelley, M. L. (1987). Mothers’ acceptance of behavioral interventions for children: The influence of parent race and income. Behavior Therapy, 18(2), 153–163. https://doi.org/10.1016/S0005-7894(87)80039-4. Jones, M. L., Eyberg, S. M., Adams, C. D., & Boggs, S. R. (1998). Treatment acceptability of behavioral interventions for children: An assessment by mothers of children with disruptive behavior disorders. Child & Family Behavior Therapy, 20(4), 15–26. https://doi.org/ 10.1300/J019v20n04_02. Kazdin, A. E. (1972). Response cost: The removal of conditioned reinforcers for therapeutic change. Behavior Therapy, 3(4), 533–546. https://doi.org/10.1016/S0005-7894(72) 80001-7. Lerman, D. C., & Iwata, B. A. (1996a). A methodology for distinguishing between extinction and punishment effects associated with response blocking. Journal of Applied Behavior Analysis, 29(2), 231–233. https://doi.org/10.1901/jaba.1996.29-231 PMID - 8682737. Lerman, D. C., & Iwata, B. A. (1996b). Developing a technology for the use of operant extinction in clinical settings: An examination of basic and applied research. Journal of Applied Behavior Analysis, 29(3), 345–382. https://doi.org/10.1901/jaba.1996.29-345 PMID - 8926226. Lerman, D. C., Iwata, B. A., & Wallace, M. D. (1999). Side effects of extinction: Prevalence of bursting and aggression during the treatment of self-injurious behavior. Journal of Applied Behavior Analysis, 32(1), 1–8. https://doi.org/10.1901/jaba.1999.32-1. Lerman, D. C., & Vorndran, C. M. (2002). On the status of knowledge for using punishment implications for treating behavior disorders. Journal of Applied Behavior Analysis, 35(4), 431–464. https://doi.org/10.1901/jaba.2002.35-431. Pisecco, S., Huzinec, C., & Curtis, D. (2001). The effects of child characteristics on teachers’ acceptability of classroom-based behavioral strategies and psychostimulant medication for the treatment of ADHD. Journal of Clinical Child Psychology, 30(3), 413–421. https://doi.org/10.1207/S15374424JCCP3003_12. Riordan, M. M., Iwata, B. A., Wohl, M. K., & Finney, J. W. (1980). Behavioral treatment of food refusal and selectivity in developmentally disabled children. Applied Research in Mental Retardation, 1(1–2), 95–112. https://doi.org/10.1016/0270-3092(80)90019-3. Skinner, B. F. (1956). A case history in scientific method. American Psychologist, 11(5), 221–233. https://doi.org/10.1037/h0047662. Weiner, H. (1962). Some effects of response cost upon human operant behavior. Journal of the Experimental Analysis of Behavior, 5(2), 201–208. https://doi.org/10.1901/jeab.1962.5201. Williams, C. D. (1959). The elimination of tantrum behavior by extinction procedures. Journal of Abnormal and Social Psychology, 59(2), 269. https://doi.org/10.1037/h0046688. Wolf, M., Risley, T., & Mees, H. (1963). Application of operant conditioning procedures to the behaviour problems of an autistic child. Behaviour Research and Therapy, 1(2–4), 305–312. https://doi.org/10.1016/0005-7967(63)90045-7.

CHAPTER 20

Time out from positive reinforcement and the time-in ribbon Contents Time-out from positive reinforcement Nonexclusionary Exclusionary Practical considerations Research on time-out Autism partnership method and time-out Time-in ribbon Practical considerations Research on time-in ribbon Summary References

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In this chapter, we discuss two procedures: time-out from positive reinforcement and the time-in ribbon. Both procedures have been implemented as part of the Autism Partnership Method (APM) to decrease challenging behavior and increase appropriate alternative behaviors.

Time-out from positive reinforcement Time-out (more technically named time-out from positive reinforcement; TOPR) is a negative punishment procedure that is commonly implemented to decrease the probability of challenging behavior. When using TOPR, if a learner engages in challenging behavior (e.g., self-injury, tantrums, yelling), the interventionist removes/withdraws access to the currently or possibly available reinforcers for a period of time. This procedure is commonly implemented by teachers and parents as part of a child’s everyday consequences. TOPR is usually implemented as nonexclusionary or exclusionary.

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Nonexclusionary Nonexclusionary TOPR involves removing the currently or possibly available reinforcers, but the learner remain in the same environment. With nonexclusionary TOPR, the learner may also observe others accessing the reinforcer that was withdrawn. There are generally three variations of exclusionary TOPR in clinical practice. The first variation involves simply removing access to the reinforcing item/activity. For example, if the learner is screaming while holding their favorite toy, the interventionist temporarily removes that toy. This type of nonexclusionary TOPR is usually done in one-to-one settings. The second variation of nonexclusionary TOPR is known as contingent observation (Bagwell et al., 2022). This variation involves removing access to the reinforcing item/activity while the learner observes others engage with the removed item/activity. For example, if the learner hits a peer during a group game, the learner is not allowed to participate and is only able to watch the group engage in the game for a period of time. As such, contingent observation is a TOPR procedure that can be implemented effectively in group instructional formats such as social skills groups or school classrooms. The third variation of nonexclusionary TOPR is planned ignoring (Bagwell et al., 2022). Planned ignoring is used when attention has been determined as the function of the challenging behavior and involves not providing the learner with social attention for a specified duration of time. During the implementation of this variation, the interventionist does not remove materials from the learner; instead, the interventionist refrains from providing any form of conversation or attention and does not engage with the learner. Planned ignoring can occur both in one-to-one and group instructional formats.

Exclusionary Exclusionary TOPR involves removing access to the reinforcing item/ activity and removing the learner from the environment. For example, a parent may leave a restaurant with their child for a short time, or a student may be removed from gym class. Further, the interventionist ensures that the learner does not observe others accessing the reinforcing item/activity. Typically, the interventionist remains in the vicinity of the learner but does not interact throughout the duration of the procedure. There are, however, exceptions when a behavior intervention plan requires the use of seclusion

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to prevent harm from extreme aggressive behavior. In this variation of TOPR, the learner is put in a room or an area with little to no items available with which to interact. Although the learner is placed in seclusion, the interventionist must constantly monitor the learner visually and auditorily to ensure that their behaviors are not escalating to the point that they may become dangerous. Since the learner is placed in isolation, this is the most restrictive form of TOPR. As such, it is rarely used within the APM and only as an emergency containment procedure.

Practical considerations The time-in environment TOPR involves removing access to a reinforcing item/activity, thus removing the “fun” or reinforcing value in the learner’s environment. In order for this procedure to be effective in changing behavior, it is critical that the time-in environment is enriched and reinforcing. In other words, the learner should yearn to be in the environment and be disappointed when the reinforcing elements are removed from that environment or when the learner is removed from the reinforcing environment. As such, there needs to be a stark difference between the time-in and time-out environments. This means that the time-in environment should include the learner’s preferred stimuli and activities and the time-out environment should not. Operationally define the target behavior Before implementing TOPR, it is important to operationally define the target behavior. This is critical so that the treatment team can implement TOPR with a high degree of fidelity. In operationally defining the target behavior, a focus should be on observable behavior and any ambiguity should be avoided. As such, it will be important to define the onset of the behavior (i.e., when the behavior begins) and the offset of the behavior (i.e., when the behavior ends). It is also important that the interventionist determines how to collect data on the target behavior. This way the interventionist creates a precise data collection system that will evaluate the effectiveness of the TOPR procedure. Identify the function(s) of the target behavior Like any behavior intervention plan, it is important to identify the function(s) of the targeted behavior. When implementing TOPR, an interventionist should ensure that the learner is not engaging in the target behavior to escape or avoid the situation or environment. This is important

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because if the function of the learner’s behavior is to avoid or escape the environment, then removal of the stimuli or the learner leaving the environment will be reinforcing, thus increasing the likelihood of the problem behavior occurring in the future. In such situations, TOPR will not be effective. Which TOPR procedure will be used It is important to determine which variation of TOPR is going to be implemented. As previously stated, rarely if ever should exclusionary TOPR be used. This is not only because of the legal requirements that must be put in place with full exclusionary TOPR but also because it could lead to escalating the topography and severity of the target behavior prior to a decrease. If it is determined that exclusionary TOPR will be used, the interventionist should ensure that all safeguards are put in place and all legal requirements have been met. Duration of time out In general, TOPR should not be implemented for long durations. While there is no equation to determine the ideal duration, anything over 15 min may be unnecessary and counterproductive. Long durations of time-out can result in building a tolerance for time-out, decrease educational opportunities, and lead to the learner engaging in other challenging behaviors (e.g., self-stimulatory behaviors). If the time-in environment is highly reinforcing and preferred, it is unlikely that the duration of timeout would need to exceed more than 5 min. Exit criterion In addition to determining the duration of time-out, the interventionist must determine how the learner gets to leave the time-out environment. This is commonly done in two ways: (a) time-based and (b) behavior-based. In the time-based method, the learner can leave the time-out environment after the specified duration of time has elapsed. No other criteria are in place when using this method, so the learner could engage in challenging behavior or sit calmly. However, within a time-based exit criterion, the time can be reset contingent upon the occurrence of challenging behavior. Either way, once the duration has elapsed, the learner gets to leave time-out. In the behavior-based method, the learner can exit time-out by exhibiting certain prespecified behaviors. For example, requiring the learner to sit calmly and

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quietly without engaging in challenging behavior before they can leave time-out. Legal requirements Prior to implementing TOPR, it is imperative that the interventionist ensures that the procedure meets all legal requirements. This is especially true for exclusionary time-out where there might be legal requirements regarding: (a) the duration the learner can be in timeout, (b) the size of the time-out room, (c) window or door size of the time-out room, and (d) ways that the interventionist must monitor the learner. Even with nonexclusionary time-out, there may be state or federal laws that an interventionist must follow. Thus, an interventionist must check all laws prior to implementing time-out. Explanation of the contingency One final consideration is if the interventionist should explain the contingency to the learner. This will likely depend on the learner’s age and skillset. When informing the learner of the TOPR procedure, an interventionist should inform the learner of: (a) the targeted behavior(s), (b) the consequence engaging in the targeted behavior, (c) the duration of time-out, and (d) criterion to exit time-out. The emphasis should be on the expected behavior and the availability of reinforcement if the learner’s behavior meets expectations, rather than stating it as a threat.

Research on time-out Bostow and Bailey (1969) conducted a seminal study evaluating the effects of a brief TOPR procedure to decrease challenging behavior for residents in a large state hospital. The study consisted of two experiments. In the first experiment, Bostow and Bailey implemented a 2-min TOPR procedure and differential reinforcement of incompatible behavior for a woman engaging in frequent loud vocalizations and swearing. The TOPR procedure consisted of placing the participant in the corner of her room. The results demonstrated that the TOPR procedure was effective in decreasing the targeted behavior to near zero levels. In the second experiment, Bostow and Bailey evaluated the same TOPR procedure to decrease aggressive behavior for a 7-year-old boy. The results were similar in that the participant’s aggression decreased to near zero levels.

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Since Bostow and Bailey’s (1969) seminal study, researchers have evaluated the effectiveness of TOPR procedures on decreasing challenging behavior for typically developing children (e.g., Miller & Kratchowill, 1979), individuals diagnosed with autism spectrum disorder (ASD; e.g., Donaldson & Vollmer, 2011), individuals diagnosed with attention deficit disorder and attention deficit hyperactivity disorder (e.g., Fabino et al., 2004), individuals diagnosed with developmental disabilities (e.g., Mace & Heller, 1990), and individuals diagnosed with intellectual disabilities (e.g., Ritschl et al., 1972).

Autism partnership method and time-out Within the APM, TOPR is a procedure that is used as part of a reactive strategy to reduce challenging behavior. As previously stated, exclusionary TOPR is hardly, if ever, implemented within the APM because it is neither safe nor compassionate in the majority of cases. The most common form of TOPR implemented in the APM is contingent observation. We implement this form of TOPR because we have found it beneficial for learners to observe that they missed out on activities. This usually increases motivation to engage in appropriate behaviors that allow them to remain in the time-in environment and provides naturalistic learning opportunities. In the APM, interventionists ensure that the time-in environment is maximally reinforcing and that learners receive a high level of positive social attention. This ensures that there is the greatest possible contrast between time-in vs time-out and that the small amount of attention that is required during time-out is minimally reinforcing. During time-out, the interventionist does not completely ignore the learner. Rather, they pay close attention to the emotional well-being of the learner including if the learner is engaging any respondent behavior and providing comfort if needed. This is done so that the learner can be ready to return to the previous activity in a state that will allow them to be receptive to learning. When we implement TOPR, the learners usually have a dual criterion to get out of the timeout (i.e., time and behavior based). That is, the learner must refrain from engaging in the targeted behavior for a specific duration of time prior to leaving the time-out environment. A large component of the APM is constantly conditioning new stimuli and events to function as reinforcers. This helps ensure that the learner enjoys the time-in environment and finds it reinforcing. Second, and possibly most importantly, interventionists work to teach functional alternative

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replacement behaviors so the learner has multiple possible responses to engage in rather than the challenging behavior to access the same reinforcer.

Time-in ribbon The time-in ribbon, also known as the time-out ribbon (e.g., Alberto et al., 2002), is one of the most commonly implemented variations of TOPR used within the APM. The time-in ribbon procedure first requires the learner to wear, and learn the significance of, a specific visual stimulus (e.g., a bracelet on their wrist, a necklace). The learner continues to wear this item as long as they are engaging in desired behaviors and not engaging in the targeted challenging behavior. When the learner is wearing the visual stimulus, they are in “time-in” (i.e., has access to reinforcement). If the learner engages in challenging behavior, the visual stimulus is removed signaling that the learner does not have access to those reinforcers. Therefore, the visual stimulus helps provide a clear signal between access to the time-in and time-out environments. Note that it may be confusing that various researchers have used contradictory terminology with both “time-in ribbon” and “time-out ribbon.” Within the APM, we prefer to use the term “time-in ribbon” to emphasize that the ribbon or other chosen time-in stimulus is associated with all the reinforcement that is available during the time-in condition. The only exception is when describing published research, we will use the term contained in the original source.

Practical considerations The time-in ribbon procedure takes a good deal of planning and preconditioning by the interventionist. First, the interventionist needs to collaborate with the learner to select the stimulus that will be used and teach the learner to wear the stimulus. The stimulus should be obvious enough to the learner, but discrete enough to ensure it does not make them stand out. One consideration in selecting a stimulus is that it should be easily removable when necessary. During the initial phase, the interventionist should provide a high rate of reinforcement for wearing the stimulus. During all sessions, the interventionist should have the learner wear the stimulus and constantly talk about and praise them for wearing it (e.g., “Wow! You have your band, so you can play with the magnatiles!”). Further, whenever the learner accesses reinforcement, the interventionist should ask the learner if they are wearing the stimulus prior to providing access to the reinforcer. Additionally, if the learner requests something, the interventionist should ask the

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learner to show them the stimulus prior to following through with the request. All of these steps are to establish the time-in stimulus as a powerful conditioned reinforcer. The second phase of the time-in ribbon is typically teaching the learner to discriminate between time-in and time-out conditions. This can begin with the interventionist making the discrimination. For example, if the learner earns access to reinforcement, the interventionist may say, “It looks like you have your band! You can go play!” or “You don’t have your band so we can’t play this time. Let’s try again.” Next, the interventionist teaches the learner to discriminate the consequences for keeping the visual stimulus and for losing the visual stimulus. For example, the interventionist may say, “Hey, you have your band on! What’s that mean?” or “What if you didn’t have your band? Would you be able to play?” Initially, it may be important for the contingency to be simple (e.g., focusing only on one highly discriminable target behavior). As the learner is successful, the contingency can be gradually expanded (e.g., focusing on a constellation of behaviors). The final phase is the full implementation of the time-in ribbon. At this point, the learner participates in the full range of learning activities that have been identified in their behavior intervention plan. During a session, there will be numerous naturally occurring check-in times, such as opportunities to take a break, choose between activities, and incidental occasions where the learner wants or needs an item. At those check-in times, the learner only gets access to reinforcement when they have retained possession of the time-in stimulus. If the learner engages in a targeted undesired behavior, the time-in stimulus is removed. This constitutes an immediate consequence (i.e., response cost) which bridges the delay between the moment the undesired behavior occurred and the subsequent unavailability of reinforcers. At the next check-in time following the undesired behavior, the learner will experience the back-up consequence, (i.e., they will not be able to access reinforcers because they do not have the time-in stimulus). Their only options are to have a short break with nothing fun to do or carry on with learning task. Similar to previously described iterations of TOPR, the interventionist can determine the criterion that must be met to access the stimulus again (e.g., time based, behavior based).

Research on time-in ribbon Foxx and Shapiro (1978) conducted the first study evaluating the effects of the time-out ribbon to decrease various disruptive behaviors (e.g., aggression, yelling, stereotypic behaviors) with five children diagnosed with

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intellectual disabilities. Prior to experiencing contingent removal of the ribbon, a reinforcement condition occurred during which edible and social reinforcers were provided every 2.5 min contingent upon the participants wearing the ribbon and not engaging in disruptive behavior. This was done in an effort to increase the reinforcing value of the time-in environment. This schedule of reinforcement continued during the implementation of the contingent removal component; however, if the participants engaged in disruptive behavior, the ribbon was removed for 3 min. This resulted in the participant not accessing reinforcement at the end of the current interval. The results indicated that the time-out ribbon was effective as decreasing the disruptive behavior for all participants. Fee et al. (1990) evaluated the use of a time-out ribbon procedure for 59 typically developing children in a school setting. The children were divided into two groups: a no treatment control group (n ¼ 30) and a time-out ribbon procedure group (n ¼ 29). In this study, the time-out item consisted of a removable wrist band. The children in the control group attended a classroom in which the teachers conducted their classrooms as usual (i.e., no time-out band). Children in the time-out band group attended a classroom in which the teacher provided a combination of praise for appropriate behavior and removal of a time-out band for disruptive behavior. Specifically, praise was provided every 3 min and recognized all the students that were wearing their wristbands. If a student engaged in disruptive behavior, the teacher first provided a warning. If the student continued to engage in disruptive behavior. The teacher removed the wristband for 3 min. The results indicated improvements in the students’ behavior who were part of the treatment group. Leaf et al. (2012) conducted a clinical case study on the effects of a timein ribbon procedure with a 16-year-old boy diagnosed with ASD. The participant engaged in high rates of stereotypic behavior that previous behavioral intervention was not successful in decreasing. In this study, a wristband served as the time-in stimulus. The researchers compared three different conditions: (a) treatment sessions using the time-in band, (b) control sessions without the band that occurred just before a treatment session, and (c) follow-up observations without the band immediately following a treatment session. The results showed that the participant engaged in reduced levels of stereotypic behavior when the time-in ribbon was placed on the participant and was used contingently. Furthermore, the learner continued to display lower levels of stereotypic behavior without the band during the observations that followed a treatment session.

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Summary While procedures using TOPR are used within the APM (e.g., time-in ribbon), it is important to note the emphasis on staff training and competence within this method. The value of the ribbon as a conditioned reinforcer is dependent on it being used correctly across environments. The incompetent practice of TOPR procedures may result in several undesired effects such as negatively impacting the magnitude and duration of behavior suppression, damaging the rapport between the learner and the interventionist, supplanting the intended use as a result of negative reinforcement contingencies for the interventionist, inadvertently suppressing appropriate and desirable behavior, and hindering the promotion of other effective behavior analytic techniques. As such, it is important that prior to any form of TOPR that the interventionist is well trained in the principles of behavior analysis and a progressive approach to ABA (Leaf et al., 2016).

References Alberto, P., Heflin, L. J., & Andrews, D. (2002). Use of the timeout ribbon procedure during community-based instruction. Behavior Modification, 26(2), 297–311. https://doi.org/ 10.1177/0145445502026002008. Bagwell, A., Barnett, M., & Falcomata, T. S. (2022). Response cost and time-out from reinforcement. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & M. J. Weiss (Eds.), Handbook of applied behavior analysis interventions for autism (pp. 479–496). Springer. https://doi.org/ 10.1007/978-3-030-96478-8_25. Bostow, D. E., & Bailey, J. B. (1969). Modification of severe disruptive and aggressive behavior using brief timeout and reinforcement procedures. Journal of Applied Behavior Analysis, 2(1), 31–37. https://doi.org/10.1901/jaba.1969.2-31. Donaldson, J. M., & Vollmer, T. R. (2011). An evaluation and comparison of time-out procedures with and without release contingencies. Journal of Applied Behavior Analysis, 44(4), 694–705. https://doi.org/10.1901/jaba.2011.44-693. Fabino, G. A., Pelham, W. E., Manos, M. J., Gnagy, E. M., Chronis, A. M., Onyango, A. N., Lopez-Williams, A., Burrows-MacLean, L., Coles, E. K., Meichenbaum, D. L., Caserta, D. A., & Swain, S. (2004). An evaluation of three time-out procedures for children with attention-deficit/hyperactivity disorder. Behavior Therapy, 35(5), 449–469. https://doi.org/10.1016/S0005-7894(04)80027-3. Fee, V. E., Matson, J. L., & Manikam, R. (1990). A control group outcome study of a nonexclusionary time-out package to improve social skills with preschoolers. Exceptionality, 1(2), 107–121. https://doi.org/10.1080/09362839009524747. Foxx, R. M., & Shapiro, S. T. (1978). The timeout ribbon: A nonexclusionary timeout procedure. Journal of Applied Behavior Analysis, 11(1), 125–136. https://doi.org/10.1901/ jaba.1978.11-125. Leaf, J. B., Leaf, R., McEachin, J., Taubman, M., Ala’i-Rosales, S., Ross, R. K., Smith, T., & Weiss, M. J. (2016). Applied behavior analysis is a science and, therefore, progressive. Journal of Autism and Developmental Disorders, 46(2), 720–731. https://doi.org/ 10.1007/s10803-015-2591-6.

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Leaf, J. B., Oppenheim-Leaf, M. L., & Streff, T. (2012). The effects of the time-in procedure on decreasing aberrant behavior: A clinical case study. Clinical Case Studies, 11(2), 152–164. https://doi.org/10.1177/1534650112443003. Mace, F. C., & Heller, M. (1990). A comparison of exclusion time-out and contingent observation for reducing severe disruptive behavior in a 7-year old boy. Child and Family Behavior Therapy, 12(1), 57–68. https://doi.org/10.1300/J019v12n01_04. Miller, A. J., & Kratchowill, T. R. (1979). Reduction of frequent stomachache complaints by time out. Behavior Therapy, 10(2), 211–218. https://doi.org/10.1016/S0005-7897(79) 80038-6. Ritschl, C., Mongrella, J., & Presbie, R. J. (1972). Group time-out from rock and roll music and out-of-seat behavior of handicapped children while riding a school bus. Psychological Reports, 31(3), 967–973. https://doi.org/10.2466/pr0.1972.31.967.

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CHAPTER 21

Measurement systems Contents Considerations in selecting a measurement system Reliable Valid Accurate Usefulness Staff preference and skill Maximizing teaching opportunities Measurement systems Estimation data Trial-by-trial First trial data Task analysis measurement Frequency Duration Whole interval recording Partial interval recording Momentary time sampling Measuring with our heart Summary References

252 252 252 253 253 253 254 254 254 258 259 260 260 262 262 263 263 265 265 265

One area that differentiates behavioral intervention from other interventions and approaches to treatment for children with autism spectrum disorder (ASD) is the reliance on objective measurement (Baer et al., 1968, 1987). Within the field of applied behavior analysis (ABA), behavior analysts are concerned with observing, measuring, and changing observable behaviors. This does not mean that private events and unobservable behaviors (e.g., thoughts, feelings) are unimportant or not targeted, but rather our concentration is on behavior that can be objectively observed. Additionally, we are more concerned about what our clients can be brought to do rather than what they can be brought to say (Baer et al., 1968). As such, researchers and clinicians have developed various methods to measure the behavior of our clients. The development of continuous and discontinuous data

A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00008-8

Copyright © 2024 Elsevier Inc. All rights reserved.

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collection systems has allowed for accurate and meaningful data collection throughout behavioral intervention (Taubman, 2008). Meaningful data collection helps interventionists and supervisors to evaluate the effectiveness of interventions, track skill acquisition, identify skill deficits, and assess overall progress throughout intervention. Although data collection is crucial to track progress and is a hallmark of behavioral intervention, it is important that the data collection system is practical to use and does not interfere with learner progress. Measurement systems and data collection should be used as a tool to make decisions and should not take precedence over the effective implementation of the intervention. There is a great deal of overlap between measurement systems used in a progressive and conventional model. There are, however, several guidelines that should be considered before selecting which measurement system to use within the Autism Partnership Method (APM).

Considerations in selecting a measurement system Reliable One of the first considerations of any measurement system is the reliability of the system. For a measurement system to be reliable, it must be consistent across different interventionists who use the measurement system and across different observational contexts. For instance, when measuring a learner’s voice volume using a 5-point Likert scale, a score of a “3” should always be reflective of the same voice volume across all interventionists and situations. If a score of “3” does not reflect the same voice volume, then the measurement system is unreliable and another measurement system should be used or more training and refinement to the current measurement system may be needed.

Valid A second consideration of any measurement system is if that measurement system is valid. For a measurement system to be valid, it must actually measure the behavior of interest. For example, if an interventionist is measuring deceitful statements or lies made by a learner, a valid measurement system would count the precise number of times in a day the learner lied. Counting the number of instances the learner told the truth each day would be invalid, as this system does not capture the behavior that the interventionist wants to measure (i.e., deceitful statements).

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Accurate A third critical component of determining a measurement system is ensuring that the measurement system is accurate. In other words, ensuring that the data recorded (observed value) correspond to the amount of behavior that is occurring (true value). For example, if a measurement system indicates a learner kicked another person 12 times in 1 h, it would be important that this is what actually occurred (e.g., as opposed to 24 times in 1 h). Otherwise, the measurement system would be inaccurate and cannot be trusted. It is also important to ensure that observer drift does not occur. Observer drift occurs when the scorer departs from the original definition of behavior and begins scoring or recording the behavior using a different definition. Thus, the observed value is not the true value. It is important that supervisors train others on how to score behavior and consistently supervise the accuracy and reliability of the scores or recording of that behavior.

Usefulness There is no point in taking data on a learner’s behavior unless that data are going to be analyzed and used to change and adapt the intervention, determine skill mastery, or impact the learner in some way. Thus, the interventionist should not take too much data to the point where the data are uninterpretable and cannot be synthesized or analyzed. Conversely, an interventionist should not take so little data that there is not enough information to provide an accurate picture of the learner’s behavior and what adjustments should be made. An interventionist needs to find the right balance. Doing so often means that the measurement systems used in clinical settings are not going to be continuous, in which every instance of behavior is recorded. The most efficient approach requires using a data system that provides a representative sample of the learner’s behavior.

Staff preference and skill A consideration which may differentiate data collection in the APM compared to a more conventional approach is which staff are taking the data on a daily basis. One of these staff considerations is the interventionists’ preference for collecting data using certain measurement systems. If a staff prefers a specific measurement system (e.g., momentary time sampling) over another measurement system (e.g., frequency) then it would be wise to consider the interventionist’s preference in the selection of a measurement system. This should especially be the case if the preferred measurement system meets all the aforementioned

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criteria. If staff prefer a system, there is an increased likelihood they will be more accurate in their measurement and more likely to take data throughout their sessions. Additionally, a supervisor should only select data systems for which staff are fully trained to implement with a high degree of accuracy. Otherwise, the measurement system will be unreliable and will not be useful in analyzing the client’s current programming and progress. As such, it is imperative for supervisors to know the skill level of each interventionist.

Maximizing teaching opportunities The final consideration when selecting a measurement system is finding a data collection system that does not interfere with teaching and learning opportunities. One of the goals of the APM is to maximize learning opportunities within every session. As such, any measurement system that will interfere with this goal should be avoided. Therefore, a supervisor must find the right balance between a data collection system that will accurately represent the behavior of their learner and a system that maximizes learning opportunities. Data are your friend, not your enemy (Taubman, 2008). If supervisors or interventionists begin to feel like data collection is becoming the enemy, then the data collection system should be reevaluated and altered to best support the clinical goals.

Measurement systems Since the goal of data collection in the APM is to balance maximizing teaching opportunities and the accuracy of the data collection system, there are a wide variety of measurement systems used. Within the APM, interventionists use continuous and discontinuous measurement systems depending on the previously stated considerations. Table 1 provides an overview and the advantages and disadvantages of each measurement system.

Estimation data One of the hallmarks of the APM is the use of estimation data. Estimation data are a discontinuous measurement system in which the interventionist estimates the duration, frequency, rate, or quality of the learner’s behavior after a specified amount of time. When taking estimation data, the interventionist typically uses a Likert scale (usually a 5-point Likert Scale). Table 2 provides an example of how the Likert scale could be used across behaviors more amenable to frequency count, duration, and percentage of opportunities.

Table 1 Advantages and disadvantages of different measurement systems. Measurement system

Advantages

Disadvantages

Estimation data

Does not interfere with learning opportunities Can be more efficient

Trial-by-trial data collection

Accurate and valid Easy to train interventionists in measurement system

First trial data

Accurate and valid Easy to implement East to train interventionists in measurement system Does not interfere with learning opportunities Helpful in identifying missing behavioral steps Accurate and valid

More difficult to train interventionists in measurement system Less accurate Minimal available research Less efficient Decreases learning opportunities Can disrupt flow of teaching and connection with learner Can over- and underestimate mastery of goals Does not provide information for all behavior Only useful for certain behaviors Can decrease learning opportunities Laborious, requires constant observation Interferes with learning process Can be laborious Can interfere with learning process Underestimates the true value of behavior Discontinuous measurement system Requires constant observation from data collector Overestimates the true value of behavior Discontinuous measurement system Can underestimate and overestimate the true value of behavior Discontinuous measurement system

Task analysis measurement

Frequency

Accurate and valid Continuous measurement system

Duration

Accurate and valid Continuous measurement system Can provide an estimate of total duration of behavior

Whole interval recording

Partial interval recording

Observer does not need to observe for entire interval if target behavior occurs

Momentary time sampling

Observer only has to observe and collect data at a specified time

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Table 2 Example of estimation scale. Estimation score

Frequency

Duration

0

Never occurring

Never occurring

1

Infrequent (e.g., 1–4 times) Moderately often (e.g., 5–9 times) Often frequent (e.g., 10–15 times) Extremely often (e.g., 15+ times)

Brief duration (e.g., 1–4 min)

2

3

4

Moderate duration (e.g., 5–9 min) High duration (e.g., 10–15 min) Extremely high duration (e.g., 15+min)

Percentage of opportunities

Never or very rare (e.g., 0%–20% of opportunities) Low occurrence (e.g., 21%–40% of opportunities) Moderately often (e.g., 41%–60% of opportunities) Frequent (e.g., 61%–80% of opportunities) Very high percentage (e.g., 81%–100% of opportunities)

Table 3 is a sample estimation data sheet that could be used in a group setting. An interventionist typically takes estimation data after a block of teaching trials (e.g., after 20 trials), or after a certain duration of time (e.g., 20 min), or at the end of the session. The estimation data system is widely used in the APM because it minimizes interference with the learning process, as the interventionist only collects data at certain periods of time as opposed to after every trial or after very short durations. This results in increased learning opportunities within a session. The estimation data collection system is, however, a discontinuous measurement system and should be used in conjunction with other data collection systems. Additionally, it requires more training for an interventionist to accurately estimate learner behavior, and therefore other measurement systems may have to be used until an interventionist is well-trained in the data collection system and the estimation data are reliable and accurate. While estimation data are commonly used clinically within the APM, there is limited research. Taubman et al. (2013) conducted the first study on estimation data by comparing trial-by-trial, momentary time sample, and estimation data across different interventionists, programs, and learner goals. The results indicated that trial-by-trial data collection was the most accurate and estimation data collection was the most efficient. Thus, more teaching was accomplished with estimation data collection, but this came

Table 3 Example of group estimation data sheet. Date: __________ Behavior

Child 1

0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1

Scorer: ___________ Child 2

2 2 2 2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4 4 4 4

0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1

Child 3

2 2 2 2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4 4 4 4

0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1

Child 4

2 2 2 2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4 4 4 4

0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1

2 2 2 2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4 4 4 4

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with a reduction in accuracy. In a follow-up study, Ferguson et al. (2020) compared trial-by-trial data collection to estimation data collection during discrete trial teaching with three children diagnosed with ASD. The results differed from Taubman and colleagues in that estimation data collection was as accurate as trial-by-trial data; however, both were equally as efficient with respect to the number of discrete trials within a 3-min teaching session. One hypothesis Ferguson and colleagues offered for why the data collection systems were found to be equally efficient was due to the skill level of the interventionist and their personal history with data collection systems.

Trial-by-trial A second commonly used data collection system in the APM is trial-by-trial data collection (e.g., Carey & Bourret, 2014). Trial-by-trial data are commonly used within discrete trial teaching as it captures the performance of a learner response on each trial. Trial-by-trial data collection are also a continuous measurement system as it measures the learner’s behavior continuously. Table 4 provides an example of a trial-by-trial data sheet. Within a trial-by-trial data collection system, a learner’s response is commonly scored as correct (+), incorrect ( ), correct with a prompt (P+), incorrect with a prompt (P ), and no response (NR; i.e., any response that occurs after the target duration or any responses that do not fall within the other categories). When taking trial-by-trial data, the interventionist should record the data that would indicate the order of trials (see Table 4) as opposed to only recording the response per target. This way the interventionist can analyze how the learner is responding during the session and how the trials occurred across the session. An interventionist should use trial-by-trial data when they need an accurate true value measure. Since trial-by-trial data are considered a continuous data collection system, it can be a very time-consuming data collection system that can interfere with learning opportunities. Thus, we recommend that an interventionist uses this measurement system only as needed to provide additional information on the true level of the learner’s behavior. Additionally, trial-bytrial data can be used to gauge the accuracy of estimation data periodically to ensure estimation data are accurate. Trial-by-trial data can also be used as a snapshot, or sample, of a client’s skill acquisition. An interventionist can use trial-bytrial data for a portion of their session in order to track skill acquisition. This method allows for continuous measurement but does not require continuous data collection throughout the entire session. This is important as in early intervention sessions may last 4–8 h a day.

