Relational Frame Theory: Made Simple 3031194209, 9783031194207

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Teresa Mulhern

Relational Frame Theory Made Simple

Relational Frame Theory

Teresa Mulhern

Relational Frame Theory Made Simple

Teresa Mulhern South East Technological University Wexford, Ireland Behaviour Detectives

Kilkenny, Ireland

ISBN 978-3-031-19420-7    ISBN 978-3-031-19421-4 (eBook) https://doi.org/10.1007/978-3-031-19421-4 © Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To my parents – for their unwavering support and never-ending belief in my ability. To Sahil – for your endless patience, understanding and love. To Dr Ian Stewart – for your mentorship, expertise and boundless knowledge. To Dr Laura Moran – for planting the seed of interest. To Dr Elle B. Kirsten and Dr Shane McLoughlin – I couldn’t have done it without you! To the wonderful people who have supported and enabled me to be the best version of myself throughout this process (and many others).

Preface

As a second-year undergraduate student in 2009, I was required to write an assignment on Relational Frame Theory (RFT), which seemed incredibly intimidating to me at the time. I quickly attempted to source readings to try to understand the theory, but... I must admit, that I was rather lost on the topic. After many, many, many mugs of tea and re-reading material more times than I am comfortable to admit, I eventually cobbled together an assignment to submit. As I handed in the hard copy of that assignment, I loudly proclaimed that I would never do RFT again. I was reminded of this fact four years later when I happened to bump into an old classmate who was suitably confused when, upon being asked what I was up to, I informed him that I was pursuing a PhD in the area of RFT. And now that you know that I am not a woman of my word, and cannot actually be trusted, I should probably clarify how this book (and my interest in RFT) came into being... Between 2011 and 2013, I pursued an MSc in Applied Behaviour Analysis and began using behavioural psychology within applied practice. I was incredibly fortunate to work on a program in conjunction with Dr Laura Moran during this time. It was during several shared car journeys that she shared the rationale behind her PhD research in RFT and I slowly came to understand the potential of RFT in applied practice. I returned to my readings and pestered Laura with endless questions on the theory and its applications (which she patiently answered), and I came to the conclusion that the only logical step forward for me was to pursue research in the field of RFT. Fortunately, the option to pursue a thesis in this domain was not only possible as part of my degree, but I also was able to persuade the exceptional Dr Ian Stewart to supervise me in my endeavours. Under his mentorship and tutelage, I gained a greater appreciation and knowledge of RFT – and will always be grateful for that (particularly in agreeing to extend his supervision of my MSc thesis to that of a PhD). I grew to further understand the complexity and depth of the field, with its simultaneously simple framework, and all that it had to offer during this time. I often think about how different the events of my life, research path and career might have been if it weren’t for the series of circumstances that brought me back to RFT  – I might indeed have never liaised with RFT ever again after that

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second-­year assignment. So, this lead me to the conclusion that a textbook that could simply explain RFT and its applications (in a step-by-step manner) may be useful for people like me who might otherwise be intimidated by the area. After all, it’s never too late to learn, and it’s never too late to learn RFT. Kilkenny, Ireland

Teresa Mulhern

Contents

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 The World of Psychology Before Relational Frame Theory����������������    1 Early Behaviourism���������������������������������������������������������������������������������     1 Behaviourism: Finding a Path for the Science����������������������������������������     3 Skinner (the Man, the Myth, the Legend)…and His Box������������������������     5 Behaviourism: Carving a New Path for the Science��������������������������������     9 Skinner’s Verbal Behaviour: The Beginning of the End? Or a New Era for Behaviourism?������������������������������������������������������������     9 Sidman’s Contributions to Behaviourism and Language������������������������    13 References������������������������������������������������������������������������������������������������    22

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 What Is Relational Frame Theory?��������������������������������������������������������   25 Relational Frame Theory: What Is It?������������������������������������������������������    25 Non-arbitrarily Applicable Relational Responding: I See the Relationship There!������������������������������������������������������������������    26 Arbitrarily Applicable Relational Responding: A Level Up!������������������    27 Mutual Entailment: A Tale of Two Stimuli����������������������������������������������    29 Combinatorial Entailment: The More the Merrier!���������������������������������    30 Transformation of Stimulus Function������������������������������������������������������    31 RFT: Is It Just a Fancy Stimulus Equivalence?����������������������������������������    32 References������������������������������������������������������������������������������������������������    35

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 Relational Frames of Coordination and Sameness ������������������������������   39 Show Me the Data!����������������������������������������������������������������������������������    40 Relational Frames of Coordination: They’re All the Same!��������������������    41 Some Prerequisites..��������������������������������������������������������������������������������    42 Selecting Your Methodology��������������������������������������������������������������������    42 The Initial Steps of Teaching ������������������������������������������������������������������    54 Let’s Talk Stimuli: Non-arbitrary Training of Coordination��������������������    54 Arbitrary Relating and Coordination ������������������������������������������������������    60 Future Directions for Research and Applications?����������������������������������    63 References������������������������������������������������������������������������������������������������    65

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 Relational Frames of Opposition and Distinction������������������������������    71 And Now for Something Completely Different: A Frame of Distinction����������������������������������������������������������������������������    71 What About the Research?������������������������������������������������������������������    74 Teaching Distinction Relational Responding��������������������������������������    79 Non-arbitrary Distinction��������������������������������������������������������������������    80 AARR and Distinction: Conceptual and Theoretical Considerations������������������������������������������������������������    87 Future Directions for Research Within Distinction?����������������������������    90 The Relational Frame of Opposition��������������������������������������������������������    90 Opposition: The Research��������������������������������������������������������������������    91 Teaching Opposition: A Non-arbitrary Approach��������������������������������    99 AARR and Opposition: Teaching and Directions for Future Research������������������������������������������������������������������������������   103 References������������������������������������������������������������������������������������������������   105

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 The Relational Frame of Comparison����������������������������������������������������  109 Nothing Compares to... Research������������������������������������������������������������   110 Comparison and NAARR������������������������������������������������������������������������   119 It’s All Arbitrary: Comparison, Assessment and Training ����������������������   125 The Future of Arbitrary Comparison: Where Do We Go from Here? ����   128 References������������������������������������������������������������������������������������������������   130

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 The Relational Frame of Temporality����������������������������������������������������  131 What’s in a Contextual Cue?��������������������������������������������������������������������   133 Relational Inflexibility for Reversed Relations: Unique to Temporal Relations?����������������������������������������������������������������   135 Temporal Relations and Early Research��������������������������������������������������   136 Temporal Framing and Intellectual Potential������������������������������������������   139 Temporality and Applied Practice?����������������������������������������������������������   145 Temporality: Training and Assessment of NAARR and AARR��������������   145 The Totally Not Ironic Future of Temporal Relations: Directions for the Future?������������������������������������������������������������������������   149 References������������������������������������������������������������������������������������������������   151

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 The Relational Frames of Containment and Hierarchy����������������������  153 Hierarchy, Containment and the Link to Cognitive and Linguistic Potential ��������������������������������������������������������������������������   155 Early Research and a Search for a Model of Hierarchical Classification������������������������������������������������������������������   160 Getting Technical: RFT Explores the Fundamentals of Hierarchical Classification������������������������������������������������������������������   162 Training Deficient Repertoires of Hierarchy and Containment ��������������   165 Teaching and Training Containment and Hierarchical Repertoires ��������   171 The Future of Hierarchy and Containment����������������������������������������������   173 References������������������������������������������������������������������������������������������������   175

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Analogy: Relating Relations������������������������������������������������������������������   177 Elle Kirsten and Ian Stewart What Is Analogy?������������������������������������������������������������������������������������   178 Cognitive Science������������������������������������������������������������������������������������   178 Behavioural Science��������������������������������������������������������������������������������   180 Relational Frame Theory ������������������������������������������������������������������������   180 The Future of Analogical Relations ��������������������������������������������������������   191 References������������������������������������������������������������������������������������������������   192

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 Relational Frame Theory and Language ��������������������������������������������   197 Generative and Derived Manding in Research����������������������������������������   197 Language Deficits and AARR������������������������������������������������������������������   200 Language Emergence and RFT����������������������������������������������������������������   202 The Brain, Language and AARR ������������������������������������������������������������   203 Relational Flexibility and Language��������������������������������������������������������   204 References������������������������������������������������������������������������������������������������   208

10 RFT and Intelligence ����������������������������������������������������������������������������   211 Shane McLoughlin What Is Intelligence? ������������������������������������������������������������������������������   211 RFT and Intelligence��������������������������������������������������������������������������������   213 The SMART Programme ��������������������������������������������������������������������   214 The PEAK Programme������������������������������������������������������������������������   216 Communicating with Lay Audiences on RFT and IQ ����������������������������   220 Ten Important Unanswered Questions to Inform Future RFT Research on Intelligence������������������������������������������������������������������   223 References������������������������������������������������������������������������������������������������   224 Index����������������������������������������������������������������������������������������������������������������   229

Chapter 1

The World of Psychology Before Relational Frame Theory

Behavioural psychology has made remarkable strides forward in its understanding of language, cognition and human behaviour in the last 125 years. Even before the introduction of relational frame theory (RFT) in Hayes et  al.’s (2001) infamous Purple Book, the contributions of behavioural psychology to our current understanding of human behaviour, language and thought have been considerable. This chapter will endeavour to provide a whistle-stop tour of the face of behavioural psychology before the introduction of RFT.

Early Behaviourism The early work of Edward L. Thorndike (1898, 1901, 1905, 1907, 1909, 1911), an American psychologist, signalled the birth of modern behaviourism. As a result of his work, Thorndike identified the law of effect (1905) using a simple puzzle box and a rather bemused cat. Thorndike placed a cat in a puzzle box and observed how long it took the cat to manipulate the lever to earn freedom (and hopefully a can of tuna). When first placed within this box, Thorndike observed that the cat only happened upon the lever and pressed it by accident leading to its freedom from the box. Although this first escape occurred by mere chance, Thorndike observed that when this same cat was placed into the box for a second time, its escape by manipulating the lever was far more quick and deliberate. Subsequent exposures to the puzzle box indicated increasingly faster escape responses indicating that the cat’s lever pressing was “strengthened every time they are used with indifferent or pleasurable results” and outlined that responses could also be “weakened every time they are used and resulting discomfort” (Thorndike, 1911, p. 166). This snippet from an article composed by Thorndike over 100  years ago formed an early foundation for operant conditioning (which we will explore later). However, to put this simply, Thorndike’s law of effect maintained that behaviours which are followed by a “good effect” are strengthened (e.g. the behaviour of the cat pressing the lever and having the “good © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_1

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effect” of escaping the puzzle box), while behaviours which are followed by a “bad effect” are weakened (e.g. the behaviour of the cat pawing at the side of the puzzle box is followed by the “bad effect” of remaining in confinement). This information generally forms the basis of an introductory class to behaviourism, including my own, and Thorndike’s work seemed to signal a new age of psychology. It was as though the gods of psychology wanted the twentieth century to herald a new age of behaviourism, as shortly before Thorndike’s seminal piece on the law of effect in 1905, Ivan Pavlov, a Russian physiologist, was to present his own work on classical conditioning in 1901, ultimately earning a Nobel Prize in 1904 (see Grimsley & Windholtz, 2000). Pavlov’s work on classical conditioning (also known as respondent conditioning or Pavlovian conditioning) was a further coup for the budding field of behaviourism. But what exactly is classical conditioning? Classical conditioning involves reflexive behaviours – those responses that we have no control over, such as blinking, sneezing, sweating, sexual arousal and salivation to name but a few. These reflexive responses are entirely involuntary, meaning that the person who engages in these behaviours is not choosing to do so but is engaging in these behaviours as a result of their physiology or biological makeup. If we want to be fancy, we can say that such behaviours have “phylogenetic provenance”  – and who doesn’t want to be fancy? This means that these behaviours have arisen as a result of the species’ evolution and do not need to be explicitly learned (Skinner, 1984). These reflexive responses have occurred as a result of evolution so that when a person (or indeed any organism) encounters a specific stimulus or situation, their body engages in this reflexive response. For example, when a puff of air is introduced to the eye, a person cannot help but blink  – they do not choose to do so, but as evolution has made human beings blink when exposed to puffs of air in order to block any potential harm to the sensitive eye area, they are compelled to blink. But can these reflexive behaviours be elicited by any other stimuli? Pavlov found that they could be. For instance, a single guitar chord (we’ll say in B minor) doesn’t compel you to blink – this is termed as a “neutral stimulus”, but the puff of air (known as an “unconditioned stimulus”) can elicit an eye blink (known as an “unconditioned response”). However, if you present this B minor guitar chord at the same time as the puff of air, you will elicit an involuntary eye blink. If this is done several times, then if you just play this B minor guitar chord without also presenting the puff of air, an involuntary eye blink will still be elicited. This means that this previously neutral stimulus now has the same effect as the puff of air (or unconditioned stimulus). Once this process has occurred, this B minor guitar chord is considered to be a “conditioned stimulus”, and the eye-blinking response that it elicits is known as a “conditioned response” (see Fig. 1.1 for an illustrated example). Pavlov’s work has served as a strong foundation for behavioural therapy, specifically that of systematic desensitisation and the treatment of fears, phobias and anxiety disorders (Lissek et al., 2005; Lydon et al., 2014; Mineka & Oehlberg, 2008).

Behaviourism: Finding a Path for the Science

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Fig. 1.1  Illustration of Pavlovian/respondent conditioning

Behaviourism: Finding a Path for the Science When a new science emerges, it’s important to determine the direction that this discipline will take, and behaviourism was no different. The early years of behaviourism was marked by “methodological behaviourism”. This perspective is quite simple and essentially outlined that the scope of behavioural research (at that time) should focus on observable events or behaviours (Moore, 2013). Although methodological behaviourists acknowledge(d) that cognitive events (e.g. thoughts and feelings) existed, they felt that this was beyond the scope of testing as this was open to subjectivity – after all, the mind cannot be observed (unless you’re Professor X – in which case, you may have bigger fish to fry!). Despite focusing on only observable behaviours, research from this era still provided some valuable information regarding the formation of fears and phobias. Possibly the most well-known (and infamous) experiment of this time was the “Little Albert” experiment by John B. Watson and Rosalie Rayner (1920) – and one, which I must confess, is hard for me to read at times. Baby Albert had been reared within a hospital environment and was the sole participant in this study. Watson remarked that baby Albert “was healthy from birth and one of the best developed youngsters ever brought to the hospital… He was on the whole stolid and unemotional. His stability was one of the principal reasons for using him as a subject in this test” (Watson & Rayner, 1920, p. 1) as “at no time did this infant ever show fear in any situation” (p. 2). They also went on to say “We felt we could do him relatively little harm by carrying out such experiments” (pp 1–2). How wrong they were! Within this experiment, they used classical conditioning to condition Albert to have a startled/fear response to a number of different objects including a white rat,

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rabbit and a dog. You might recall that I said that classical conditioning was concerned with reflexive responses? Well, if a person hears a loud noise, they tend to startle (some might jump, squeal or possibly yelp) – and this is what Watson and Rayner did within this study. They found that striking a steal bar would result in an immediate startle reaction from Albert, noting that “the child started violently, his breathing was checked… in addition the lips began to pucker and tremble… the child broke into a sudden crying fit” (Watson & Rayner, 1920, p. 2). In classical conditioning terms, this unconditioned stimulus (loud sound) elicited an unconditioned response (crying and fear). They began to present a rat to Albert – as a curious 11-month-old he had no initial problem with this rat. However, they began the classical conditioning process by striking this bar whenever he went to touch the rat and over time, just seeing the rat (and things that resembled a rat – including a rabbit and cotton wool), began to elicit this fear response. This meant that these stimuli were now conditioned stimuli which elicited a conditioned fear response. Undoubtedly such an experiment would never make it past an ethics committee today, but it does indicate that by focusing on these observable behaviours (i.e. startle reflex) and employing classical conditioning, methodological behaviourists were still able to show the impact of their work. Watson, in particular, later went on to make a rather grandiose statement in his book (titled Behaviorism), which most die-hard behaviourists are probably familiar with  – “Give me a dozen healthy infants, well-formed, and my own specified world to bring them up in and I’ll guarantee to take any one at random and train him to become any type of specialist I might select- doctor, lawyer, artist, merchant-chief, and yes, even beggar-man and thief, regardless of his talents, penchants, tendencies, abilities, vocations and the race of his ancestors” (Watson, 1924, p.  104). This sort of statement seemed to reflect the feeling of the time – that behaviourism was a significant contender in the realm of psychology and was currently riding high on the crest of a major behavioural wave. Experimentation was all the rage at this point in behaviourism – discoveries were waiting to be made, and the science had yet to be fully understood. This leads to a specific branch within behaviourism known as experimental behaviour analysis. This research branch specifically focused on the “nitty gritty” of behaviourism – essentially figuring out the most fundamental and basic components of behaviour. In 1938 Burrhus F. Skinner published The Behaviour of Organisms: An Experimental Analysis outlining some of the major contributions to the field. Potentially, one of the most significant breakthroughs was the identification of the operant three-term contingency. Depending on who you ask, this is also known as an ABC contingency (antecedent, behaviour, consequence – incidentally, this is the term I tend to favour) or an SRS contingency (stimulus, response, stimulus). Essentially, this means that behaviour doesn’t occur in a vacuum – it’s subject to external forces (sounds spooky, right?). For instance, before a behaviour occurs, the organism has perceived some event within their environment (i.e. something has happened – this is known as an antecedent). The behaviour of answering a phone, for example, probably won’t be executed by a person without first hearing the phone ringing (unless you’re a child and that’s part of the game). The ringing phone is an antecedent which signals the

Skinner (the Man, the Myth, the Legend)…and His Box

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appropriateness of answering the phone. This first part of the three-term contingency started to answer one fundamental question of behaviourism – why? Why do we engage in certain behaviours? The final part of the three-term contingency provided further information to behaviourists – how probable would that behaviour be in the future? This is the consequence. The three-term contingency outlined that each behaviour is followed by a consequence which may increase or decrease the future likelihood of that behaviour. For example, if I perceive the phone to be ringing (the antecedent) and I answer it (the behaviour) to hear a call from my mother (the consequence), then I’m more likely to answer the phone in the future – particularly if we consider Thorndike’s early law of effect (1905) outlined above. This discovery was a major coup for behaviourists at that time and also resulted in further discoveries.

Skinner (the Man, the Myth, the Legend)…and His Box Skinner went on to progress Thorndike’s law of effect (1905) and provided one of the most fundamental findings of behaviourism – operant conditioning (Skinner, 1938, 1953). Operant conditioning refers to the increase or decrease of a behaviour as a result of a stimulus change. For instance, in the above phone example, I outlined an increase in the behaviour of answering the phone as a result of a stimulus change (i.e. hearing my Mother on the line) – this is an example of operant conditioning. The term operant conditioning encompasses a number of behavioural process including reinforcement, punishment and extinction. Skinner was focused on determining the exact probability of an organism emitting a behaviour and using his own Skinner box (presumably taking inspiration from Thorndike’s cat puzzle box) he set off on this mission. However, this Skinner box was far more advanced than that of Thorndike as it included a loudspeaker, lights, response lever, food dispenser and an electrified grid. It was using this box that Skinner provided evidence for reinforcement as a behavioural process. Reinforcement, in essence, is quite simple and involves any stimulus change (e.g. giving praise or turning off the air conditioning) after an individual or organism emits a behaviour that results in a future increase of that behaviour. Skinners’ work provided ample evidence and example of this – he placed a hungry rat inside the specially designed Skinner box and observed its behaviour. Initially, the rat didn’t do a lot (doubtless it was confused about its current predicament), but after a time it began to explore the confines of its new abode. While shuffling along in this box, the rat leaned against the lever – this seemingly innocuous behaviour (pressing the lever) resulted in the delivery of a food pellet from the food dispenser inbuilt in the box. The rat, quite pleased in the discovery of this food pellet happily consumed it and began once more to explore the box. As a quick aside, rats don’t have a natural tendency to press levers – after all, there are no wild levers out in the ratty wilderness. During this second box expedition, the rat again pressed the lever in the box, again resulting in the delivery of another food pellet. This process was repeated for a third, fourth and fifth time indicating