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Table 4 Example of trial-by-trial data sheet. Participant: Trial

Target

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Scorer:

Date:

Response

+ + + + + + + + + + + + + + + + + + + + + + + + +

NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR

P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+ P+

P P P P P P P P P P P P P P P P P P P P P P P P P

Scoring key:

+ NR P+ P

Independent correct response Independent incorrect response No response Prompted correct response Prompted incorrect response

First trial data A variation of trial-by-trial data which are more commonly used in the APM is first trial data (e.g., Cummings & Carr, 2009). First trial data are a variation of trial-by-trial data in which the interventionist only records the learner’s response to a target the first time it is presented during a teaching session.

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Given that an interventionist only takes data on the first trial, this method is less likely to interfere with the learning process when compared to trial-bytrial data collection. Cummings and Carr (2009) compared first trial data collection with continuous measurement for six children diagnosed with ASD across a variety of skills. The results indicated that the first-trial measurement system resulted in faster acquisition, but the continuous measurement system resulted in better maintenance. As long as first-trial measurement does not interfere with the learning process, its efficiency makes it a highly recommended measurement system in teaching sessions.

Task analysis measurement When teaching chains of behaviors or behaviors that require a task analysis (e.g., social skills), task analysis measurement can be useful (see Table 5). Within this measurement system, the interventionist puts all behavioral steps on the data sheet. Then when the behavior should occur, the interventionist marks if the learner displayed the step (e.g., marking “yes”), if the learner did not display the step (e.g., marking “no”), or if the opportunity to display the step did not occur (e.g., marking “N/A”). This data system allows the interventionist to see exactly what steps the learner is displaying or not displaying and can help inform any necessary changes. Thus, if a learner is struggling to learn a complex behavior, this type of measurement system may be perfect in identifying the reason why the learner is not making progress. However, this type of data system is rather cumbersome and should not be used frequently if it is interfering with teaching or learning opportunities.

Frequency A common measurement system in a conventional approach is frequency data collection. Frequency data collection involves recording every instance of a response. For example, if an interventionist is collecting data on how often a learner engages in self-injurious behavior, then a frequency count would involve scoring every instance. A frequency count should only be used with discrete responses that have a clear beginning and end and should not be used with continuous responses or those with an unclear beginning and end. Additionally, a frequency count is only meaningful if the duration of the measurement is rather consistent (e.g., always measuring behavior for 30 min). To illustrate, suppose an interventionist is evaluating a learner’s aggression toward others. On the first day, they observed the learner for 30 min and the learner kicked 10 times. On the second day, they observed

Table 5 Example of task analysis data sheet. Date: ___________ Step

1 2 3 4 5 6 7 8 9 10 11 12

Behavior

Child 1

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Scorer: ____________ Child 2

No No No No No No No No No No No No

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Child 3

No No No No No No No No No No No No

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Child 4

No No No No No No No No No No No No

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

No No No No No No No No No No No No

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

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the learner for 60 min and the learner kicked 10 times. The frequency count would be identical, but there is a large difference in the rate of the behavior. Therefore, when measuring behavior across different durations of time, it would be important to report it as a rate instead of frequency. Rate is calculated by dividing the frequency by the duration of time. Taking frequency data can be laborious as it requires constant observation and recording. As such, it could greatly interfere with learning and therefore is not often used within the APM.

Duration A duration measurement system involves recording the duration of time a response occurs from its onset to its conclusion. These data can be collected in at least two ways. First, the duration per occurrence can be recorded. For example, if measuring the duration of each tantrum, it may be recorded as the first tantrum lasting 90 s, the second tantrum lasting 60 s, and the third tantrum lasting 33 s. The second way is the total duration within a session. Using the previous example, the total duration of all tantrums would be 3 min 3 s. Duration measures are typically used if the behavior is not discrete, occurs at high rates, or if it is useful to identify how long the learner is engaged in the activity (e.g., playing with others). Although they are not as strenuous as frequency measures, duration measures can still be burdensome, especially recording duration for every occurrence. As such, this method is not as commonly used within the APM.

Whole interval recording A time sampling approach which is used in the APM is whole interval recording. In this system, the evaluation period (e.g., 30 min) is divided into smaller time intervals (e.g., 15 s). The response is scored as occurring or not occurring within these smaller time intervals. For the response to be marked as occurring within the interval, the learner must have engaged in the response for the entire duration of the interval. For example, when measuring interacting with a peer and the learner interacts with a peer for the entire 15 s, it would be scored as occurring. If, however, the learner only interacted with a peer for 14 s of the 15 s interval, the response would not be scored as occurring during that interval. As such, this measurement system can underestimate the frequency of behavior. When the session ends, the data are converted into a percentage by dividing the number of intervals in which the response occurred by the total number of intervals. Of all of the time

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sampling measures (e.g., whole interval, partial interval, momentary time sampling), whole interval is the most labor intensive for an interventionist as the interventionist must attend for the entire duration of an interval or until the learner does not engage in the behavior for any portion of the interval so that they can score the interval accurately.

Partial interval recording A second time sampling approach used in the APM is partial interval recording. Similar to whole interval recording, the evaluation period (e.g., 30 min) is divided into smaller intervals (e.g., 15 s). The response is scored as “occurred” if it happens at any point during the interval, no matter how many times it occurs. The response is scored as “not occurred” during the interval if the response does not occur at any time during the interval. For example, if measuring interacting with a peer and the learner interacted with a peer several times or one time within an interval, the interval would be scored as the response has occurred. Partial interval recording can overestimate the total duration and underestimate the rate of behavior. When the session ends, the data are converted into a percentage score using the same formula as was used for whole interval recording. Of all of the time sampling measures (e.g., whole interval, partial interval, momentary time sampling), this is the one most commonly used in the APM.

Momentary time sampling The third time sampling approach which is used in the APM is momentary time sampling. Again, the evaluation period (e.g., 30 min) is divided into smaller intervals (e.g., 15 s). The response is scored as having occurred if it happens at a specific point during the interval (e.g., at the beginning of the interval, at the end of the interval). This measurement system should be avoided if the response occurs infrequently and/or for shorter durations. A momentary time sampling procedure can result in an overestimation or underestimation of the occurrence of a response. When the session ends, the data are converted into a percentage by dividing the number of intervals in which the response occurred by the total number of intervals. This type of measurement system is commonly used in the APM as the interventionist is only required to attend for a brief moment to determine if the response is occurring or not and therefore has more time to allocate to teaching.

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Table 6 Example of a social validity questionnaire. Social validity questionnaire Functional assessment interview and functional analysis Instructions: Please circle the number that corresponds with your response to the following questions regarding the functional assessment interview and analysis process in which you participated. Please then add any additional comments about the interview and analysis process that you would like to share. 1. I found the interview process to be acceptable. 1 Not acceptable

2

3

4

5

6

7 Highly acceptable

4

5

6

7 Highly comfortable

5

6

7 Highly acceptable

5

6

7 Highly safe

5

6

7 Highly comfortable

2. I was comfortable during the interview process. 1 Not comfortable

2

3

Additional comments about the interview process:

3. I found the functional analysis of my child’s problem behavior to be acceptable. 1 2 3 4 Not acceptable

Additional comments about the functional analysis:

4. After having witnessed it, I consider the functional analysis to be safe for my child and the therapist. 1 Not safe

2

3

4

Additional comments about the safety of the functional analysis:

5. I was comfortable watching the functional analysis of my child’s problem behavior. 1 Not comfortable

2

3

4

Additional comments about your comfort level during the functional analysis:

Please provide any additional comments or feedback for our team about the functional assessment interview and functional analysis process that we used to better understand your child’s problem behavior.

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Measuring with our heart Wolf (1978) provided one of the most seminal articles in the field of ABA. In this article, Wolf made the important argument that behavior analysts must use subjective measures to assess consumer satisfaction with goals, procedures, and the effects of those procedures. As such, there should be constant measurement and assessment of how our clients feel about what and how they are being taught. Since our clients and caregivers may not always be comfortable directly telling us how they feel, we recommend providing a questionnaire on at least a yearly basis but preferably on a 3-month cycle. Table 6 provides an example of a social validity survey.

Summary There is no perfect data collection or measurement system; each comes with its pluses and minuses. Within the APM, we view data collection on a sliding scale. That means taking as much data as necessary to inform progress and changes and no more. If you find yourself spending more time taking data than teaching, it is time to change the data collection system.

References Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. https://doi.org/ 10.1901/jaba.1968-1-91. Baer, D. M., Wolf, M. M., & Risley, T. R. (1987). Some still-current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 20(4), 313–327. https://doi.org/ 10.1901/jaba.1987.20-313. Carey, M. K., & Bourret, J. C. (2014). Effects of data sampling on graphical depictions of learning. Journal of Applied Behavior Analysis, 47(4), 749–764. https://doi.org/ 10.1002/jaba.153. Cummings, A. R., & Carr, J. E. (2009). Evaluating progress in behavioral programs for children with autism spectrum disorders via continuous and discontinuous measurement. Journal of Applied Behavior Analysis, 42(1), 57–71. https://doi.org/10.1901/jaba.2009.42-57. Ferguson, J. L., Milne, C. M., Cihon, J. H., Dotson, A., Leaf, J. B., McEachin, J., & Leaf, R. (2020). An evaluation of estimation data collection to trial-by-trial data collection during discrete trial teaching. Behavioral Interventions, 35(1), 178–191. https://doi.org/10.1002/ bin.1705. Taubman, M. T. (2008). Data can and should be your friend! In R. Leaf, M. Taubman, & J. McEachin (Eds.), It’s time for school (pp. 137–151). Taubman, M. T., Leaf, R. B., McEachin, J. J., Papovich, S., & Leaf, J. B. (2013). A comparison of data collection techniques used with discrete trial teaching. Research in Autism Spectrum Disorders, 7(9), 1026–1034. https://doi.org/10.1016/j.rasd.2013.05.002. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203.

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CHAPTER 22

Formal assessments Contents The assessments Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview Revised (ADI-R) Gilliam Autism Rating Scale Vineland-3 Adaptive Behavior Scales Adaptive Behavior Assessment System—Third edition Wechsler Intelligence Scale for Children-V (WISC-V) Wechsler Preschool and Primary Scale of Intelligence-IV Mullen Scales of Early Learning Social Skills Improvement System Social Responsiveness Scale Walker-McConnell Peabody Picture Vocabulary Test Expressive One Word Picture Vocabulary Test Aberrant Behavior Checklist Parenting Stress Index World Health Organization Quality of Life-BREF with Autism Supplement Quality of Life Summary References

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It is important that children receive a battery of formal assessments when receiving a diagnosis of autism spectrum disorder (American Psychiatric Association, 2013). Following a diagnosis, a battery of assessments should be provided on a yearly basis to track a learner’s progress, skill strengths, and areas of need. The battery of assessments should include assessments that evaluate an individual’s language (e.g., Expressive One-Word Picture Vocabulary Test; Martin & Brownell, 2011), adaptive behaviors (e.g., Vineland Adaptive Behavior Scales; Sparrow et al., 2016), challenging behavior (e.g., Aberrant Behavior Checklist; Aman & Singh, 1994), social behavior (e.g., Social Responsiveness Scale; Constantino, 2012), caregivers stress (e.g., Parenting Stress Index; Abidin et al., 2006), autism characteristics (e.g., Gilliam Autism Rating Scale; Gilliam, 2013), cognition (e.g., Wechsler Preschool and

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Primary Scale of Intelligence; Wechsler, 2012), and quality of life (e.g., World Health Organization Quality of Life measure; McConachie et al., 2018; Skevington et al., 2004). The assessments must be conducted and scored by professionals who are trained to administer the assessments and who meet the standards required of each of the assessments. It is also important to note that a professional should be familiar with state or regional laws as they might regulate who can administer an assessment. This will often require a team of experts across various disciplines to help with administration. This team of experts can include psychologists, teachers, school administrators, and speech-language pathologists who all use formal assessments to track progress. Formal assessments are valuable for the learner and the behavior analyst for many reasons. First, assessments are required to make a formal medical or educational diagnosis of autism spectrum disorder. Second, formal standardized assessments are often needed to secure funding from third-party payers like insurance companies. Third, formal assessments are great ways to evaluate a learner’s skill strengths and areas of need. Fourth, formal assessments can be used to help create a comprehensive and meaningful curriculum. Fifth, standardized normative assessments are a way to track progress across years and in comparison to same-age peers. For the behavior analyst, the use of formal assessments may be important for collaborating with other professionals (e.g., psychologists, speech-language pathologists, occupational therapist), as they are more likely to use, and be familiar with, these formal assessments. Finally, formal assessments are widely used to measure outcomes in peer-reviewed journals outside of behavior analysis. This makes the use of formal assessments critical if behavior analysts want to publish in nonbehavioral, peer-reviewed journals that reach larger audiences. As such, within the Autism Partnership Method (APM), a variety of formal assessments are used at intake (i.e., assessment prior to intervention) and on an ongoing basis. This chapter briefly describes a variety of assessments we use within our practice and why they may be important for clinicians.

The assessments Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview Revised (ADI-R) Catherine Lord is the creator of two of the gold standard assessments that help in the diagnostic process for autism. The first of these assessments is the ADOS (Lord et al., 2012). The ADOS evaluates a learner’s social interactions, communication and language, play skills, and how they use toys

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imaginatively through the use of a structured observation. The assessment consists of five different modules based on the learner’s language and age. The administrator provides a score on a scale from 0 to 3 for each of the behaviors. This assessment is primarily used for diagnostic purposes. It is also a good assessment for helping an interventionist determine deficits in social behavior. However, it is an analog assessment and therefore information cannot be used to determine how behaviors are displayed in the natural environment. The second assessment that Catherine Lord and her colleagues created was the ADI-R (Rutter et al., 2003). The ADI-R is an interview for the caregivers of a child suspected to have autism spectrum disorder. The assessment contains five different sections. These sections are: (a) beginning questions, (b) social behavior and play, (c) communication, (d) repetitive and restricted behavior, and (e) general problems. Like the ADOS, the ADI-R is scored on a scale of 0–3; however, all the scores pertain to the learner’s behavior prior to the age of five. The ADI-R is a comprehensive interview and is often used during the diagnostic process. Since both assessments are great at identifying the strengths and deficits of the learner, they can be used to help in the initial development of the curriculum.

Gilliam Autism Rating Scale The Gilliam Autism Rating Scale (GARS; Gilliam, 2013) is a brief questionnaire that can be filled out by parents, caregivers, clinicians, and teachers to identify autism symptoms and estimate the severity of autism. The GARS can be administered to children as young as 3 to adults as old as 22. It is a relatively short questionnaire and only takes 5–10 min to complete. The GARS has an informant rate the learner’s behavior across the domains of restrictive/repetitive behavior, social interactions, social communication, emotional responses, cognitive style, and maladaptive speech. The GARS conforms to the DSM-V diagnostic criteria for a diagnosis of ASD, so this assessment also identifies the level of support (i.e., requires very substantial support, requires substantial support, requires support) the learner needs based on the respondent’s answers to the questions.

Vineland-3 Adaptive Behavior Scales Teaching adaptive behaviors is of the utmost importance for individuals diagnosed with autism spectrum disorder. One assessment that evaluates a learner’s adaptive behavior is the Vineland-3 Adaptive Behavior Scales

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(Sparrow et al., 2016). The Vineland-3 evaluates behavior in three large domains: communication, social behavior, and daily living skills. Within each of these domains are subdomains. For the communication domain, there are three subdomains: receptive communication, expressive communication, and written communication. For the daily living domain, there are also three subdomains: personal daily living, domestic daily living, and community/school daily living skills. The subdomains of play/leisure, coping, and interpersonal relationships make up the socialization domain. Additionally, the Vineland-3 has questions on motor skills (i.e., fine and gross) and challenging/maladaptive behaviors. The Vineland-3 can be completed as either an interview or filled out directly by the respondent. For each question, the person states if a behavior has never happened (i.e., score of a “0”), sometimes happens (i.e., score of a “1”), or usually happens (i.e., score of a “2”). Those three domains (i.e., communication, social, daily living) are compiled into the Adaptive Behavior Composite score. An Adaptive Behavior Composite Score of 100 is considered the mean standard score (i.e., the 50th percentile) for an individual’s age. The Vineland-3 is an excellent way to measure a learner’s progress on adaptive behavior and can help in the curricular process.

Adaptive Behavior Assessment System—Third edition Another measure to evaluate a learner’s adaptive behavior is the Adaptive Behavior Assessment System (ABAS; Harrison & Oakland, 2003). Within this assessment, there are three broad domains: social, practical, and conceptual. Each of these domains has subdomains as well. For example, the conceptual domain has the subdomains of communication, academics, and self-direction. The practical domain has four subdomains which are self-care, health and safety, home/school living, and life in the community. There are only two subdomains in the social domain which are leisure skills and social skills. Interviewees have a four-point scale to rate each of the behaviors. A score of a “0” means not able to perform, a score of “1” means almost never/never, a score of “2” means sometimes, and a score of a “3” means almost always. Each domain provides a standard score as well as a composite score. Like the Vineland-3 the mean standard score is 100. This assessment is excellent for helping with curriculum development in adaptive skills and as another way to track overall progress.

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Wechsler Intelligence Scale for Children-V (WISC-V) The WISC-V (Wechsler, 2014) is an intelligence test that measures a child’s cognitive ability across five domains. The WISC-V is conducted with children between the ages of 6 years 0 month and 16 years 11 months. The five cognitive areas assessed through the WISC-V are: (a) verbal comprehension, (b) visual spatial, (c) fluid reasoning, (d) working memory, and (e) processing speed. Subtests in the verbal comprehension domain include similarities, vocabulary, information, and comprehension. Subtests in the visual spatial domain include block design and visual puzzles. Subtests in the fluid reasoning domain include matrix reasoning, figure weights, picture concepts, and arithmetic. Subtests in the working memory domain include digit span, picture span, and letter-number sequencing. Subtests in the processing speed domain include coding, symbol search, and cancelation. For a child to receive a Full-Scale IQ score, only seven subtests need to be administered (i.e., similarities, vocabulary, block design, matrix reasoning, figure weights, digit span, coding), which typically only takes an hour to administer. The WISC-V can only be implemented by a trained professional but can yield a variety of important information when it comes to a child’s skill strengths and skill deficits. The results can often shine a light into gaps or holes in a child’s skill set and help develop additional curricular targets.

Wechsler Preschool and Primary Scale of Intelligence-IV The Wechsler Preschool and Primary Scale of Intelligence-IV (WPPSI-IV; Wechsler, 2012) is an intelligence test that measures a young child’s cognitive development. The WPPSI-IV can be administered to children between the ages of 2 years 6 months and 7 years 7 months. For a child between the ages of 2 years 6 months and 3 years 11 months, the domains assessed are verbal comprehension, visual spatial, and working memory. For a child between the ages of 4 years 0 month and 7 years 7 months, the five domains assessed include: (a) verbal comprehension, (b) visual spatial, (c) fluid reasoning, (d) working memory, and (e) processing speed. Similar to the WISC-V, each domain is comprised of subtests, but the subtests administered are dependent on the child’s age. To receive a Full-Scale IQ score on the form for children 2 years 6 months to 3 years 11 months, only five subtests need to be administered (i.e., receptive vocabulary, information, block design, object assembly, picture memory). To receive a Full-Scale IQ score on the form for children ages 4 years-0 month and 7 years-7 months, six subtests need to be administered (i.e., information, similarities, block design, matrix

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reasoning, picture memory, bug search). The WPPSI-IV can also only be administered by a trained professional. This test also reveals a variety of important information regarding a child’s strengths and weaknesses and can help in curriculum planning.

Mullen Scales of Early Learning The Mullen Scales of Early Learning (Mullen, 1995) is a developmental assessment that measures receptive and expressive language, fine and gross motor skills, and visual reception skills. The Mullen Scales of Early Learning can be administered for children ages birth to 68 months (i.e., 5.5 years). Four domains within the Mullen Scales of Early Learning (i.e., visual reception, fine motor, receptive language, and expressive language) are used to calculate the Early Learning Composite score. The Mullen Scales of Early Learning also provides age equivalent scores for each domain score and overall Early Learning Composite Score which allows benchmarking for overall developmental growth. The age equivalent scores allow for evaluation of growth for learners whose ability falls below the average standard scores for their age and the measure is very sensitive in the range of developmental achievement. This measure of sensitivity is especially useful for learners diagnosed with ASD participating in early intensive behavioral intervention.

Social Skills Improvement System The Social Skills Improvement System (SSiS; Gresham & Elliott, 2008) is a standardized assessment that evaluates a learner’s social skills and problem behavior. The SSiS is meant for learners between 3 and 18 years of age. The SSiS is norm referenced for age and gender of the learner. The social skills domain is broken up into seven subdomains which are: (a) communication, (b) cooperation, (c) assertion, (d) responsibility, (e) empathy, (f ) engagement, and (f ) self-control. The questions in the problem behavior domain cover the subdomains of: (a) externalizing problem behaviors, (b) internalizing problem behavior, (c) bullying, (d) hyperactivity/inattention, and (e) problem behavior related to autism spectrum disorder. The rater uses a four-point scale to answer the question in each domain as either “never,” “seldom,” “often,” and “almost always.” One of the great assets of this assessment is that the rater can indicate how important each of the behaviors are by indicating them as “not important,” “important,” and “critical.” This feature of the SSiS is an excellent way to evaluate social validity of potential curricular goals.

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Social Responsiveness Scale Another assessment that is utilized in the APM to evaluate social behavior is the Social Responsiveness Scale (SRS-2; Constantino, 2012). The purpose of this assessment is to measure social symptoms directly related to a diagnosis of autism spectrum disorder. This assessment consists of a total of 65 questions. The different domains of this assessment are: (a) social awareness, (b) social cognition, (c) social communication, (d) social motivation, and (e) restricted interests and repetitive behavior. The assessment also uses a four-point Likert scale for the respondent to answer each question. The respondent scores each item on the questionnaire as “not true” of the learner, “sometimes true,” “often true,” or “always true.” The assessment provides a T-score which evaluates the level of a learner’s overall social behavior, and it categorizes their social behavior as falling in the mild range, moderate range, or severe range. It is an inverse scoring system in which a lower T-score denotes better overall social behavior. A T-score under 59 indicates social behavior in the normal range, a score from 60 to 65 indicates mild social impairments, a score of 66 to 75 indicates moderate social impairment, and a score higher than 76 indicates severe social impairment.

Walker-McConnell A third measure that is utilized in the APM to evaluate social behavior is the Walker-McConnell Scale of Social Competence and School Adjustment (Walker and McConnell, 1985). This assessment is also a great way to measure school readiness behaviors. There are two forms of the Walker-McConnell: an elementary version and an adolescent version. There are 43 questions in the elementary version and 53 questions in the adolescent version. The elementary version of the Walker-McConnell is divided into three subscales: (a) teacher-preferred social behavior, (b) peer-preferred social behavior, and (c) school adjustment. The adolescent version is divided into four subscales: (a) self-control, (b) peer relations, (c) school adjustment, and (d) empathy. The Walker-McConnell is meant to be filled out by a teacher. The teacher responds to the various questions using a five-point Likert scale with 1 representing “never” engaging in a behavior and 5 representing “frequently” engaging in a behavior. The teacher must have at least 6 weeks of interaction with the student before filling out the form.

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Peabody Picture Vocabulary Test Within the APM, it is important to measure a learner’s language. In doing so, we use direct observation measures, the first being the Peabody Picture Vocabulary Test (Dunn, 2018). This assessment can be applied to learners from ages 2.5 years to adulthood (i.e., 90+years). The purpose of the assessment is to measure a learner’s receptive language vocabulary for single words. The assessment consists of showing a learner a page with four different pictures on it. The interventionist then asks the learner to touch a certain picture. As the learner correctly responds, the words and/or discriminations between the pictures on the page become more difficult. The Peabody Picture Vocabulary Test is a standardized norm-referenced assessment with an average score of 100 indicating that a learner has age-typical receptive vocabulary skills for their age.

Expressive One Word Picture Vocabulary Test To evaluate a learner’s one-word expressive vocabulary, we use the Expressive One Word Picture Vocabulary Test (Martin & Brownell, 2011). The assessment can be administered to children aged 2 years through adulthood (i.e., 99 years +). In this assessment, the interventionist shows a picture to the learner and asks them to name what is in the picture is (e.g., “What is this?”). The Expressive-One Word Picture Vocabulary Test is also a standardized and norm-referenced assessment with a score of 100 indicating that a learner has age-typical expressive vocabulary skills for their age.

Aberrant Behavior Checklist To evaluate a learner’s aberrant behavior, we use the Aberrant Behavior Checklist (Aman & Singh, 1994). This assessment is meant for learners age five and older. The Aberrant Behavior Checklist consists of 58 questions across 5 different domains: (a) irritability, (b) social withdrawal, (c) stereotypic behavior, (d) hyperactivity/noncompliance, and (e) inappropriate speech. The rater has to answer each of the 58 questions using a 4-point Likert scale. A score of a “0” means the behavior is not a problem, a score of a “1” means slight problem, a score of a “2” means a serious problem, and a “3” means a severe problem. Cutoffs determine if the score for each subscale is indicative of elevated levels of aberrant behavior for their age and gender.

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Parenting Stress Index We find it imperative to assess how caregivers are functioning and see if their stress levels are increasing or decreasing over time. To measure this, we use the Parenting Stress Index-Short Form (Abidin, 2012). This assessment is administered to parents with a child less than 12 years of age. This assessment includes 36 questions across three different subscales: (a) parental distress, (b) parent-child dysfunctional interaction, and (c) difficult child. The rater fills out each of the questions using a five-point Likert scale ranging from “strongly agree” to “strongly disagree.” The total score of the assessment can yield a percentile of total stress. The higher the percentile, the higher the level of stress for the caregiver. Total stress scores that are in the 86th percentile or higher are considered to be elevated. Information gathered from this assessment can help guide the interventionist in terms of the supports that parents may need (e.g., more parent training, counseling services, respite services) and the urgency of when these supports are needed.

World Health Organization Quality of Life-BREF with Autism Supplement Quality of Life Having an assessment related to an individual’s quality of life in adulthood is crucial to ensure that an autistic individual is living a high-quality life. The World Health Organization developed a Quality-of-Life assessment that is either 100 questions long (WHOQoL-100) or a brief form (WHOQoL-BREF) that consists of 26 questions (Skevington et al., 2004). The World Health Organization developed both of these assessments for adults, so these quality-of-life assessments can only be used with individuals aged 18 years or older. Additionally, these assessments are only intended to be filled out by the individual themselves, not a parent or caregiver, so the individual filling out the assessment will need to be able to read and comprehend the questions independently. The World Health Organization’s quality-of-life assessments pose questions related to an individual’s positive feelings, their energy and fatigue, self-esteem, body image, activities of daily living, employment, personal relationships, social support, sexual activity, safety, home environment, financial resources, access to services, access to information, leisure activities, physical environment, access to transportation, and spirituality. In addition to the WHOQoL-100 and WHOQoL-BREF, an additional autism-specific supplement, the Autism Spectrum Quality of Life (ASQoL), has been created with nine additional autism-specific questions (McConachie et al., 2018). The nine autism-

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specific questions ask the autistic individual to think about their life in the last 2 weeks and rate each question. Topics of the autism-specific questions include: (a) if they feel that they have enough support from others to make important decisions, (b) if they can be themselves around people they know well, (c) how secure they feel financially, (d) if they have enough support to help deal with problems, (e) if they are satisfied with their current friendships, (f ) if they feel that there are barriers to accessing health services, (g) if sensory issues make it difficult to do things they like, (h) if there are barriers to their needs being met in official situations, and (i) if they are at ease with autism as an aspect of their identity. Information gathered via these assessments can help determine aspects where an individual may not feel as fulfilled or secure in adulthood and where more support can be provided to ensure a high quality of life.

Summary This is not a comprehensive description of the plethora of assessments that are used for individuals diagnosed with autism spectrum disorder. Rather, it is a description of the assessments most commonly used within the APM. These assessments are provided at intake (i.e., prior to the learner starting behavioral intervention) and then provided on a yearly basis. This is one way we can track the progress of the learner and ensure that their curriculum is appropriate.

References Abidin, R. R. (2012). Parenting stress index-short form (4th ed.). PAR Inc. Abidin, R., Flens, J. R., & Austin, W. G. (2006). The parenting stress index. In R. P. Archer (Ed.), Forensic uses of clinical assessment instruments (pp. 297–328). Lawrence Erlbaum Associates Publishers. Aman, M. G., & Singh, N. N. (1994). Aberrant behavior checklist. APA PsycTests. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Association. Constantino, J. N. (2012). Social responsiveness scale (2nd ed.). WPS Publish. Dunn, D. M. (2018). Peabody picture vocabulary test (5th ed.). Pearson. Gilliam, J. E. (2013). Gilliam autism rating scale (3rd ed.). Pearson. Gresham, F., & Elliott, S. N. (2008). Social skills improvement system. Pearson. Harrison, P., & Oakland, T. (2003). Adaptive behavior assessment system—Second edition. Harcourt Assessment. Lord, C., Rutter, M., DiLavore, P. C., Risi, S., Gotham, K., & Bishop, S. L. (2012). Autism diagnostic observation schedule (2nd ed.). Western Psychological Services. Martin, N. A., & Brownell, R. (2011). Expressive-one word picture vocabulary test (4th ed.). Pro Ed Inc.

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McConachie, H., Mason, D., Parr, J. R., Garland, D., Wilson, C., & Rodgers, J. (2018). Enhancing the validity of a quality of life measure for autistic people. Journal of Autism and Developmental Disorders, 48, 1596–1611. https://doi.org/10.1007/s10803-0173402-z. Mullen, E. M. (1995). Mullen scales of early learning. Pearson. Rutter, M., Couteur, A. L., & Lord, C. (2003). Autism diagnostic interview-revised. Western Psychological Services. Skevington, S. M., Lofty, M., & O’Connell, K. A. (2004). The world health organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL group. Quality of Life Research, 13(2), 299–310. Sparrow, S. S., Cicchetti, D. V., & Sauliner, C. A. (2016). Vineland adaptive behavior scales (3rd ed.). Pearson. Walker, H. M., & McConnell, S. R. (1985). Walker-McConnell scale of social competence and school adjustment. Singular Publishing Group. Wechsler, D. (2012). Wechsler preschool and primary scale of intelligence (4th ed.). Pearson. Wechsler, D. (2014). Wechsler intelligence scale for children (5th ed.). Pearson.

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CHAPTER 23

Curriculum assessment Contents Common curriculum assessments Verbal Behavior Milestones Assessments and Placement Program The Assessment of Basic Language and Learning Skills—Revised Essential for Living Brigance Inventory of Early Development III Eden Autism Assessment and curriculum series Psychoeducational Profile Revised—Third Edition Hawaii Early Learning Profile Autism Partnership Method and curricular assessment Who assesses curriculum? The curriculum process Factors in prioritizing curriculum Building the curriculum References

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For children diagnosed with autism spectrum disorder (ASD) to make meaningful progress, supervisors must ensure that they teach meaningful, functional, and applied skills. These skills must be comprehensive, targeting a wide range of areas including: (a) learning-how-to-learn, (b) social, (c) language, (d) adaptative, (e) academic, and (f ) play/leisure. To ensure an intervention is addressing these key areas, a curriculum assessment should be conducted. Deno (1987) defined a curriculum-based assessment “as any set of measurement activities that uses direct observation and recording of a student’s performance in the local curriculum as a basis for gathering information to make instructional decisions” (p. 41). Many of the curriculumbased assessments that currently exist are focused on identifying the strengths and weaknesses of the learner and lead directly to a preestablished curriculum (Nadjdowski et al., 2014; Rubin & Laurent, 2004). The goal of any curricular assessment should be the development of an individualized, meaningful curriculum for the learner. This individualized curriculum should include all the necessary goals to result in an improved overall quality of life. Today, many behavior analysts use a variety of different curricular assessments to help identify what targets to A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00029-5

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teach. In what follows, we describe a sample of norm-referenced and criterion-referenced assessments that are most commonly used. Some, but not all, are standardized, and it is important to understand the strengths and weaknesses of each type of instrument. Although there is often overlap, each assessment covers a different combination of skill areas and can be helpful in identifying areas of strength and skills that may need remediation. It should be recognized that identified skill deficits do not automatically translate into high-priority treatment goals, nor should it be assumed that one single instrument will uncover all important areas of need. Therefore, assessment instruments should not be used in a prescriptive manner and should be used in conjunction with other assessment tools and methods and require the use of clinical judgment to prioritize treatment objectives.

Common curriculum assessments Verbal Behavior Milestones Assessments and Placement Program The Verbal Behavior Milestones Assessments and Placement Program (VB-MAPP) (Sundberg, 2008) is a criterion-referenced assessment that is based on the work of Skinner (1957). The VB-MAPP consists of five different components. One of these components is the milestone assessment. The milestone assessment consists of 170 language milestones that Sundberg broke down into three developmental levels (i.e., 0–18 months, 18–30 months, and 30–48 months). The second component of the VB-MAPP is the Barriers Assessment which focuses on 24 different barriers that autistic children will face. These barriers include such things as prompt dependency, stereotypic behavior, and obsessive-compulsive disorder. The third component of the VB-MAPP is the Transition Assessment which consists of 18 areas that assess skills associated with transition to school so that the child can participate in the least restrictive educational environment. The fourth component is the Task Analysis and Supporting Skills. The final component is the Placement and Individualized Educational Placement (IEP) Goals which help clinicians develop meaningful IEP goals. This assessment is commonly used by supervisors and can be useful in providing curricular guidance. However, it can take from 3 to 10 h to administer depending on the developmental level of the child.

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The Assessment of Basic Language and Learning Skills— Revised Another assessment that is based on the work of Skinner (1957) is the Assessment of Basic Language and Learning Skills—Revised (ABLLS-R) (Partington, 2006). The ABLLS-R is an assessment designed to help identify language, self-help, academic, and motor delays of children with developmental or language delays. The ABLLS-R is also a criterion-referenced assessment tool. The ABLLS-R consists of 25 skill sets with over 500 items as part of the assessment. The assessment includes a variety of behaviors including social skills, language, and school readiness skills. Conducting the ABLLS-R assessment can be laborious, taking up to 14 h to administer and should be readministered on at least a yearly basis.

Essential for Living Essential for Living (McGreevy et al., 2014) is an assessment and a curriculum that examines a wide variety of functional skills including communication, daily living skills, leisure skills, vocational skills, and functional academic skills. Essential for Living is an assessment and a curriculum but is not age or grade referenced, but, rather, is criterion referenced. The assessment can be used for children and adults diagnosed with ASD, but the assessment and curriculum are more relevant to children and adults with significant levels of impairment. Essential for Living has over 3000 skills across the domains of what is referred to as the essential eight skills. These skills include: (a) making requests, (b) waiting after making a request, (c) accepting removals (e.g., transitions, sharing, taking turns), (d) completing required tasks, (e) accepting “no,” (f ) following directions around health and safety, (g) completing daily living skills related to health and safety, and (h) tolerating skills surrounding health and safety. McGreevy and colleagues identify these sets of skills as “must-haves” and the curriculum guides interventionists to develop these skills.

Brigance Inventory of Early Development III Another curriculum-based assessment is the Brigance Inventory of Early Development (IED) III (Brigance & French, 2013). The assessment is criterion referenced and focuses on a child’s strengths (e.g., a learner’s current skills) and areas of need. The assessment was developed to align with Common Core Standards to meet the Individuals with Disabilities Education Act

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(IDEA) requirements so it can be used to help develop and plan instruction and develop individuated education plan (IEP) goals. The Brigance IED III is comprised of 55 items across key skill areas such as: (a) physical development, (b) language development, (c) literacy, (d) mathematics and science, (e) daily living, and (f ) social and emotional development. The assessment can be used for learners up to 7 years and 11 months of age; the assessment takes up to 1 h to administer. The assessment also includes the Brigance Readiness Activities Inventory, which is a manual that includes 300 activities for teaching the learner the needed skills.

Eden Autism Assessment and curriculum series Another assessment that can be used for learners diagnosed with ASD is the Eden Autism Assessment (Eden Autism Services, 2013). This assessment is meant for individuals as young as Pre-K and as old as 12th grade. The assessment is comprehensive in that it focuses on skills such as: (a) speech and language, (b) vocational education, (c) self-care and domestic skills, (d) cognition, and (e) physical education, recreation, and leisure. The purpose of the assessment is for the supervisor to create goals by identifying a learner’s strengths and weakness. In addition to the Eden Autism Assessment, there are corresponding curriculum books. The curriculum series is five volumes and addresses the needs of a child diagnosed with ASD in each skill area.

Psychoeducational Profile Revised—Third Edition Yet another assessment that can be used to help with the curriculum process is the Psychoeducational Profile Revised—Third Edition (PEP-3) (Schopler et al., 2005). The PEP-3 is a standardized and norm-referenced assessment. The assessment evaluates a learner’s communication, maladaptive behavior, and motor behavior. The assessment was designed for individuals diagnosed with autism who are between 2 and 7 years old. The PEP-3 consists of over 170 items. There are 10 subsets within the assessment which are: (a) cognition, (b) receptive language, (c) expressive language, (d) gross motor, (e) fine motor, (f ) imitation, (g) social reciprocity, (h) motor behaviors, (i) verbal behaviors, and (j) affective expression. The assessment consists of direct observation and a caregiver report, it can take up to 90 min to complete.

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Hawaii Early Learning Profile The Hawaii Early Learning Profile (HELP; Parks, 2006) curriculum assessment was developed based on a federally funded grant. The assessment is broken up for learners ages birth to three and then ages three to six. The assessment for children birth to 3 years of age consists of over 600 skills. It is broken into six different domains: (a) self-help, (b) fine motor, (c) gross motor, (d) social-emotional behavior, (e) cognition, and (f ) language. The assessment for children ages three to six has over 500 skills and uses the same six domains described above. These six domains are assembled into different developmentally sequenced strands.

Autism Partnership Method and curricular assessment It should be noted that there are many more curriculum assessments available that have not been discussed in this chapter. This was not meant to be an exhaustive list, but rather a sample of some commonly used curriculum assessments. The Autism Partnership Method (APM) for assessing curriculum needs is different from how many behavior analysts may determine curriculum. First, there is a reliance on standardized assessments that are norm-referenced and have demonstrated reliability and validity (e.g., Wechsler Intelligence Scale for Children, Vineland Adaptive Behavior Scales, Social Skills Improvement System, Social Responsiveness Scale) as a means of benchmarking progress over time. Many of the curriculum assessments used in this chapter are very unreliable for quantifying progress during intervention and have unknown measurement properties. Within the APM, they can serve as a resource for less experienced clinicians of potential areas of programming to consider. But they should not be used to automatically generate treatment objectives in a prescriptive one-formula-fits-all manner. Additionally, full implementation of many of these curriculum assessments requires an inordinate amount of time, and they cannot yield the level of comprehensiveness and individualization that is needed for each learner. Second, only practitioners who are trained specifically on curriculum should be the ones assessing and creating assessments (described later).

Who assesses curriculum? Not everyone is qualified to determine a learner’s curriculum. For a practitioner to be qualified they must have a thorough understanding of

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curricular goals across various domains (e.g., language, social, adaptative behavior). This means knowing the scope and sequence of targeted skills, and often requires a strong knowledge of developmental norms across the lifespan. The practitioner (usually a supervisor level behavior analyst) will also need to know how to interpret scores of standardized assessments as that data inform the development of curriculum. Additionally, the practitioner will need to know how to work with caregivers and learners compassionately and empathetically, which is especially important during the interview process. Finally, the practitioner must have a robust understanding of autism and how autism differs from neurotypical development.

The curriculum process It takes multiple steps to develop a curriculum plan for a learner. First, the family is provided with a variety of formal assessments. These assessments can include the Vineland, Social Skills Improvement System, Aberrant Behavior Checklist, Parenting Stress Index, Gilliam Autism Rating Scale, and Social Responsiveness Scale. Next, the interventionist should arrange a time for the learner to be observed to complete direct formal assessments. These assessments should measure cognition (e.g., Mullen Scale of Early Learning, Wechsler Intelligence Scale for Children) and language (e.g., Peabody Picture Vocabulary Test, Expressive One Word Test) they are used to assess the strengths and weakens of a learner and to track progress through the course of intervention. Third, the interventionist should arrange a time to interview the caregiver and learner if possible. In the interview, the interventionist should identify the family’s goals and priorities, and the strengths of the learner. Finally, the interventionist should identify opportunities to observe the client in their natural, everyday environments (e.g., home, school, community).

Factors in prioritizing curriculum Ensuring a learner has an individualized curriculum goes far beyond identifying their strengths and weaknesses. One consideration would be the preference of the caregivers. The caregivers might have important goals that they want their child to learn which would better improve the lives of their child or the whole family. Thus, it is important to target goals that the caregivers find important. However, there may be times that the caregiver may want to work on a goal that the interventionist may find is not a current priority. For example, parents may prioritize working on multiplication when a

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learner is struggling with making friendships or is engaging in dangerous challenging behavior. In these instances, it may be helpful to discuss with the parents why a certain skill, while important, may not be a priority at the time. A second consideration is the preference of the learners themselves. One of the hallmarks of our science is listening to our consumers (Wolf, 1978). As such the interventionist should seek out the client’s input to the extent possible. Like parents, sometimes the learner may not choose skills that are in their best interest or with knowledge of the long-term consequences of their behavior. For example, the learner may say they do not want to work on social skills but at the same time lacks understanding of the potential long-term negative consequences (e.g., depression, loneliness, suicide ideation). Thus, as helping professionals we may not be able to honor every learner request. Third, an interventionist should consider the age of the learner. This helps to select developmentally appropriate goals and age-appropriate goals. Fourth, the interventionist must consider cultural norms. Goals should be selected that are appropriate for the culture of which the learner is a member. Fifth, the interventionist should consider the skill level of the direct interventionist and the supervisor themselves. If the team is well trained and has a wide scope of competence (Brodhead et al., 2018) then more complex skills can be taught. If the team is less well trained, then simpler skills may need to be targeted while more staff training is conducted. The interventionist should also evaluate the strengths and weakness of the learner within specific skills (e.g., expressive labels) and within a domain (e.g., language). Thus, identifying a comprehensive list of skills that need to be taught. Finally, the interventionist should examine the rate of learning. If the learner acquires new skills at a quick rate, then more goals will need to be developed. Once all of this is done, it is important to consider which programs in the curriculum will be of a higher priority. This is to say that even though each program will be an important piece of the curriculum, there is limited amount of time in a day to teach all the necessary skills. A supervisor will need to make sure that interventionists know the priority of the programs to be targeted. To this point, whenever possible, it will be crucial that when designing the curriculum it does not become overly broad, but rather is focused. It is far better to target a smaller amount of behaviors efficiently and then move on to the next set, then to target multiple behaviors inefficiently.

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Building the curriculum This process should lead to the development of a meaningful and robust curriculum. The interventionist should draw from a variety of curriculum and curriculum assessments when developing goals and not rigidly adhere to only one curriculum assessment or book. Further, an interventionist may have to create their own programs for teaching certain skills. What follows in the remaining chapters is a description of some programs across different learning domains (e.g., language, social, learning how to learn). However, this book is not designed to be an exhaustive curriculum book, and we encourage the reader to seek out additional available resources.

References Brigance, A. H., & French, B. F. (2013). Brigance inventory for early development III (3rd ed.). Curriculum Associates. Brodhead, M. T., Quigley, S. P., & Wilczynski, S. M. (2018). A call for discussion about scope of competence in behavior analysis. Behavior Analysis in Practice, 11(4), 424–435. https://doi.org/10.1007/s40617-018-00303-8. Deno, S. L. (1987). Curriculum-based measurement. Teaching Exceptional Children, 20(1), 40–42. https://doi.org/10.1177/004005998702000109. Eden Autism Services. (2013). Eden autism services assessment and curriculum series. DRL Books. McGreevy, P., Fry, T., & Cornwall, C. (2014). Essential for living: A communication, behavior, and functional skills assessment, curriculum and teaching manual for children and adults with moderate-to-severe disabilities. DRL Books. Nadjdowski, A. C., Gould, E. R., Lanagan, T. M., & Bishop, M. R. (2014). Designing curriculum programs for children with autism. In J. Tarbox, D. R. Dixon, P. Sturmey, & J. L. Matson (Eds.), Handbook of early intervention for autism spectrum disorders: Research, policy, and practice (pp. 227–259). Springer. https://doi.org/10.1007/978-1-4939-04013_10. Parks, S. (2006). Hawaii early learning profile. Vort Corporation. Partington, J. W. (2006). Assessment of basic language and learning skills, revised. Partington Behavior Analysts. Rubin, E., & Laurent, A. (2004). Implementing a curriculum-based assessment to prioritize learning objectives in Asperger syndrome and high-functioning autism. Topics in Language Disorders, 24(4), 298–315. Schopler, E., Lansing, M. D., Reichler, R. J., & Marcus, L. M. (2005). Psychoeducational profile-revised (PEP-3). WPS Publishers. Skinner, B. F. (1957). Verbal behavior. Prentice-Hall. Sundberg, M. L. (2008). Verbal behavior milestones assessment and placement program: A language and social skills assessment program for children with autism or other developmental disabilities. AVB Press. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203.

CHAPTER 24

Learning-how-to-learn curriculum Contents The skills Establishing contingency Cooperation Attending Environmental awareness Returning reinforcers Reducing fidgeting Wait Learning from prompts Memory Observational learning Joint attention Summary References

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The goal of comprehensive behavioral intervention for individuals diagnosed with autism spectrum disorder (ASD) is to learn valuable skills that will lead to a higher quality of life and to become an active participant in the learning process. As part of a comprehensive curriculum, the Autism Partnership Method (APM) has identified a group of foundational skills that we have called learning-how-to-learn skills. Learning-how-to-learn skills can be defined as “skills that have a pivotal role in teaching students the process of learning. It is the foundation which enables them to acquire all other skills” (Leaf, McEachin, & Mountjoy, 2012, p. 20). These skills help the learner better participate in the learning process and accelerate learning of more advanced skills (e.g., matching, conversation, academic tasks) in the later stages of intervention. Within the APM, interventionists teach these skills from the outset, regardless of the learner’s age. Even before the Autism Partnership clinic was established, the importance of teaching what is now known as learning-how-to-learn skills was an essential part of comprehensive programming (e.g., Lovaas, 1981). Lovaas (1981) described three skills as getting ready to learn. These three skills were

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teaching a learner how to sit appropriately, sustain attention, and decrease disruptive behavior. Lovaas hypothesized that teaching these skills would make it easier to teach the learner other skills and would result in better outcomes. For over 30 years, the APM has fine-tuned and evolved our understanding of learning-how-to-learn skills. Our clinical data have shown that when learning-how-to-learn skills are emphasized early during intervention, learners achieve better outcomes than when it is not a major component of intervention (Leaf et al., 2011). As such, the importance of learning-how-to-learn skills has been disseminated in curriculum books (Leaf, McEachin, & Mountjoy, 2012), workshops (Leaf, Taubman, et al., 2012), and other trainings. This chapter provides an overview of different learning-how-to-learn skills and ways in which to teach learning-howto-learn skills to children with autism. As this is not a curriculum book, and is not meant to be an exhaustive overview, we encourage our readers to refer to other materials that may provide more detailed information about learning-how-to-learn curriculum and skills (e.g., Leaf, McEachin, & Mountjoy, 2012). Readers should take these as examples of a progressive approach to establishing foundational skills. It is intended to serve as inspiration for the process and not meant to be the final product. As we have said before, we think of this as a work in progress.

The skills Establishing contingency Within the APM, the learner will contact many different contingency systems. Although a learner does not need to understand or comprehend contingencies for reinforcement to be effective, understanding contingencies can help facilitate learning. Teaching contingency (i.e., learning from feedback) can help the learner to: (a) change their response based on feedback, (b) better understand the relationship between their behavior and the contingent consequences, (c) escape from nondesired situations (e.g., ask for a break, alternative ways to attain free time), and (d) improve joint attention. Prior to starting the program, the interventionist should create a work area and a reinforcer area. The interventionist should also create a token board to help teach contingencies. The interventionist should start by placing the learner in the reinforcement area to play. The interventionist should then have a full token board prepared. The interventionist should give verbal instructions to go and sit down and guide the learner to the table if necessary. The second that the learner sits in the chair, the interventionist should help the learner hand over

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the completed token board and the learner then goes back to the reinforcement area for a brief period and the procedure is continued. Once the learner is reliably handing over the completed token board, then the interventionist can remove a token. Now when the learner comes to the table, the token is provided (not contingent on any specific behavior) and the learner then hands over the token board. In this phase, the learner is being taught the contingency that a full token board means that they hand it over and can go play, while a token board with a token missing means they need to wait. This process is continued, removing one token at a time, until a few tokens can be off of the board. The learner would then wait for them to be put on (still not contingent on any behavior) and then hand over the board when the token board is filled; if possible, the learner here can also indicate that they know they have finished earning their tokens (e.g., saying “all done”). The learner will be ready to move to the next phase when they are waiting for the token board to be filled, handing over the token board independently, and moving toward their reinforcement area without prompting. The next phase of the program is for the learner to not only sit in the chair, but also sit in the chair calmly, prior to earning the token. The third phase of the program is to start placing simple known demands (e.g., receptive instructions) that the learner needs to follow to earn a token in conjunction with sitting and remaining calm. It is important here that the tokens remain contingent on the behavior of sitting calmly and not the following of simple known demands. Initially, only one instruction should be provided for each token, but this schedule should be thinned out as the client demonstrates success and understanding of the contingencies. Once the learner is reliably waiting for their tokens prior to handing over the token board, sitting calmly, and following the known instructions, and leaving the chair to go to the reinforcement area, the interventionist can feel confident that they understand this contingency and continue on with more learning-how-to-learn curriculum.

Cooperation It is important for learners to cooperate with instructions from relevant adults (e.g., parents, teachers). Following instructions is necessary to make the learning process efficient, maintain a reasonable amount of order, ensure that steps of an activity are carried out in the correct sequence, keep learners out of dangerous situations and help ensure that the learner will be successful within the community. Obviously, as the learner engages in more cooperation, it is the responsibility of the interventionist to teach the difference

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between requests that should be honored (i.e., safe) and requests that should not be honored (i.e., exploitative). Recently, there have been some calls to not target cooperation. The argument is that insisting on compliance with requests can lead to a decrease in personal autonomy and blind obedience to others. Although those are considerations that should inform how to approach targeting cooperation, cooperation is a critical skill when learners are young when it comes to safety, health, and quality of life. To be successful in school, activities, or life one needs to be cooperative with teachers, coaches or aides, and relationship partners. Interventionists should teach learners to discriminate between adults that are safe and not safe and instructions that are safe and not safe when it comes to cooperation. When teaching cooperation, interventionists should also teach appropriate protests and appropriate noncompliance (i.e., assertiveness) and that has always been part of the APM. Prior to teaching cooperation skills, the interventionist should create a hierarchy (see Fig. 1) of requests that are more likely to be followed vs requests that are less likely to be followed. When initially teaching Highly Likely to Follow

Somewhat Likely to Follow

Fig. 1 Cooperation with requests hierarchy form.

Unlikely to Follow

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cooperation, the interventionist should start with a request that the learner is most likely going to follow. For example, telling the learner to eat a cookie. Once the learner cooperates and engages in the action that corresponds to the instruction, the interventionist should provide the learner with reinforcement. As the learner cooperates with more requests, the interventionist should move up the hierarchy to instructions that the learner is less likely to engage in (e.g., clean up toys).

Attending Every learner, regardless of diagnosis, must develop skills related to attending. This means attending to the relevant visual and auditory stimuli in the environment—especially during instructional time. It is important to note that attending does not only mean eye contact. Although eye contact is an important skill across many cultures in certain contexts, attending goes far beyond just eye contact. Thus, when we teach attending, we are not doing so with archaic procedures like a “look at me” program (e.g., Lovaas, 1981) or with physically orientating a person to make eye contact. Rather, we teach visual and auditory attending with dynamic and progressive programming. It is also important to note that throughout our time in the field, we have heard many people make comments such as, autistic children attend better visually so we do not really work on auditory attending, this is even more of a reason to work on attending via both modalities. The learners we work with must become good visual and auditory attenders. Shaping visual attending One way to increase visual attending is through shaping (Cihon, 2022; Peterson, 2000). Shaping refers to a reciprocal process between the interventionist and the learner during which the interventionist assesses the learner’s behavior and provides a consequence based on that assessment. Generally, responses that are progressing toward the terminal goal are candidates for reinforcement. Within the APM, we avoid using antecedent cues because the goal is to increase the rate of looking as a free operant. When using this approach to develop visual attending, the interventionist may provide reinforcement when the learner orients any part of their face or body toward the interventionist. Visual attending can be targeted in isolation or can be embedded within trials targeting other simple responses (e.g., vocal imitation or matching). Token reinforcers work well when targeting this behavior as they allow rapid delivery of reinforcement. For many students, looking at the instructor is not an easily discriminable behavior, and they are more

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likely to have success after having sufficient previous experience with other simple contingencies (e.g., drop a block in a bucket). Across the shaping process, the interventionist will assess the learner’s responding and provide differential consequences to shape responding toward the terminal goal of visual attending (e.g., longer durations, shorter latencies). Shell game The shell game is a program that targets visual attending. In the shell game, the interventionist takes some identical cups and flips them upside down on the table. The interventionist then places a small, preferred item (e.g., toy, piece of food, token) under one of the cups in view of the learner. Next, the interventionist moves one or more of the cups and asks the learner to select the cup where the item is located. If the learner chooses the correct cup, they get the item under the cup. Over time, the interventionist can increase the complexity of this task in several ways to continue advancing visual attending skills. First, more cups can be added, which requires the learner to attend to and scan a larger field. Second, two cups can be moved simultaneously, the cups can be rotated using more moves or greater speed to ensure the learner is attending the whole duration. Third, the interventionist hides the item without the learner seeing where it is placed and have a confederate first choose the wrong cup to target deductive reasoning through visual attending. Each of these changes, as well as others not mentioned here, help develop important skills such as visual attending, scanning, tracking, avoiding distractions, and deductive reasoning. Slapjack Slapjack is an instructional game that targets visual and auditory attending and is commonly used as part of the APM. The core of slapjack is based on the common card game in which the goal is to win all the cards in a deck by being first to slap each jack as it is played to the center. When used as an instructional game, the interventionist gives the learner an item (e.g., picture, object) to hold. Meanwhile, the interventionist will hold other items, at least one of which is the same as what the learner is holding. The interventionist will then put one item down at a time. The goal is that the learner puts down their item (i.e., matches) when the interventionist puts down the same item. The learner should not place their card/picture down until there is an identical match. Throughout the process, the interventionist should provide reinforcement when the learner correctly matches the picture and when

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they wait and do not match when the sample pictures do not match. Over time, the interventionist should move at a faster pace to help increase the learner’s attending behavior. The interventionist should increase the difficulty of this program as the learner progresses. First, the interventionist could provide multiple cards for the learner to match. Thus, increasing the number of stimuli to which the learner must attend. Second, the interventionist can move from matching identical cards to matching nonidentical cards, requiring the learner to pay closer attention to the pictures. Secret word Secret word is an instructional program that targets auditory attending and can be conducted in one-to-one instructional and classroom settings. Within this program, the interventionist informs the learner that there will be a secret word for the session, day, or during an activity (e.g., “train”) and anytime that the interventionist says the secret word, the learner should engage in a certain action (e.g., ringing a bell, clapping their hands). If the learner does the correct action when the secret word is said, then the interventionist provides reinforcement. There are several phases within this program. The interventionist may begin by saying the secret word very often with a limited number of other words (i.e., distractors). For example, if “train” is the secret word, the interventionist may begin by saying “train, train, train, apple, train, train, apple, train.” Note that the pause after “train” should be no longer than the pause following “apple” and the intonation should not be different across the words. The number and frequency of distractors is an important variable to consider as the more distractors presented together, the longer the learner must attend. The interventionist can also advance to saying the secret word in the context of shorter sentences and work toward paragraphs, a book, or a long series of instructions. Finally, the interventionist can incorporate the secret word throughout the day or for longer periods of time. It is important to consider the typical “chatter” that the learner may contact and use that as the goal of this phase.

Environmental awareness Environmental awareness is a program that targets: (a) increasing awareness of the environment, (b) improving motor coordination, (c) developing problem-solving skills, (d) increasing safety, and (e) developing social awareness. Within this program, the interventionist may create an obstacle course that the learner must navigate by going over, around, and under various

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obstacles. If the learner can navigate the environment without knocking anything over, then reinforcement is provided. If the learner knocks over any part of the obstacle course, they will start over again. There are numerous phases within this program. First, the interventionist should establish how the learner is going to access reinforcement (e.g., crossing the finish line). Second, the interventionist should systematically increase the number of obstacles that the learner must navigate through. Third, the interventionist can systematically increase the length of the course. Finally, the interventionist works toward generalized awareness by having a longer series of trials where there are no obstacles and arranges from time to time to have an obstacle present where there recently was no obstacle. This eventually becomes the “always be on the lookout for obstacles” program.

Returning reinforcers One issue that occurs frequently throughout intervention and teaching sessions is that a learner engages in challenging behavior when they are requested to return a reinforcer or terminate a preferred activity. We hypothesize that this may occur when contingencies are ambiguous, and the learner is unclear how they will gain access to the item again. Thus, an interventionist should specifically teach how to return reinforcers and preferred items as part of comprehensive programing. Doing so may help the learner: (a) tolerate giving back preferred items, (b) understand that reinforcement will soon become available again, and (c) increase reciprocity. The interventionist needs to prepare and select the appropriate time to target the development of this skill. Before the interventionist instructs the learner to put the item down or give the item to the interventionist, they should place their hand on the item. Then, in a calm voice, the interventionist should declare “time’s up” (or similar phrase) while gently taking ownership of the item. The interventionist should immediately praise the child for giving back the toy. Initially the interventionist only keeps it for a very brief time, then returns the item to the child regardless of the occurrence of challenging behaviors. The goal is that this should occur quickly enough that the child does not have time to react intensely. It can help make the temporary unavailability of the item more tolerable if the interventionist gives a simple cue in advance (e.g., “one more time” or “almost done”). This continues until the learner relinquishes the stimuli without any challenging behavior. The interventionist should systematically increase the delay before giving the item back. This can progress to interspersing a brief activity

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during the time the learner does not have the item, initially with no expectation for the child to participate and eventually receiving the item back becomes contingent on participation and remaining calm.

Reducing fidgeting When a learner engages in excessive movement (e.g., motor stereotypy), it can interfere with the learning process (Koegel & Covert, 1972). As such, one program that we implement targets the reduction of excessive fidgeting. Working on reduced fidgeting can help the learner: (a) control their own behaviors, (b) learn to remain calm, and (c) help reduce behaviors that interfere with the learning process. The contingency is straightforward. The interventionist starts by waiting for the learner to demonstrate a behavior that is incompatible with fidgeting. Once the learner is not engaging in fidgeting and instead engaging in an incompatible behavior, the interventionist provides reinforcement. If the learner engages in excessive fidgeting, then the interventionist should gently prompt/correct the learner (e.g., placing the learner’s hands in their laps). This can be done using shaping, differential reinforcement, and prompting. It is essential to select a response that is very salient to the student (e.g., not grabbing at materials or not bouncing) so that the contingency is highly discriminable.

Wait One of the most important skills any learner can demonstrate is waiting. This skill is essential for situations where it is necessary to receive instructions before responding and to tolerate delay in accessing preferred items. Waiting is also an important safety skill (e.g., waiting at a crosswalk). A wait program has many goals for the learner including: (a) tolerating a delay, (b) reducing challenging behavior, (c) building behavioral control, and (d) enhancing communication. Prior to teaching, the interventionist should create a wait card (see Fig. 2). The wait card will be used as a visual cue that the learner must wait to receive an item. Additionally, the learner will exchange the wait card for the item for which they were waiting. The interventionist starts the wait program by tempting the learner to make a request. Once the learner makes the request, the interventionist hands the learner the wait card and tells them they need to wait. Next, the interventionist engages in some other activity for a short period of time. Once that time has concluded, the interventionist: (a) praises the learner for waiting, (b) has the learner hand over the wait card,

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Fig. 2 Wait card.

and (c) provides the learner with the item that they were waiting for. If at any point the learner engages in challenging behavior while waiting, then the interventionist should provide feedback to the learner (e.g., “remember you need to wait”) and then have more time elapse before having the waiting period end. If this contingency is difficult for the learner to understand, you may use a visual timer to show the learner how much time is left before the waiting period is over. However, we do believe it is best to start without the timer when possible, as learning to wait without the visual timer will lead to quicker generalization of this skill. A variation on this approach is to arrange in advance that the desired item is located at a distance from the student. When they ask for the item, the interventionist says, “Just wait here, I will get it for you.” The movement of the instructor toward the item is used to differentially reinforce the desired waiting response. When beginning the wait program, the interventionists should arrange brief periods (i.e., a few seconds) of time that the learner needs to wait. Ideally, the interventionist should start with lesser preferred items prior to starting with more preferred items as it will be easier for the learner to wait. The interventionist will systematically increase the amount of time that the learner must wait for the desired item. Additionally, during initial teaching, the interventionist should have the learner practice waiting free from any other demands. Once the learner has mastered waiting free from any other demands, the interventionist should systematically increase the number of demands presented during the wait period. The interventionist can do this by creating a hierarchy of low, moderate, and high demands, then systematically add in demands based on this hierarchy. Ultimately, the goal of the intervention is that the learner: (a) waits independently, (b) generalizes

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waiting across different people, (c) generalizes waiting across different settings, (d) waits in social situations, and (e) waits in the community.

Learning from prompts As described in the prompting chapter, there are a variety of prompt types that can be used within flexible prompt fading (Soluaga et al., 2008). These prompt types include, but are not limited to, reduction of the field, multiple alternative prompts (Leaf et al., 2016), gesture prompts (Anson et al., 2008), verbal prompts (Barnett et al., 2020), partial physical prompts (Schnell et al., 2020), and full physical prompts (Fletcher et al., 2003). It is important that learners can follow and learn from a variety of prompt types. In other words, a learner must be able to respond correctly when a prompt is provided. Thus, it is important to teach the learner how to respond to a variety of prompt types to expedite the learning process. To teach the learner how to respond to multiple prompt types, the interventionist can develop a procedure like a controlling prompt assessment (Leaf et al., 2010). In doing so, the interventionist presents an array of unknown targets. The interventionist then provides an instruction to find one of the targets and immediately provides one of the prompt types. When the learner touches the stimulus that corresponds with the instruction and the prompt, then interventionist provides reinforcement. If the learner does not touch the stimulus that corresponds with the instruction and the prompt, then corrective feedback is provided. The interventionist should provide multiple trials per prompt type until the learner is consistently responding correctly to a given prompt type. The interventionist should repeat this procedure for all prompt types that the learner may encounter during teaching.

Memory Memory matching Memory matching is a game that can be used to: (a) improve memory and recall, (b) increase sustained attention, (c) reduce off-task behavior, and (d) increase social interaction. This program is no different than many of the commercial memory games that can be purchased for children today. The main difference is in the systematic nature of how the game is introduced. The interventionist should start by placing a limited number of cards face down on the playing surface. Next, the interventionist would give the student a single card. The interventionist then would instruct the learner to match or find the match. The learner should then flip over the cards until a

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match is found. Once a match is found, then the interventionist should provide the learner with reinforcement. Once the learner understands this concept, then the interventionist can play memory as is typically played. This will help work on client recall and attending. Magic word Magic word is a program very similar to secret word (described above). Magic word helps the learner work on long-term recall. Within this program, the interventionist provides a word that the learner should remember. Ideally this word is something that is meaningful to the learner. After a brief period, the interventionist asks the learner to tell them what the word was. If the learner can recall the word, then reinforcement is provided. If they are unable to recall the word, then informative feedback should be provided. As the learner gets better at recalling the word, the delay between when the word is provided and expected recall should be gradually increased.

Observational learning Observational learning might be one of the most pivotal skills for any individual. Observational learning is anytime the learner acquires information that is not directly taught to them, but instead is acquired by observing others’ behavior as well as them receiving consequences for engaging or not engaging in certain behaviors (Plavnick and Hume, 2014). Research has shown that individuals diagnosed with ASD often have impairments in observational learning (Taylor & DeQuinzio, 2012) and that these impairments can have a negative impact on learning new skills (Taylor & DeQuinzio, 2012). Thus, observational learning has been a core program in behavioral intervention for numerous years (Lovaas, 1981). There are many advantages to teaching observational learning including: (a) learning to attend to others without direct instruction, (b) acquiring concepts and information by listening and watching, (c) learning from more natural teaching, (d) developing social skills, (e) making group instruction more productive, (f ) developing awareness and attending skills, (g) developing retention, and (h) improving waiting. To teach observational learning, a group instructional format is recommended. The interventionist should ask one learner in the group to either engage in a behavior or answer a question. If they engage in the behavior or answer the question correctly, the interventionist provides reinforcement. After a short delay, the interventionist provides the same instruction to a different learner to see if they respond correctly. Throughout, it is imperative that the interventionist does

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Table 1 Observational learning phases. Phase

Description of the phase

1 2 3 4 5 6 7 8

Gets information about desired behavior from model Gets verbal information from the model Choral Nonverbal Imitation Do That Shell Game Choral Verbal Responses I Do/Not Me In a group setting ask learner questions that required observation of a group member Every member of the group makes a statement about themselves Information acquisition-verbal Listen to incidental information Information acquisition-observation of activity Detects incorrect answer or information Show accomplice a picture, without learner being able to see the picture Choral group instruction Shell game-deductive reasoning Drawing inferences-verbal Drawing inferences-observation of activity Ask learner to describe peer’s interests

9 10 11 12 13 14 15 16 17 18 19

Modified from Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books.

not over prompt the learners to pay attention to each other. There are numerous phases of this program that have been detailed in other curriculum books (Leaf & McEachin, 1999). Table 1 provides a brief overview of the various phases that are a part of the observational learning programs.

Joint attention A final critical skill that is important for any learner to display is joint attention (Charman et al., 2003). Joint attention is a group of behaviors that occur in conjunction in which attention is shared between two people and an object or an event that occurred in the environment (Charman et al., 2003; Mundy & Crowson, 1997). There are generally two types of joint attention: a response to a joint attention bid or initiating a bid for joint attention. A response to a joint attention bid is when the learner responds to another person’s direction to orient toward an object or event in the environment (Bruinsma et al., 2004). A bid of joint attention is when the learner directs the other person to look at an object or event that is occurring in the

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Table 2 Joint attention. Phase

Description of the phase

1 2 3 4 5 6 7 8 9 10 11

Ask learner where object is Ask learner to give an object to a certain person Getting a person attention Showing off something that they have made Identifying where a person is pointing Identifying where a person is looking Identifying the direction of movement Identifying whether a person can hear Identifying whether person can see Identifying whether a person knows some information Do unusual things to get learner to respond

Modified from Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books.

environment and monitors where the other person is directing their attention. Researchers have demonstrated a correlation between joint attention and improvement in language, social behavior, and friendship development (Bruinsma, Koegel and Koegel, 2004; Charman et al., 2003; Lawton & Kasari, 2012). Joint attention usually develops before a typically developing child turns 1 year old (Mundy and Crowson, 1997). Researchers have demonstrated that individuals diagnosed with ASD have impairments in joint attention and, if it develops, it develops later (Charman et al., 2003). Given the importance of engaging in joint attention, it has been part of the curriculum for numerous years (Lovaas, 1981). Table 2 provides a brief overview of the various phases that are included in the joint attention programs.

Summary The learning-how-to-learn skills described above are critical to target because they lay the foundation for more independent and faster learning of the curriculum that follows in this book. It is important that the skills of attending (visual and auditory), recall, waiting, observational learning and more are skills that are well established. This might mean that the majority of the early curriculum in intervention is working almost solely on learning-how-to-learn skills. Although this might seem like a lot of time devoted to one domain of curriculum, it will help speed the learning process, and ultimately is worth the investment in time.