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evidence for reinforcement of lever pressing with this little rat participant. More specifically, Skinner outlined that this was an example of positive reinforcement, which involves the increase of a specific behaviour due to the addition or the presentation of a stimulus (i.e. a reinforcer). In this experiment, the behaviour of lever pressing increased as a result of the addition of the food pellet which served as a reinforcer. There are, of course, an abundance of examples of positive reinforcement within the everyday environment. For example, my cat Ceci has learned to open doors that are slightly ajar by headbutting them – this behaviour has been positively reinforced. The behaviour of headbutting ajar doors has increased in probability as it has resulted in her gaining access to another room (i.e. this is the added/ presented stimulus which acts as a reinforcer). My other cat, Lewie, will throw herself down on the ground in front of a person (the behaviour) – this has increased in probability as she receives belly rubs (i.e. the positive reinforcer) for this behaviour, meaning that this flopping behaviour has been positively reinforced by the delivery of cuddles and attention. Emmy, however, is a much more dignified cat and will instead make eye contact with a person and meow at them – this behaviour has been positively reinforced with attention and copious amounts of head cuddles. This example plays in nicely with the three-term contingency outlined above as the antecedent is the presence of a human (and the absence of a human means this meowing does not occur), the behaviour is a gentle meow while facing the human in question, and the consequence is that of a positive reinforcer (a head scratch) which increases the future probability of that behaviour. However, Skinner went on to outline that reinforcement was not confined to positive reinforcement alone  – there was another contender for the throne  – negative reinforcement. Negative reinforcement also involves the increase of a behaviour, but this is due to the subtraction or removal of a stimulus (i.e. eliminating or avoiding an aversive or unpleasant stimulus). To demonstrate this phenomenon, Skinner again turned towards a trusty rat participant and the Skinner box. Skinner again placed the rat inside the Skinner box; however, the electrified grid was activated, meaning that the chamber (and the rat within) was subject to an unpleasant electric current. The rat, startled by this electric shock, began to bustle about the box, inadvertently pressing the lever by doing so. The act of knocking against this lever immediately suspended the unpleasant electric current for a period of time. However, this reprieve was not a permanent one, and the electric grid was reactivated. The rat again scurried around in its box again knocking the lever to deactivate the electric current. After a few of these instances, the rat began to go directly to the lever to prevent the electric grid from becoming activated and therefore avoiding the unpleasant electric shock it would otherwise receive. This experiment indicated that the act of lever pressing had been negatively reinforced (i.e. that lever pressing had increased as it resulted in the removal or prevention of the electric shock). As with positive reinforcement, there are numerous examples of negative reinforcement within everyday life. For example, when your phone alarm rings at an indecent time of the morning and rudely awakens you, you’re likely to press the snooze button or press the button to stop the alarm. Why? This act has been negatively reinforced – pressing this button removes that aversive ringing noise and means that you’re more likely to do this in the future.

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However, negative reinforcement can also be further categorised into either escape or avoidance. Escape is a form of negative reinforcement in which the individual or organism has already been exposed to the aversive or unpleasant stimulus and the behaviour that they engage in seeks to escape from this. An example of this might be that if you are feeling unwell with the flu (i.e. you are already exposed to an unpleasant event or stimulus), you might take a painkiller to relieve these symptoms, and from this instance onwards, whenever you feel unwell, you turn towards taking a painkiller. The behaviour of taking a painkiller is likely to be negatively reinforced as this act has resulted in escaping feelings of sickness. Avoidance, on the other hand, is another form of negative reinforcement in which the individual has not been exposed to the aversive or unpleasant stimulus, but the behaviour they engage in seeks to avoid coming into contact with this stimulus or event. For instance, you may feel perfectly physically healthy, but you wish to avoid becoming sick during the Winter seasons, as such, you decide to invest in getting a flu shot and successfully avoid becoming sick that Winter. From then on, each Autumn, you seek out a flu vaccine – the behaviour of seeking and accepting a flu shot is negatively reinforced as this behaviour has increased in order to avoid sickness. If a stimulus change can result in an increase in a behaviour, then surely a stimulus change could also result in a decrease in a behaviour as well. Skinner went on to further his conception of operant conditioning by including the behavioural process of punishment. Punishment also involves a stimulus change following a behaviour; however, this stimulus change decreases the future likelihood of that behaviour. As with reinforcement, punishment can also be divided into positive punishment and negative punishment. Positive punishment involves the decrease of a behaviour following the addition or presentation of an aversive stimulus. For instance, as the older sister, I was legally required to mercilessly tease my younger brother (much to the chagrin of my long-suffering mother). My mother, appalled at such unmannerly behaviour, wished to stop it, and every time I would tease my brother, she would verbally reprimand me. This addition of an aversive stimulus (i.e. a verbal reprimand) after I teased my brother ultimately resulted in a decrease of teasing (at least while she was present). Another interesting example of positive punishment was that of Sajwaj et al. (1974) who had a 6-month-old client with life-threatening rumination. Due to the urgent nature of this potentially fatal behaviour, they wished to decrease and ultimately eliminate it. As such, whenever the infant began to engage in rumination, Sajwaj and colleagues added a drop of lemon juice in the infant’s mouth (i.e. the punisher). This intervention resulted in a rapid decrease in rumination and ultimately eliminated this behaviour. Negative punishment also results in a decrease in a behaviour; however, this is as a result of the removal or subtraction of a pleasant or appetitive stimulus. For example, I was not the only difficult child in the household – my younger brother would happily hit and flail in my general direction (as younger brothers have the tendency to do). Again, my long-suffering mother intervened and took his favourite toy from him whenever such behaviours arose. From then on, he refrained from this (again, if my mother was within earshot), meaning that this behaviour was negatively punished (i.e. hitting had decreased because a pleasant stimulus was taken away).

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Skinner went on to discover that punishment was not the only behavioural process which could result in a decrease or elimination of a behaviour. Extinction involves withholding reinforcement for a behaviour which ultimately results in its decrease. For instance, I once lived in an apartment complex with an elevator which I would use to get to my apartment on the second floor (it’s best not to think about how lazy I actually am). One day, I pressed the button to open the elevator but nothing happened, and after several further attempts, I surrendered to the elevator Gods and took the stairs instead. For the next few days, I didn’t bother approaching the elevator and instead chose the stairs – meaning that my behaviour of using the elevator had decreased as the reinforcement of the doors opening and bringing me to my destination was no longer being delivered. Skinner went on to outline that behaviours which were subject to extinction were also characterised by an extinction burst and spontaneous recovery. When first implementing extinction (i.e. withholding reinforcement for a previously reinforced behaviour), you generally see an extinction burst which is a sudden increase in this behaviour followed by a decrease. For example, when I attempted to open the elevator doors for my apartment, I pressed the button but nothing happened. I then pressed the button again several times in an attempt to get the door open before eventually retreating and taking the stairs. This increase in responding (i.e. pressing the elevator door button) occurred in response to the withholding of reinforcement and was also accompanied with some very colourful language on my part and a not insignificant amount of frustration. This is not uncommon as an extinction burst is typically accompanied with an emotional response, such as frustration and sometimes aggression. For example, modern dating is filled with examples of extinction and the subsequent extinction bursts. A modern dater may be enjoying a series of back-and-forth texts or online messages with their paramour when suddenly they’re no longer receiving replies to their messages – it’s as though their conversation partner has dropped off of the face of the earth. Young, cool people would say that this person has been “ghosted”, but the keen behaviourist would say that their texting behaviour had been put on extinction (i.e. the reinforcement they had received in the form of replies to their texts was no longer being provided). Typically, if a person has been ghosted (or their texting has been put on extinction), then they may send a flurry of texts, potentially with a series of expletives, before eventually giving up on their conversation partner. This sudden increase in texting was an extinction burst which was eventually followed by a decrease in texting. However, as previously outlined, the extinction process is also sometimes characterised by spontaneous recovery which is when the behaviour reappears after a period of time in which there has been no occurrences. For example, in the above elevator example, I did not stop going to the elevator forever – for a period of a week I refrained from pressing the elevator button and instead used the stairs, but by day 8, I decided I would try the elevator button again. This re-­ occurrence of a behaviour after a period of time where I had not engaged in this behaviour is known as spontaneous recovery. If this behaviour is reinforced at this point, then the behaviour is likely to return to its pre-extinction levels. For instance, on day 8, when I pressed the elevator button, the doors mercifully opened, and I resumed my regular elevator rides (i.e. the behaviour had returned to pre-extinction

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levels). Additionally, in the dating example above, while the person involved may have gone several days without contacting their conversation partner (after their texting had been put on extinction), they may decide to send a message again. This is an additional example of spontaneous recovery as it’s a resumption of the behaviour after a period of non-occurrences. However, if the individual receives no reply during this time, it is likely that this behaviour will no longer be emitted by this person. The world of extinction (and online dating), after all, can be brutal!