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References Anson, H. M., Todd, J. T., & Cassaretto, K. J. (2008). Replacing overt verbal and gestural prompts with unobtrusive covert tactile prompting for students with autism. Behavior Research Methods, 40(4), 1106–1110. https://doi.org/10.3758/BRM.40.4.1106. Barnett, M. R., Jowett Hirst, E. S., & Boydston, P. S. (2020). A comparison of simple versus elaborative verbal prompts on acquisition of picture associations. Behavior Analysis: Research and Practice, 20(1), 24–35. https://doi.org/10.1037/bar0000160. Bruinsma, Y., Koegel, R. L., & Koegel, L. K. (2004). Joint attention and children with autism: A review of the literature. Mental Retardation and Developmental Disabilities Research Reviews, 10(3), 169–175. https://doi.org/10.1002/mrdd.20036. Charman, T., Baron-Cohen, S., Swettenham, J., Baird, G., Drew, A., & Cox, A. (2003). Predicting language outcome in infants with autism and pervasive developmental disorder. International Journal of Language & Communication Disorders, 38(3), 265–285. https:// doi.org/10.1080/136820310000104830. Cihon, J. H. (2022). Shaping: A brief history, research overview, and recommendations. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & M. J. Weiss (Eds.), Handbook of applied behavior analysis interventions for autism (pp. 403–415). https://doi.org/10.1007/978-3-03096478-8_21. Fletcher, K. L., Huffman, L. F., & Bray, N. W. (2003). Effects of verbal and physical prompts on external strategy use in children with and without mild mental retardation. American Journal on Mental Retardation, 108(4), 245–256. https://doi.org/10.1352/0895-8017 (2003)1082.0.CO;2. Koegel, R. L., & Covert, A. (1972). The relationship of self-stimulation to learning in autistic children. Journal of Applied Behavior Analysis, 5(4), 381–387. https://doi.org/10.1901/ jaba.1972.5-381. Lawton, K., & Kasari, C. (2012). Teacher-implemented joint attention intervention: Pilot randomized controlled study for preschoolers with autism. Journal of Consulting and Clinical Psychology, 80(4), 687–693. https://doi.org/10.1037/a0028506. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, R., McEachin, J., & Mountjoy, T. (2012). A work in progress: Video series. Autism Partnership. Leaf, J. B., Sheldon, J. B., & Sherman, J. A. (2010). Comparison of simultaneous prompting and no-no prompting in two-choice discrimination learning with children with autism. Journal of Applied Behavior Analysis, 43(2), 215–228. https://doi.org/10.1901/ jaba.2010.43-215. Leaf, R. B., Taubman, M. T., McEachin, J., & Leaf, J. B. (2012). Teaching “learning to learn” skills to children diagnosed with an autism spectrum disorder (Workshop presentation). Seattle, WA: Association of Behavior Analysis International. Leaf, R. B., Taubman, M. T., McEachin, J. J., Leaf, J. B., & Tsuji, K. H. (2011). A program description of a community-based intensive behavioral intervention program for individuals with autism spectrum disorders. Education and Treatment of Children, 34(2), 259–285. Leaf, J. B., Townley-Cochran, D., Mitchell, E., Milne, C., Alcalay, A., Leaf, J., Leaf, R., Taubman, M., McEachin, J., & Oppenheim-Leaf, M. L. (2016). Evaluation of multiple-alternative prompts during tact training. Journal of Applied Behavior Analysis, 49(2), 399–404. https://doi.org/10.1002/jaba.289. Lovaas, O. I. (1981). Teaching developmentally disabled children: The me book (1st ed.). Pro-Ed. Mundy, P., & Crowson, M. (1997). Joint attention and early social communication: Implications for research on intervention with autism. Journal of Autism and Developmental Disorders, 27(6), 653–676. https://doi.org/10.1023/A:1025802832021.

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Peterson, G. B. (2000). The discovery of shaping: Bf skinner’s big surprise. The Clicker Journal: The Magazine for Animal Trainers, 43, 6–13. Plavnick, J. B., & Hume, K. A. (2014). Observational learning by individuals with autism: A review of teaching strategies. Autism, 18(4), 458–466. https://doi.org/ 10.1177/1362361312474373. Schnell, L. K., Vladescu, J. C., Kisamore, A. N., DeBar, R. M., Kahng, S., & Marano, K. (2020). Assessment to identify learner-specific prompt and prompt-fading procedures for children with autism spectrum disorder. Journal of Applied Behavior Analysis, 53(2), 1111–1129. https://doi.org/10.1002/jaba.623 (Spr 2020). Soluaga, D., Leaf, J. B., Taubman, M., McEachin, J., & Leaf, R. (2008). A comparison of flexible prompt fading and constant time delay for five children with autism. Research in Autism Spectrum Disorders, 2(4), 753–765. https://doi.org/10.1016/j. rasd.2008.03.005. Taylor, B. A., & DeQuinzio, J. A. (2012). Observational learning and children with autism. Behavior Modification, 36(3), 341–360. https://doi.org/10.1177/0145445512443981.

CHAPTER 25

Social skills curriculum Contents Reasons why we teach social skills Reasons why social skills development is often not a priority What to teach: The social skills taxonomy Social awareness Social communication Social interaction Social learning Social relatedness How to teach social behavior Reminder Summary References

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Autism spectrum disorder (ASD) is characterized by deficits in social communication and social interactions across multiple environments (American Psychiatric Association, 2013). There are many social behavior deficits that have been observed clinically and evaluated experimentally for individuals with autism. These deficits include social language (Tager-Flusberg, 1981), empathy (Song et al., 2019), executive functioning (Mason et al., 2021), play skills (Wing et al., 1977), emotional behavior (Baron-Cohen & Wheelwright, 2004), joint attention (Charman, 1998), social communication (Mundy & Crowson, 1997), self-regulation (Loveland, 2005), and not developing meaningful friendships or having friendships of lower quality (Bauminger & Shulman, 2003). Teaching social skills to autistic children is of extreme importance for several reasons.

Reasons why we teach social skills First, teaching social skills can help promote natural language which is of particular importance when it comes to how children speak to their peers. Second, researchers have shown that when children have social relationships and meaningful friendships, they tend to like school more and do better in school (Ladd et al., 1999). Unfortunately, many caregivers and educators put A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00028-3

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a high value on teaching academic skills or language development, sometimes at the expense of teaching social behavior. Given the research on the effects social behavior can have on language and academic skill development, it appears that ignoring social skills development may be counterproductive to these other goals. Third, we live in a social world. Engaging in social behaviors throughout the day helps us navigate this world. Whether it is how a person interacts during work, school, or in the community, every person, regardless of diagnosis, is likely required to engage in some level of social behavior on a daily basis. It is difficult to develop friendships and prosocial relationships without at least some appropriate social behavior. Appropriate social behaviors are often necessary to maintain effective relationships with peers, colleagues, and others we encounter in everyday life. If one does not respond to others, does not react to social cues, is a poor sport, or does not share, it is unlikely that peers will approve of their behavior. Simply put, we do not teach social behaviors like joint attention (e.g., Taylor & Hoch, 2008), changing the conversation when someone is bored (e.g., Leaf et al., 2012), or observational learning (DeQuinzio & Taylor, 2015) just to check it off a curriculum list. Rather, these skills are taught because they increase the likelihood that individuals will develop positive, prosocial relationships and, ultimately, meaningful friendships. These relationships can bring a new sense of love, joy, and happiness into our learners’ lives. Fourth, there are several demonstrated negative ramifications associated with a lack of friendships. For instance, research has shown that individuals diagnosed with ASD are often lonely (Bauminger et al., 2003) and depressed (e.g., Hurley, 2008). These negative outcomes could be related to the lack of social behavior and/or friendships. As behavior analysts, it is imperative that we do all we can to help avoid these negative outcomes for our learners. Further, the combination of a lack of prosocial relationships, loneliness, and depression can lead to even further dire outcomes (Mayes et al., 2013). For example, Mayes et al. (2013) found “suicide ideation or attempts to be 28 times greater in children with autism than in typical children” (p. 117). These are not the outcomes we want for any person, let alone our learners. Thus, this research further highlights the importance of teaching social behavior to individuals with autism. Ultimately, the goal of the Autism Partnership Method (APM) is to improve the overall quality of life for our learners. If we were to ask most caregivers what their ultimate goal is for their child, words like “happiness,” “joy,” “meaningful,” and “productive” would come up. These are the same

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goals of most, if not all, behavior analysts and professionals. We all want to ensure that our clients have a high quality of life. Within the APM, a core belief is that for children with autism to have a high quality of life we must make teaching social behavior a priority for our learners.

Reasons why social skills development is often not a priority Despite the compelling reasons for teaching social skills, there remains resistance from professionals, caregivers, and autism advocates to make teaching social behavior a top priority. This resistance, unfortunately, has come largely from professionals and caregivers. One reason for the resistance is the belief that it is against the nature of an autistic person to be social. But in the APM, we believe that a child cannot make an informed decision about the value of being socially proficient. Our goal is to provide them with useful tools (i.e., skills) so that when they become older, they will have the option of choosing whether and how to use those tools. To say that autistic individuals are just not social, and therefore one should not provide the opportunity to teach social behavior just becomes a self-fulfilling prophecy. While one diagnostic criterion for ASD is impairments in social behavior, that does not mean that the individual does not desire to be social or that they never will be social, it simply means they are currently not displaying appropriate social behavior as part of their everyday lives. A second reason why social behavior has not been prioritized as part of behavioral intervention is that there tends to be a focus on teaching and/or working on other behaviors that the learner might not be displaying. For example, within a comprehensive model of behavioral intervention, we typically see a large focus on language development (Sundberg & Michael, 2001), teaching academic skills (e.g., Stasolla et al., 2016), or reducing challenging behaviors (e.g., Wunderlich & Vollmer, 2015). Within the APM, increasing language development and functional academic skills is viewed as essential, but we believe that increasing social behavior should have equal priority as the other goals. Within the APM, when challenging behavior is interfering with learning or social opportunities, it is also essential that we address such challenging behavior. But even as we are building learninghow-learn skills, we take advantage of every opportunity to incorporate the foundations of social behavior (e.g., responsiveness to others, experiencing that activities can be more enjoyable when there is a social component).

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A rationale that is becoming more common for not addressing social behavior is that doing so will change the learner (Leaf et al., 2022). Many of these claims are being made by members of the neurodiversity movement (Leaf et al., 2022). The argument is that individuals diagnosed with ASD are neurodiverse and, as such, they have differences in how they experience the world, which results in the individuals thinking, behaving, and learning in different ways. Therefore, according to the argument, we should not see these differences as deficits, and therefore interventionists should not teach social behavior because it would be disrespectful of their individual differences. Furthermore, it is viewed as forcing the individual with autism to conform to societal norms (Devita-Raeburn, 2016), which would be seen as abusive. A guiding principle of the APM is that we individualize intervention. As such, interventionists understand that each learner is unique. The goal of intervention is for learners to reach adulthood being comfortable with who they are. Once they reach adulthood or have developed the repertoire to make informed decisions, then they can choose which social behaviors they want to display or not display. This does not mean, however, that teaching social behaviors should not occur. At the end of the day, interventionists are helping professionals. It is their job to help their learners to the best of their ability. Further, young children often are not aware of the positive or negative outcomes that can occur depending on their social behavior. Thus, they are not making well-informed decisions. Given the positive outcomes associated with teaching social behavior and the serious negative consequences when an individual does not engage in appropriate social behavior, it is the duty of interventionists to teach social behavior. A fourth rationale that has been used to not focus on improving social behavior is parents saying statements such as, “We are not social ourselves. Why does our child have to be?” While this may be true, it is not a valid rationale for not teaching social behaviors. Parents can make informed decisions. In other words, they know the consequences of not being social. If a parent chooses not to go out with their friends for a night and stay at home watching television, they are aware of what they have missed. Further, parents should understand the positive and negative consequences for missing social opportunities. Finally, although parents may elect not to engage in social opportunities, this does not mean that their children will want to make the same decisions. Perhaps one of the biggest reasons why there has been a resistance to teaching social behavior is that social behaviors are very difficult skills to teach. Social behavior is nuanced, and the context of any given situation will

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vary. Additionally, there are many components to any social behavior. For example, when teaching changing the game when a person is bored, there are several possible steps such as: (a) play the game, (b) recognize when someone is bored, (c) try and change the game, and (d) play the new game. However, it is more difficult than just these four steps. Recognizing when someone is bored is complex and how to respond to someone when they are bored is equally difficult. This example is just a basic skill, where more complex social behaviors (e.g., joining in, friendship development, handling rejection, asking someone out on a date) would have many more variables to consider. Further, there are many subtle discriminations when it comes to social behavior. For example, the discrimination between goofing around, teasing, and bullying is very complex. We consider the argument against targeting social skills to be shortsighted and continue to believe that improving social behavior will lead to more options and better quality of life for individuals with autism. That is why members of Autism Partnership and the Autism Partnership Foundation have long advocated for the importance of teaching social skills, and disseminated how to teach social skills, and what social skills to teach (e.g., Leaf, 2015; Leaf & Streff, 2009; Milne et al., 2015; Taubman et al., 2012). These dissemination efforts have occurred in workshops (e.g., Leaf & Streff, 2009; Taubman et al., 2012), conferences (e.g., Leaf, 2015; Milne et al., 2015), research articles (e.g., Ferguson et al., 2021), book chapters (e.g., Cihon et al., 2017), and curriculum books (e.g., Leaf, Milne, et al., 2020; Taubman et al., 2011). For the remainder of this chapter, a brief overview of social skills will be provided regarding social skills to teach and ways to teach these various social skills. This chapter and this book are not meant to be a comprehensive curriculum; we recommend readers contact additional sources for a more comprehensive curriculum (e.g., Leaf, Milne, et al., 2020; Taubman et al., 2011). Additionally, throughout this book, numerous chapters have been devoted to various teaching procedures; as such, we encourage the readers to contact those chapters for a more detailed description about how to teach social behavior.

What to teach: The social skills taxonomy For any individual to be socially adept, it requires hundreds and even thousands of social skills. As such, there is no one social curriculum that describes all the social programming that an autistic/individual diagnosed with ASD might need to be taught. There are, however, many curriculum books that

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provide a level of detail that can be helpful in determining what skills to teach learners (e.g., Leaf, Milne, et al., 2020; Taubman et al., 2011). Although there are several curriculum books, it is often difficult for interventionists to determine what to teach their learners and even more difficult to determine the appropriate sequence of skills to teach. Members of Autism Partnership ran into these same difficulties, in their clinical work and in consulting to schools and with other professionals. As such, in 2011 members of Autism Partnership created a Social Skills Taxonomy (Taubman et al., 2011). There were multiple reasons the social skills taxonomy was created. First, at the time, there was a limited number of curriculum books available on social behavior and this taxonomy provided professionals and caregivers with a valuable resource. Second, the taxonomy was used to provide professionals and caregivers a framework of how to target social behavior comprehensively. Third, the social skills taxonomy was used to provide additional targets to teach as part of a comprehensive intervention. Fourth, the social skills taxonomy was created to provide a scope and sequence of how to create a comprehensive intervention for social skills. The social skills taxonomy consists of five broad domains into which specific social behaviors fall. In each domain there are early, intermediate, and advanced social behaviors which allow professionals and caregivers to determine the appropriate sequence of social behaviors. It should be noted that behaviors in each domain are not mutually exclusive as some social behavior may fall into two or more domains. The five broad domains of the social skills taxonomy are: (a) social awareness, (b) social communication, (c) social interaction, (d) social learning, and (e) social relatedness.

Social awareness The first domain of the social skills taxonomy is Social Awareness. Social awareness is defined as “the discrimination and understanding of social cues” (Taubman et al., 2011, p. 95). This domain focuses on the learner’s recognition of social cues and general awareness of other people around the learner; it does not necessarily focus on the learner responding to the social cues observed. There are numerous social behaviors that fall into this domain including labeling emotions and receptive identification of family and friends of the learner. This domain also includes intermediate social behaviors such as understanding gestures or the impact that behavior has on others in the environment. The domain also includes more advanced skills such as inferences and perspective taking.

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Social communication The second domain of the social taxonomy is social communication. Social communication is defined as being concerned with the social aspects of communication. It involves all aspects of social communication—for example, verbal and nonverbal expression; what is said and how it is said; direct and implied conversation; figurative and literal speech; serious, sarcastic, and humorous statements; and tone, inflection, emphasis, and style (Taubman et al., 2011, p. 97). Others outside the field of behavior analysis might refer to this domain as pragmatic language. Ultimately, the social communication domain is concerned with social exchanges, such as conversation, and nonverbal aspects of communication. There are numerous social behaviors that fall into this domain including social skills such as expressive labeling or basic conversation. The domain also includes intermediate social behaviors such as interrupting or giving compliments. Advanced skills under the social communication domain may include being subtle and being persuasive.

Social interaction The third domain of the social taxonomy is social interaction. Social interaction is defined as skills that “go beyond the conversational aspect of social behavior to address the process passing between individuals. This area focuses on teaching the skills necessary to be successful in social interchanges” (Taubman et al., 2011, p. 99). The purpose of this domain is to improve the interactions between the learner and their peers. When learners are younger, the skills are more basic; however, as the learner ages, the skills get more sophisticated and nuanced. There are numerous social behaviors that fall into this domain, including basic social skills such as tolerating others in their environment and showing interest to others. Intermediate skills include social behavior such as helping others and negotiation, while more advanced skills include social problem solving and coping.

Social learning The fourth domain of the social skills taxonomy is social learning. Social learning can be defined as an area “concerned with a child’s ability to learn from and be influenced by his or her social environment” (Taubman et al., 2011, p. 101). Social learning could be further defined as “skills [that] involve direct acquisition of social competency from peers through a variety of avenues, including direct imitation (live and in the moment), video modeling, and learning from pictorial sources” (Taubman et al., 2011, p. 101).

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This domain includes social behaviors that improve an individual’s ability to learn social skills through everyday interactions. There are numerous social behaviors that fall into this domain including basic social skills such as social imitation and observational learning. Intermediate social behaviors include incidental learning and how to seek information in a group. Advanced skills include understanding group affiliation and social influences.

Social relatedness The final domain in the social skills taxonomy is social relatedness. Social relatedness is “concerned with the affective, connected, and relational aspect of social behaviors. It involves the intent and desire behind social interaction and the essence and true purpose (not just action) of social competency” (Taubman et al., 2011, p. 103). This domain includes social behaviors that focus on understanding how relationships develop and promoting friendship. This domain includes some of the most difficult skills to identify and teach. The domain is less about specific social behaviors and more about the meaning of socialness and prosocial relationships. There are numerous social behaviors that fall into this domain, including basic social skills such as the desire to be close to peers and establishing peers as reinforcers. Intermediate social behaviors in this domain include joint attention and friendship development. Advanced social skills in this domain include interpersonal reciprocity and compassion for others.

How to teach social behavior There is no one way to teach social behavior. Interventionists should feel free to use a wide variety of behavior analytic procedures when teaching social behavior. This entire book has been dedicated to describing different procedures/interventions that are used within the APM. Many of these procedures can and should be used to teach social behavior to individuals with autism. Interventions such as discrete trial teaching (Weiss et al., 2017), incidental teaching (Alai-Rosales et al., 2017), shaping (Fonger & Malott, 2019), behavioral skills training (Roberts et al., 2021), the Cool versus Not Cool procedure (Ferguson et al., 2021), the teaching interaction procedure (Cihon et al., 2017), and social skills groups (Leaf et al., 2017) are all well suited to teach a variety of social behaviors to children with autism. These procedures can be used alone or can be used in conjunction with each other. It is up to the interventionist to determine the most appropriate procedure

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based on the skill(s) that are being taught and the strengths and weaknesses of the learner. It is also important that interventionists not only implement procedures that are conceptually systematic with behavior analysis, but also that are empirically supported, evidence based, and are not pseudoscientific or antiscientific. Unfortunately, the field of autism is marred with hundreds of interventions that purport to improve social behavior; but many of these interventions have weak to no evidence to support their effectiveness (e.g., Social Stories; Leaf, Cihon, et al., 2020), some are considered pseudoscientific (e.g., Social Thinking; Leaf et al., 2018), and some are antiscientific (e.g., Facilitated Communication; Foster, 2019). Implementing these types of interventions will not only fail to increase social behavior but also can be harmful for the learner, or at the very least, waste precious time that could be used to greater advantage (e.g., Kassardjian et al., 2014).

Reminder After reading this chapter, we hope that you are excited to jump into the taxonomy and start planning the social curriculum for some of the learners you have. But do not forget that prior to teaching, and throughout teaching it is important to make sure that you are building the learners’ peers as reinforcing stimuli. If the learner does not see peers as fun, engaging, and a source of reinforcement, it is far less likely that they will engage in the social behaviors being taught, and the skills are less likely to generalize. There are many ways to make peers reinforcing. One way is to pair already preferred reinforcers with peers. For example, if a learner enjoys playing with a specific toy, you can make that toy only available when playing with peers. If the learner, you are working with does not enjoy certain activities, you can have a peer come and rescue them by inviting them to do something else. You can even have peers deliver the reinforcer to your learner. All of these and more are good ways to establish peers as reinforcing stimuli. This is a crucial step that is often overlooked, so make sure you plan ways to establish peers as a reinforcer prior to, during, and after teaching social skills.

Summary Individuals diagnosed with ASD have impairments in social behavior. It is critical that interventionists implementing the APM work on teaching social skills to all learners regardless of age and deficit. Doing so will mitigate serious

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negative consequences (e.g., depression) and can help promote a higher quality of life for our learners. Ultimately, teaching social behavior helps reach our goal of bringing happiness, fulfillment, and joy into our client’s lives.

References Alai-Rosales, S., Toussaint, K. A., & McGee, G. G. (2017). Incidental teaching: Happy progress. In J. B. Leaf (Ed.), Handbook of social skills and autism spectrum disorder: Assessment, curricula, and intervention (pp. 171–185). Springer International Publishing AG. https:// doi.org/10.1007/978-3-319-62995-7_11. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Author. Baron-Cohen, S., & Wheelwright, S. (2004). The empathy quotient: An investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. Journal of Autism and Developmental Disorders, 34(2), 163–175. https://doi.org/10.1023/ b:jadd.0000022607.19833.00. Bauminger, N., & Shulman, C. (2003). The development and maintenance of friendship in high-functioning children with autism: Maternal perceptions. Autism, 7(1), 81–97. https://doi.org/10.1177/1362361303007001007. Bauminger, N., Shulman, C., & Agam, G. (2003). Peer interaction and loneliness in highfunctioning children with autism. Journal of Autism and Developmental Disorders, 33(5), 489–507. https://doi.org/10.1023/a:1025827427901. Charman, T. (1998). Specifying the nature and course of the joint attention impairment in autism in the preschool years: Implications for diagnosis and intervention. Autism, 2(1), 61–79. https://doi.org/10.1177/1362361398021006. Cihon, J. H., Weinkauf, S. M., & Taubman, M. (2017). Using the teaching interaction procedure to teach social skills for individuals diagnosed with autism spectrum disorder. In J. B. Leaf (Ed.), Handbook of social skills and autism spectrum disorder: Assessment, curricula, and intervention (pp. 313–323). Springer International Publishing AG. https://doi.org/ 10.1007/978-3-319-62995-7_18. DeQuinzio, J. A., & Taylor, B. A. (2015). Teaching children with autism to discriminate the reinforcered and nonreinforced respones of others: Implications for observational learning. Journal of Applied Behavior Analysis, 48(1), 38–51. https://doi.org/10.1002/jaba.192. Devita-Raeburn, E. (2016). Is the most common therapy for autism cruel? The Atlantic. https:// www.theatlantic.com/health/archive/2016/08/aba-autism-controversy/495272/. Ferguson, J. L., Milne, C. M., Cihon, J. H., Leaf, J. B., McEachin, J., & Leaf, R. (2021). Using the teaching interaction procedure to train interventionists to implement the Cool versus Not Cool™ procedure. Behavioral Interventions, 36(1), 211–227. https://doi.org/ 10.1002/bin.1741. Fonger, A. M., & Malott, R. W. (2019). Using shaping to teach eye contact to children with autism spectrum disorder. Behavior Analysis in Practice, 12(1), 216–221. https://doi.org/ 10.1007/s40617-018-0245-9. Foster, C. A. (2019). Deej-a Vu: Documentary revisits facilitated communication pseudoscience. Behavioral Interventions, 34(4), 577–586. https://doi.org/10.1002/bin.1687. Hurley, A. D. N. (2008). Depression in adults with intellectual disability: Symptoms and challenging behavior. Journal of Intellectual Disabilities Research, 52(11), 905–916. https://doi.org/10.1111/j.1365-2788.2008.01113.x. Kassardjian, A., Leaf, J. B., Ravid, D., Leaf, J. A., Alcalay, A., Dale, S., Tsuji, K., Taubman, M., Leaf, R., McEachin, J., & Oppenheim-Leaf, M. L. (2014). Comparing the teaching interaction procedure to social stories: A replication study. Journal of Autism

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and Developmental Disorders, 44(9), 2329–2340. https://doi.org/10.1007/s10803-0142103-0. Ladd, G. W., Birch, S. H., & Buhs, E. S. (1999). Children’s social and scholastic lives in kindergarten: Related spheres of influence? Child Development, 70(6), 1373–1400. https:// doi.org/10.1111/1467-8624.00101. Leaf, J. B. (2015). A preliminary evaluation of a behaviorally based social skills group for young children diagnosed with autism spectrum disorder: A randomized control trial (Conference presentation). CITY, STATE, United States: Massachusetts Association for Behavior Analysis. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Milne, C. M., Leaf, R., & McEachin, J. (2020). Recommendations for behavior analysts regarding the implementation of Social Stories for individuals diagnosed with autism spectrum disorder. Behavioral Interventions, 35(4), 664–679. https://doi.org/10.1002/bin.1736. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Taubman, M., Leaf, R., & McEachin, J. (2018). Social thinking®, pseudoscientific, not empirically supported, and non-evidence based: A reply to Crooke and Winner. Behavior Analysis in Practice, 11(4), 456–466. https://doi. org/10.1007/s40617-018-0241-0. Leaf, J. B., Cihon, J. H., Leaf, R., McEachin, J., Liu, N., Russell, N., Unumb, L., Shapiro, S., & Khosrowshahi, D. (2022). Concerns about ABA-based intervention: An evaluation and recommendations. Journal of Autism and Developmental Disorders, 56(6), 2838–2853. https://doi.org/10.1007/s10803-021-05137-y. Leaf, J. B., Leaf, J. A., Milne, C., Taubman, M., Oppenheim-Leaf, M., Torres, N., TownleyCochran, D., Leaf, R., McEachin, J., & Yoder, P. (2017). An evaluation of a behaviorally based social skills group for individuals diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(2), 243–259. https://doi.org/10.1007/s10803016-2949-4. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The Autism Partnership Method: Social skills groups. Different Roads to Learning. Leaf, J. B., Oppenheim-Leaf, M. L., Call, N. A., Sheldon, J. B., Sherman, J. A., Taubman, M., McEachin, J., Dayharsh, J., & Leaf, R. (2012). Comparing the teaching interaction procedure to social stories for people with autism. Journal of Applied Behavior Analysis, 45(2), 281–298. https://doi.org/10.1901/jaba.2012.45-281. Leaf, J. B., & Streff, T. (2009). Teaching social skills using the teaching interaction procedure (Workshop presentation). In Northwest Missouri conference on Autism, St. Joseph, MO, USA. Loveland, K. A. (2005). Social-emotional impairment and self-regulation in autism spectrum disorders. In J. Nadel, & D. Muir (Eds.), Emotional development: Recent research advances (pp. 365–382). Oxford University Press. Mason, L. A., Zimiga, B. M., Anders-Jefferson, R., & Paap, K. R. (2021). Autism traits predict self-reported executive functioning deficits in everyday life and an aversion to exercise. Journal of Autism and Developmental Disorders, 51(8), 2725–2750. https://doi.org/ 10.1007/s10803-020-04741-8. Mayes, S. D., Gorman, A. A., Hillwig-Garcia, J., & Syed, E. (2013). Suicide ideation and attempts in children with autism. Research in Autism Spectrum Disorders, 7(1), 109–119. https://doi.org/10.1016/j.rasd.2012.07.009. Milne, C., Leaf, J. A., Townley-Cochran, D., Leaf, J. B., & Oppenheim-Leaf, M. (2015). Teaching social behaviors to individuals with autism: Within the context of a social skills group (Conference presentation). San Antonio, TX, USA: Association of Behavior Analysis International. Mundy, P., & Crowson, M. (1997). Joint attention and early social communication: Implications for research on intervention with autism. Journal of Autism & Developmental Disorders, 27(6), 653–676. https://doi.org/10.1023/a:1025802832021.

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Roberts, K., DeQuinzio, J. A., Taylor, B. A., & Petroski, J. (2021). Using behavioral skills training to teach interview skills to young adults with autism. Journal of Behavioral Education, 30(4), 664–683. https://doi.org/10.1007/s10864-020-09389-z. Song, Y., Nie, T., Shi, W., Zhao, X., & Yang, Y. (2019). Empathy impairment in individuals with autism spectrum conditions from a multidimensional perspective: A meta-analysis. Frontiers in Psychology, 10, 1902. https://doi.org/10.3389/fpsyg.2019.01902. Stasolla, F., Perilli, V., Boccasini, A., Caffo, A. O., Damiani, R., & Albano, V. (2016). Enhancing academic performance of three boys with autism spectrum disorders and intellectual disabilities through a computer-based program. Life Span and Disability, 19(2), 153–183. Sundberg, M. L., & Michael, J. (2001). The benefits of Skinner’s analysis of verbal behavior for children with autism. Behavior Modification, 25(5), 698–724. https://doi.org/ 10.1177/0145445501255003. Tager-Flusberg, H. (1981). On the nature of linguistic functioning in early infantile autism. Journal of Autism and Developmental Disorders, 11(1), 45–56. https://doi.org/10.1007/ BF01531340. Taubman, M., Leaf, R., & McEachin, J. (2011). Crafting connections: Contemporary applied behavior analysis for enriching the social lives of persons with autism spectrum disorder. DRL Books. Taubman, M. T., Leaf, R. B., McEachin, J., & Leaf, J. B. (2012). Teaching social skills that change lives: Developing meaningful relationships for people diagnosed with autism [Workshop presentation]. Seattle, WA, USA: Association of Behavior Analysis International. Taylor, B. A., & Hoch, H. (2008). Teaching children with autism to respond to and initiate bids for joint attention. Journal of Applied Behavior Analysis, 41(3), 377–391. https://doi. org/10.1901/jaba.2008.41-377. Weiss, M. J., Hilton, J., & Russo, S. (2017). Discrete trial teaching and social skill training: Don’t throw the baby out with the bathwater. In J. B. Leaf (Ed.), Handbook of social skills and autism spectrum disorder: Assessment, curricula, and intervention (pp. 155–169). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-62995-7_10. Wing, L., Gould, J., Yeates, S. R., & Brierley, L. M. (1977). Symbolic play in severely mentally retarded and in autistic children. Journal of Child Psychology and Psychiatry, 18(2), 167–178. https://doi.org/10.1111/j.1469-7610.1977.tb00426.x. Wunderlich, K. L., & Vollmer, T. R. (2015). Data analysis of response interruption and redirection as treatment for vocal stereotypy. Journal of Applied Behavior Analysis, 48(4), 749–764. https://doi.org/10.1002/jaba.227.

CHAPTER 26

Language curriculum Contents Language programs Nonverbal imitation Matching Receptive instructions Receptive labels Communication temptations Verbal imitation Expressive labels Expanding language Pronouns Basic conversation Intermediate conversation Advanced conversation Auditory attending Finding the Message in the Chatter Keep it interesting Follow the conversation thread Conversation: Movers and stoppers Proper skepticism Summary References

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A hallmark characteristic of autism spectrum disorder (ASD) is impairments in social communication and language (Whitehouse et al., 2008). In fact, researchers have reported that 35%–50% of individuals diagnosed with ASD do not develop communicative skills and functional language without intensive early intervention (Mesibov et al., 1997; Rutter, 1978; Volkmar & Klin, 1994). Researchers have also shown that autistic individuals also display echolalia (e.g., van Santen et al., 2013), ritualistic language (e.g., TagerFlusberg, 1981), and difficulty engaging in pragmatic language (Cardillo et al., 2021). Language is important for a variety of reasons. Language can help a learner indicate their desires and needs (e.g., requesting materials, toys, food, drinks), express thoughts and feelings (e.g., saying “I love you”), or communicate with their family or peers. Additionally, research A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00031-3

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has shown a correlation between the use of functional language and positive outcomes for individuals with autism (Venter et al., 1992). Further, delayed speech development is often one of the first indicators of a “problem” for caregivers and an area that is often a top priority to address (Kurita, 1985). As such, working on improving language is often a top priority in comprehensive intervention for autistic children. Although some might assume that language is best left to be handled by a speech language pathologist, behavior analysts have an extensive history of developing, shaping, and improving communication and language skills with a variety of populations, including those with an autism diagnosis. Within the field of applied behavior analysis (ABA), there have been many methods developed and used to help improve language for individuals diagnosed with autism, including discrete trial teaching (DTT; Flores and Ganz, 2014), shaping (Ghaemmaghami et al., 2018), video modeling (Maione and Mirenda, 2006), script fading (Topuz & Ulke-Kurkcuoglu, 2022), and prompting (Finke et al., 2017). Depending on the needs of the individual, there are also various communication modalities that can be used, including the Picture Exchange Communication System (PECS; Bondy & Frost, 2011), Augmentative and Alternative Communication Devices (AAC; White et al., 2021), and sign language (Bonvillian et al., 1981). Within the field of ABA, approaches to developing communication and language skills are commonly based on the work of Lovaas (1977) and B. F. Skinner (Sundberg & Michael, 2001). Within the Autism Partnership Method (APM), communication and language development are one of the top priorities for our learners. Although some learners require alternative modes of communication via PECS or AAC devices, many of our learners are able to successfully communicate through vocal-verbal language. The development of vocal-verbal language is the ultimate goal because it is generally the most effective and is how the majority of the population communicates. This is accomplished using a variety of behavior analytic interventions and through a variety of programs. Occasionally, an interventionist/supervisor will collaborate with speech language pathologists, and sometimes, the intervention is solely developed by the interventionist/supervisor. The APM is heavily influenced by the foundational work on language development conducted by Lovaas (1977). These interventions have been well documented within empirical research (e.g., Garvey et al., 2022; Leaf et al., 2014; Leaf, Cihon, et al., 2020; Wong et al., 2020) and have been disseminated in curriculum books (Leaf et al., 2018; Leaf & McEachin, 1999) and other training materials (Leaf, Milne, et al., 2020). As such, this chapter provides a brief overview of the

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different types of programming that can be implemented to improve language. This overview is not meant to be comprehensive, and the programming is ever evolving; it is encouraged that interventionists contact a variety of published curricula and books (e.g., Leaf et al., 2018; Leaf & McEachin, 1999) and, more importantly, customize the language curriculum to meet the individual needs of their learners.