Behaviourism: Carving a New Path for the Science Following the experiments within early behaviourism, the procedures used began to filter out of the laboratories to be used within clinics and residential settings. The first study of this ilk was conducted by Paul Fuller in 1949 who sought to use operant conditioning with a patient who was entirely vegetative. The patient was described as being only capable of laying on his back, never moving his trunk or legs, and was unable to roll over. Fuller used a sugar milk solution to increase the patients right arm movements by providing this sugar milk solution contingent on any arm movement (i.e. using positive reinforcement). This use of positive reinforcement successfully increased this patient’s right arm movement and signalled a shift in behaviourism towards the application of behavioural principles to real-­ world issues. Armed with this knowledge of both operant and classical conditioning, Skinner proposed a new direction for the field of behaviourism – that of radical behaviourism. Radical behaviourism, like that of methodological behaviourism, still emphasised a strong environmental role on the influence of behaviour; however, it suggested that behaviourism should also include the study of thoughts, feelings and other private events in addition to observable behaviours. The idea of radical behaviourism was proposed in Skinner’s, 1953 book, Science and Human Behavior, in which he speculated on how the principles of behaviour could be applied to complex human behaviour in a myriad of areas including education, religion, ageing, government and law. Soon, Skinner was to turn his hand towards one of the most challenging topics of psychology – that of language.

 kinner’s Verbal Behaviour: The Beginning of the End? Or S a New Era for Behaviourism? As previously outlined, Skinner felt that it was within the remit of radical behaviourists to consider complex human issues, including that of language, and it wasn’t long before he published his own book on the subject in 1957 offering a behavioural perspective of language – Verbal Behavior. Unlike Skinner’s earlier work, this was

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primarily theoretical, lacking the previous empirical depth of his earlier work. However, this work introduced a functional analytic conceptualisation of language (and behaviour in general). This essentially outlined that language primarily develops in order to serve a function (e.g. to get food, to get attention, to refuse broccoli) and that this was based upon a process of operant conditioning and the needs or desires of that individual. This is now commonly referred to as a four-term contingency. This model outlined that there were four elements responsible for the understanding of behaviour. The first of these is motivating operations (Michael, 1982) – which is an event that affects how strongly a person’s behaviour is reinforced (or punished) by the consequences of their behaviour. Incidentally, motivating operations are further divided into establishing operations and abolishing operations (Michael, 1993). An establishing operation increases the reinforcing or punishing capacity of a stimulus, while an abolishing operation decreases the reinforcing or punishing ability of a stimulus. For example, if you are walking through a desert and are without water, the reinforcing capacity of water has suddenly increased due to this establishing operation (or as some may call it, a setting event). A further example may be that you’ve gone to an all-you-can-eat buffet and really got your money’s worth, now the reinforcing effect of food has decreased due to your satiation – this is an abolishing operation. The second element in the four-term contingency is that of the discriminative stimulus (SD) – this is a type of stimulus or event that consistently signals to an individual (or organism) that a specific response is appropriate and helps to increase the possibility that this response will occur. For example, a green traffic light signals to a driver that they can proceed, and their ability to proceed through traffic unimpeded by wayward drivers increases the probability that they will proceed whenever confronted with a green traffic light in the future. This green traffic light acts as a discriminative stimulus. The third element is that of the response, or the behaviour, while the final element is the stimulus or consequence (i.e. reinforcer, punisher, etc.). In addition to providing a functional analytic perspective of language, Skinner also introduced primary verbal operants including the echoic, mand (or demand), tact (or contact), intraverbal and textual. He maintained that language could be divided into these verbal operants (also including information regarding the autoclitic which he regarded as a secondary verbal operant), and, as such, he maintained that these fundamental building blocks of language could be taught using operant conditioning. An echoic is simply a vocal repetition, or echo, of what has been said by another speaker. For example, if a mother turned to a child and said “Say Mama” and the child then said “mama”, the child’s reply is an echoic as it has point-to-point correspondence with what was said just before it. I often think echoics are a favourite game of a child to drive their parents utterly insane – but I don’t think that’s what Skinner had in mind when he put that forward. A mand is a requesting behaviour where you are putting a demand on the environment and can take many forms including sign language, vocal speech and picture requests. For instance, asking for a tall black coffee without sugar at a local coffee shop is a mand. A tact, like that of mands, can take a number of forms including sign language, but it is verbal behaviour that describes a stimulus or event that the individual has come into contact with.

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For example, when a young child sees a cow in a field and excitedly points towards it to alert their parents to its presence and yells “Cow! Cow!”, this constitutes a vocal tact. Intraverbals are often considered to be conversation skills as they are a verbal response that occurs in response to another verbal response that bears no similarity and is like a back-and-forth verbal response. For example, if asked “what’s your favourite colour” and a person responds “Blue – I’m practically the Queen of Blue!”, the response of blue is an intraverbal. Additionally, intraverbals can include finishing sentences, fill-in-the-blanks and finishing a song lyric. For example, if you hear a friend singing the following lyrics “Let’s go out tonight. I have to go out tonight…”, you might join in on the choral festivities by completing the song with “You wanna prowl, be my night owl…” thereby constituting an intraverbal. There’s no point-to-point correspondence between the two verbal responses, and it only functions as a means of social reinforcement. Textual behaviour involves being presented with a written stimulus, such as a paragraph from a book, and providing the corresponding vocal response. For example, if you were to read this sentence aloud, then you would have engaged in a textual verbal operant – Hurray! Finally, Skinner outlined that the autoclitic depended on the presence of other verbal behaviours for its occurrence and modified the effects or functions of that verbal behaviour on the listener and that this specific verbal operant emerged once an individual acquired a strong verbal repertoire of primary operants (i.e. mands, tacts, intraverbals, etc.). He outlined that autoclitics can come in many forms including suffixes and prefixes, specific words and intonations, punctuation and the order in which statements and the words within them are produced. For example, the phrase “I believe it will snow tonight” possesses the autoclitic “I believe”, which changes the strength of the statement “it will snow tonight”. These autoclitics can be further divided into descriptive autoclitics, quantifying autoclitics, qualifying autoclitics and relational autoclitics. A descriptive autoclitic changes the listener’s reaction by indicating something about the context in which the response was emitted or the condition of the speaker offering the verbal response, and this autoclitic can be designated as an “autoclitic tact”. The descriptive autoclitic is considered an autoclitic tact as the speaker is tacting something about the origin of the stimulus control over the statement they have provided. Descriptive autoclitics include phrases such as “I doubt”, “I think”, “I see”, etc., and these indicate that the source of the individuals information comes from their own thoughts (i.e. the origin of the stimulus control is internal). The autoclitic “I believe” in the previous example can be categorised as a descriptive autoclitic. Additionally, the statement “I shouted goodbye” contains the descriptive autoclitic “I shouted” which provides the condition under which “goodbye” was produced. Quantifying autoclitics are also considered to be a type of autoclitic tact; however, unlike descriptive autoclitics, these affect the listener by indicating a specific property of their statement and are generally modifiers, such as “some”, “all”, “few”, “many”, “the”, “this, “that”, “a”, etc. The statement “Take all of the money” ensures that the listener knows that they are firstly specifying a specific item with the quantifying autoclitic “the” and also lets them know how much they can take with the additional quantifying autoclitic “all”. Qualifying autoclitics can be considered as “autoclitic mands” as this autoclitic is

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reinforced when the listener behaves in a specific way after hearing this autoclitic. This autoclitic qualifies an accompanying verbal response to change the intensity or direction of the listener’s behaviour. Qualifying autoclitics can include negation (e.g. no), assertion (e.g. yes), specific adverbs and suffixes (e.g. -like, −ly, −less). For example, the statement “It is not snowing tonight” contains the qualifying autoclitic of “not” which changes the effect of the sentence on the listener and can be considered as a mand as it signals to the listener that the sentence should not be considered as a tact. Relational autoclitics also impact the behaviour of the listener and are also considered as an additional type of “autoclitic mand”. Relational autoclitics can include spatial prepositions (e.g. above, below, etc.), punctuation, syntactical word ordering, possessives, predication (e.g. use of “to be”), etc. For example, the relational autoclitic “in” contained in the statement “the money is in my purse” indicates to the listener where they can find the money, which ultimately changes where the listener looks for the money. Adding “-ed” to the end of a verb indicates to a speaker that the events described within a sentence occurred in the past – meaning that “-ed” are a further type of relational autoclitic. Skinner maintained that autoclitics were a core process in grammar and syntax and explored this in depth in three chapters within his 1957 book. He outlined that autoclitic frames allow individuals to rapidly learn new verbal behaviour and follow the rules of language. Autoclitic frames are generalised responses to untrained situations. For example, the sentence “Cat pet I Sarah” would produce no reinforcement from the verbal community due to the mis-ordering of the words contained within it. Palmer (1996) found that reinforcement for syntactical correctness may be automatic as the ordering of words in the correct sequence may “sound better” than those which are not in order. This ability to produce novel arrangements of words within a coherent sentence (i.e. in a correct order) is an autoclitic frame. Some autoclitic frames conform to the conventional sequence for emitting verbal behaviour such as agent-­action-­ object (e.g. “I pet a cat”). Skinner’s book on verbal behaviour was comprehensive, but did not go without receiving extensive scrutiny. Most notably, Noam Chomsky (1959) offered some very considered critiques of Skinner’s account of language. Possibly, the greatest critique offered by Chomsky was that Skinner’s account of language failed to indicate how generative language developed. Generative language refers to an individuals’ ability to both understand and produce novel sentences. Chomsky remarked that reinforcement alone could not possibly account for this complex process – after all, how could a person produce a novel sentence in the first place if all aspects of language, including this aspect of novelty, were founded upon reinforcement? This core issue rocked behaviourism and left even the most devout behaviourist speculating as to the efficacy (or even suitability) of a behavioural account of language. So it was that the focus of psychology began to drift from behaviourism, with psychologists at the time feeling that this discipline could not shed light on the complexities of language and cognition. Debatably, the golden era of behaviourism had come to an abrupt close. Despite these issues, Skinner’s account of verbal behaviour nonetheless left an indelible mark on the face of behaviourism that persists to this day, most notably in

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the field of applied behaviour analysis (ABA). ABA is concerned with using the principles of behaviourism within the everyday environment to improve the quality of life and wellbeing of others. For example, in a key applied behaviour analytic study conducted by Lovaas et al. (1973), Lovaas used the principles put forward by behaviourism, such as reinforcement and punishment, and also considered Skinner’s (1957) functional account of language as a basis to teach autistic children basic language skills and general living and social skills (of course, this study comes with its own ethical issues and is not an accurate representation of modern ABA, but that is a point reserved for another day). Skinner’s account of verbal behaviour has also been used as a model for assessment tools to build individualised language and general development curriculums for individuals with developmental delays and disorders, such as the Verbal Behaviour Milestones Assessment and Placement Program (VB-MAPP; Sundberg, 2008). The VB-MAPP uses Skinner’s account of verbal operants, including echoics, mands, tacts and intraverbals, to provide an overview of a client’s language learning needs and abilities. Although Skinner’s Verbal Behavior (1957) received criticism, it has also provided the field with useful tools and theories to employ within applied practice. Nevertheless, the issue of generative language remained at large – how exactly would behaviourism address this? And more importantly, could it?