Language programs Nonverbal imitation A foundational program used to prepare children for participating in language development is nonverbal imitation (see Leaf & McEachin, 1999, p. 153). Although this program does not require any language output from the learner, it helps to build the foundations of which language curriculum will be targeted going forward. The goal of this program is for the learner to imitate the actions (e.g., throw a ball, bang a drum, roll a car) of the interventionist. By doing so, the learner can begin to develop an imitative repertoire of the actions of others, which is a precursor to imitating sounds and/ or words. There are no prerequisite language skills to this program and is appropriate for early learners. The objectives of the program are: (a) learn to imitate the interventionist, (b) build a positive relationship between the learner and the interventionist, (c) build responsiveness to others, (d) improve attending, (e) establish a means of teaching more advance skills (e.g., through modeling), and (f ) lay the foundation for observational learning. Leaf and McEachin (1999) identified 13 different phases of this program which is typically taught using DTT.

Matching Matching is a second foundational program used to develop conditional discrimination skills. Matching and nonverbal imitation do not require language skills and are therefore the curriculum entry point for virtually all learners (see Leaf & McEachin, 1999, p. 165). The goal of this program is for the learner to match two or more stimuli (e.g., pictures, objects, sounds). For example, starting with matching a picture of identical dogs and then moving to matching a picture of a Doberman to a picture of a Husky. Leaf and McEachin (1999) identified prerequisites for this program to include attending, sitting for short durations of time, and the ability to hold objects. The objectives of the program are: (a) learn to put similar items together,

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(b) increase attending, (c) develop symbolic representation, (d) develop skills that can be used in play, and (e) establish an early foundation for receptive and expressive language. Leaf and McEachin outlined 20 different phases of this program. This program is typically taught using DTT.

Receptive instructions For many learners, the entry into language curriculum is receptive instructions (see Leaf & McEachin, 1999, p. 189). The goal of this program is for the learner to follow directions that are provided by the interventionist. Leaf and McEachin (1999) suggested that a learner should display some level of imitation before starting this program, as imitation can be used as a prompt throughout the program. The objectives of this program are to: (a) increase a learner’s understanding of language, (b) help establish appropriate listening, (c) improve instructional control, (d) help learning occur in the natural environment, (e) improve attending, (f ) improve memory, and (g) improve independence. Leaf and McEachin identified 12 different phases of the program which is typically taught using DTT.

Receptive labels Similar to receptive instructions, receptive labeling is used to advance listening skills (see Leaf & McEachin, 1999, p. 193). The goal of this program is for the learner to hear a word and find the corresponding item or picture. Leaf and McEachin (1999) have recommended that the learner should be able to imitate and match prior to starting the program. The objectives of the program are to: (a) learn the labels of different objects, activities, or concepts; (b) develop abstract reasoning; (c) improve attending; and (d) establish the meaning of words as a foundation for expressive labeling. As with all programming, it is important that meaningful targets are selected for the receptive labels programming. Even though these are early language skills, the targets selected are important. It is far better to have the targets be meaningful for the learner (e.g., park, goldfish, daddy) than selected because it comes from a prefabricated list (e.g., umbrella, bowl, pineapple). Leaf and McEachin identified 17 different phases of the program which is typically taught using DTT.

Communication temptations A program that is often the entry into vocal language is communication temptations (see Leaf & McEachin, 1999, p. 199). The goal of this program

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is for the learner to request items or actions. Followers of B. F. Skinner’s analysis of verbal behavior (e.g., Sundberg & Partington, 1998) refer to this as mand training. However, for many caregivers and teachers with limited technical knowledge, the term “Communication Temptations” can be more user friendly and intuitive. We adopted this term from Wetherby and Prizant (1989). As an example, an interventionist might begin pushing a child on a swing and modeling a simple phrase like, “Push.” Then, the interventionist pauses the swing and waits for the learner to repeat the phrase before pushing the child on the swing again. There are no prerequisites to this program nor are there any phases. Rather, the interventionist should determine ways to arrange tempting situations for the learner to communicate throughout the day. Additionally, once the learner is consistently requesting with one or two words, the complexity of the request should be shaped to resemble what typical language should look like for that learner’s age. It is also ideal that the words selected are specific so that it is clear what the learner is communicating. For example, it is preferable that the learner says “push” or “swing” then to say “more.” This program is typically implemented using incidental teaching, shaping, and prompting.

Verbal imitation Verbal imitation is a program that is used to develop the skill of imitating sounds or words after an interventionist’s model (see Leaf & McEachin, 1999, p. 203). For example, if an interventionist says “dog” the goal is for the learner to say “dog.” Leaf and McEachin (1999) suggested that the learner should engage in spontaneous sounds, attending skills, and have at least three nonverbal imitation responses prior to beginning this program. The objectives of this program are to: (a) improve vocalizations, (b) help shape articulation, (c) reduce echolalia, (d) improve speech modulation, and (e) improve vocal verbal language. Leaf and McEachin identified 11 different phases within the program, which is commonly implemented through DTT, and generally a great deal of shaping is required so that the learner can become more accurate with their approximation of the modeled sound or word.

Expressive labels Another program used to develop and improve vocal verbal skills is expressive labeling (see Leaf & McEachin, 1999, p. 209). The goal of this program is for a learner to label (i.e., vocally state) the names of various stimuli (e.g.,

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objects, locations, actions). As noted previously, we select labels that are motivating and functional. Leaf and McEachin (1999) recommended a learner should have mastered matching through at least phase one and two, have verbal imitation skills, and ideally have started some receptive labeling programs. The objectives of this program are to: (a) increase communication, (b) increase language, and (c) increase environmental awareness. Leaf and McEachin stated that this program consists of 15 phases and is typically taught using DTT.

Expanding language Expanding language is used to promote longer and more descriptive statements (see Leaf & McEachin, 1999, p. 261). For example, in response to a picture of someone engaged in an activity, the learner provides a description consisting of two or more elements such as person-action (e.g., “daddy eating”), actionobject (e.g., “kicking ball”), or adjective-object (e.g., “big cookie”). Leaf and McEachin (1999) recommended that the prerequisite for this program is the learner have an adequate vocabulary of labels. The objectives for this program are: (a) facilitate spontaneous language, (b) facilitate conversational skills, (c) improve verbal production (e.g., fluency, fluidity, length), (d) improve awareness, and (e) improve attending. The program is usually taught with incidental teaching, shaping, and DTT.

Pronouns A program that is used for developing parts of speech skills is pronouns (see Leaf & McEachin, 1999, p. 253). The goal of this program is for the learner to use and identify pronouns (e.g., they, he, her) that are part of everyday language. When teaching personal pronouns, it is important to incorporate the client’s preferences and gender identity. Relatedly, it is also important to teach clients how to ask individuals for their pronouns and avoid biases and assumptions related to sex and gender identification. Leaf and McEachin (1999) stated that the prerequisites of this program are, for vocally verbal children, that they should have mastered body parts, have mastered all phases in expanding language, and have at least two-word phrases. For nonvocal verbal children, they should have mastered receptive labels. The objectives of this program are to: (a) teach the relationship of the learner to others in the environment, (b) help improve general language, (c) avoid using incorrect pronouns, (d) appropriately identifying pronouns when unknown, and (e) develop the concept of “who.” Leaf and McEachin identified three

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different phases within this program. The program is usually implemented through incidental teaching, shaping, and DTT.

Basic conversation Basic conversation is the first step in the use of language within social interactions (see Leaf & McEachin, 1999, p. 213). The goal of this program is for the learner to reciprocate others’ comments in longer and more complete sentences. The objectives of this program are to: (a) expand a learner’s vocal verbal language, (b) develop pragmatic language, and (c) getting desires met. This program is usually implemented through DTT.

Intermediate conversation The next program used to develop and improve language is intermediate conversation (see Leaf & McEachin, 1999, p. 273). The goal of this program is for the learner to answer questions and begin having short conversations with adults and/or peers. The objectives of this program are to: (a) improve social interaction via conversation, (b) expand the length of utterances, and (c) teach conversational strategies. This program is usually implemented through DTT, shaping, incidental teaching, role-playing, Cool versus Not Cool (CNC) procedure, or the teaching interaction procedure (TIP).

Advanced conversation More advanced pragmatic language skills are targeted in the advanced conversation program (see Leaf & McEachin, 1999, p. 303). The goal of this program is to advance conversation skills that the learner is using with their peers and adults including more complex aspects of social interaction. The objectives of this program are to: (a) provide a structure to have peer conversations, (b) improve awareness of peers, and (c) to teach the learner how to gain information from others. This program is usually implemented through DTT, shaping, incidental teaching, role-playing, the CNC procedure, or the TIP.

Auditory attending Leaf, Milne, et al. (2020) described an auditory attending program with the goal of improving listening behavior. In this program, the interventionist describes an item/picture using multiple descriptors and the learner finds the single example that meets all the descriptors (e.g., “find the dog sleeping in the garden”). Leaf, Milne, et al. stated that a prerequisite behavior is that

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the learner has a variety of receptive labels prior to beginning this program. The objective of this program is to improve the learner’s social communication and attending behavior. Leaf, Milne, and colleagues identified four different phases of the program which is usually implemented using DTT.

Finding the Message in the Chatter “Finding the Message in the Chatter” was described by Leaf, Milne, et al. (2020) as another way of improving listening behavior. This activity requires extracting the most essential information while listening to a conversation. Leaf, Milne, et al. identified four different phases of the program and is usually implemented with DTT.

Keep it interesting Another program used to develop conversational skills is “Keep it Interesting” (see Leaf, Milne, et al., 2020, p. 265). The goal of this program is for the learner to increase their rate of novel and interesting comments. This program, along with the other following programs, start to become social in nature and are not purely just language programing. Selecting appropriate and quality programs often incorporates multiple domains (e.g., social and language). The programming selected should overlap with what the learner needs. Leaf, Milne, et al. (2020) identified four different phases of the program. The program is usually taught with the CNC procedure.

Follow the conversation thread Follow the conversation thread (see Leaf, Milne, et al., 2020, p. 273) is a program that teaches the learner to stay on topic within conversations. Leaf, Milne, et al. (2020) identified five different phases of the program and is usually taught with the CNC procedure, the TIP, or DTT.

Conversation: Movers and stoppers Leaf, Milne, et al. (2020) described this program used to develop and improve the skill of continuing a conversation with “movers” while avoiding conversation “stoppers.” “Movers” is a term used to describe comments that keep the conversation going (e.g., “Oh really? Tell me more about that.”) while “stoppers” is a term used to describe comments that break the flow of a conversation or are minimally responsive (e.g., “ok”) or abruptly change the topic. The goal of this program is to teach the learner

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what keeps conversations going (e.g., asking more on-topic questions) and what stops conversations (e.g., making boring statements or not responding). Leaf, Milne, et al. identified six different phases of the program which is usually taught with the CNC procedure or the TIP.

Proper skepticism An example of a very advanced language program is developing proper skepticism (see Leaf, Milne, et al., 2020, p. 290). The goal of this program is for the learner to start to identify true orplausible statements versus false or unlikely statements. Leaf, Milne, et al. (2020) identified eight different phases of the program. The program is usually taught with the CNC procedure or the TIP.

Summary Although the programs in this and other chapters are provided in a sequential order it is important to note that this is not a “cookbook” or “cookie cutter” approach to selecting curriculum. Although many learners will need the same prerequisite skills taught to access higher level curriculum, each learner comes with their own repertoires and there is no one correct order to teach these skills. It is important that when selecting language (or any) curriculum that interventionists are continually assessing the needs of the students and which curricular priorities should be targeted. Teaching language and communication should be a part of any comprehensive program for individuals diagnosed with ASD. In this chapter, we provided a brief overview of 19 programs that can be used to promote and develop language skills. It is highly recommended for interventionists to cross reference a variety of developmentally sequenced curricular materials and, more importantly, to continue to create their own programs to address the individual needs of their learners.

References Bondy, A., & Frost, L. (2011). A picture’s worth: PECS and other visual communication strategies in autism (2nd ed.). Woodbine House. Bonvillian, J. D., Nelson, K. E., & Rhyne, J. M. (1981). Sign language and autism. Journal of Developmental Disorders, 11(1), 125–137. https://doi.org/10.1007/BF01531345. Cardillo, R., Mammarella, I. C., Demurie, E., Giofre`, D., & Roeyers, H. (2021). Pragmatic language in children and adolescents with autism spectrum disorder: Do theory of mind and executive functions have a mediating role? Autism Research, 14(5), 932–945. https:// doi.org/10.1002/aur.2423.

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Finke, E. H., Davis, J. M., Benedict, M., Goga, L., Kelly, J., Palumbo, L., Peart, T., & Waters, S. (2017). Effects of a least-to-most procedure on multisymbol message production in children with autism spectrum disorder who use augmentative and alternative communication. American Journal of Speech Language Pathology, 26(1), 81–98. https:// doi.org/10.1044/2016_AJSLP-14-0187. Flores, M. M., & Ganz, J. B. (2014). Comparison of direct instruction and discrete trial teaching on the curriculum-based assessment of language performance of students with autism. Exceptionality, 22(4), 191–204. https://doi.org/10.1080/09362835.2013.865533. Garvey, C. C., Milne, C., Ferguson, J. L., Cihon, J. H., Leaf, J. B., Leaf, R., McEachin, J., & Schulze, K. (2022). Comparing in-view to out-of-view stimulus arrangements when teaching receptive labels for children diagnosed with autism spectrum disorder. Behavior Analysis in Practice, 15(2), 475–484. https://doi.org/10.1007/s40617-021-00596-2. Ghaemmaghami, M., Hanley, G. P., Jessel, J., & Landa, R. (2018). Shaping complex functional communication responses. Journal of Applied Behavior Analysis, 51(3), 502–520. https://doi.org/10.1002/jaba.468. Kurita, H. (1985). Infantile autism with speech loss before the age of thirty months. Journal of the American Academy of Child Psychiatry, 24(2), 191–196. https://doi.org/10.1016/ S0002-7138(09)60447-7. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Milne, C. M., Leaf, R., & McEachin, J. (2020). Comparing error correction to errorless learning: A randomized clinical trial. The Analysis of Verbal Behavior, 36(1), 1–20. https://doi.org/10.1007/s40616-019-00124-y. Leaf, J. B., Dale, S., Kassardjian, A., Tsuji, K. H., Taubman, M., McEachin, J. J., Leaf, R. B., & Oppenheim-Leaf, M. L. (2014). Comparing different classes of reinforcement to increase expressive language for individuals with autism. Education and Training in Autism and Developmental Disabilities, 49(4), 533–546. Leaf, R., Leaf, J. B., & McEachin, J. (2018). Clinical judgment. DRL Books. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J. M., Cihon, J. H., Ferguson, J. L., Oppenheim-Leaf, M. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The autism partnership method: Social skills groups. DRL Books. Lovaas, O. I. (1977). The autistic child: Language development through behavior modification. Irvington. Maione, L., & Mirenda, P. (2006). Effects of video modeling and video feedback on peerdirected social language skills of a child with autism. Journal of Positive Behavior Interventions, 8(2), 106–118. https://doi.org/10.1177/10983007060080020201. Mesibov, G. B., Adams, L. W., & Klinger, L. G. (1997). Autism: Understanding the disorder. Plenum Press. https://doi.org/10.1007/978-1-4757-9343-7. Rutter, M. (1978). Diagnosis and definitions of childhood autism. Journal of Autism and Childhood Schizophrenia, 8(2), 139–161. https://doi.org/10.1007/BF01537863. Sundberg, M. L., & Michael, J. (2001). The benefits of Skinner’s analysis of verbal behavior for children with autism. Behavior Modification, 25(5), 698–724. https://doi.org/ 10.1177/0145445501255003. Sundberg, M. L., & Partington, J. W. (1998). Teaching language to children with autism or other developmental disabilities. Pleasant Hill, CA: Behav. Analysts. Tager-Flusberg, H. (1981). On the nature of linguistic functioning in early infantile autism. Journal of Autism and Developmental Disorders, 11(1), 45–56. https://doi.org/10.1007/ BF01531340. Topuz, C., & Ulke-Kurkcuoglu, B. (2022). Script fading procedure: A systematic review and meta-analysis. Review of Autism and Developmental Disorders, 9, 366–385. https://doi.org/ 10.1007/s40489-021-00258-7.

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van Santen, J. P. H., Sproat, R. W., & Hill, A. P. (2013). Quantifying repetitive speech in Autism spectrum disorders and language impairment. Autism Research, 6(5), 372–383. https://doi.org/10.1002/aur.1301. Venter, A., Lord, C., & Schopler, E. (1992). A follow-up study of high-functioning autistic children. Child Psychology & Psychiatry & Allied Disciplines, 33(3), 489–507. https://doi. org/10.1111/j.1469-7610.1992.tb00887.x. Volkmar, F. R., & Klin, A. (1994). Social development in autism: Historical and clinical perspectives. In S. Baron-Cohen, H. Tager-Flusberg, & D. J. Cohen (Eds.), Understanding other minds: Perspectives from autism (pp. 40–55). Oxford University Press. Wetherby, A. M., & Prizant, B. M. (1989). The expression of communicative intent: Assessment guidelines. Seminars in Speech and Language, 10(1), 77–91. White, E. N., Ayres, K. M., Snyder, S. K., Cagliani, R. R., & Ledford, J. R. (2021). Augmentative and alternative communication and speech production for individuals with ASD: A systematic review. Journal of Autism and Developmental Disorders, 51(11), 4199–4212. https://doi.org/10.1007/s10803-021-04868-2. Whitehouse, A. J. O., Barry, J. G., & Bishop, D. V. M. (2008). Further defining the language impairment of autism: Is there a specific language impairment subtype? Journal of Communication Disorders, 41(4), 319–336. https://doi.org/10.1016/j.jcomdis.2008.01.002. Wong, E., Ferguson, J. L., Milne, C. M., Cihon, J. H., Leaf, J. B., McEachin, J., Leaf, R., Schulze, K., & Rudrud, E. (2020). Evaluating three methods of the presentation of target stimuli when teaching receptive labels. Behavioral Interventions, 35(4), 542–559. https:// doi.org/10.1002/bin.1744.

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CHAPTER 27

Self-help and adaptive behaviors Contents Toilet training Schedule training Intensive training Diapers Nighttime toileting Mealtime challenges Sleep Appearance checks Basic efficiency and organization Walk with me Crossing the street safely Following a visual or written schedule Self-advocacy Summary References

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One of the main goals for any individual, regardless of diagnosis, is that they become as independent as possible and have a high quality of life. As children grow older, it is important for them to have the skills to take care of their needs (e.g., bathing, toileting, hygiene) as well engage in functional adaptive behaviors that will result in more independence and a higher quality of life. Manente et al. (2022) defined adaptive behavior as “a multi-dimensional construct corresponding to the degree to which a person demonstrates the capacity to independently succeed within their environment” (p. 333). Unfortunately, individuals diagnosed with autism spectrum disorder (ASD) often display significant deficits in self-help and adaptive behaviors (Bal et al., 2018), which ultimately leads to less independence and more dependence on others as an individual grows older (Manente et al., 2022). Therefore, it is important to teach self-help and adaptive behaviors as part of a comprehensive behavioral intervention program. In most behavior analytic programs, some self-help behaviors are targeted early in intervention (e.g., toileting, feeding, washing hands), but other adaptive behaviors (e.g., bathing, cooking, laundry) are typically saved A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00011-8

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for preadolescence or adolescence. Within the Autism Partnership Method (APM), we strive to target all self-help and adaptive behaviors as early as possible. This means that toileting, feeding, and washing hands are not the only early self-help skills taught. Adaptive behaviors such as throwing away trash, folding clothes, or cleaning/clearing plates are also taught when appropriate. Targeting a variety of self-help and adaptive behaviors will increase a learner’s independence and will also help decrease stress and dependence on family members and caregivers. Table 1 provides information on some of the self-help and adaptive behaviors that are taught in the APM and recommendations related to the developmental age of when these skills may be targeted. It should be noted, these are general recommendations to which one should not rigidly adhere. What follows is an outline of some of the self-help skills often taught within the APM. Table 1 Self-help skills. Domain

Skill

Feeding

Drinks from cup without help Uses spoon to scoop food Takes spoon from plate to mouth without spilling Sucks from a straw Drinks from cup with one hand Uses fork Uses spoon without spilling Uses side of fork to cut soft food Holds fork in finger Uses knife for spreading Uses knife for cutting Removes socks Removes shoes Removes coat Removes shirt Removes pants Removes sweater Puts on jacket Puts on shoes Puts on pants Puts on socks Puts on sweater Dresses with little supervision Dresses independently

Undressing

Dressing

Recommended age

1.03 1.03 1.06 1.06 1.06 2.0 2.0 3.0 4.0 4.0 6.0 1.06 1.06 2.0 2.0 2.0 4.0 2.06 2.06 2.06 3.0 3.0 3.0 5.0

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Table 1 Self-help skills—cont’d Domain

Skill

Recommended age

Unfastening

Front buttons Unties bow Unsnaps front snaps Unzips Buttons large buttons Zips front zipper Attempts to lace shoes Buttons small buttons Laces shoes Ties shoes Dries hands without assistance Wash hands without assistance Turns faucet on and off Dries faces without assistance Washes face without assistance Bathes without assistance Brushes teeth without assistance Brushes hair without assistance

2.0 2.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 5.0 2.6 3.0 3.0 3.0 4.0 4.0 4.0 5.0

Fastening

Bathing

Grooming

Toilet training There have been several studies that have demonstrated how the principles of behavior analysis can work to teach and increase independent toileting skills (e.g., Azrin & Foxx, 1971; Greer et al., 2016; Kroeger & SorensenBurnworth, 2009; Perez et al., 2020; Tarbox et al., 2004; Wingate et al., 2017). Additionally, there are several books that are excellent resources for interventionists and parents for teaching independent toileting (e.g., Azrin & Foxx, 2019; Cicero, 2012; Leaf & McEachin, 1999). Within the APM, toilet training is a top priority of intervention, as toilet training can allow learners to attend school, help create more independence, and decrease the risk of abuse later in life (Bahry et al., 2022). Typically developing children are usually toilet trained prior to 3 years of age (Leaf & McEachin, 1999). Independent toileting by the age of three is also the goal within the APM. It is also suggested that an interventionist should not target toilet training until a child is at least 2 years of age. When deciding to target toilet training, there are several factors that should be taken into consideration. First, an interventionist should only start toilet training when a learner can hold their urine for 60 min. Second, the learner should be able to

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recognize they have a full bladder and start showing signs of initiating needing to use the restroom. Third, general cooperation and learning-how-to-learn programs should first be targeted and mastered (see Leaf & McEachin, 1999). Fourth, the learner should have minimal tantrums, self-stimulatory behaviors, or other challenging behavior, especially if those challenging behaviors would interfere with sitting on the toilet. Finally, if the goal is for independent toileting, then the learner must be able to locate the restroom. Although not a criterion for starting a toilet training program, it would be beneficial for a learner to be able to take off their clothes, wipe, flush, and wash their hands independently. Finally, if there are bowel movement difficulties it is important that an interventionist rule out any medical problems.

Schedule training Scheduled toilet training means teaching a learner to stay dry between prompted visits to the bathroom. Within this program, the goal is for the learner to urinate when they are on the toilet and to not urinate when they are not on the toilet. Once beginning toilet training, the interventionist should avoid putting the learner into diapers or pullups, except for naps and bedtime. The goal is to create a clear discrimination that when wearing pull-ups or diapers urination is appropriate anywhere, but when wearing underwear urination is only appropriate in the toilet. To start, the interventionist should set a timer for a specified time (e.g., 60 min). When the timer goes off, the interventionist should prompt the learner to go to the toilet and sit for a brief period (i.e., no more than 3–5 min). When the learner is on the toilet, it is important for the interventionist to provide reinforcement for appropriate sitting. When the learner urinates in the toilet, they should receive a reinforcer that is only provided for eliminating on the toilet. If the learner does not urinate when sitting on the toilet, the interventionist should shorten the next duration of time before sitting on the toilet again to avoid accidents. If the learner initiates going to the bathroom or eliminates in the toilet during a scheduled sitting, then the interventionist should provide the learner with a highly preferred reinforcer and provide a lot of praise (e.g., “Yay! You went in the potty!!”). If the learner has an accident at any time, the interventionist should provide neutral corrective feedback and limited attention while they have the learner help as much as possible to clean up the mess and change their clothes. When the learner is successful, the interventionist should gradually increase the duration of time before sitting on the toilet again. The goal is

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that, as the interventionist lengthens the interval, the learner will be motivated to independently request when needed instead of waiting for the next scheduled sitting or risk the chance of an accident. Finally, the interventionist should conduct dry checks throughout to ensure that the learner is staying dry when they are not on the toilet. Dry checks are also a time to provide reinforcement for remaining dry and reminding the learner to go to the toilet when needed. Schedule training does not mean that the learner is independent, rather that they have learned to go at scheduled times. As such, the learner often becomes dependent on an adult to schedule bathroom trips. Simply put, they have learned to urinate contingent on a schedule and not contingent on the urge to urinate, which is why we generally start toilet training with an intensive program.

Intensive training Another way of teaching independent toileting is through intensive toilet training. Just like schedule training, it is important for the learner to have the previously described prerequisites. Usually, this intensive toilet training is done in a few days or spread across a week. When starting an intensive toilet training program, it is important to withhold the learner’s highly preferred reinforcers including small snacks and preferred liquids for at least 1 week prior to build motivation to consume and earn those items. When starting an intensive toilet training program, the learner is placed on the toilet with no pants or underwear and preferred liquids are provided. It is recommended that the learner does not drink their favorite liquids prior to toilet training so that they are excited to drink their preferred drink. The learner should be encouraged to drink regular amounts of liquid to ensure a sufficiently frequent need to urinate. This increases the number of opportunities to teach and reinforce urinating on the toilet. The interventionist provides reinforcement for sitting on the toilet in short intervals (e.g., every 2–3 min). This could be in the form of food items, preferred toys, or interactions. During these initial phases, it is preferred that the learner is not engaging in overly stimulating activities (e.g., playing with toys) because we want them focused on the sensation in their body. When the learner voids in the toilet, the interventionist should provide the highest level of reinforcement possible and be enthusiastic with their praise (i.e., make it a circus!). But it is important that the interventionist waits until voiding is complete so as not to startle the learner. It is imperative during this initial teaching that no accidents occur; due to the nature of the intervention,

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accidents should not occur since the learner is sitting on the toilet. An interventionist can consider this phase mastered when the learner shows signs of anticipation (e.g., smiles, laughs, looks at the reinforcer, looks at trainers, verbalizes, looks down before urinating). The second phase of intensive toilet training is developing initiation. In this phase, the interventionist places the learner in a chair next to the toilet but still in the bathroom without any underwear or pants. The interventionist should be patient and not prompt the learner to use the toilet. When the learner initiates and voids in the toilet, an abundance of reinforcement should be provided. Initiating might take several forms (e.g., using verbal utterances, handing over a picture, getting up from the chair and moving toward the toilet). It is important to note that accidents may happen during this phase which is part of the learning process. If an accident occurs, neutral corrective feedback and limited attention should be provided while the learner is prompted to assist in cleaning up the mess. As the learner is successful, the interventionist should gradually create distance between the learner and the toilet and gradually have the learner be clothed. This phase can be considered mastered when the learner is consistently initiating toileting from a greater distance and is fully clothed. In the third phase, other programing is reintroduced so the learner can demonstrate requests to go to the bathroom while engaged in other activities. The interventionist works on generalization by having the learner use multiple restrooms, engaging in a variety of activities, and fading the use of external reinforcers.

Diapers It is not uncommon for learners to have rituals or display certain toileting behaviors when wearing diapers. For example, a learner may only want to have a bowel movement in the diaper. If this is occurring, it is important to be patient with the process. The interventionist should only provide the diaper when the learner is in the restroom. When the learner voids in the diaper, then dispense of it in the toilet. Over time, have the learner sit on the toilet with the diaper and cut holes in the diaper so that they are voiding into the toilet. Systematically and gradually fade the diaper by cutting away more and more of the material.

Nighttime toileting An interventionist should not work on nighttime toileting until the learner is independently toileting during the daytime. As such, a learner should wear

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diapers during nighttime and during any naps that they take. Nighttime voiding is commonly reflexive and involuntary. To help with nighttime toileting, it is recommended that the interventionist and caregivers purchase commercial devices that set off an alarm at the beginning of urination to develop the wakening reflex. Doing so will help them realize they are about to go earlier in the process.

Mealtime challenges Researchers have shown that individuals diagnosed with ASD have commonly engaged in a range of mealtime challenges. These challenges range from picky eating (Crowley et al., 2020; Peterson et al., 2019) to failure to thrive (Keen, 2008). Researchers have demonstrated that a variety of behavior analytic procedures can help autistic individuals with mealtime challenges (Anglesea et al., 2008; Fu et al., 2015; Peterson et al., 2016; Peterson et al., 2019; Peterson et al., 2021; Sarcia, 2021). These procedures include escape extinction (e.g., Tarbox et al., 2010), differential reinforcement (e.g., Buckley & Newchock, 2005), modeling (e.g., Fu et al., 2015), prompting (e.g., Anglesea et al., 2008), and shaping (e.g., Hodges et al., 2017). While procedures that rely on escape extinction have been extremely successful in treating mealtime challenges, families may not implement them with high degrees of fidelity (Tarbox et al., 2010; Vazquez et al., 2019). As a result, escape-extinction is rarely used in the APM, but it does not mean that we should abandon the procedure altogether as escape extinction may be a necessary procedure in extreme occasions (e.g., failure to thrive). Anytime mealtime challenges are addressed, it is important to rule out any medical problems and reach out to other professionals when necessary (e.g., doctor, nutritionist, occupational therapist). If all other medical problems have been ruled out, it still may be necessary for an interventionist to contact other professionals and colleagues with more experience to help assist in the intervention. Additionally, mealtime challenges should only be addressed in coordination with the family to take into consideration variables such as the family’s typical mealtime context, common meals or foods within the family’s mealtimes, and goals for the family as well as the learner with respect to meals. Given the complexity of mealtime challenges and interventions to address these challenges, the reader is encouraged to contact more comprehensive resources (e.g., Cihon et al., 2022).

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Sleep Researchers have also shown that individuals diagnosed with ASD have higher rates of sleep challenges (Carnett et al., 2020; Johnson, 1996; Ribeiro et al., 2015; Schreck, 2001). These challenges can include difficulty going to bed, difficulty falling asleep, night terrors, difficulty staying asleep, and sleeping in undesired locations (e.g., parent’s bed, couch; Carnett et al., 2020; Johnson, 1996; Ribeiro et al., 2015; Schreck, 2001). Working on sleep may be very difficult for everyone involved, but it is important to establish a nighttime routine. Each learner’s nighttime routine may vary but it is important that this routine remains consistent. For example, a nighttime routine may include going to the bathroom, taking a bath, brushing teeth, reading a book, singing a song, and being tucked into bed. It is important that the activities that are selected are calming to the learner so they can transition to sleep more easily. In establishing a nighttime routine, it is also important to select an appropriate time that the learner goes to bed. Ideally when first selecting a bedtime, it should be a time in which the learner is already tired and exhibiting behaviors that are correlated with being tired. This will likely avoid instances of protest and challenging behavior that often occur when demands for bedtime are placed. When initially selecting a bedtime, it may be beneficial to select a time that is later than when one would want the learner to go to bed. This is done to increase the level of deprivation for sleep and increase the likelihood of cooperation when the bedtime routine is initiated and falling asleep shortly after getting into bed. The interventionist or caregiver should also condition an object to be a sleep object. This sleep object should be something that can help soothe the learner and can be used in case they wake up. Usually, these sleep objects are special stuffed animals or blankets. It is critical that the learner does not fall asleep anywhere besides their bed. If the learner wakes up at night, it is imperative that they are placed back in their bed and not allowed to sleep with the parents or engage in any other activities (e.g., watching tv). This needs to be done consistently no matter how many times the learner wakes up.

Appearance checks Another self-help skill that the interventionist can address is for the learner to complete self-evaluations on their overall appearance (e.g., clothing, hair, cleanliness of face and teeth). This skill is often important for successful social

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interactions and eventually for job placement. When a learner has a clean and neat appearance, it can have a positive effect on themselves and people around them in the environment and, therefore, it is a skill that is taught as part of the APM. Usually, this skill is taught using the teaching interaction procedure (Leaf, Oppenheim-Leaf, et al., 2012) or the Cool versus Not Cool procedure (Leaf, Tsuji, et al., 2012). The interventionist would identify meaningful rationales for the learner to engage in self-checks and good appearance and can also use demonstration to help the learner discriminate between a clean/neat appearance and a disheveled appearance. Within the teaching interaction procedure, the interventionist would identify different strategies for the learner to engage in to ensure that they are correctly doing self-checks.

Basic efficiency and organization It is important for any person to be organized and use their time wisely. Thus, in the APM we teach learners how to engage in basic processing/ problem solving strategies as it relates to organizational skills and efficiency. Some of the goals of this program include teaching the learner to organize a list, retrieve items, and scan their environment. As the learner gets more efficient in these strategies, the interventionist should then teach them to manipulate variables leading to more efficient problem solving. Also, in this category are remembering-to-remember skills (e.g., as you put your jacket on the ground outdoors, notice where you are putting it and remind yourself to retrieve it when you go inside).