Sidman’s Contributions to Behaviourism and Language Murray Sidman has made significant contributions to the field of behaviourism – firstly in the form of free-operant avoidance (Sidman, 1953) and secondly with his account of stimulus equivalence (Sidman, 1971). Free-operant avoidance describes a situation in which an individual responding at any time during an interval before an aversive stimulus occurs functions to delay the presentation of that aversive stimulus. For example, imagine that you know you’re going to have an unwanted visitor arrive at your doorstep at 9:30 am – it is now 9:20 am – you have 10 minutes before this unwanted visitor (or aversive stimulus) presents itself. You decide that the best solution to avoid this person is to pop over to your next-door neighbour for a chat – so that this visitor can no longer find you! This sneaky (and somewhat covert) redirection of yourself has resulted in the successful avoidance of this unwanted visitor. It was, however, Sidman’s discovery of stimulus equivalence in 1971 that further advanced the field of behaviourism by providing not only a theory, but also empirical data, of language generativity. But what is stimulus equivalence? In essence, it’s a very simple concept which describes the condition in which two or more related stimuli elicit the same response. For example, the stimuli chair, stool and sofa would all elicit the same response – sitting. But if I was to tell you that a “cathaoir” was the same as a chair, and then asked if you would like a “cathaoir”, you might say yes if you wanted to sit down. Within Sidman’s, 1971 study, he aimed to teach reading skills to an adolescent with a diagnosed intellectual disability. Sidman noted that before this teaching

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intervention, the boy had never shown evidence of any reading comprehension but was able to correctly select a picture (Stimulus A) based on a given word (e.g. picking a picture of an orange when asked to find the orange), thereby indicating a matching repertoire. Armed with this knowledge, Sidman used a match-to-sample procedure to teach the participant to select printed words (which was referred to as Stimulus C) in the presence of spoken words (i.e. Stimulus B). For example, this involved teaching the participant to select the written word “cat” from an array of words when the word “cat” was spoken by the researcher or experimenter. At this point in the experiment, the participant had learned to select a picture (Stimulus A) in the presence of the spoken word (Stimulus B) and to select the written word or text (Stimulus C) in the presence of the spoken word (Stimulus B; see Fig. 1.2). Sidman discovered that without any additional training, the participant showed a number of further untaught or derived matching repertoires. For example, the participant was now able to match the written word (Stimulus C) to its corresponding picture (Stimulus A) and the picture (Stimulus A) to the written word (Stimulus C). How was this new matching repertoire explained? Sidman hypothesised that the repertoire demonstrated by this participant suggested that he considered the stimuli A, B and C to be mutually substitutable or equivalent – thereby sparking a new wave of stimulus equivalence research. Sidman and his colleagues went on to extend and replicate this research through a series of experiments involving related conditional discriminations. From these investigations, he maintained that stimulus equivalence and the derived equivalence relations which emerged from this training were comprised of three core properties. These included reflexivity, symmetry and transitivity (Sidman & Tailby, 1982). Reflexivity, or generalised identity, involves matching a single stimulus to itself (e.g. matching a picture of a cat to another picture of a cat). Symmetry involves the

Fig. 1.2  Illustration of stimulus equivalence as per Sidman (1971)

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ability to reverse relations that have been taught. For example, if you have been taught to select a picture of a cat from an array of comparisons when provided with the printed word “cat”, you will have demonstrated symmetry if you then select the printed word “cat” from a selection of printed words when presented with a picture of a cat. Finally, transitivity requires at least three stimuli and involves the execution of a novel conditional discriminative performance that is founded upon the establishment of two related conditional discriminative performances. This transitive performance was demonstrated in Sidman’s, 1971 experiment, where the participant demonstrated derived A-C and C-A matching repertoires following the acquisition of A-B and B-C matching repertoires. Sidman maintained that if all three of these properties (i.e. reflexivity, symmetry and transitivity) are demonstrated, then an equivalence class or equivalence relation has been formed successfully. Stimulus equivalence continued to be an intense topic of study over time for a number of reasons. Firstly, the findings generated by Sidman and his team appeared to contradict the established conceptions of behaviour analysis in that the results could not be explained using previously outlined behavioural principles such as classical or operant conditioning (see, e.g. Barnes, 1994; Hughes & Barnes-Holmes, 2016). Secondly, the results of Sidman’s works provided a potentially useful framework for exploring generative responding. As this had been the goal of behaviour analysis from its inception, this finding was a major coup for the field and lead to a swell of stimulus equivalence research aiming to model generativity (e.g. Murphy et  al., 2005; Rehfeldt & Root, 2005; Wulfert & Hayes, 1988). Finally, given the potential for stimulus equivalence to impact generative responding, the consensus was that this research could be theoretically and empirically linked with human language (e.g. Stewart & Roche, 2013). Subsequent research has indicated that stimulus equivalence and language are correlated (e.g. Barnes et al., 1990; Ogawa et al., 2009), and this has been demonstrated across populations, stimuli and procedures (see Sidman, 1994, 2000, 2009). However, the existing body of research has indicated that stimulus equivalence can only be successfully performed by verbally able humans and is not a repertoire present amongst verbally disabled humans or non-humans (Barnes, 1994; Barnes et al., 1990; Brino et al., 2014; Devany et al., 1986; Dugdale & Lowe, 1990, 2000; Lionello-Denolf, 2009). Importantly, further research has also revealed that stimulus equivalence training can be employed to remediate language deficits in populations with verbal disabilities (see Barnes, 1994; Cowley et al., 1992; Matos & d’Oliveira, 1992). So, that was it! Stimulus equivalence had unequivocally demonstrated and provided a framework for generative language and cognition - or did they? (If they had, this would have been an unsatisfyingly short book). While it provided a very useful framework for practitioners, there were some criticisms of this theory – namely, that it was descriptive rather than explanatory (Barnes, 1994; Barnes & Roche, 1996), meaning that it outlined what happened, but not how it happened in relation to the acquisition of skills. Additionally, when considering language and complex thoughts, stimulus equivalence is rather basic as it only examines the concept of “sameness” and fails to consider the more complex components of language such as hierarchical relations (e.g. a ragdoll is a type of cat, and a cat is a type of animal),

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distinction (e.g. a ragdoll cat is different to a Maine Coon) or comparison (e.g. Teresa loves cats more than Kate). It was this gap in the stimulus equivalence framework that leads to the introduction and rise of relational frame theory, better known as RFT. This theory was introduced to the field via a number of research papers but was catapulted to the attention of behavioural psychologists with the 2001 Purple Book By Hayes, Barnes-Holmes and Roche. The topic of RFT will be explored in the subsequent chapters, beginning with Chap. 2 “What is Relational Frame Theory?”. TLDRa Cheat Sheet Phylogenetic Behaviours that are said to have phylogenetic provenance are those provenance behaviours that are based on the evolutionary history of that species (e.g. reflexes). Phylogenetic behaviours are essentially “pre-loaded” behaviours for that species, meaning that there is a basic repertoire of responses that are unlearned but that the individual or organism can use to interact with their environment that will allow that species to survive Unconditioned These are any stimuli which naturally, and without training, elicit a response. stimulus For example, a puff of air into the eye elicits a blinking response – The puff of air is the unconditioned stimulus Unconditioned These are responses which are elicited, without training, in response to an response unconditioned stimulus and are uncontrollable and involuntary. In the above example, the response of blinking is the unconditioned response as it occurred involuntarily in response to the puff of air being introduced to the eye Conditioned A conditioned stimulus is one which was previously neutral (i.e. did not elicit stimulus a response); however, after repeated pairings with an unconditioned stimulus, this stimulus begins to trigger a response – The conditioned response Conditioned A conditioned response is the learned response to the previously neutral response stimulus (i.e. conditioned stimulus) that arises as a result of multiple pairings of the unconditioned and conditioned stimuli together. This response bears a physical, or topographical, similarity to an unconditioned response Methodological This was the original stance of behavioural psychology and contends that the behaviourism stimuli and events that are examined must be observable and measurable, meaning that private events such as thoughts and inner dialogues or speech or any events assessed via methods such as introspection were strictly off-limits for study This is a branch of behavioural psychology that predominantly focuses on Experimental the examination of behavioural principles under controlled laboratory behaviour settings. This field of behavioural psychology focuses on using data-driven analysis procedures to determine functional relations between antecedents and behaviours. Ultimately, the empirical observations provided by this field allow practitioners to predict and control behaviours via behavioural principles This is also referred to as the ABC (antecedent-behaviour-consequence) or Operant SRS (stimulus-response-stimulus) contingency. This contingency outlines the three-term relationship between a behaviour, its consequence and the context in which contingency this behaviour is evoked (i.e. the antecedent) (continued)

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Operant conditioning

Operant conditioning refers to the process and discriminatory effects of consequences on the future probability of behaviour – These may consequences which increase, decrease or have no impact upon the future occurrence of behaviour Skinner box Also known as an operant conditioning chamber, this is a laboratory apparatus which typically contains a lever which can be manipulated to gain access to a reinforcer (e.g. food pellet) or to avoid punishment (e.g. an electric shock). This box is used to assess operant conditioning by monitoring the behaviours of animals placed within its confines Reinforcement Reinforcement involves the addition or subtraction of a stimulus following the execution of a behaviour that increases the future probability of that behaviour Punishment Punishment involves the addition or subtraction of a stimulus following the execution of a behaviour that decreases the future probability of that behaviour Extinction Extinction involves the cessation of reinforcement for a behaviour that was previously reinforced, ultimately leading to a decrease in the future probability of that behaviour (i.e. when a previously reinforced behaviour is emitted, no stimulus is presented or subtracted following its emission) Positive Positive reinforcement involves the addition of a stimulus following the reinforcement execution of a behaviour that increases its future probability. For example, if a child cleans up their room and their mother tells them “well done!” and gives them a hug and the future probability of them cleaning their room increases, then this is an example of positive reinforcement (as praise and affection have been added following the room-cleaning behaviour) Reinforcer This is a stimulus, whose addition or subtraction, following a behaviour, increases its future probability. In the previous example, praise and affection were reinforcers. Importantly, reinforcers can be classified as either negative (i.e. aversive stimuli that are taken away or subtracted) or positive (i.e. appetitive stimuli that are added) following the execution of a behaviour that results in an increase of this behaviour over time Negative Negative reinforcement involves the subtraction of a stimulus following the reinforcement execution of a behaviour that increases its future probability. For example, if I give my cat a sachet of food and she stops yowling and I am then more likely to give her a sachet of food to stop her from yowling, then this is an example of negative reinforcement (as the dramatic cat yowling has been subtracted or taken away following the opening of a sachet). Importantly, negative reinforcement can be categorised as either escape or avoidance Escape (negative Escape is a form of negative reinforcement whereby an organism is already reinforcement) exposed to an aversive stimulus and the behaviour that they engage in will increase if it results in the successful termination or escape from this aversive situation. For example, when feeling in pain, you may take a painkiller to relieve the pain – This successfully diminishes the pain, and you go on to use this painkiller when you are in pain to escape this feeling of discomfort. In this example, the pain is the aversive stimulus present; the taking of the pain killer is the behaviour which increases due to the ingestion of the painkiller, while the lack of pain and discomfort is the negative reinforcer (continued)