Walk with me Having a learner (especially a younger learner) stay with an adult (e.g., parent, interventionist, caregiver) is an important safety skill. To start this program, have the learner practice waiting while standing next to the interventionist and provide access to reinforcement. Next, the learner is taught to walk next to the interventionist when they start walking, and to stop next to the interventionist when the walking stops. Again, reinforcement should be provided for walking at the same pace and next to the interventionist as well as stopping and waiting until walking begins again. As the learner masters this skill, the interventionist should start to practice in less structured environments (e.g., hallway, busy room), increase the temptation of items in the room where the learner might want to elope (e.g., put a

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favorite toy at the end of the hallway), and begin to allow more distance between the interventionist and the learner (e.g., instead of being right next to the interventionist, the learner can be a step or two ahead). Once this skill is mastered, then it needs to be generalized to the natural environment (e.g., outside, in a store, parking lot) and the people with whom the learner spends time (e.g., caregivers). This is a skill that needs to be learned 100% to ensure that elopement or darting does not happen in dangerous areas (e.g., walking on the sidewalk next to a busy street).

Crossing the street safely It is important that learners can be safe in the community setting. One of these safety/adaptive skills is crossing the street safely. It is imperative that the learner displays this skill with 100% accuracy, as any failure can result in severe harm. The interventionist would start by first teaching the learner to discriminate if a car is on the road or not on the road. At this point, it would not matter if the car were moving or parked. After the learner makes this discrimination, the interventionist would start teaching the discrimination if a car is moving or not moving. Next, the interventionist would teach the learner different safety and street signs. The interventionist then would work on teaching the learner to discriminate if it is safe or dangerous for the learner to cross the street. Finally, the interventionist will practice the skill of crossing the street with the learner.

Following a visual or written schedule Throughout the day, a person may have to follow a schedule. Whether that is looking at a calendar, crossing items off a to-do list, or following a recipe. As such, it may be important to teach a learner how to follow a schedule. In the initial phase, the interventionist identifies a type of controlling stimulus that signals clearly to the student what action or item is required such as a picture of a person engaged in a discrete action. For learners who can read, the most efficient type of stimulus is a written word or phrase. The stimuli are arranged in order and the learner is taught to follow the cues one-by-one and after each step, they mark the item as completed (e.g., turn over the picture or cross off the step from the list). Initially, an interventionist may have the learner follow and engage in a list of actions while sitting at the table. Next, the interventionist may have the learner follow a list of different actions while away from the table. After the learner has accomplished this,

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then the interventionist can start working on a daily schedule and having the learner follow their daily schedule.

Self-advocacy One goal of intervention should be to teach the learner how to be an advocate for themselves. Doing so will improve their ability to get their wants or needs met and to stick up for themselves. To start this program, it is important for the learner to develop their own treatment goals, which is a hallmark of applied behavior analysis (Wolf, 1978). Another step of this program is to teach the learner how to select items or events for which they would like to earn. In other words, have the learner pick what they earn for the accomplishments they achieve.

Summary The importance of targeting self-help and adaptive behaviors as early as possible cannot be overstated. Self-help and adaptive behaviors are inextricably linked to enhancing options, increasing independence, and an increased quality of life. This chapter provided only some self-help skills that should be considered in a comprehensive behavior intervention plan. These skills, just like any other skills, should be individualized for each client and adjusted as necessary and appropriate.

References Anglesea, M. M., Hoch, H., & Taylor, B. A. (2008). Reducing rapid eating in teenagers with autism: Use of a pager prompt. Journal of Applied Behavior Analysis, 41(1), 107–111. https://doi.org/10.1901/jaba.2008.41-107. Azrin, N. H., & Foxx, R. M. (1971). A rapid method of toilet training the institutionalized retarded. Journal of Applied Behavior Analysis, 4(2), 89–99. https://doi.org/10.1901/ jaba.1971.4-89. Azrin, N. H., & Foxx, R. M. (2019). Toilet training in less than a day. Gallery Books. Bahry, S. N., Cauchi, J., Driscoll, N. M., & Gerhardt, P. F. (2022). Meaningful curriculum and functional intervention for adults with autism. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & P. F. Gerhardt (Eds.), Handbook of quality of life for individuals with autism spectrum disorder (pp. 313–331). Springer. https://doi.org/10.1007/978-3-030-98507-3_18. Bal, V. H., Hendren, R. L., Charman, T., Abbeduto, L., Kasari, C., Klinger, L. G., Ence, W., Glavin, T., Lyons, G., & Rosenberg, E. (2018). Considerations from the 2017 IMFAR Preconference on measuring meaningful outcomes from school-age to adulthood. Autism Research, 11(11), 1446–1454. https://doi.org/10.1002/aur.2034. Buckley, S. D., & Newchock, D. K. (2005). An evaluation of simultaneous presentation and differential reinforcement with response cost to reduce packing. Journal of Applied Behavior Analysis, 38(3), 405–409. https://doi.org/10.1901/jaba.2005.71-04.

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Carnett, A., Hansen, S., McLay, L., Neely, L., & Lang, R. (2020). Quantitative analysis of behavioral interventions to treat sleep problems in children with autism. Developmental Neurorehabilitation, 23(5), 271–284. https://doi.org/10.1080/17518423.2019.1646340. Cicero, F. (2012). Toilet training success guide for teaching individuals with developmental disabilities. DRL Books. Cihon, J. H., Tereshko, L., Marshall, K. B., & Weiss, M. J. (2022). Behavior analytic approaches to promote enjoyable mealtimes for autistics/individuals diagnosed with autism and their families. Vernon Press. Crowley, J. G., Peterson, K. M., Fisher, W. W., & Piazza, C. C. (2020). Treating food selectivity as resistance to change in children with autism spectrum disorder. Journal of Applied Behavior Analysis, 53(4), 2002–2023. https://doi.org/10.1002/jaba.711. Fu, S. B., Penrod, B., Fernand, J. K., Whelan, C. M., Griffith, K., & Medved, S. (2015). The effects of modeling contingencies in the treatment of food selectivity in children with autism. Behavior Modification, 39(6), 771–784. https://doi.org/10.1177/ 0145445515592639. Greer, B. D., Neidert, P. L., & Dozier, C. L. (2016). A component analysis of toilet—training procedures recommended for young children. Journal of Applied Behavior Analysis, 49(1), 69–84. https://doi.org/10.1002/jaba.275. Hodges, A., Davis, T., Crandall, M., Phipps, L., & Weston, R. (2017). Using shaping to increase foods consumed by children with autism. Journal of Autism and Developmental Disorders, 47(8), 2471–2479. https://doi.org/10.1007/s10803-017-3160-y. Johnson, C. R. (1996). Sleep problems in children with mental retardation and autism. Child and Adolescent Psychiatric Clinics of North America, 5(3), 673–683. https://doi.org/ 10.1016/S1056-4993(18)30355-9. Keen, D. V. (2008). Childhood autism, feeding problems and failure to thrive in early infancy: Seven case studies. European Child & Adolescent Psychiatry, 17(4), 209–216. https://doi.org/10.1007/s00787-007-0655-7. Kroeger, K. A., & Sorensen-Burnworth, R. (2009). Toilet training individuals with autism and other developmental disabilities: A critical review. Research in Autism Spectrum Disorders, 3(3), 607–618. https://doi.org/10.1016/j.rasd.2009.01.005. Leaf, R., & McEachin, J. (1999). A work in progress: Behavior management strategies and a curriculum for intensive behavioral treatment of autism. DRL Books. Leaf, J. B., Oppenheim-Leaf, M. L., Call, N. A., Sheldon, J. B., Sherman, J. A., Taubman, M., McEachin, J., Dayharsh, J., & Leaf, R. (2012). Comparing the teaching interaction procedure to social stories for people with autism. Journal of Applied Behavior Analysis, 45(2), 281–298. https://doi.org/10.1901/jaba.2012.45-281. Leaf, J. B., Tsuji, K. H., Griggs, B., Edwards, A., Taubman, M., McEachin, J., Leaf, R., & Oppenheim-Leaf, M. L. (2012). Teaching social skills to children with autism using the cool versus not cool procedure. Education and Training in Autism and Developmental Disabilities, 47(2), 165–175. Manente, C. J., LaRue, R. H., Maraventano, J. C., Butler, C., Budge, J., Scarpa, C., & Kahng, S. (2022). Leisure and adaptive behavior for individuals with autism. In J. B. Leaf, J. H. Cihon, J. L. Ferguson, & P. F. Gerhardt (Eds.), Handbook of quality of life for individuals with autism spectrum disorder (pp. 333–356). Springer. https://doi.org/ 10.1007/978-3-030-98507-3_19. Perez, B. C., Bacotti, J. K., Peters, K. P., & Vollmer, T. R. (2020). An extension of commonly used toilet-training procedures to children with autism spectrum disorder. Journal of Applied Behavior Analysis, 53(4), 2360–2375. https://doi.org/10.1002/jaba.727. Peterson, K. M., Iban˜ez, V. F., Volkert, V. M., Zeleny, J. R., Engler, C. W., & Piazza, C. C. (2021). Using telehealth to provide outpatient follow-up to children with avoidant/ restrictive food intake disorder. Journal of Applied Behavior Analysis, 54(1), 6–24. https://doi.org/10.1002/jaba.794.

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Peterson, K. M., Piazza, C. C., Iban˜ez, V. F., & Fisher, W. W. (2019). Randomized controlled trial of an applied behavior analytic intervention for food selectivity in children with autism spectrum disorder. Journal of Applied Behavior Analysis, 52(4), 895–917. https://doi.org/10.1002/jaba.650. Peterson, K. M., Piazza, C. C., & Volkert, V. M. (2016). A comparison of a modified sequential oral sensory approach to an applied behavior-analytic approach in the treatment of food selectivity in children with autism spectrum disorder. Journal of Applied Behavior Analysis, 49(3), 485–511. https://doi.org/10.1002/jaba.332. Ribeiro, A., Liddon, C. J., Gadaire, D. M., & Kelley, M. E. (2015). Sleep, elimination, and noncompliance in children. In H. S. Roane, J. E. Ringdahl, & T. S. Falcomata (Eds.), Clinical and organizational applications of applied behavior analysis (pp. 247–272). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-420249-8.00011-3. Sarcia, B. (2021). The impact of applied behavior analysis to address mealtime behaviors of concern among individuals with autism spectrum disorder. Psychiatric Clinics of North America, 44(1), 83–93. https://doi.org/10.1016/j.psc.2020.11.007. Schreck, K. A. (2001). Behavioral treatments for sleep problems in autism: Empirically supported or just universally accepted? Behavioral Interventions, 16(4), 265–278. https://doi. org/10.1002/bin.98. Tarbox, J., Schiff, A., & Najdowski, A. C. (2010). Parent implemented procedural modification of escape extinction in the treatment of food selective in a young child with autism. Education and Treatment of Children, 32(2), 223–234. https://doi.org/10.1353/ etc.0.0089. Tarbox, R. S. F., Williams, W. L., & Friman, P. C. (2004). Extended diaper wearing: Effects on continence in and out of the diaper. Journal of Applied Behavior Analysis, 37(1), 97–100. https://doi.org/10.1901/jaba.2004.37-97. Vazquez, M., Fryling, M. J., & Herna´ndez, A. (2019). Assessment of parental acceptability and preference for behavioral interventions for feeding problems. Behavior Modification, 43(2), 273–287. https://doi.org/10.1177/0145445517751435. Wingate, H. V., Falcomata, T. S., & Ferguson, R. (2017). Applications of operant-based behavioral principles to toilet training. In J. L. Matson (Ed.), Clinical guide to toilet training children (pp. 119–141). Springer International Publishing. https://doi.org/10.1007/9783-319-62725-0_8. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203.

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CHAPTER 28

Working with parents of autistic children Contents Prediagnosis stress Diagnostic process stress Postdiagnosis stress Intervention stress Autism partnership method of parent support Leading with compassion and understanding Understanding and embracing the autism partnership method Our approach Different modalities to provide parent support Research on parent training Summary References

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Being a parent is one of the most wonderful aspects of life. Getting to see your child grow, learn, and bond with them is truly special. Being a parent can also be one of the most stressful times in life. Researchers have found that being a parent of a child diagnosed with autism spectrum disorder (ASD) causes significantly more stress for mothers and fathers than for parents of typically developing children (Baker et al., 2002; Fisman & Wolf, 1991; Wolf et al., 1989).

Prediagnosis stress Parents are often the first ones to notice that some things are different about their child compared to other children of the same age. It might be that their child is not talking as much, not playing with toys the same way as other children, or is not socially engaged with them or others. Whatever it may be, the parent notices that something is different, and this causes initial stress and deep concern. This stress can escalate further when the parents share their concerns with family and friends, only to be dismissed with reassurance that nothing is wrong (e.g., “Boys usually take longer to talk,” “My son A Progressive Approach to Applied Behavior Analysis https://doi.org/10.1016/B978-0-323-95741-0.00021-0

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didn’t talk until he was 5,” “She will grow into having friends,” “It’s just a phase”). This leaves the parents not only scared about their child’s development but also confused about what to do next due to the lack of affirmation from their support group. Another area that could cause more stress is when there are diverging views among parents. The mother may believe something is wrong and the father does not or vice versa, all while family friends and the pediatrician assure both parents that everything is fine.

Diagnostic process stress At a certain point, the parents will decide (whether based on their own views or recommendations from others) to get their child assessed. They must find and contact a diagnostician. Unfortunately, there is often a waiting list for their child to be evaluated, sometimes as long as 6 months. Knowing that something is potentially wrong with their child and having to wait for answers can be gut-wrenching. Then, hopefully sooner rather than later, comes the day when their child goes in for diagnostic testing. They watch as their child completes a battery of assessments and complete long questionnaires themselves only to receive the news that their child is diagnosed with ASD. Immediately they are likely to begin thinking, What is autism? What does it mean for my child? Will they learn to talk? How can we help them? What is their future like? If the parents are lucky, they will work with a diagnostician who will explain ASD and their options to them fully. The reality is that for many parents, after their child receives a diagnosis, they are on their own and must seek out their own resources and services. Simply going through the diagnostic process and receiving a diagnosis can be a stressful time and one of great uncertainty. The vision of a child playing in little league, excelling in high school, dating, attending college, and getting married starts to evaporate. Navigating early intervention services, Individualized Education Program (IEP) meetings, and the long-term future of their child consumes their thoughts.

Postdiagnosis stress Now, the parents are at home with a new diagnosis, and they must find an appropriate intervention for their child. When they Google “autism intervention,” the parents are inundated with hundreds of interventions for their child, including ones that promise cures. How does a parent select

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an intervention with so many options out there and no clear information? Moreover, the recommendations are completely contradictory. For example, “never do ABA” versus “you must do ABA.” As a parent, how do you know which information is accurate? More stress! Hopefully, they find their way to behavioral intervention based on the principles of applied behavior analysis (ABA). How can they ensure the intervention is high quality? What features should they seek? When trying to obtain funding for behavioral intervention, they get the run around from insurance companies or they do not have coverage with their current provider. More stress! When they seek out the early intensive services that they need, they are told that they will be placed on a waitlist that can be up to 1 year. What are they supposed to do when they need this intervention now? More stress! Now they go to the school system to get an IEP and can encounter resistance, confusion, bureaucracy, and a lack of teamwork. More stress!

Intervention stress Then, there is the ongoing stress of intervention; hours upon hours of therapy (or the agency not being able to provide enough hours), professionals in their home, IEPs, phone calls when their child is not doing well, and much time spent coordinating with multiple service providers. These are just some of the factors as to why parents of an individual diagnosed with ASD report higher levels of stress than parents of typically developing children or parents of a child with another disorder/disability (Baker et al., 2002; Fisman & Wolf, 1991; Wolf et al., 1989). It is also why parents of a child diagnosed with ASD often have high levels of loneliness and depression (Hastings et al., 2005) and why the divorce rates are much higher than parents who do not have a child diagnosed with ASD (Hartley et al., 2010). It is why it is imperative that behavioral intervention includes parent support in the form of training, education, and counseling.

Autism partnership method of parent support Within the Autism Partnership Method (APM), there are many ways that we can help parents with their journey. The main tenet of the APM is that a supervisor uses a psychoeducational approach when it comes to parent support. This approach entails providing parents a solid behavioral knowledge base, then skillfully leading them to answers. Essentially, parents learn to

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“independently” develop effective strategies to implement with their child. Within the APM, the supervisor does not automatically prescribe what the parents should do, but, rather, helps guide the parents to a deeper understanding of the principles behind the procedures. Throughout this process, the supervisor and parents work together collaboratively on understanding the most meaningful principles, application of these principles, and development of meaningful goals.

Leading with compassion and understanding As previously stated, parents of autistic children can have a great deal of stress, anxiety, depression, and loneliness (Baker et al., 2002; Fisman & Wolf, 1991; Hartley et al., 2010; Hastings et al., 2005). When working with parents and caregivers, we must keep this in mind. Most importantly, supervisors must be compassionate, empathetic, caring, and understanding (Leaf et al., 2023; LeBlanc et al., 2020; Taylor et al., 2019). Part of being compassionate is realizing that parents may be resistant to taking advice or receiving feedback. Before expecting parents to seek out and follow a supervisor’s counsel, trust must be built. One way of doing this is to listen, hear, and understand the parents’ story. To fully understand their story, supervisors need to be active listeners (Burt, 2021), ask thoughtful questions, and acknowledge their very real feelings (e.g., sadness, anxiety, frustration). As clinicians, we must understand that parents are sometimes desperate to “fix” their child. Having compassion and empathy toward parents means that supervisors will have to realize some important points. First, parents unconditionally love their children and may not be as objective as staff members. The lack of objectivity should not be frowned upon or corrected by the supervisor, but rather shaped over time. This lack of objectivity may make it difficult for parents to follow through on contingency systems and this should not be seen as nonadherence or noncompliance with a treatment plan (Fryling, 2014). Rather, it is just the reality of being a parent. Second, it is important for supervisors to fully accept that they will never truly understand what the parents are going through. Although you do not need to be a parent to be an excellent supervisor, without being a parent it may be harder to understand what parenthood is like. Even if a supervisor is a parent, it may be difficult to understand what parents of children with autism are going through, and even if the supervisor does have a child on the spectrum, no two autistic individuals are exactly alike. As such, a supervisor must be mindful with how they give advice and how training is provided.

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Understanding and embracing the autism partnership method When parents are stressed, when their child is not speaking, when their child is engaging in aggression or self-injury, parents often want an immediate fix. Parents are often seeking immediate solutions during parent training. This, of course, is aligned with so many other services that children and parents receive. When a child gets sick, parents go to the doctor and get medicine to make them better. When a car breaks down, you go to a mechanic and the car gets fixed. Unfortunately, this is not the reality with behavioral intervention, as meaningful, lasting improvements often take time. Behaviors are complex and everchanging, therefore so is the “fix.” With this understanding, it is important for supervisors to discuss the model and reasonable expectations with parents from the very beginning. In doing so, a supervisor should be able to provide different rationales of the model and the plan and by doing so, the parents will hopefully feel more at ease throughout the journey. Supervisors must include the parents as part of the plan from the onset and throughout intervention (Wolf, 1978). While initially describing the model, it is important to let parents know that the approach is going to be a psychoeducational approach and they are not going to be provided with easy solutions. Rather, the supervisor will teach them how to develop and implement behavioral intervention strategies to manage everyday situations and behaviors. Further, the supervisor will need to prepare the parents that the whole process will be an emotional journey. A journey where there will be good, bad, happy, and sad days; just as their child’s treatment progress will not be linear, neither will their journey with effectively approaching their child’s behaviors. Finally, supervisors must inform parents that there will be many times that uncomfortable discussions may occur and that the supervisor’s priority is to provide them with the help they seek despite it not being provided as quickly as they would likely want. It is important that parents feel comfortable asking questions and expressing any concerns or confusion that they may have throughout the process so that their needs can be adequately met. The supervisor should also normalize that many of concepts that will be covered may initially seem counterintuitive to general parenting norms, so they should not feel any guilt or embarrassment for not using them prior.

Our approach Once a supervisor informs the parents about the APM’s parent training, it is important to begin developing meaningful strategies for the parents to be

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able to interact with and manage their child’s behavior(s). In doing so, a supervisor will not jump to a prescriptive approach (i.e., telling the parents what to do), but instead will utilize a psychoeducational approach in which parents are guided to uncover the answers themselves. One of the first steps is helping a parent understand why their child behaves the way they behave. In doing so, a supervisor helps the parent identify what behaviors are occurring or not occurring, identify the reasons why they are occurring (i.e., functions), understand that behaviors are logical and predictable, and understand that the reasons behavior occurs are not due to mysterious forces (e.g., a full moon). Parents’ journeys navigating daily behaviors can feel like riding a roller coaster in the dark; they know they are on the ride, but often may not always be able to tell when the twists, turns, and dips may occur. This initial training will help parents make better sense of why their child behaves in certain ways in certain contexts, therefore making the behaviors less unforeseeable. We have found it to be very beneficial to teach parents the principles and functions of behavior by starting out more globally (e.g., why a teen may begin vaping) rather than using their own child as the example. Doing so will help take out some of the emotionality, some of the resistance, and may lead to more objective understanding of behavior. Once the parents can objectively identify behaviors and their causes with others, then they are better able to start doing so with their own child. Once a parent can fluently identify behaviors, their function(s), and understands that function fluctuates over time, then a supervisor can introduce how to teach functional replacement behaviors (McKenna et al., 2016). The supervisor should start broadly with the concept of teaching replacement behaviors (e.g., leisure skills) and then systematically move toward how to target the specific behavior that they will need to teach their child (e.g., how to appropriately play independently). As part of this discussion, the supervisor will need to explain the general principles of reinforcement. When teaching a parent about reinforcement, there should be discussions on what constitutes reinforcers, how to know if an item is functioning as a reinforcer, and how to develop reinforcers. Within this discussion, it is equally important to cover how to provide corrective feedback. Parents need to understand how to provide corrective feedback in a calm manner while reserving reinforcement contingently upon desirable behaviors. Essentially, this phase enhances a parents’ understanding of consequences and how they influence behaviors. The concepts of functions and reinforcement might be difficult for parents. Understanding that behavior is lawful and that the

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environment—possibly even the parent’s own behavior as part of that environment—may be contributing to the undesirable behavior can be difficult to hear and accept. Some parents may believe that internal or external factors (e.g., having too much sugar, “sensory dysregulation,” because they are “bad” kids) result in undesirable behavior. Such beliefs can impede recognition that the current and past environmental interactions are what evoke and maintain behavior. Additionally, some caregivers may believe that children should engage in appropriate behavior simply because that is what kids are supposed to do and that rewards should not be provided for appropriate behavior. Such ideologies may make teaching these concepts difficult, but it is crucial that objective observation is achieved. Once the parents have a firm understanding of reinforcement, corrective feedback, contingencies, and responding to challenging behavior, the supervisor should start teaching parents intervention strategies that will provide them the ability to teach new behaviors (i.e., the replacement behaviors) to their child. Intervention strategies like shaping (Cihon et al., 2019), prompting (Seaver and Bourret, 2014), chaining (Valentino et al., 2015), and incidental teaching (Fenske et al., 2001) may be vital for parents to learn. This level of training does not need to be done at the same level that we would use to train staff, but rather at a simplified level that is feasible for parents. In doing so, the supervisor should provide the parents with many practical examples. Parents should also be provided with training on the importance of teaching proactively rather than only responding reactively and how to identify suitable times to teach their child. Once these principles are understood, then a plan can be developed collaboratively with parents; the more parents feel ownership in the development of a plan, the more likely they are to follow it. It is imperative that throughout the parent support and training process, the supervisor maintain the mindset that the goal is not for parents to become an interventionist—that is simply not nor should be their role. Parents should continue to be warm and lead with their hearts, just in a manner that is more objective and ultimately helps them feel and become more effective with their child.

Different modalities to provide parent support Parental support groups One option that is provided to parents within the APM is parental support groups. Support groups allow parents to come together to share different ideas, stories, and experiences that they have with their child diagnosed with

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ASD, other children in their family, and other family members. The parental support groups are usually hosted by a supervisor, a licensed psychologist, or a licensed Marriage and Family Therapist. The group is usually semistructured; a general topic or theme for the group is predetermined (e.g., what to do over summer vacation, toilet training issues, IEPs), and the supervisor introduces the topic with some pertinent information or suggestions. Following the initial introduction of the topic, the supervisor’s role shifts to facilitating communication among the parents. The supervisor must skillfully navigate the conversation among parents, ensure that no one parent is monopolizing the conversation, artfully correct inaccurate information or misconceptions, and build rapport among the parents. Parental support groups provide an avenue to: (a) provide multiple parents with information simultaneously, (b) build a community/network of friends among participants, and (c) build rapport with parents and families. Parent education A second type of approach that is used in the APM is parent education. Parent education can take place in a group or individual learning opportunities. Typically, group parent education involves multiple parents coming together to learn about specific principles (e.g., reinforcement, functional assessment, developmental norms) and concepts related to autism (e.g., stereotypic behavior, learning styles, working in schools). Group parent education is similar to parental support in that parents can participate and share, but the session is much more focused and didactic. The supervisor introduces a specific topic each week, describes that topic, provides a rationale for the principle or procedure, and models correct and incorrect utilization of that principle, if applicable. Throughout, the supervisor checks parents’ knowledge of the topic and skillfully answers questions that parents may have (yet still in a psychoeducational manner). Next, the supervisor assigns the parents “homework” for the week that involves application of the principles discussed. It is important this homework is practical for the parents (e.g., only takes 10–15 min to complete). The homework assignment is then reviewed in the following session through a group discussion. This type of education generally occurs for some specified period (e.g., 8–10 sessions) before it moves into the home setting and is individualized to each parent. During individual parent sessions, the focus moves away from education and toward more practical application of the concepts that were discussed in the group sessions. Throughout the sessions, the supervisor continues using

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a psychoeducational approach in which they lead the parent to the answer instead of just providing it for them. One approach that is used within this training is the implementation of the teaching interaction procedure. First, the supervisor describes a procedure/principle that they want the parents to apply. Next, the supervisor provides rationales as to why the parent should engage in the procedure (ideally, based on the material covered in the group sessions, the parent is also able to come up with rationale). The supervisor may also provide recommendations of ways parents can be successful in implementing the procedure and model proper implementation of the principle/procedure. The parents are then asked to practice the skill with their child followed by the supervisor providing feedback. Just as when teaching children, high success rates are important for momentum, building rapport, and creating buy-in; therefore, the supervisor should use various prompting strategies (that need to be systematically faded) throughout the hands-on practice component. The teaching interaction procedure is a wonderful way to teach parents for numerous reasons. First, the supervisor can help build a meaningful rationale with the parent as to why they should engage in the behavior. This building of a rationale might lead to long-term maintenance, as it could create genuine “buy-in” from the parents. Second, by the supervisor demonstrating the behavior in front of the parents, it allows the parents to see the proper implementation of the principle or procedure and ideally, how it is effective. Third, the role-playing component allows parents the opportunity to practice the principle or procedure in front of the parent trainer in order to get feedback on what they are doing well and where they can improve. Finally, the teaching interaction procedure allows for the supervisor to train loosely, program for common stimuli, and allow for natural contingencies which are all strategies that lead to generalization (Stokes & Baer, 1977). Active coaching Another modality for parent support is active coaching. During active coaching, the supervisor can: (a) provide instructions to the parents, (b) pose questions to the parents (e.g., “Why do you think your child did that?”), (c) provide prompts, (d) provide reinforcement, and (e) provide corrective feedback. This can all be done in the moment (e.g., while parents are directly interacting with their child) or occur as part of a debriefing following an observation. This type of coaching is often how new interventionists are trained in the APM.

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Parent counseling A final component of parent support is parent counseling. Parent counseling is typically provided by a licensed psychologist or licensed Marriage and Family Therapist. The parent counselor should have a wealth of knowledge and experience with applied behavior analysis and an understanding of the special circumstances and concerns that surround parenting a child on the autism spectrum. Most importantly, the counseling individual needs to have excellent clinical skills (e.g., therapeutic alliance, active listening, sensitivity). They should work closely with the supervisor to ensure there is a continuity of services. Counseling services are provided for a variety of reasons, which can include: (a) how to share the diagnosis with their child, (b) how to share the diagnosis with other family members, (c) sibling issues, (d) managing financial stress, (e) marital issues, (f ) long-term care issues, (g) child development, and (h) managing other emotions (e.g., sadness, grief, stress) that parents might experience.

Research on parent training Like so many of the procedures and principles of ABA, one of the first examples of parent training traces back to the work of Montrose Wolf and his colleagues at the University of Kansas. In their seminal “Dickey study” (Wolf et al., 1963), not only did the researchers implement operant conditioning procedures to decrease tantrums, teach appropriate bedtime behavior, and teach Dickey to wear his glasses, but they also trained parents on these procedures. The specific details of this parent training were not discussed, but Wolf and colleagues noted that parent training occurred throughout the duration of the study and may have been a contributing factor for the successful results. Another seminal study in terms of comprehensive intervention and parent training was conducted by Lovaas et al. (1973). In this study, there were 20 participants diagnosed with ASD. The intervention included 12–14 months of intensive behavioral intervention (e.g., reinforcement, shaping, DTT) to improve the behaviors of the participants. Within this study, some participants’ parents received training and some participants returned to the state hospital where they had previously resided. The results were that follow-up measures recorded one to four years after treatment indicated that large differences between groups of children were related to the posttreatment environment (those groups whose parents were trained to carry out behavior therapy continued to improve; while children who were institutionalized regressed). Lovaas et al. (1973, p. 156)

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These results indicated that parent training was critical to a participant’s long-term maintenance of skills originally learned in a clinical setting. Lovaas et al. (1973) also paved the way for one of the most influential articles in ABA and autism treatment (Lovaas, 1987). Lovaas (1987) was discussed in previous chapters, but it is important to note that one key variable was the training that parents received in the study. Within the article, Lovaas (1987) stated, “The parents worked as part of the treatment team throughout the intervention; they were extensively trained in the treatment procedures so that treatment could take place for almost all of the subjects’ waking hours, 365 days a year.” (p. 5). As Leaf et al. (2008) stated, the parents became experts in ABA and ASD. The work of Bruce Baker has also been instrumental in molding the APM (e.g., Baker et al., 1980). For example, Baker et al. (1980) conducted a study evaluating parent training for 95 families of individuals diagnosed with intellectual disabilities. This study was a 14-month follow-up of a previous study (Heifetz, 1977). The purpose was to evaluate the long-term maintenance of parent education and training. The results showed that 44% of parents continued to implement the procedures taught through parent education and training. The study indicated the importance of leaving parents with instructional materials after training had ended. In another study, Baker and Brightman (1984) compared parents who were trained as teachers to parents who were trained as advocates. Baker and Brightman measured parental knowledge about procedures as well as advocacy behaviors. The results indicated that those assigned to the teaching condition scored better on teaching and those assigned to the advocacy group better understood laws, regulations, and advocacy. Baker has also been instrumental in developing methods to evaluate parents on their implementation of behavioral intervention, assessing reasons why parents drop out of parent training, and other materials to support the use of effective parent training (Baker, 1988; Baker & Clark, 1987; Baker et al., 1980; Brightman et al., Brightman, Baker, Clark and Ambrose, 1982; Clark et al., 1982; Ellingsen et al., 2014; Marquis & Baker, 2019; Tung et al., 2019). The work of Sandra Harris has also been instrumental in how the APM approaches parent support for families who are caring for an individual diagnosed with ASD (Harris, 1984). In a seminal study, Harris et al. (1981) taught 11 families how to implement behavioral intervention to their autistic children who were in preschool. Harris and colleagues randomly divided the parents into two groups receiving parent training either in the home or in a research lab at a university. Each group received 10 weeks of instruction using behavioral skills training (BST) that followed the curriculum created

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by Baker et al. (1976). The training covered behavior analytic procedures (e.g., shaping, reinforcement, punishment) and how to target language for individuals diagnosed with ASD. Additionally, Harris and colleagues conducted home visits throughout the study, with home visits consisting of BST targeting specific procedures. The main measure was the children’s language after training. The results showed that children assigned to both conditions made significant language gains.

Summary Parents are an important factor in any child’s success, and over the years, the research has demonstrated this. Having a child diagnosed with ASD is stressful to many parents (Baker et al., 2002; Fisman & Wolf, 1991; Wolf et al., 1989) and may require specialized training. Within the APM, we consider parents to be an important member of the treatment team and providing them education and support is often required. The goal is not to have parents become therapists. Rather, parents should learn the necessary skills to be as consistent as possible with implementing the principles of applied behavior analysis with their child in their everyday lives.

References Baker, B. L. (1988). Evaluating parent training. The Irish Journal of Psychology, 9(2), 324–345. https://doi.org/10.1080/03033910.1988.10557724. Baker, B. L., Blacher, J., Crnic, K. A., & Edelbrock, C. (2002). Behavior problems and parenting stress in families of three-year-old children with and without developmental delays. American Journal of Mental Retardation, 107(6), 433–444. https://doi.org/ 10.1352/0895-8017(2002)1072.0CO;2. Baker, B. L., & Brightman, R. P. (1984). Training parents of retarded children: Programspecific outcomes. Journal of Behavior Therapy and Experimental Psychiatry, 15(3), 255–260. https://doi.org/10.1016/0005-7916(84)90034-X. Baker, B. L., Brightman, A. J., Heifetz, L. J., & Murphy, D. M. (1976). Behavioral problems. Research Press. Baker, B. L., & Clark, D. B. (1987). Intervention with parents of children with mental retardation. In S. Landesman, P. M. Vietze, & M. J. Begab (Eds.), Living environments and mental retardation (pp. 269–292). American Association on Mental Retardation. Baker, B. L., Heifetz, L. J., & Murphy, D. M. (1980). Behavioral training for parents of mentally retarded children: One-year follow-up. American Journal of Mental Deficiency, 85(1), 31–38. Brightman, R. P., Baker, B. L., Clark, D. B., & Ambrose, S. A. (1982). Effectiveness of alternative parent training formats. Journal of Behavior Therapy and Experimental Psychiatry, 13(2), 113–117. https://doi.org/10.1016/0005-7916(82)90051-9. Burt, S. (2021). Listening in coaching. In J. Passmore (Ed.), The coaches’ handbook: The complete practitioner guide for professional coaches (pp. 104–113). Routledge/Taylor & Francis Group.

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Cihon, J. H., Ferguson, J. L., Leaf, J. B., Leaf, R., McEachin, J., & Taubman, M. (2019). Use of a level system with flexible shaping to improve synchronous engagement. Behavior Analysis in Practice, 12(1), 44–51. https://doi.org/10.1007/s40617-018-0254-8. Clark, D. B., Baker, B. L., & Heifetz, L. J. (1982). Behavioral training for parents of mentally retarded children: Prediction of outcome. American Journal of Mental Deficiency, 87(1), 14–19. Ellingsen, R., Baker, B. L., Blacher, J., & Crnic, K. (2014). Resilient parenting of children at developmental risk across middle childhood. Research in Developmental Disabilities, 35(6), 1364–1374. https://doi.org/10.1016/j.ridd.2014.03.016. Fenske, E. C., Krantz, P. J., & McClannahan, L. E. (2001). Incidental teaching: A notdiscrete-trial teaching procedure. In C. Maurice, G. Green, & R. M. Foxx (Eds.), Making a difference: Behavioral intervention for autism (pp. 75–82). PRO-ED. Fisman, S., & Wolf, L. (1991). The handicapped child: Psychological effects of parental, marital, and sibling relationships. Psychiatric Clinics of North America, 14(1), 199–217. https:// doi.org/10.1016/S0193-953X(18)30333-2. Fryling, M. J. (2014). Contextual intervention for caregiver non-adherence with behavioral intervention plans. Child and Family Behavior Therapy, 36(3), 191–203. https://doi.org/ 10.1080/07317107.2014.934172. Harris, S. L. (1984). The family of the autistic child: A behavioral systems view. Clinical Psychology Review, 4(3), 227–239. https://doi.org/10.1016/0272-7358(84)90001-1. Harris, S. L., Wolchik, S. A., & Weitz, S. (1981). The acquisition of language skills by autistic children: Can parents do the job? Journal of Autism and Developmental Disorders, 11(4), 373–384. https://doi.org/10.1007/BF01531613. Hartley, S. L., Barker, E. T., Seltzer, M. M., Floyd, F., Greenberg, J., Orsmond, G., & Bolt, D. (2010). The relative risk and timing of divorce in families of children with an autism spectrum disorder. Journal of the Division of Family Psychology of the American Psychological Association (Division 43), 24(4), 449–457. https://doi.org/10.1037/ a0019847. Hastings, R. P., Kovshoff, H., Ward, N. J., Espinosa, F. D., Brown, T., & Remington, B. (2005). Systems analysis of stress and positive perceptions in mothers and fathers of preschool children with autism. Journal of Autism and Developmental Disorders, 35, 635–644. https://doi.org/10.1007/s10803-005-0007-8. Heifetz, L. J. (1977). Behavioral training for parents of retarded children: Alternative formats based on instructional manuals. American Journal of Mental Deficiency, 82(2), 194–203. Leaf, R., Dayharsh, J., Rafuse, J., McEachin, J., & Leaf, J. B. (2023). The clinician’s toolbox: Rediscovering compassionate ABA. DRL Books. Leaf, R. B., McEachin, J. J., & Taubman, M. (2008). Sense and nonsense in the behavioral treatment of autism: It has to be said. Different Roads to Learning. LeBlanc, L. A., Taylor, B. A., & Marchese, N. V. (2020). The training experiences of behavior analysts: Compassionate care and therapeutic relationships with caregivers. Behavior Analysis in Practice, 13(2), 387–393. https://doi.org/10.1007/s40617-019-00368-z. Lovaas, O. I. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55(1), 3–9. https://doi.org/10.1037//0022-006x.55.1.3. Lovaas, O. I., Koegel, R., Simmons, J. Q., & Long, J. S. (1973). Some generalization and follow-up measures on autistic children in behavior therapy. Journal of Applied Behavior Analysis, 6(1), 131–165. https://doi.org/10.1901/jaba.1973.6-131. Marquis, W. A., & Baker, B. L. (2019). Comparing observations and perceptions of motheradolescent conflict: Youth with typical development, intellectual disability, or autism spectrum disorders. Journal of Mental Health Research in Intellectual Disabilities, 12(3–4), 196–210. https://doi.org/10.1080/19315864.2019.1679300.

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McKenna, J. W., Flower, A., & Adamson, R. (2016). A systematic review of function-based replacement behavior interventions for students with and at risk for emotional and behavioral disorders. Behavior Modification, 40(5), 678–712. https://doi.org/ 10.1177/0145445515621489. Seaver, J. L., & Bourret, J. C. (2014). An evaluation of response prompts for teaching behavior chains. Journal of Applied Behavior Analysis, 47(4), 777–792. https://doi.org/10.1002/ jaba.159. Stokes, T. F., & Baer, D. M. (1977). An implicit technology of generalization. Journal of Applied Behavior Analysis, 10(2), 349–367. https://doi.org/10.1901/jaba.1977.10-349. Taylor, B. A., LeBlanc, L. A., & Nosik, M. R. (2019). Compassionate care in behavior analytic treatment: Can outcomes be enhanced by attending to relationships with caregivers? Behavior Analysis in Practice, 12(3), 654–666. https://doi.org/10.1007/s40617-01800289-3. Tung, I., Noron˜a, A. N., Morgan, J. E., Caplan, B., Lee, S. S., & Baker, B. L. (2019). Patterns of sensitivity to parenting and peer environments: Early temperament and adolescent externalizing behavior. Journal of Research on Adolescence, 29(1), 225–239. https://doi. org/10.1111/jora.12382. Valentino, A. L., Conine, D. E., Delfs, C. H., & Furlow, C. M. (2015). Use of a modified chaining procedure with textual prompts to establish intraverbal storytelling. The Analysis of Verbal Behavior, 31(1), 39–58. https://doi.org/10.1007/s40616-014-0023-x. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203. Wolf, L. C., Noh, S., Fisman, S. N., & Speechley, M. (1989). Brief report: Psychological effects of parenting stress on parents of autistic children. Journal of Autism and Developmental Disorders, 19(1), 157–166. https://doi.org/10.1007/BF02212727. Wolf, M., Risley, T., & Mees, H. (1963). Application of operant conditioning procedures to the behaviour problems of an autistic child. Behaviour Research and Therapy, 1(2–4), 305–312. https://doi.org/10.1016/0005-7967(63)90045-7.

CHAPTER 29

Siblings Contents Sibling relationship throughout the lifespan The Autism Partnership Method and siblings Caregivers Regular meetings Counseling Sibling support group Behavioral intervention and siblings References

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Siblings have a special and unique relationship with one another. Because siblings are usually raised in the same environment, they share many of the same histories and memories. About siblings, Luhrmann (1998) said, “… they’re your best link to your past. And the people most likely to stick with you in the future.” When a family has a child diagnosed with autism spectrum disorder (ASD), it can cause disruption to the family unit. Siblings are not immune to this disruption. Fortunately, Ferraioli and Harris (2009) reported that “The majority of brothers and sisters of children with ASD function well as children, adolescents, and adults” (p. 50). This does not mean that having a brother or sister with autism does not affect the sibling or the sibling relationship. Researchers have shown that having a sibling with ASD can have positive effects such as enhanced selfconcept/emotional intelligence (Verte et al., 2003), resiliency (Bayat, 2007), a closer sibling bond (Olufowote et al., 2019), and joining a helping profession (Lounds Taylor & Shivers, 2011). Researchers have also found that having a sibling with ASD can have negative effects such as displaying more problem behaviors themselves (Brewton et al., 2012), lower levels of prosocial behavior (Toth et al., 2007), displaying negative emotions (Watson et al., 2021), negative impacts on social life and friendships (Watson et al., 2021), and feeling responsible and burdened for caring for their sibling as they grow older (Roper et al., 2014). It is for these reasons that interventionists and supervisors must have a good understanding of the role of siblings

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throughout the lifespan. More importantly, supervisors must know how best to help siblings of individuals diagnosed with ASD.

Sibling relationship throughout the lifespan For young children, what they know about autism is what they see and hear in the confines of their own home. As it is very likely that their sibling is the first exposure they have to any person with a developmental disability or with ASD. As early as 3 years of age, and for sure by 6 years of age, a neurotypical (NT) child will realize that there is something different about their sibling diagnosed with ASD compared to other sibling relationships they encounter (Green, 2013). In early childhood, the NT sibling may generalize their knowledge of ASD and misunderstand the causes and or effects of ASD (Green, 2013). If the sibling with ASD displays aggression or other forms of challenging behavior, this can put the NT sibling at risk for emotional and physical harm and often negatively impacts the NT sibling’s relationship with friends (Benedrix & Sivberg, 2007; Green, 2013). Additionally, stereotypic behavior may be very confusing to the NT sibling as it stands out in comparison to the behaviors of others in their environment. It is at this time that the bond between siblings is strong; however, sometimes the NT sibling takes on a caregiver role. Finally, jealousy or resentment can occur at this age since parents might need to spend a great deal of time with the sibling diagnosed with ASD. As a NT sibling enters adolescence, their knowledge of ASD continues to increase, the bond with their sibling with ASD can strengthen, and they engage in more shared activities together (Orsmond et al., 2009). In adulthood, the relationship can change positively and negatively. It is reported that for NT female siblings, the relationship in adulthood continues to strengthen and become more positive, while NT male relationships with female siblings with ASD deteriorate (Orsmond et al., 2009). Individuals with a sibling diagnosed with ASD must consider their sibling’s future and welfare as their parents grow older and often have to become the primary manager of care or caregiver (Moss et al., 2019). Ensuring that their sibling has proper housing, support, health care, and interventions throughout the course of their life can be very stressful and a major concern for the NT sibling. Often, this role of caregiving leads to more altruistic behaviors in adulthood, and it is often predictive of working in a helping profession (Lounds Taylor & Shivers, 2011).

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The Autism Partnership Method and siblings Caregivers One of the best ways a supervisor can help siblings is by helping the caregivers. Research and clinical practice have shown that having a child diagnosed with ASD can be stressful for caregivers (Bonis, 2016). It is not uncommon for caregivers to feel overwhelmed, depressed, or have anxiety (Bitsika & Sharpley, 2016). A lot of the focus of their lives suddenly turns to their child diagnosed with ASD: finding services; attending educational placement school meetings; taking their child to behavioral intervention and other services; or working additional jobs to save for their child’s needs after they pass away. Being a parent of a child diagnosed with ASD is a very busy and, often, hectic life. All too often, the sibling may be left behind or, at least, feel left behind.

Regular meetings One of the ways in which we help caregivers is by having regular meetings with supervisors and the caregivers. During these meetings, the supervisor can help parents find the best ways to make time for their other child(ren), help them with ways to talk about autism with their other child(ren), and help them better manage all of the stressors in their lives. During these meetings, the supervisor will individually talk to the caregivers away from other interventionists and their children. This is done so that an authentic conversation and plan can be reached without others listening. Along these lines, within the Autism Partnership Method (APM), it is often the case that we refer parents to receive additional counseling services. Typically, these counseling services are provided by either a Marriage and Family Therapist or a licensed psychologist. This professional often works in conjunction with the behavior analysts but also works on larger issues with parents such as reducing stress. When working with parents, one of the molecular goals is to teach them the best ways to talk to their children about the sibling who has been diagnosed with ASD. A parent should provide the right amount of information about ASD and explain it in a way that the sibling can understand. Too little information can lead to more questions, anxiety, and filling in the gaps with inaccurate information sought out from unreliable sources. Too much information can overwhelm the sibling and decrease comprehension of ASD. Rather, the parent must provide just the right amount of information which can be a challenge. Thus, part of our role is to help them with explaining a

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diagnosis to their typically developing children and offering any support the parents may need. Additionally, we need to help guide parents to ensure that they are supporting (physically and emotionally) the children who are not diagnosed with ASD. This may be ensuring that the other children have a special time with the caregiver (e.g., a special day with them) so they receive individualized attention. Further, a supervisor may need to work with the parent on ensuring that the siblings feel that they can come to the parents with any concerns or questions that they may have.

Counseling A second way in which the APM supports siblings is recommending or providing counseling services for the sibling, when needed. If the sibling is showing signs of anxiety, depression, withdrawal, or challenging behavior, counseling services might be warranted. Once again, these counseling services are provided by either a Marriage and Family Therapist or a licensed psychologist. These counseling services should be a safe place where the sibling can work through their issues/concerns with a licensed helping professional.

Sibling support group A third approach is offering a sibling support group. These support groups are set up with a variety of siblings of individuals diagnosed with ASD. The support groups can be more (e.g., going over topics each week) or less structured (e.g., having a theme and letting them discuss). Sibling groups are an excellent way for children, adolescents, or adults to come together and discuss challenges and commonalities. They are also excellent because they allow the siblings to realize that they are not alone. Discussing these feelings may make their journey easier knowing that others are dealing with similar issues. Further, it can allow for the forming of support networks with each other, which could result in lifelong friendships. Research has shown that sibling support groups can have an overall positive effect on the sibling and the sibling relationship (Zucker et al., 2022).

Behavioral intervention and siblings One form of intervention that has increased in popularity is sibling-mediated interventions (e.g., Walton & Ingersoll, 2012). Research has shown that siblings can be the ones who help provide the intervention (Bene & Lapina, 2021). In turn, becoming “mini” therapists. While we certainly endorse

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teaching siblings better ways to interact and/or play with each other, we do not endorse using siblings as therapists during intervention. Within the APM, we do not want siblings to have the burden of providing intervention. Further, we do not want siblings to participate in social skills groups in which their sibling is participating (Leaf et al., 2020). The rationale behind this is that it takes away from their own sense of self. It makes even more of their daily life revolve around their sibling with ASD. We would never want siblings to be seen as the teacher or therapist, nor would we want the sibling to feel that their place in the family is dependent on their role with the ASD sibling. As such, we focus on developing a sibling bond outside of a teaching context. We also encourage parents to do something special with their child when possible as the person with autism is receiving intervention, so that all family members are getting equal attention and sense of belonging to the family.

References Bayat, M. (2007). Evidence of resilience in families of children with autism. Journal of Intellectual Disability Research, 51(Pt 9), 702–714. https://doi.org/10.1111/j.13652788.2007.00960.x. Bene, K., & Lapina, A. (2021). A meta-analysis of sibling-mediated intervention for brothers and sisters who have autism spectrum disorder. Review Journal of Autism and Developmental Disorders, 8, 186–194. https://doi.org/10.1007/s40489-020-002120z. Benedrix, Y., & Sivberg, B. (2007). Siblings’ experiences of having a brother or sister with autism and mental retardation: A case study of 14 siblings from five families. Journal of Pediatric Nursing, 22(5), 410–418. https://doi.org/10.1016/j.pedn.2007.08.013. Bitsika, V., & Sharpley, C. F. (2016). Stress, anxiety, and depression among parents of children with autism spectrum disorder. Australian Journal of Guidance and Counselling, 14(2), 151–161. https://doi.org/10.1017/S1037291100002466. Bonis, S. (2016). Stress and parents of children with autism: A review of literature. Issues in Mental Health Nursing, 37(3), 153–163. https://doi.org/10.3109/016122840. 2015.1116030. Brewton, C. M., Nowell, K. P., Lasala, M. W., & Goin-Kochel, R. P. (2012). Relationship between the social functioning of children with autism spectrum disorders and their siblings’ competencies/problem behaviors. Research in Autism Spectrum Disorder, 6(2), 646–653. https://doi.org/10.1016/j.rasd.2011.10.004. Ferraioli, S. J., & Harris, S. L. (2009). The impact of autism on siblings. Social Work in Mental Health, 8(1), 41–53. https://doi.org/10.1080/15332980902932409. Green, L. (2013). The well-being of siblings of individuals with autism. ISRN Neurology, 2013, 417194. https://doi.org/10.1155/2013/417194. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., OppenheimLeaf, M. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The Autism Partnership Method: Social skills groups. DRL Books. Lounds Taylor, J., & Shivers, C. M. (2011). Predictors of helping profession choice and volunteerism among siblings of adults with mild intellectual deficits. American Journal of

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Intellectual and Developmental Disabilities, 116(4), 263–277. https://doi.org/ 10.1352/1944-7558-116.3.263. Luhrmann, B. (1998). Something for everybody [Album]. Capitol Records. Moss, P., Eirinaki, V., Savage, S., & Howlin, P. (2019). Growing older with autism—The experiences of adult siblings of individuals with autism. Research in Autism Spectrum Disorder, 63, 42–51. https://doi.org/10.1016/j.rasd.2018.10.005. Olufowote, R. A. D., Turns, B., & Eddy, B. (2019). The effects of being raised with an individual with ASD. Routledge. Orsmond, G., Kuo, H. Y., & Seltzer, M. M. (2009). Siblings of individuals with an autism spectrum disorder: Sibling relationships and wellbeing in adolescence and adulthood. Autism, 13(1), 59–80. https://doi.org/10.1177/1362361308097119. Roper, S. O., Alfred, D. W., Mandleco, B., Freeborn, D., & Dyches, T. (2014). Caregiver burden and sibling relationships in families raising children with disabilities and typically developing children. Families, Systems, & Health, 32(2), 241–246. https://doi.org/ 10.1037/fsh0000047. Toth, K., Dawson, G., Meltzoff, A. N., Greenson, J., & Fein, D. (2007). Early social, imitation, play, and language abilities of young non-autistic siblings of children with autism. Journal of Autism and Developmental Disorders, 37, 145–157. https://doi.org/10.1007/ s10803-006-0336-2. Verte, S., Roeyers, H., & Buysse, A. (2003). Behavioral problems, social competence, and self-concept in siblings of children with autism. Child: Care, Health, and Development, 29(3), 193–205. https://doi.org/10.1046/j.1365-2214.2003.00331.x. Walton, K. M., & Ingersoll, B. R. (2012). Evaluation of a sibling-mediated imitation intervention for young children with autism. Journal of Positive Behavior Interventions, 14(4). https://doi.org/10.1177/1098300712437044. Watson, L., Hanna, P., & Jones, C. J. (2021). A systematic review of the experience of being a sibling of a child with an autism spectrum disorder. Clinical Child Psychology, 26(3), 734–749. https://doi.org/10.1177/13591045211007921. Zucker, A., Chang, Y., Maharaj, R., Wang, W., Fiani, T., McHugh, S., Feinup, D. M., & Jones, E. A. (2022). Quality of the sibling relationship when one sibling has autism spectrum disorder: A randomized controlled trial of a sibling support group. Autism, 26(5), 1137–1152. https://doi.org/10.1177/13623613211042135.

CHAPTER 30

Staff and staff training Contents Characteristics of quality interventionists Tireless worker Impeccable reliability Passionate about the field Eager to learn Takes initiative Embraces the Marathon Self-evaluator Requires little validation Seeks critical feedback Incorporates feedback Synthesizes information Welcomes change Enjoys variety Effortlessly multitasks Organized Good communicator Thrives under pressure Assertive decision maker Calculated Precise with timing Creative Fun Does not create or participate in drama Understands their role Team player Inspires staff Makes others better Objective Balances big and small picture Systematic Effective with all children Exercises clinical judgment Critical thinking Clinically skilled

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Additional skills interventionists should display Professionalism General skills Curriculum Implementation of procedures Additional skills supervisors should display Knowledgeable Report writing Presenting Staff training Caregiver training Staff training Summary References

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Throughout this book, we have described different principles and procedures which help comprise what we have termed the Autism Partnership Method (APM). One of the most important variables of quality intervention is having well-trained staff implementing these procedures with a high degree of quality and fidelity. Our clinical and empirical data have demonstrated that learners make meaningful improvements when the intervention is implemented by high-quality staff (Leaf et al., 2011). High-quality staff are vital to implementing the best possible intervention, as the procedures used in the APM should be implemented in a flexible manner that is rooted in clinical judgment and in-the-moment assessment. An interventionist should be knowledgeable in all principles and procedures within the APM, how to effectively implement all procedures, and how to make changes in-the-moment allowing for maximized, meaningful learning. Numerous behaviors define what constitutes a quality staff, with some behaviors being more important than others (Cihon et al., 2023). We have identified 34 behaviors that comprise a quality staff member. We have also identified an additional four domains of behavior that a direct line staff should display and five domains of behavior that a supervisory level staff should display. Although it is highly unlikely that any one staff would display all of these behaviors, each one is an important skill set and something for which to strive and train. Some of these behaviors have been described in greater detail in It’s Time for School! Building Quality ABA Educational Programs for Students with Autism Spectrum Disorders (Leaf et al., 2008), The Autism Partnership Method: Social Skills Groups (Leaf et al., 2020), and The Clinician’s Toolbox: Rediscovering Compassionate ABA (Leaf et al., 2023).

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Characteristics of quality interventionists Tireless worker One analogy that we use with our staff is to ask if they want to be recreational, competitive, or an Olympic swimmer. A recreational swimmer is a person who never practices and occasionally swims on the weekends. A competitive swimmer is a person who practices several hours daily so they can win competitions. But an Olympic swimmer is a person who dedicates their life to their craft (e.g., trains nonstop, eats exactly the right food, sleeps exactly on schedule). In essence, their life is swimming. It is desirable for interventionists to be either competitive or Olympic swimmers. They are ideally dedicated to learning all about applied behavior analysis (ABA) and autism spectrum disorder (ASD). Interventionists should work to improve their skills over time and never stop learning. Being a tireless worker is vital because the learners we work with deserve nothing less.

Impeccable reliability A quality interventionist is one that shows up. They are not late to sessions nor leave early. They rarely cancel sessions because they understand and care about the negative impacts their absence would have on the clients they serve. Not only their attendance but also their work (e.g., time sheets, session notes, data) and its quality are reliable (e.g., on time, accurate). Overall, they are someone on whom you can count.

Passionate about the field One’s quality of work is often directly related to their passion for their profession. Ultimately, interventionists should be passionate about the field. They should love the field of behavior analysis and autism and respect the ultimate responsibility that they have working with clients with autism (i.e., the clients’ lives are in their hands). A quality interventionist treasures working with autistic individuals and understands how much of a difference they make in the lives of these individuals and their families. Interventionists should work because they know they are improving the lives of so many and not simply receiving a paycheck.

Eager to learn Passion creates a desire to learn. As John Wooden famously said, “It’s what you learn after you know it all that counts.” This means interventionists should regularly participate in activities that expand their knowledge

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(e.g., attend conferences, listen to podcasts, read curriculum books and research articles) because they believe that there is always more to learn. This often also means interventionists go on to acquire additional advanced degrees and certifications in behavior analysis and ASD. Interventionists should want to learn everything they can about ABA and ASD.

Takes initiative An eager person does not wait for growth to happen, rather they take initiative and create opportunities for themself. This includes an interventionist seeking out their supervisors with ideas, asking for feedback, and taking the lead in their careers. They set in motion a path to progress their knowledge and skills.

Embraces the Marathon All too often interventionists want to quickly advance through their organization and become supervisors. The field, largely due to certification, has created the idea that direct line staff after 2 years in the field and 1500–2000 experience hours are qualified to become a supervisor. Essentially, the view is that anyone with a master’s degree and a certification can effectively supervise other interventionists. Within the APM, advancing through the organization and becoming a supervisor takes time and a specific skill set (regardless of academic degree and certifications). It takes substantial practice and dedication. Becoming a supervisor or even gaining a promotion as an interventionist should not be based on a degree or the number of hours of experience. Rather, an interventionist’s performance of the necessary skills with a high level of competence should dictate movement and promotion. Interventionists that desire achieving a supervisory position should not only accept but also understand and share the belief that it is a process that cannot be rushed.

Self-evaluator A quality interventionist is one who can self-evaluate and self-reflect on their own behavior. They can identify the areas they are excelling in, the areas which they are adequate at, and the areas which need improvement. They recognize and are comfortable knowing that they are going to need to constantly improve and develop their skill set. They can identify short- and long-term goals for improvement and adjust their goals as needed. It is important to self-evaluate their overall skills as an interventionist, and their

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effectiveness throughout a session. A strategy that was effective in one moment may not necessarily continue to be effective the next. Quickly and accurately assessing their effectiveness on a moment-to-moment basis maximizes meaningful learning opportunities for the client.

Requires little validation When an interventionist can self-evaluate, they are already aware of their strengths and therefore require little validation. They do not need to be constantly told that they are doing well, as they can recognize this in the meaningful progress that their client is making. They do not ask how they are doing on certain tasks simply for the purpose of receiving praise from others. They find the job itself reinforcing and a child learning and progress serves as validation and a reinforcer for their behavior. Essentially, they care more to hear about how they can improve than to hear about areas in which they already excel.

Seeks critical feedback In their effort to focus on the areas in which they require improvement, a quality interventionist will seek critical feedback. They do not want to be told what they are doing correctly but would rather be told what they can do better next time. They also do not wait for a supervisor to tell them what they need to improve upon, rather they take the initiative to pursue the feedback themselves because they identify the personal and therapeutic value. This skill often coincides with being eager to learn.

Incorporates feedback Not only does a quality interventionist seek feedback, but they apply and incorporate the feedback immediately, then sustain it consistently. In clinical practice, it is not uncommon to observe staff who accept the feedback that is provided to them in-the-moment but rarely or even never make changes based on that feedback. Thus, no real improvement occurs, and the same feedback is given repeatedly. For an interventionist to be considered a quality interventionist, they need to make the changes based on feedback. In a situation where the interventionist does not know how to make the changes, they should request further explanation and/or guidance from their supervisor.

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Synthesizes information Receiving feedback from a supervisor is part of the training process and it is not uncommon for an interventionist to receive feedback from multiple supervisors. Sometimes this feedback is consistent, while other times it may vary and be applicable only to a specific context. A quality interventionist must take the feedback from these multiple sources, synthesize it, and apply it to the intervention based on the multiple contexts and sources of information. Essentially, the interventionist should be able to interpret the feedback provided in the context of the principles of behavior rather than receive the feedback as a blanket rule. If confusion remains, then the interventionist should seek clarification from the supervisors.

Welcomes change As John C. Maxwell said, “Change is inevitable. Growth is optional.” A quality interventionist does not stress over new changes, but instead sees them as an opportunity to grow. Change can occur in many ways (e.g., schedule, programming, supervisor, behavior plan, operations). Quality interventionists do not try to avoid or escape changes, rather they readily welcome them.

Enjoys variety An interventionist often has multiple responsibilities and tasks on any given day. Interventionists may have to work with a client in the morning, write a report in the afternoon, then run a social skills group at the end of the day. It is essential that an interventionist not only be able to shift from executing one responsibility to another within an appropriate time frame, but also find joy in the variety and range of responsibilities.

Effortlessly multitasks Not only does an interventionist need to juggle multiple tasks throughout their day, but also simultaneously. A quality interventionist should implement a behavior plan with high fidelity, monitor for patterns of behavior, teach a new skill, assess prompting strategies, gauge potential distractors, collect data, and evaluate the type and rate of reinforcement, etc. simultaneously within a single teaching opportunity. This mental and physical multitasking must occur continuously throughout an effective session.

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Organized Quality interventionists establish their own organizational systems and have all needed materials, reinforcers, data collection, and files readily available. They should also construct a plan for a meaningful flow within their session (e.g., challenging targets are balanced with easier ones, reinforcers are rotated, proactive approach). If interventionists do not develop or have their own organizational system, they problem solve and reach out to others who can help develop and increase their organizational skills.

Good communicator A quality interventionist is multilingual. Not in the sense that they speak multiple languages, rather they can clearly and effectively transmit information to different audiences. The interventionist needs to know how to communicate in the language of behavior analysts, teachers, paraprofessionals, other professionals, supervisors, supervisees, parents, siblings, and other family members; this includes being an active and empathetic listener. This means they must be able to confer technically with some audiences and avoid technical jargon (Critchfield et al., 2017) when speaking to others. They must be able to speak in a way that the listener will understand.

Thrives under pressure Working with individuals diagnosed with ASD can sometimes be stressful and chaotic. Interventionists must balance the implementation of quality intervention, reducing challenging behavior, collecting and analyzing data, and having fun during sessions. There are times where it becomes very challenging to manage all these different aspects of their job within a session. Pressure may be self-imposed or come from families, supervisors, or other professionals. Quality interventionists can handle this pressure. They remain calm, focused, and objective in all situations. They can problem solve which aspect of their job takes priority over other aspects at that moment and develop a plan that is in the best interest of the learner. Doing so ensures that clients are receiving the best intervention possible.

Assertive decision maker Part of being able to handle pressure is being able to make decisions quickly. Quality interventionists are decisive across a variety of situations. They realize that mistakes happen and that making a mistake is not the end of the world, rather a learning opportunity. It is better to choose decisively, not

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waver, analyze the outcome of the decision, then adjust accordingly in the next situation.

Calculated Decisions are constantly made throughout a session; however, it is important that decisions are also analytical and calculated. A quality interventionist is observant of patterns of behaviors not only within their session, but also over time. This gives them the ability to predict behaviors quite accurately and carefully time moments that increase the expectation for the client (e.g., difficulty, independence).

Precise with timing In order to teach effectively, impeccable timing is required on the part of the interventionist in order to facilitate the connection between a behavior and a consequence. Poor timing can result in learner confusion and inefficient teaching. An interventionist must be able to provide meaningful consequences with precision.

Creative The APM requires interventionists to be creative. They must be creative in terms of how they provide instruction, develop new curriculum and programs, modify old curriculum, present and sell reinforcers, etc. This requires that the interventionist think outside of the box and probe new programs and/or curriculum. It means that they might make mistakes, but that these mistakes will be learning opportunities that will result in better intervention and curriculum. Some learners require repeated practice of a specific and limited set of skills, so the interventionist needs to keep the necessary repetition from feeling monotonous for the learner.

Fun Interventionists need to be fun. They must become a conditioned social reinforcer (Leaf et al., 2016) for the learners with whom they work. Becoming a social reinforcer increases a learner’s motivation to learn and engage in the learning process. There are many ways that interventionists can be fun. One way to become a conditioned reinforcer is the interventionist using expressive voice tones and interactions to ensure that their praise or corrective feedback is different than when they provide instructions. A second way is to use a variety of instructional materials. Having materials that are

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functional and ever changing may reduce boredom for learners and make learning fun. A third way is to use toys, activities, and items that are fun, preferred by the learner, and interesting. Another way of being more fun is to follow the learner’s lead and allow them to control components of the session. Being fun means actively playing with the learner, not just sending them off for a break without engagement. It means running around, playing silly games, and often acting like a child yourself while playing.

Does not create or participate in drama The biggest killer of any organization or agency is drama between staff members. When interventionists bring drama into the company it may be a sign that they are not a team player. We have seen staff bully other members of a team, attempt to make other members of the team look incompetent, and recruit other staff to team up against staffs that they do not like. We have also seen principals of schools play favorites with teachers and not provide the same level of support to other teachers and aides whom they do not like as much. All of this can make the workplace a hostile environment and in turn and can negatively impact the learners and their progress. In essence, drama is reflective of interventionists who may not be there for the purpose of making a positive difference in their clients’ lives.

Understands their role On some teams an interventionist might be the lead interventionist and on others they may not. On some teams an interventionist might be the best interventionist but the weakest on others. No matter the case, the interventionist should understand their role, the dynamic of the team for that case, and then follow the job responsibilities of that role.

Team player Since quality interventionists do not bring drama to the agency and know their role, they are the ultimate team players. They do whatever it takes to make themselves better, make their colleagues better, and in turn help learners make the most progress possible. They do the job that is required of them while also supporting other colleagues and staff members. They see the value in helping others become just as, if not more skilled than themselves.

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Inspires staff A quality interventionist’s passion, positivity, and supportiveness are infectious and will organically inspire staffs to be like them. They will lead by example and make staffs want to be better behavior analysts and professionals in general.

Makes others better James Sherman, a founder in the field of ABA (Leaf, Leaf, & McEachin, 2018), always used to say, it does not matter how good you are as a behavior analyst, but rather how good you can make others become. Whether you are a supervisor or an interventionist, one of the goals should be to make your teammates better. Providing them with advice, working and collaborating with them on skill deficits, and providing praise can all lead to making others better.

Objective ABA is an objective science. ABA relies on objective data. Although subjective data can and should be used in the context of social validity (Wolf, 1978), an interventionist must be objective when making decisions. An interventionist should make decisions based on what is occurring in the environment, what they observe, and what the data tell them rather than making decisions based on emotions, gut feelings, or personal biases. This helps ensure that the most effective interventions are occurring.

Balances big and small picture Balancing the big and small picture is related to programming. It is knowing why the program is currently being implemented (i.e., short-term goals) and why the program and corresponding goals are important for the learner in the long run. Two clients may have the same programmatic target (e.g., matching) for very different reasons (e.g., one as a learning how to learn skill and the other for flexibility), which is important to in order to emphasize and expand the appropriate areas.

Systematic Quality interventionists have a plan. They methodically plan out their sessions. They go into each session knowing what objectives they want the learner to achieve, how they want to teach these objectives, and what reinforcers to use and develop within a session. Quality interventionists are often

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obsessive about being systematic. Their attention to the details is extraordinary. A quality interventionist ensures the environment is always set up to facilitate learner success. They are not only systematic in the overall approach to the session, but also within their teaching. They are aware of the effects of an array of variables (e.g., naturalness of language, amount of structure, temptation of materials) and the effects these variables have on the skills and behaviors that they are teaching. A skilled interventionist can fluidly break skills down or build them up to meet the learner’s current needs.

Effective with all children Autism is a spectrum disorder. Meaning that there are going to be learners that interventionists work with who have vocal-verbal behavior and learners who do not. There will be learners who engage in high rates of stereotypic behavior and others who engage in serious challenging behavior. There will be some learners who are social and some who struggle with social initiations and motivation. There will be some learners who have typical cognitive functioning while others are more impacted cognitively. A quality interventionist is effective with learners across the spectrum. This does not mean that an interventionist starts out being effective with all learners, rather it means that interventionists stay within their scope of competence (Brodhead et al., 2018) and receive further training and supervision for learners with whom they do not have expertise.

Exercises clinical judgment What sets apart a quality interventionist who embraces the APM is the use of clinical judgment. This means that the interventionist makes changes based on the learner and the environment. They might go into a session with a plan but quickly realize that plan will have to change. Simply put, quality interventionists are flexible. For more information about the concept of clinical judgment see Chapter 2, though the essence of clinical judgment is present throughout this book.

Critical thinking Clinical judgment requires a quality interventionist to be a critical thinker. They make their decisions based on critical analysis of many variables. They examine all possible explanations for what is occurring and make an analytic decision about the best possible explanations. They are healthy skeptics and are always questioning. They also know how to critically evaluate research

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and other interventions and can distinguish science from pseudoscience and antiscience (Green, 1996).