18 Avoidance (negative reinforcement)

Positive punishment

Negative punishment

Punisher

Extinction burst Spontaneous recovery Radical behaviourism

Four-term contingency

1  The World of Psychology Before Relational Frame Theory Avoidance is a form of negative reinforcement whereby an organism is not exposed to an aversive stimulus or situation but engages in a behaviour in order to avoid coming into contact with this aversive stimulus. The behaviour engaged in to avoid this event is negatively reinforced (i.e. increases in future probability) because it results in the subtraction of a future aversive event. For example, becoming sick with the flu is highly aversive, so in order to avoid contracting the flu, an individual may get the seasonal flu jab every year – Meaning that the behaviour of inoculating has increased. In this example, becoming sick with the flu is the aversive stimulus, getting the flu vaccine is the behaviour which increases over time in an attempt to avoid becoming sick, while continued good health is the negative reinforcer Positive punishment involves the addition of a stimulus following the execution of a behaviour that decreases its future probability. For example, if a cat jumps onto a counter and their owner sprays them with water and the future probability of them jumping onto the counter decreases, then this is an example of positive punishment (as the water spray – Or positive punisher – Was added following the jump onto the counter, resulting in a decrease in the future probability of jumping on the kitchen counters) Negative punishment involves the removal of an appetitive stimulus following the execution of a behaviour that decreases its future probability. For example, if a person is speeding through a 50 km/h zone and is pulled over by the police and issued with a €500 fine, the person’s speeding behaviour then decreases in the future; this equates to negative punishment. The fine was subtracted following the behaviour of speeding, the negative punisher, and resulted in a decrease in the future probability of speeding This is a stimulus, whose addition or subtraction, following a behaviour decreases its future probability. Punishers can be classified as either negative (i.e. appetitive stimuli that are taken away or subtracted) or positive (i.e. aversive stimuli that are added) following the execution of a behaviour which results in the decrease of this behaviour in the future This is a temporary increase or burst in a behaviour which has been put on extinction (i.e. the reinforcement for that behaviour has been removed) This is when a previously extinguished behaviour reappears after a period of time during which that behaviour has been suppressed and returns to pre-extinction levels This strand of behaviourism maintains that all human behaviour, both public (i.e. overt and observable) and private (i.e. internal thoughts and dialogue) are open for examination. Furthermore, radical behaviourism would maintain that these behaviours can be explained in regard to its functional relations with environmental events. It is radical in the sense that it is all-­ encompassing and was a very novel and ground-breaking concept at the time of its introduction to behavioural psychology This is similar to the operant three-term contingency outlined above; however, it considers the addition of motivation (known as motivating operations). This fourth variable helps to set the stage to occasion a behaviour and can also serve to increase or decrease the reinforcing or punishing value of a stimulus (continued)

Sidman’s Contributions to Behaviourism and Language Motivating operations

Establishing operation

Abolishing operation

Discriminative stimulus (SD)

Echoic

Mand

Tact

Intraverbal

Textual

Autoclitic

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This is a setting event or variable that increases or decreases the value of a reinforcer or punisher and increases or decreases the frequency in behaviour that provides access to the stimulus in question. Ultimately, motivating operations affects how strongly an individual or organism is reinforced or punished by the consequences of their behaviour This is a motivating operation that increases the value of a reinforcer and therefore increases the frequency of a behaviour that provides access to a stimulus. Typically, this involves bringing the organism to a state of deprivation. For example, if a person is walking through the desert for 2 days and is without water, this has increased the value of water and thereby altered events so that that person will engage in a variety of behaviours in order to gain access to this stimulus This is a motivating operation that decreases the value of a reinforcer and therefore decreases the frequency of a behaviour that provides access to a stimulus. Typically, this involves bringing the organism to a state of satiation. For example, if a person has been at an all-you-can-eat buffet and has gorged themselves, this has decreased the value of food and has altered events so that the person is less likely to engage in behaviours to gain access to this stimulus These are stimuli which set the occasion for behaviours that have been reinforced in their presence in the past (i.e. they let us know what set of behaviours to engage in). For example, a green traffic light alerts us to the fact that it is now appropriate to drive. This green traffic light is a discriminative stimulus and has let us know in the past that this is an appropriate time to drive forward as it has been reinforced in the past This is a verbal operant in which an individual verbally repeats, or echoes, what another person says. An echoic has point-to-point correspondence which means that the verbal stimulus (SD) and response product (i.e. echoic) match each other in their totality A mand, or demand, is a verbal operant in which an individual requests an item, activity or event, from the listener. This verbal behaviour is reinforced by the compliance of the listener This is a verbal operant in which an individual communicates about an item or event that they come into contact with (tact being the shortened version of contact). This verbal operant is controlled by a non-verbal stimulus (e.g. object, event, activity, etc.) and is reinforced and maintained by social reinforcement (e.g. praise) This is a verbal operant in which the speaker responds to the verbal behaviour of another person – As such, this is often considered to be a conversation skill – This is generally considered to be the most complex verbal behaviours to teach This is a verbal operant in which the verbal stimulus corresponds to a textual or written SD and essentially is the equivalent of reading out loud. Although this has some similarity to an echoic (in that it is mirroring a verbal stimulus to some degree), it does not have point-to-point correspondence like that of echoics This is a verbal operant that is reinforced and maintained by the effects it has on the reinforcement of other verbal operants and is a verbal behaviour that changes the functions of other verbal behaviours. For example, the phrase “I think it is red” contains the autoclitic “I think” which moderates or changes the strength of the remainder of the phrase (i.e. “it is red”) (continued)

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Descriptive autoclitic

Descriptive autoclitics change the listener’s reaction by detailing something about the conditions under which a response was emitted by a speaker. A descriptive autoclitic is influenced by characteristics of the environment or response that it is associated with and allows listeners to respond appropriately to these situations without having any direct experience with that environment. In the previous example, “I think” describes the strength of the statement “it is red” making this a descriptive autoclitic (i.e. it specifies some condition of a response). Descriptive autoclitics can also indicate that the emitted response is subordinate in relation to what is being discussed. The phrase “for example” is one such example of a descriptive autoclitic which indicates that the remainder of the sentence is subordinate to what preceded it Quantifying These are autoclitics that have the potential to change the actions of the autoclitic listener as it specifies the range of the application of a listener’s responses by indicating the relation between the speaker’s response and the controlling stimulus – These include the words “all”, “the”, “that”, “a”, “some” and “no” (to name but a few). These autoclitics can change the behaviour or responses or the listener as they can specify the actions required. For example, by placing the autoclitics “a” or “that” after the phrase “I want” and before the word “cat”, this can change how the speaker would react to that sentence (it’s specifying a response) Qualifying These are autoclitics which also can change a listener’s responses by autoclitic indicating the direction or intensity of a tact; these can include negation or affirmation of facts and can also serve to assert a response. For example, within the phrase “it is not warm”, the qualifying autoclitic “not” indicates what behaviour would be appropriate for the listener (e.g. wearing a coat and gloves). When at a pantomime and the audience yells “He’s behind you!”, the panto character will usually reply with “no he isn’t” – This is an example of a further autoclitic (specifically negation, as it reverses the direction of the listener’s response), while the audience’s response of “yes he is!” is a further qualifying autoclitic (specifically assertion) Relational Relational autoclitics affect the behaviour of the listener by describing the autoclitic relation between verbal operants. For example, the phrase “the cat is on the table” contains the relational autoclitic “is on” specifying to the listener where to look for the cat Autoclitic frames These are phrases in which the relation amongst verbal responses has an autoclitic function. For example, the phrase “give me your …” is a mand with the frame of a relational autoclitic because the relation between the frame and the response is important. The frame occasions specific responding on the part of the listener (i.e. giving the object requested), indicating the type of verbal operant (i.e. mand) Generative This is the ability to emit novel sentences that have not been explicitly taught language and to understand sentences that you have not been exposed to before This is a specific branch of behavioural psychology that seeks to employ the Applied behavioural principles explored within experimental behaviour analysis and behaviour applies them within our wider society, including education, health and social analysis services (to name but a few) in order to facilitate meaningful and positive change (continued)

Sidman’s Contributions to Behaviourism and Language Free-operant avoidance

Stimulus equivalence

Derived

Conditional discrimination

Reflexivity

Symmetry

Transitivity

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This is a contingency in which responses emitted at any time during a specific time interval prior to the scheduled onset of an aversive stimulus delays the presentation of the aversive stimulus. For example, going to replace the pay and display ticket on your parked car as it is close to running out is a response emitted before you could potentially be fined or clamped for illegal parking, but by replacing the ticket you have delayed the onset of a fine or clamping (i.e. you have successfully avoided the aversive stimulus) This is the phenomenon whereby two or more stimuli which are related in the context of sameness elicit the same response. For example, the words “dog”, “chien”, “madra” and “hund” are all related to one another and should elicit the same responses; if a person is told that a madra is in the next room and that person is afraid of dogs, they may demonstrate a fear response (i.e. the word “madra” has elicited the same fear response that the word “dog”, “chien” or “hund” would) This refers to the emergence of untrained responses that are based on a small set of trained responses. For example, if you are taught that my cat Ceci is the same as my cat Lewie, and that Lewie is a black cat, you may derive from this that Ceci is a black cat – This was untaught but was “figured out” based upon the information provided This is a discrimination in which responding, and subsequent reinforcement, is dependent upon other stimuli. For example, if presented with an array of three animals (a dog, a cat and a parakeet), the response emitted by a person is dependent upon the SD provided. If they are given a parakeet and asked to match it with the same, then the behaviour of matching parakeet to parakeet will be reinforced; however, if the individual matches a parakeet to a dog, this response will not be reinforced, indicating that this discrimination is conditional upon other stimuli within the environment This refers to the matching of a stimulus to itself (i.e. identity matching). For example, this may involve matching the letter A to an identical letter A (same colour, same font, same size) Symmetry refers to the reversibility of a relation. For example, if you are told that Lola the pug is the same as Peggy the pug, you are able to reverse this relation and say that Peggy the pug is the same as Lola the pug Transitivity relates to the transfer of the relation between stimuli in the equivalence class to new (i.e. derived) combinations through shared memberships. For example, if you are taught that Tiia is a queen, and another name for queen is kuningatar, you would derive that Tiia is a kuningatar, and a kuningatar is Tiia. These derived relations are an example of transitivity

TLDR: Too long, didn’t read. This is an acronym used to indicate a summarised version of a longer text that is too long (and usually, too boring) to read. However, I’m sure that this chapter wasn’t boring at all, and this section is simply a refresher or second helpings of behaviourism!

a

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References Barnes, D. (1994). Stimulus equivalence and relational frame theory. The Psychological Record, 44, 91–124. Barnes, D., & Roche, B. (1996). Relational frame theory and stimulus equivalence are fundamentally different: A reply to Saunders’ commentary. The Psychological Record, 46(3), 489–507. Barnes, D., McCullagh, P., & Keenan, M. (1990). Equivalence class formation in non-hearing impaired children and hearing impaired children. Analysis of Verbal Behavior, 8, 1–11. Brino, A.  L., Campos, R.  S., Galvào, O.  F., & McIlvane, W.  J. (2014). Blank-comparison matching-­to-sample reveals a false positive symmetry test in a capuchin monkey. Psychology and Neuroscience, 7(2), 193–198. http://psycnet.apa.org/doi/10.3922/j.psns.2014.008 Chomsky, N. (1959). Review: Verbal behaviour by B. F. Skinner. Language, 35(1), 26–58. Cowley, B. J., Green, G., & Braunling-McMorrow, D. (1992). Using stimulus equivalence procedures to teach name-face matching to adults with brain injuries. Journal of Applied Behavior Analysis, 25, 461–475. https://doi.org/10.1901/jaba.1992.25-­461 Devany, J. M., Hayes, S. C., & Nelson, R. O. (1986). Equivalence class formation in language-­ able and language-disabled children. Journal of the Experimental Analysis of Behavior, 46, 243–257. https://doi.org/10.1901/jeab.1986.46-­243 Dugdale, N., & Lowe, C.  F. (1990). Naming and stimulus equivalence. In D.  E. Blackman & H. Lejeune (Eds.), Behavior analysis in theory and practice: Contributions and controversies. Lawrence Erlbaum Associates. Dugdale, N., & Lowe, C. F. (2000). Testing for symmetry in the conditional discriminations of language-trained chimpanzees. Journal of the Experimental Analysis of Behavior, 73, 5–22. https://doi.org/10.1901/jeab/2000/73-­5 Fuller, P. R. (1949). Operant conditioning of a vegetative human organism. The American Journal of Psychology, 62(4), 587–590. https://psycnet.apa.org/doi/10.2307/1418565 Grimsley, D.  L., & Windholtz, G.  L. (2000). The neurophysiological aspects of Pavlov’s theory of higher nervous activity: In honor of the 150th anniversary of Pavlov’s birth. Journal of the History of the Neurosciences, 9(2), 152–163. https://doi.org/10.1076/ 0964-­704X(200008)9:2;1-­Y;FT152 Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer Academic Publishers. Hughes, S., & Barnes-Holmes, D. (2016). Relational frame theory: The basic account. In R. D. Zettle, S. C. Hayes, D. Barnes-Holmes, & A. Biglan (Eds.), The Wiley handbook of contextual behavioural science. Wiley. Lionello-DeNolf, K.  M. (2009). The search for symmetry: 25 years in review. Learning and Behavior, 37, 188–203. https://doi.org/10.3758/LB.37.2.188 Lissek, S., Powers, A. S., McClure, E. B., Phelps, E. A., Woldehawariat, G., Grillon, C., & Pine, D. S. (2005). Classical fear conditioning in the anxiety disorders: A meta-analysis. Behavior Research and Therapy, 43, 1391–1424. https://doi.org/10.1016/j.brat.2004.10.007 Lovaas, O. I., Koegel, R., Simmons, J. Q., & Stevens Long, J. (1973). Some generalization and follow-up measures on autistic children in behaviour therapy. Journal of Applied Behavior Analysis, 6(1), 131–166. Lydon, S., Healy, O., O’Callaghan, O., Mulhern, T., & Holloway, J. (2014). A systematic review of the treatment of fears and phobias among children with autism spectrum disorders. Review Journal of Autism and Developmental Disorders, 2, 1–14. https://doi.org/10.1007/ s40489-­014-­0043-­4 Matos, M. A., & d’Oliveira, M. M. H. (1992). Equivalence relations and reading. In S. C. Hayes & L. J. Hayes (Eds.), Understanding verbal relations. Context Press. Michael, J. (1982). Distinguishing between discriminative and motivational functions of stimuli. Journal of the Experimental Analysis of Behavior, 37(1), 149–155. https://doi.org/10.1901/ jeab.1982.37-­149

References

23

Michael, J. (1993). Establishing operations. The Behavior Analyst, 16(2), 191–206. Mineka, S., & Oehlberg, K. (2008). The relevance of recent developments in classical conditioning to understanding the etiology and maintenance of anxiety disorders. Acta Psychologica, 127, 567–580. https://doi.org/10.1016/j.actpsy.2007.11.007 Moore, J. (2013). Methodological behaviourism from the standpoint of a radical behaviourist. The Behavior Analyst, 36(2), 197–208. Murphy, C., Barnes-Holmes, D., & Barnes-Holmes, Y. (2005). Derived manding in children with autism: Synthesising Skinner’s verbal behaviour with relational frame theory. Journal of Applied Behavior Analysis, 38(4), 445–462. https://doi.org/10.1901/jaba.2005/97-­04 Ogawa, A., Yamazaki, Y., Ueno, K., Cheng, K., & Iriki, A. (2009). Neural correlation of species-­ typical illogical cognitive bias in human inference. Journal of Cognitive Neuroscience, 22(9), 2120–2130. https://doi.org/10.1162/jocn.2009.21330 Palmer, D. (1996). Achieving parity: The role of automatic reinforcement. Journal of the Experimental Analysis of Behavior, 65, 289–290. https://doi.org/10.1901/jeab.1996.65-­289 Rehfeldt, R. A., & Root, S. L. (2005). Establishing derived requesting skills in adults with severe developmental disabilities. Journal of Applied Behavior Analysis, 38(1), 101–105. https://doi. org/10.1901/jaba.2005.106-­03 Sajwaj, T., Libet, J., & Agras, S. (1974). Lemon-juice therapy: the control of life-threatening rumination in a six-month-old infant. Journal of Applied Behavior Analysis, 7(4), 557–563. https:// psycnet.apa.org/doi/10.1901/jaba.1974.7-­557 Sidman, M. (1953). Avoidance conditioning with brief shock and no exteroceptive warning signal. Science, 118, 157–158. https://doi.org/10.1126/science.118.3058.157 Sidman, M. (1971). Reading and auditory-visual equivalences. Journal of Speech and Hearing Research, 14(1), 5–13. https://doi.org/10.1044/jshr.1401.05 Sidman, M. (1994). Equivalence relations and behaviour: A research story. Authors Cooperative. Sidman, M. (2000). Equivalence relations and the reinforcement contingency. Journal of the Experimental Analysis of Behavior, 74, 127–146. https://doi.org/10.1901/jeab.2000.74-­127 Sidman, M. (2009). Equivalence relations and behaviour: An introductory tutorial. The Analysis of Verbal Behavior, 25, 5–17. https://doi.org/10.1007/BF03393066 Sidman, M., & Tailby, W. (1982). Conditional discrimination vs. matching to sample: An expansion of the testing paradigm. Journal of the Experimental Analysis of Behavior, 37(1), 5–22. https://doi.org/10.1901/jeab.1982.37-­5 Skinner, B.  F. (1938). The behaviour of organisms: An experimental analysis. Appleton Century Crofts. Skinner, B. F. (1953). Science and human behaviour. Macmillan. Skinner, B. F. (1957). Verbal Behavior. Copley Publishing Group. Skinner, B. F. (1984). The phylogeny and ontogeny of behavior. Behavioral and Brain Sciences, 7(4), 669–677. https://doi.org/10.1017/S0140525X00027990 Stewart, I., & Roche, B. (2013). Relational frame theory: An overview. In S. Dymond & B. Roche (Eds.), Advances in relational frame theory: Research and application. Context Press. Sundberg, M.  L. (2008). VB-MAPP: Verbal behaviour milestones assessment and placement program: A language and social skills assessment program for children with autism or other developmental disabilities. AVB Press. Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative processes in animals. Psychological Review Monograph Supplement, 2(4, Whole No. 8). Thorndike, E. L. (1901). The human nature club: An introduction to the study of mental life (2nd ed.). Macmillan. Thorndike, E. L. (1905). The elements of psychology. A. G. Seiler. Thorndike, E. L. (1907). The elements of psychology (2nd ed.). A. G. Seiler. Thorndike, E. L. (1909). Darwin’s contribution to psychology. University of California Chronicle, 12, 65–80. Thorndike, E. L. (1911). Animal intelligence. Macmillan. Watson, J. B. (1924). Behaviorism. People’s Institute Publishing Company.

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Watson, J.  B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology, 3(1), 1–14. Wulfert, E., & Hayes, S. C. (1988). Transfer of a conditional ordering response through conditional equivalence classes. Journal of the Experimental Analysis of Behavior, 40(2), 125–144. https:// doi.org/10.1901/jeab/1988.50-­125

Chapter 2

What Is Relational Frame Theory?