Clinically skilled An interventionist can be great at implementing a variety of procedures, conditioning themselves as reinforcers, taking data, and thinking critically and still be an ineffective interventionist. One way that this could occur is lacking soft skills and clinical sensitivity. Unfortunately, our field has a mixed history of being clinically skilled and sensitive (Leaf et al., 2023; LeBlanc et al., 2020; Taylor et al., 2019); this has resulted in numerous attacks about behavior analysts’ ability to be humane. Although clinical skills were an integral part of ABA pioneering work, it is only recently that the softer side of behavior analysis has been rediscovered (see Leaf et al., 2023; Leaf, Leaf, & McEachin, 2018). Fortunately, the area of soft skills and compassion is being discussed more frequently by behavior analysts in the past few years (Leaf et al., 2023; LeBlanc et al., 2020; Taylor et al., 2019). In order to implement the APM, an interventionist must lead with compassion, humility, and humaneness. They must attempt to understand the struggle and emotions that their clients experience. They must empathize with the difficulties a parent faces, and the challenges autistic children face as well. At the same time, they must also realize they will never fully understand because they have not lived in their client’s shoes. Regardless, they must show compassion and always display these soft skills, which may be the most important skills in an interventionist’s repertoire.

Additional skills interventionists should display Professionalism In addition to the skills mentioned previously, there are other professional behaviors that an interventionist should display. These include: (a) being a good ambassador (e.g., making positive comments about the agency for which they work), (b) dressing appropriately, (c) maintaining professional boundaries, (d) following through on commitments, (e) behaving ethically, and (f ) being culturally sensitive.

General skills There are other general skills that an interventionist should display. These general skills include: (a) an engaging and natural teaching style, (b) conducting

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teaching sessions that are appropriate in duration, and (d) understanding the research behind the methods that they are implementing.

Curriculum Interventionists also must have a thorough understanding of curriculum (see Chapters 23–27). This means that an interventionist understands the priority list of goals for a learner and understands the short- and long-term goals of a program. Additionally, an interventionist must know the mastery criterion of any given program. This way the interventionist can move onto the next target and not keep a learner in a program that is already mastered, ultimately causing boredom, and wasting the learner’s time. Further, an interventionist must demonstrate how to blend programs (i.e., they combine multiple targeted behaviors in a single activity). Finally, an interventionist must prioritize programs within a given session by selecting the most important goals to work on in any given moment.

Implementation of procedures One of the main behaviors an interventionist must engage in is implementing procedures with a high degree of fidelity and quality. Thus, an interventionist must engage in several important behaviors throughout each session. These skills include: (a) identify potential reinforcers, (b) condition reinforcers, (c) implement a variety of contingency systems, (d) implement discrete trial teaching, (e) implement incidental teaching, (f ) implement flexible prompt fading, (g) implement shaping, (h) implement the teaching interaction procedure, (i) implement the Cool versus Not Cool procedure, (j) implement behavior management procedures, (k) collect data appropriately, (l) provide shadow support within a group, and (m) be able to conduct group instruction.

Additional skills supervisors should display Knowledgeable In addition to the aforementioned skills, a supervisor has to display additional knowledge and skills. First, supervisors must understand evidence-based practice, nonevidence-based practice, empirically supported treatments, and pseudoscience or antiscience (e.g., Green, 1996; Leaf, Cihon, et al., 2018). This is because there are thousands of interventions that are propagated for autistic individuals. A supervisor needs to be able to identify if an intervention is evidence-based or not and know how to navigate situations

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when a request is made to implement or oversee nonevidence-based procedures. Second, a supervisor should have a deep knowledge of ABA. This means that they should know the history of the field, past research, current research, and an understanding of historical figures (e.g., Don Baer, Ivar Lovaas, Sandra Harris, Joseph Wolpe) and their contributions to our field. Third, a supervisor needs to understand school systems and the Individualized Education Program (IEP) process. This is because often the supervisor must write goals as part of the IEP, attend the IEP meetings, and ensure that their client is receiving the best intervention possible. Fourth, a supervisor must have a thorough understanding of formal assessments (e.g., Wechsler Intelligence Scale for Children, Vineland Adaptive Behavior Scales, Gilliam Autism Rating Scale), how to interpret assessment scores, and how to use assessments to help guide curriculum and behavioral intervention plans. Finally, a supervisor must have a complete understanding of the characteristics of ASD.

Report writing In addition to the skills mentioned above, a supervisor must write thorough and accurate reports which include: (a) describing baseline levels of behavior, (b) writing objective information about the client, (c) using appropriate language, (d) writing objective, meaningful goals, (e) selecting an appropriate data collection method, (f ) analyzing data, and (g) making accurate and well-formatted graphs.

Presenting Often supervisors must present publicly, whether these are presentations to parents, school districts, or at national/international conferences. It is imperative that supervisors engage in many important behaviors when presenting including: (a) developing clear slides, (b) speaking with professionalism (e.g., reframing from derogatory comments), (c) using appropriate body posture, (d) talking for appropriate duration, (e) expanding on their main points, (f ) using universal language, (g) having an appropriate speaking style, and (h) answering questions appropriately.

Staff training One of the main job responsibilities of any supervisor is to train interventionists. When training interventionists, the supervisor must prioritize the goals of the interventionists, ensuring that they are working on the most

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important targets. The supervisor must also identify effective ways to build rapport with interventionists so that a collaborative and productive relationship is developed. Also, a supervisor must be able to describe and model any program (e.g., waiting, nonverbal imitation, sharing toys) they are training the interventionists to implement with a high degree of fidelity and quality. Supervisors need to be able to provide individualized, systematic, and proactive training (just as they would do so when teaching a child). Additionally, a supervisor must provide appropriate feedback (e.g., reinforcement, corrective feedback) to interventionists based on the interventionists’ behavior. Finally, a quality supervisor must be able to listen to the interventionists and all of their concerns.

Caregiver training Supervisors often have a lot of contact with caregivers. They must work collaboratively with parents and be able to train parents how to implement important skills. This means that a supervisor must (a) convey information in a sensitive way, (b) assess level of understanding, (c) empathize with parents, (d) build rapport with parents, (e) provide parents with accurate information, (f ) model procedures and principles appropriately, (g) provide objective information to parents, (h) avoid dual relationships, (i) balance a prescriptive and psychoeducational approach, and (j) accurately assess situations with the learner and caregivers.

Staff training To implement the APM with a high degree of fidelity, it takes a quality interventionist who is well trained. Within the APM, training is intensive and comprehensive. A trainee does not complete training until they perform procedures with a high degree of fidelity and quality. Thus, training is not time-based, but rather performance-based. It is not 40, 100, 2000 h, or even 20,000 h of training that will determine if staff are qualified, but it is when they can effectively perform the tasks that are needed as part of their job. Training within the APM consists of multiple modalities. First, training consists of didactic information. Within the didactic training, the trainer discusses different concepts, curriculum, principles, and procedures which they might implement. This training should be at least 40 h and provides interventionists with foundational knowledge. Training does not conclude with the didactic training but proceeds into other modalities.

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The second modality is role-playing with the supervisor. Role-playing provides opportunities for the supervisor to arrange specific situations in an analog setting where the situation can be reasonably controlled. This allows the supervisor to specifically focus on specific behaviors with the interventionist without any other distractions. It also allows for the supervisor to provide specific feedback and consequences in a less intimidating setting. Once the interventionist is proficient in role-play, the training then happens with actual learners. Most of the training occurs hands-on with the population with whom the interventionist will be providing intervention. During this type of training, the interventionist works directly with the learner diagnosed with ASD. The supervisor arranges specific goals (e.g., working on conditioning reinforcers, providing instructions, fading prompts) during each session. The supervisor then provides feedback in-the-moment and after a teaching session. When needed, the supervisor may model the correct behavior for the interventionist. The goal is to shape the interventionist’s behavior over time. The combination of these modalities is the best way to produce well-trained interventionists. These training modalities are not necessarily presented in a perfectly linear manner. The trainer must be flexible in their implementation and use clinical judgment in order to meet the interventionist in training’s current needs.

Summary Overall, a high-quality interventionist will be able to provide clients with high-quality therapy using the APM. An interventionist is not expected to flawlessly display all the traits outlined above from the outset of training, rather those skills should be encouraged, taught, and progressed over time such that growth is ongoing. The domains that a supervisor should be able to demonstrate are even more critical, as their skills must also translate to and be effective with new interventionist, family members, caregivers, and other professionals. The journey will take time, but ultimately the clients we serve will benefit tremendously when demonstrating competence as an interventionist and supervisor are prioritized.

References Brodhead, M. T., Quigley, S. P., & Wilczynski, S. M. (2018). A call for discussion about scope of competence in behavior analysis. Behavior Analysis in Practice, 11(4), 424–435. https://doi.org/10.1007/s40617-018-00303-8.

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Cihon, J. H., Milne, C. M., Weiss, M. J., & Weinkauf, S. M. (2023). Some important repertoires to consider when training autism interventionists. In J. L. Matson (Ed.), Handbook of applied behavior analysis for children with autism (pp. 193–208). https://doi.org/ 10.1007/978-3-031-27587-6_10. Critchfield, T. S., Doepke, K. J., Epting, L. K., Becirevic, A., Reed, D. D., Fienup, D. M., Kremsreiter, J. L., & Ecott, C. L. (2017). Normative emotional responses to behavior analysis jargon or how not to use words to win friends and influence people. Behavior Analysis in Practice, 10(2), 97–106. https://doi.org/10.1007/s40617-016-0161-9. Green, G. (1996). Evaluating claims about treatments for autism. In C. Maurice, G. Green, & S. C. Luce (Eds.), Behavioral intervention for young children with autism: A manual for parents and professionals (pp. 15–28). Pro-Ed. Leaf, J. B., Cihon, J. H., Ferguson, J. L., Taubman, M., Leaf, R., & McEachin, J. (2018). Social Thinking®, pseudoscientific, not empirically supported, and non-evidence based: A reply to Crooke and Winner. Behavior Analysis in Practice, 11(4), 456–466. https://doi. org/10.1007/s40617-018-0241-0. Leaf, R., Dayharsh, J., Rafuse, J., McEachin, J., & Leaf, J. B. (2023). The clinician’s toolbox: Rediscovering compassionate ABA. DRL Books. Leaf, R., Leaf, J. B., & McEachin, J. (2018). Clinical judgment. DRL Books. Leaf, R., McEachin, J., & Taubman, M. (2008). Sense and nonsense in the behavioral treatment of autism: It has to be said. DRL Books. Leaf, J. B., Milne, C. M., Leaf, J. A., Rafuse, J., Cihon, J. H., Ferguson, J. L., Leaf, R., McEachin, J., & Mountjoy, T. (2020). The autism partnership method: Social skills groups. Different Roads to Learning. Leaf, J. B., Oppenheim-Leaf, M. L., Townley-Cochran, D., Leaf, J. A., Alcalay, A., Milne, C., Kassardjian, A., Tsuji, K., Dale, S., Leaf, R., Taubman, M., & McEachin, J. (2016). Changing preference from tangible to social activities through an observation procedure. Journal of Applied Behavior Analysis, 49(1), 49–57. https:// doi.org/10.1002/jaba.276. Leaf, R. B., Taubman, M. T., McEachin, J. J., Leaf, J. B., & Tsuji, K. H. (2011). A program description of a community-based intensive behavioral intervention program for individuals with autism spectrum disorders. Education and Treatment of Children, 34(2), 259–285. LeBlanc, L. A., Taylor, B. A., & Marchese, N. V. (2020). The training experiences of behavior analysts: Compassionate care and therapeutic relationships with caregivers. Behavior Analysis in Practice, 13(2), 387–393. https://doi.org/10.1007/s40617-019-00368-z. Taylor, B. A., LeBlanc, L. A., & Nosik, M. R. (2019). Compassionate care in behavior analytic treatment: Can outcomes be enhanced by attending to relationships with caregivers. Behavior Analysis in Practice, 12(3), 654–666. https://doi.org/10.1007/s40617-01800289-3. Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203.

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Index Note: Page numbers followed by f indicate figures and t indicate tables.

A ABA. See Applied behavior analysis (ABA) Aberrant Behavior Checklist (ABC), 198–199, 207, 274 Access to preferred items, 205–206 Active coaching, 349 Active learning, 184 Activity-based instruction, 157–158 Adaptive Behavior Assessment System (ABAS), 270 Advanced conversation, 321 Antecedent-behavior-consequence (ABC) data collection, 208 Antecedent functional analysis, 213 APM. See Autism Partnership Method (APM) APM prompting system, 126–130 Appearance checks, 334–335 Applied behavior analysis (ABA), 1, 17–18, 205–206, 212, 342–343, 363 application, 11 certification, 8–9 definition, 2 dimensions, 2–3, 3t early research and publications, 3–6 equity, 9–10 progressive approach to, 10–11, 26 seminal research and publications, 6–8 social validity within, 3 Approach-based assessments, 55–56 Assessment of Basic Language and Learning Skills—Revised (ABLLS-R), 281 Assessments, 268–276 Attending skills, 291–293 Attention. See Social positive reinforcement Auditory attending, 321–322 Autism Diagnostic Interview Revised (ADI-R), 268–269 Autism Diagnostic Observation Schedule (ADOS), 268–269 Autism Partnership Method (APM), 117, 136, 157–158, 160–162, 171, 179 autism intervention, 18

behavior, 206 behaviorally based social skills groups (see Behaviorally based social skills groups) clinical judgment decision-making model, 18–19 learning-how-to-learn skills, presence/absence of, 20 learning, learner’s receptivity to, 19–20 nonverbal and verbal behavior, 18–19 physical and emotional health, 20–21 reinforcing items and activities, 20 undesired behavior, presence/ absence of, 19 compassion, 23 curricular assessment, 283–285 flexible procedures, 22 functional analysis (FAs), 214–216 functional behavioral assessment (FBA), 214–216 history of, 23–26 learner centered, 21 meaningful and functional curriculum, 21–22 of parent support active coaching, 349 compassion and understanding, leading with, 344 parental support groups, 347–348 parent counseling, 350 parent education, 348–349 parent training, research on, 350–352 psychoeducational approach, 343–347 understanding and embarrassment, 345 performance-based staff training, 23 siblings, with ASD behavioral intervention, 358–359 caregivers, 357 counseling, 358 regular meetings, 357–358 support group, 358 time-out, 244–245 whole family, working with, 22–23 379

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Autism spectrum disorder (ASD), 159–161 siblings with, 355–356 Autism Supplement Quality of Life, 275–276 Automatic reinforcement, 205–206

B Backward chaining, 99–100 Basic conversation, 321 Basic efficiency and organization, 335 Behavior, 29–30, 205 applied behavior analysis (ABA), 205–206 control, 206 function, 205 respondent behavior, 206 Behavioral contrast, 66 Behavioral intervention, 17, 39, 188 and siblings, 358–359 Behaviorally based social skills groups autism partnership method (APM), research on, 197–200 caregivers, 195–196 contingency systems, 194 curriculum, 194–195 definition, 191 evidence-based practices and conceptually systematic, 192–193 as naturalistic as possible, 194 peers, 195 research, 196–197 sessions, 196 teachable moments, 193 teaching strategies, use of, 193 for young children, 191 Behavioral skills training (BST), 351–352 Behavioral steps, 95 Behavioral treatment, 7–8 Behavior Analyst Certification Board (BACB), 8 Behavior analytic leadership, 10 Behavior analytic research, 2 Behavior chain, 95 Behaviorism, 2 Blank task analysis data sheet, 98–99, 99t Board Certified Assistant Behavior Analysts (BCaBAs), 8

Board Certified Behavior Analysts (BCBAs), 8 Brief functional analysis, 209–210, 213–214 Brigance Inventory of Early Development (IED) III, 281–282

C Caregivers, 215 Certification, applied behavior analysis, 8–9 Clinical judgment, 18–21 CNC procedure. See Cool versus Not Cool (CNC) procedure Communication temptations, 160, 318–319 Compassion, 344 Competitive token system, 83–84 Conditional discrimination, 40–41 Conditional-only method, 151–152 Conditioning reinforcers, 57–60 considerations in, 59–60 in desired environment, 60 individual preferences, 59–60 research examples, 57–59 Constant time delay, 121–122 Contingency skills, 288–289 Contingent observation, 240 Controlling prompt, 115 assessment, 120 Conversation advanced, 321 basic, 321 intermediate, 321 movers and stoppers, 322–323 Cool versus Not Cool (CNC) procedure history, 185–188 labeling, 179–180 misuses, 184–185 modeling/demonstrations, 180–183 research, 185–188 role-play, 183–184 steps, 179–184 Cooperation, 289–291, 290f Corrective feedback, 70, 179–181, 183–184 Counseling parent counseling, 350 for siblings, 358 Counter conditioning, 88–89, 91–92 COVID-19, 188

Index

Crossing the street safely, 336 Curriculum, 21, 194–195 meaningful and functional curriculum, 21–22 Curriculum assessments, 280–283 Autism Partnership Method, 283–285

381

Discriminations, 40 Discriminative stimulus, 135–136, 142–144 Diversity, in behavior analysis, 10 DTT. See Discrete trial teaching (DTT) Duration measurement system, 262

E D Decision-making model, 18–19 Delay-denial tolerance training, 213–214 Descriptive assessments, 208 Diagnostic process stress, 342 Diapers, 332 Differential reinforcement, 109–111, 219 vs. graduated reinforcement, 223–225 progressive considerations, 223–226 putative reinforcers, ranking of, 225–226 Differential reinforcement of alternative behavior (DRA), 220–221 Differential reinforcement of high rates of behavior (DRH), 222 Differential reinforcement of incompatible behavior (DRI), 221–222 Differential reinforcement of low rates of behavior (DRL), 222–223 Differential reinforcement of other behavior (DRO), 219–220 Discrete trial teaching (DTT), 135–136, 161–162 components, 135–152 conditional-only method, 151–152 discriminative stimulus, 142–144 feedback, 146–147 field size, 139–140 instructional format, 136–138 group instructional format, 137–138 one-to-one instructional format, 136–137 instructive feedback, 147–149 intertrial interval, 150 learner’s response, 145–146 mass trialing vs interspersal, 150–151 placement and rotation of stimuli, 140–141 prompts, 144–145 simple-to-conditional method, 151–152 trial order, 141–142

Eden Autism Assessment, 282 Elicited aggression, 65 Embedded instruction, 157–158, 161–162 Emotional behavior, 91 Emotional responding, 65 Empathy, 344 Engagement-based assessments, 55–56 Environmental awareness, 293–294 Equity, 9–10 Error correction, 128, 149 Escape/avoidance, 65–66 Essential for Living, 281 Estimation scale, 254–256, 256t Exclusionary time-out from positive reinforcement, 240–241 Expanding language, 320 Experimental analysis of behavior (EAB), 2 Expressive labels, 319–320 Expressive One Word Picture Vocabulary Test, 274 External reinforcement, 76–77 Extinction clinical studies, 231–232 ignoring, 230–231 misperceptions and clarifications, 230–233 naturally occurring behavioral contingency, 232–233 punishment, 232 schedule of reinforcement, 230 target behavior, elimination of, 231 Extinction-based procedures, 90–91

F Faulty stimulus control, 42 FBA. See Functional behavioral assessment (FBA) Feedback, 146–147 Fidgeting, reducing of, 295 Finding the Message in the Chatter, 322

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First trial data, 259–260 Flexible earning requirement, 78–79, 81 Flexible prompt fading, 119–120, 126–130 Follow the conversation thread, 322 Formal assessments, 268 Formal experimental functional analysis, 214–215 Forward chaining, 99–101 Free-operant preference assessments, 51 Frequency data collection, 260–262 Full physical prompt, 116–117 Full verbal prompt, 116 Functional alternative behavior, 206–207 Functional analysis (FA) attention condition, 208–209 autism partnership method (APM), 214–216 challenging behavior, 209 escape condition, 209 experimental functional analysis, 208–209 history, 212–214 types brief functional analysis, 209–210 latency-based functional analysis, 210–211 practical functional assessment, 211–212 precursor functional analysis, 211 standard functional analysis, 209 trial-based functional analysis, 210 Functional Analysis Screening Tool (FAST), 207 Functional behavioral assessment (FBA) autism partnership method (APM), 214–216 challenging behavior, 206–207 descriptive assessments, 208 functional alternative behavior, 206–207 functional analysis (see Functional analysis) history of, 212–214 indirect measures, 207–208 Functional communication training (FCT), 213–214, 220 Functional replacement behaviors, 346

G Generalization, 41–46 Gilliam Autism Rating Scale (GARS), 269 Graduated reinforcement, 223–225 Group estimation data sheet, 254–256, 257t Group instructional format, 137–138

H Habilitation, right to, 8 Hawaii Early Learning Profile (HELP), 283

I IMRA. See In-the-moment reinforcer analysis (IMRA) Incidental teaching, 157–160 Incorrect alternative prompt, 118–119 Individualized education program (IEP), 342, 373–374 In-moment assessment, 215–216 Instructional format, 136–138 Instructive feedback, 147–149 Intensive toilet training, 331–332 Intermediate conversation, 321 Intermittent schedules, 45 International Behavior Analysis Organization, 8–9 Interspersal, 150–151 Intertrial interval, 150 Intervention stress, 343 In-the-moment analysis, 215–216 In-the-moment assessment, 103, 106–107 In-the-moment reinforcer analysis (IMRA), 51–54, 52t

J Janitorial skills, 100 Joint attention, 299–300, 300t Journal of the Experimental Analysis of Behavior, 4–5 Jumpstarts, 25

Index

K Keep it interesting, 322

L Language curriculum auditory attending, 321–322 communication temptations, 318–319 conversation advanced, 321 basic, 321 intermediate, 321 movers and stoppers, 322–323 expanding language, 320 expressive labels, 319–320 Finding the Message in the Chatter, 322 follow the conversation thread, 322 keep it interesting, 322 matching, 317–318 nonverbal imitation, 317 pronouns, 320–321 proper skepticism, 323 receptive instructions, 318 receptive labels, 318 verbal imitation, 319 Latency-based functional analysis, 210–211 Learner’s response, 145–146 Learning-how-to-learn skills, 138 attending, 291–293 contingency, 288–289 cooperation, 289–291, 290f definition, 287 environmental awareness, 293–294 joint attention, 299–300, 300t learning from prompts, 297 Magic word, 298 memory, 297–298 observational learning, 298–299, 299t reducing fidgeting, 295 returning reinforcers, 294–295 wait, 295–297 Least-to-most prompting, 123 Level systems, 84–85

M Magic number token system, 82–83 Magic word, 298 Mand-model procedure, 157–158

383

Mass trialing, 150–151 Matching, 317–318 Mealtime challenges, 333 Meaningful rationale, 166–167 Measurement system accurate, 253 advantages, 254, 255t disadvantages, 254, 255t duration, 262 estimation data, 254–258, 256–257t first trial data, 259–260 frequency, 260–262 momentary time sampling, 263–264 partial interval recording, 263 reliable, 252 staff preference and skill, 253–254 task analysis, 260, 261t teaching opportunities, 254 trial-by-trial data, 258, 259t usefulness, 253 valid, 252 whole interval recording, 262–263 Memory matching, 297–298 Model prompt, 116 Momentary time sampling, 263–264 Most-to-least prompting, 124, 128–129 Motivational Assessment Scale (MAS), 207 Mullen Scales of Early Learning, 272 Multiple alternative prompt, 118–119 Multiple-stimulus preference assessments, 51 Multiple stimulus without replacement (MSWO) preference assessment, 54 Mute psychotics, 4

N Naturalistic instruction, 157–162 embedded instruction, 161–162 incidental teaching, 158–160 Naturalistic probe, 181 Naturalistic teaching, 136–137 Natural language, 157–158, 171 Negative punishment, 64 Negative reinforcement, 49 Neurotypical (NT) sibling’s relationship, 356 Nighttime toileting, 332–333 Noncontingent reinforcement, 194

384

Index

Noncontrolling prompt, 115 Nonexclusionary time-out from positive reinforcement, 240 No-no-prompting, 124–125, 129 Nonverbal behavior, 19 Nonverbal imitation, 317

O Observational learning, 298–299, 299t Obstacle course, 293–294 One-to-one instructional format, 136–137 Open-ended interview, 211–212 Operant behavior, 32–33 operant conditioning, 33 Operant bigotry, 90 Operant prominence, 34

P Paired-stimulus preference assessments, 51, 53–54 Parenting Stress Index, 275 Parents, of autistic children autism partnership method (APM), of parent support active coaching, 349 compassion and understanding, leading with, 344 parental support groups, 347–348 parent counseling, 350 parent education, 348–349 parent training, research on, 350–352 psychoeducational approach, 343–347 understanding and embarrassment, 345 diagnostic process stress, 342 intervention stress, 343 postdiagnosis stress, 342–343 prediagnosis stress, 341–342 Partial interval recording, 263 Partial physical prompt, 116–117 Partial verbal prompt, 116 Peabody Picture Vocabulary Test, 274 Peer models, 96 Peers, 195 Performance-based staff training, 23 Personal liberties, right to, 8 Physical prompt, 116–117 Pivotal response training, 157–158

Planned ignoring, 240 Point/gestural prompt, 115–116 Portable Operant Research and Teaching Lab (PORTL), 107–108 Positional prompt, 117 Positive punishment, 64 Positive reinforcement, 49 Postdiagnosis stress, 342–343 Practical functional assessment, 211–212 Precursor functional analysis, 211 Prediagnosis stress, 341–342 Preference assessments, 50–51 Premack principle, 225 Priming prompt, 117–118 Probe-and-test model, 216 Problem behavior, 6–7 Program for the Education and Enrichment of Relational Skills (PEERS) model, 197 Progressive Behavior Analyst Autism Council, 8–9 Progressive time delay, 122–123 Prompting systems, 119–126 common conventional prompting, 120–126 constant time delay, 121–122 least-to-most prompting, 123 most-to-least prompting, 124 no-no-prompting, 124–125 progressive time delay, 122–123 simultaneous prompting, 120–121 stimulus fading, 125–126 stimulus shaping, 126 Prompts, 144–145 defined, 115 learning from, 297 types, 115–119 Pronouns, 320–321 Proper skepticism, 323 Psychoeducational approach, 343–347 Psychoeducational Profile Revised—Third Edition (PEP-3), 282 Punishment, 63, 71–72 behavioral contrast, 66 in behavior analysis, 63–64 clinical considerations, 67–70 contextual effects, 68–69

Index

emotional responses, 65 escape/avoidance, 65–66 negative punishment, 64 overuse, 66–67 positive punishment, 64 procedures, 64–67 punishment-based procedures, 70–71 corrective feedback, 70 time-in ribbon, 70–71 response probability, 68 temporary use, 69

Q Quality behavioral intervention, 17–18, 24–25

R Radical behaviorism, 2 Rapid prompting method, 192 Recency prompt, 117–118 Receptive instructions, 318 Receptive labels, 318 Reduction of the field prompt, 118 Reflexes, 30–32 Reflexive aggression, 65 Registered Behavior Technicians (RBTs), 8 Reinforcement, 4–5, 49–50, 99–100, 109–112, 346–347 identification, 50–57 context, 55 formal preference assessments, 50–51 in-the-moment reinforcer analysis (IMRA), 51–54, 52t measures, 55–56 time, 56–57 Reinforcers, returning of, 294–295 Replacement behaviors, 347 Respondent aggression, 65 Respondent behavior, 30–32, 31t, 87–88, 93, 206 in autism intervention, 89–93 benefits, 90–91 conditioning, 88–89 counter conditioning, 88–89, 91–92 extinction-based procedures, 90–91 respondent conditioning, 30–32, 91–92

385

systematic desensitization, 92–93 teaching emotions, 91 Respondent conditioning, 30–32, 31t, 87 counter conditioning, 91–92 procedures, 91–92 Respondent/operant distinction, 33–34 Response classes, 34–35 Response cost definition, 233–234 implementing procedure, 234–235 misperceptions and clarifications, 234–235 progress, effects, and misuse, 236 recommendations for practice, 235–237 society, 234 Role-play Cool versus Not Cool (CNC) procedure, 183–184 teaching interaction procedure (TIP), 165, 169

S Same-aged peer model, 96 Scheduled toilet training, 330–331 Secret word, 293 Selection-based assessments, 55–56 Self-advocacy, 337 Self-help and adaptive behaviors appearance checks, 334–335 basic efficiency and organization, 335 crossing the street safely, 336 mealtime challenges, 333 outline of, 327–328, 328–329t self-advocacy, 337 sleep, 334 toilet training, 329–333 diapers, 332 intensive training, 331–332 nighttime toileting, 332–333 schedule training, 330–331 visual/written schedule, following of, 336–337 walking, 335–336 Self injurious behavior (SIB), 6–7, 211–213, 231–232 Self-monitoring systems, 101, 194 Sensory dysregulation, 346–347

386

Index

Sequential modification, 43 Sequential trial, 137 Shaping clinical recommendations avoid overreliance on protocols, 107–109 be patient, 111–112 contact behavior analytic animal training literature, 109 linear and nonlinear approaches, 109–111, 110f nonlinear perspective, 109–111 shape and shape often, 109 definition, 103 research, 103–107 Shell game, 292 Siblings, with ASD, 355–356 autism partnership method (APM) behavioral intervention, 358–359 caregivers, 357 counseling, 358 regular meetings, 357–358 sibling support group, 358 neurotypical (NT) sibling’s relationship, 356 Simple discrimination, 40 Simple-to-conditional method, 151–152 Simultaneous prompting, 120–121 Single-stimulus preference assessments, 51 Slapjack, 292–293 Sleep, 334 Social awareness, 308 Social behaviors, 96 Social communication, 186, 309 Social discrimination, 179 Social interaction, 185–186, 309 Social learning, 309–310 Social negative reinforcement, 205–206 Social positive reinforcement, 205–206 Social relatedness, 310 Social Responsiveness Scale (SRS), 198–199, 273 Social skills, 101 how to teach, 310–311 taxonomy, 307–310 awareness, 308 communication, 309 interaction, 309

learning, 309–310 relatedness, 310 why we teach, 303–305 Social skills groups. See Behaviorally based social skills groups Social Skills Improvement System (SSiS), 198–199, 272 Social stories, 175, 186 Social thinking, 192 Social validity questionnaire, 264t, 265 Staff and staff training additional skills, interventionists curriculum, 373 general skills, 372–373 implementation of procedures, 373 professionalism, 372 additional skills, supervisors caregiver training, 375 knowledgeable, 373–374 presentations, 374 report writing, 374 staff training, 374–375 quality interventionists, characteristics of analytical and calculated, 368 assertive decision maker, 367–368 balances big and small picture, 370 clinical skills, 372 creative, 368 critical thinking, 371–372 desire to learn, 363–364 does not create/participate in drama, 369 effective with all children, 371 enjoys variety, 366 exercises clinical judgment, 371 fun, 368–369 good communicator, 367 impeccable reliability, 363 incorporates feedback, 365 inspire staffs, 370 makes others better, 370 multitasks, 366 objective, 370 organizational systems, 367 passion for their profession, 363 precise with timing, 368 requires little validation, 365 seek critical feedback, 365

Index

self-evaluator, 364–365 supervisory position, 364 synthesizes information, 366 systematic, 370–371 takes initiative, 364 team player, 369 thrives under pressure, 367 tireless worker, 363 understands their role, 369 welcomes change, 366 training within APM, 375–376 Staff preference and skill, 253–254 Standard functional analysis (SFA), 6–7, 209, 213–214 Stimulus class, 34–35 Stimulus control, 39–42 Stimulus fading, 125–126 Stimulus shaping, 126 Synchronous engagement, 79–80, 106–107 Systematic desensitization, 92–93

T Tangible positive reinforcement, 205–206 Task analysis, 95–99 blank task analysis data sheet, 98–99, 99t and chaining, 99–100 research, 100–101 selection of, 101 competent model, 96 creation, 96–97 critical steps, 97 data sheet, 98–99, 98t, 171, 172f mastery creation, 97 measurement, 260 peer models, 96 Teaching Family Model, 173 Teaching interaction procedure (TIP), 165, 349 components, 166–170 considerations, 171–172 demonstration, 168–169 description, 167–168 feedback, 169–170 generalization, 170 label and identify, 166 rationales, 166–167

387

research, 173–176 role-play, 169 Teaching procedures, 193 Telehealth, 188 Time delay prompting, 128–129 Time-in ribbon procedure, 70–71, 245–247 practical considerations, 245–246 research on, 246–247 Time-out from positive reinforcement (TOPR) contingency, explanation of, 243 duration, 242 exclusionary, 240–241 exit criterion, 242–243 legal requirements, 243 nonexclusionary, 240 practical considerations, 241–243 research on, 243–244 TIP. See Teaching interaction procedure (TIP) Toilet training, 329–333 diapers, 332 intensive training, 331–332 nighttime toileting, 332–333 schedule training, 330–331 Token economy, 85 behavioral intervention, use in, 75 behaviors, improving/developing, 75–76 extrinsic reinforcement, 76–77 Token systems, 85 advantages and disadvantages, 77–78 clinical recommendations, 80–81 components, 76 progressive approaches competitive, 83–84 level system, 84–85 magic number, 82–83 reduction of the field, 82 research on, 78–80 Total task chaining, 99–100 Treatment fidelity data sheet, 173f Trial-based functional analysis, 210, 213–214 Trial-by-trial data, 258, 259t

388

Index

U

W

UCLA Young Autism Project, 23–24 Undesired behavior, 19

Wait card, 295–296, 296f Waiting skills, 295–297 Walker-McConnell Scale of Social Competence and School Adjustment, 273 Walking, 335–336 Wechsler Intelligence Scale for Children-V (WISC-V), 271 Wechsler Preschool and Primary Scale of Intelligence-IV (WPPSI-IV), 271–272 Whole interval recording, 262–263 Whole-task presentation/chaining. See Total task chaining Women, in behavior analysis, 9 World Health Organization Quality of LifeBREF, 275–276 Written prompt, 116

V Verbal behavior, 19 Verbal Behavior Milestones Assessments and Placement Program (VB-MAPP), 280 Verbal imitation, 319 Verbal prompt, 116 Video modeling, 101 Vineland-3 Adaptive Behavior Scales, 269–270 Visual attending, shaping of, 291–292 Visual/written schedule, following of, 336–337