The introduction of Hayes et al.’s (2001a) book brought relational frame theory (RFT) hurtling forward into the consciousness of behavioural psychologists across the globe. The utility of this approach has been explored over the last two decades within educational and behavioural research. The current chapter seeks to define what RFT is, introduces its core components, provides a brief overview of relational frames and outlines how this approach addresses the concerns outlined by Chomsky in relation to Skinner’s verbal behaviour.

Relational Frame Theory: What Is It? Put very simply, relational frame theory (RFT) is a behavioural conceptualisation of language and cognition that considers these complex patterns of behaviour to be comprised of learned operants – more specifically, derived relational responses (i.e. derived relational responding; DRR). This pattern of complex responding is known by many different names including relational framing and arbitrarily applicable relational responding (AARR). These phrases seem to be initially very intimidating, but at their heart explain very simple core concepts that are essential to the understanding of the field. Essentially, RFT states that the uniquely human ability of language and cognition is all about relating. Hughes and Barnes-Holmes (2016) outline that relating involves responding to at least one stimulus in terms of at least one other stimulus (e.g. relating the stimulus “pomegranate” to the stimulus “fruit” based upon the contextual cue of “type of”). Furthermore, relating is considered to be a generalised pattern of behaviour (i.e. the capacity to relate these two items to one another has not been explicitly taught). Relating, therefore, is our ability to relate one object or event to another based on specific contextual cues that indicate to us what relationship they have with one another (e.g. are they the same, different, a type of, etc.?). Our ability to relate stimuli to one another can vary in their complexity, and both human and animal © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_2

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populations have demonstrated the capacity to respond relationally to stimuli and events at its most basic. This is non-arbitrarily applicable relational responding (NAARR), which involves relating stimuli to one another based upon physical and observable characteristics. Meanwhile, at the most complex level, there is AARR which has only been demonstrated by human subjects and appears to be a uniquely human (and rather complex) capability.

 on-arbitrarily Applicable Relational Responding: I See N the Relationship There! As previously outlined, this capacity has been demonstrated in non-human populations such as birds, insects, fish and mammals (Frank & Wasserman, 2005; Harmon et al., 1982; Yamazaki et al., 2014), as the extant research indicates that these organisms can be taught to respond to the physical relationship between stimuli within these experiments. It is important to note that this ability is solely confined to stimuli in which there is a clear physical relationship between them (Giurfa et al., 2001; Harmon et al., 1982; Hughes & Barnes-Holmes, 2016). For example, a non-human may be able to discriminate that one stimulus is bigger than another or that one stimulus is identical to another based upon the physical properties of the stimuli presented to them. However, non-human populations have not demonstrated this relating repertoire with stimuli in which there is an abstract relationship between stimuli (e.g. that a pound coin is worth more than a euro coin – even though they are physically the same size and bare physical similarities otherwise) which constitutes AARR. Furthermore, although NAARR repertoires have been demonstrated amongst non-human populations, this research has also indicated that this responding is based on prior experience and learning histories with these stimuli, indicating that these are not generative responses. NAARR is an important repertoire and may be considered to be a building block for more complex AARR. Previous research has indicated that these NAARR repertoires must first be established and strengthened prior to the emergence and development of more complex AARR (Berens & Hayes, 2007; Luciano et  al., 2007; Mulhern et al., 2017). I often think of NAARR as being analogous to learning to crawl before you can walk or even run. For example, in order to understand that a pound coin is worth more than a euro coin, we have to first understand what the concept of “more than” actually is. To do this, we have to first understand what the contextual cue “more than” actually refers to – this cue is established by pairing it with a physical representation of this cue (e.g. five apples are more than two apples; see Fig. 2.1). Over time, the contextual cue of “more” becomes established when, for example, an individual selects the sample with “more” when asked “which one has more?”, and this correct selection is reinforced. As such, NAARR is typically established as a result of an individuals’ exposure to naturally occurring

Arbitrarily Applicable Relational Responding: A Level Up!

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Fig. 2.1  Illustration of NAARR of comparison Here, it is somewhat easy to determine the relationship between these two stimuli. If I asked you which plate has more, you would correctly identify the plate on the left – not because I have told you about the relationship between these stimuli, but because you can see the relationship – you have based your responding on the physical characteristics of the stimuli (i.e. have performed NAARR). Being able to see these physical relationships provides the basis for the establishment of contextual cues for more abstract responding (i.e. AARR)

contingencies within their everyday environment that may support and establish these response patterns (Luciano et al., 2007). From these building blocks, NAARR, once established, can then facilitate the more abstract AARR. It is at this point that it should be noted to any potential practitioners reading this book that the importance of NAARR repertoires must not be understated. When considering how to teach and facilitate complex patterns of responding such as comparison, opposition or distinction, you must first begin by assessing these non-arbitrary abilities before delving into more arbitrary repertoires. Remember: walk before you can run, or, in the case of DRR, you must non-arbitrarily relate before you arbitrarily relate.

Arbitrarily Applicable Relational Responding: A Level Up! As previously outlined, AARR is a skill that appears to be confined to the human population and is an advanced form of relating. Let’s be more specific and outline what AARR, or relational framing, actually is. AARR involves relating stimuli or events based upon contextual cues rather than simply the physical properties of the stimuli. For example, if I tell you that sodium is more reactive than calcium, you should then derive that calcium is less reactive than sodium. This derivation is not based on the physical properties of these stimuli, but is instead based on the contextual cues of “more” and “less” which cue a relating behaviour in accordance with comparison. This repertoire is considered to be an operant, meaning that it is a specific behaviour (or set of behaviours) that are defined and shaped by contingencies of reinforcement. This complex pattern of responding is established when an individual is exposed to sufficient exemplars of non-arbitrary relations which allow this responding to

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come under the control of the contextual cue alone. This responding can then be applied in contexts where the physical properties of the stimuli cannot be seen, thus becoming an abstract skill built on the foundation of NAARR. But why is this pattern of responding known as AARR? The word “arbitrarily” is potentially the most important part of this label as it indicates that these are relational responses that can be applied in any circumstance irrespective of the actual physical relationship between the stimuli (Hayes et  al., 2001b; O’Toole et  al., 2009). For example, although a 2 pence coin is physically larger than a 5 pence coin, we know that the 5 pence coin is worth more than the 2 pence coin based upon the contextual cues “more than” and “less than”, and we disregard the physical sizes of these coins when considering their relative value or worth (see Fig. 2.2). In essence, therefore, AARR is simply the capacity to relate one stimulus or event to another based only on the contextual cues provided. Importantly, these patterns of responding, whether they are non-arbitrary or arbitrary, are characterised by three core features – mutual entailment, combinatorial entailment and transformation of stimulus function. As is the case with all of RFT, these terms sound much more imposing than they actually are and denote quite simple units of behaviour which form the basis of all relational frames and DRR.

Fig. 2.2  Example of AARR of comparison Above is a one euro coin and a 50 cent coin – and despite the perpetually worrying economic climate, a one euro coin is worth more than a 50 cent coin. If I asked you which coin you would prefer to have, you would probably say the one euro coin. Your decision to choose this coin is not based on its size – even though a 50 cent piece is larger than the euro – instead, your decision is based on the information provided (i.e. that a one euro coin is worth more than a 50 cent piece). Despite seeing a physical relationship between these stimuli, your selection of the one euro coin was not based on the physical characteristics of the stimuli (i.e. was not based on NAARR), but instead was based on the contextual cues outlining the relationship between these coins (i.e. AARR of comparison)

Mutual Entailment: A Tale of Two Stimuli

29

Mutual Entailment: A Tale of Two Stimuli This is a core feature of relational framing and involves the ability to relate two stimuli to one another using a contextual cue. This feature of relational framing outlines that when a specified unidirectional relation from Stimulus 1 to Stimulus 2 within a given context is provided, a second unidirectional relation from Stimulus 2 to Stimulus 1 is then entailed (Stewart, 2018). For example, if we are told that Stimulus A is bigger than Stimulus B, then we derive that Stimulus B is smaller than Stimulus A (i.e. the relationship of “bigger” and “smaller” only goes in one direction and is, therefore, unidirectional). This derivation of a relationship of comparison between these stimuli is mutual entailment. Mutual entailment bears some resemblance to symmetry as proposed by stimulus equivalence research (which we explored in Chap. 1). However, the notable difference between mutual entailment and symmetry is that symmetry only refers to a relationship of sameness, meaning that the relationship between the stimuli are bidirectional (i.e. the relationship goes both ways), while mutual entailment refers to any relationship between stimuli (such as comparison, opposition, distinction, etc.) and is therefore unidirectional (meaning that the relationship between stimuli may operate in one direction, but may not necessarily operate in the same way in the other direction). The primary assumption of RFT is that human beings learn to relate stimuli mutually (and in combination) “without being limited by their form” (Fletcher & Hayes, 2005, p. 318). Mutually entailed relations are fundamentally bidirectional, as if Stimulus 1 is related to Stimulus 2 and then Stimulus 2 is related to Stimulus 1 (Barnes-Holmes et al., 2001). This means that in addition to being unidirectional, these relationships are also bidirectional (but not always symmetrical). For example, if you are told that Miranda finished the race before Heather, you could then derive that Heather finished the race after Miranda, but you can’t derive that Heather finished the race before Miranda (i.e. the contextual cue of “before” and “after” only operates in one direction and is unidirectional). In this example, Miranda is related via temporality to Heather, and Heather is related via temporality to Miranda indicating that the relationship between these stimuli is bidirectional. This derivation is mutual entailment and, unlike symmetry, does not solely indicate a relationship of equivalence or sameness between the stimuli in question and is, instead, based on any relationship between stimuli. It is important to note that mutual entailment can refer to any number of different kinds of relationships between stimuli including opposition, comparison, distinction, hierarchy, etc. Of course, the example of Miranda and Heather’s placement in the race which we explored above is AARR mutual entailment of temporality (as we cannot see the physical relationship between the stimuli and are instead basing our understanding of this relationship on the contextual cues of “before” and “after” alone) and is an abstract level of understanding that cannot be mastered before NAARR mutual entailment of temporality has been fully established (Kirsten & Stewart, 2021; Luciano et al., 2007; Mulhern et al., 2017). Arguably, this feature of relational framing (i.e. mutual entailment) is the first step towards more complex

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repertoires and appears to be a necessary (and logical) step towards acquiring the remaining two features of relational framing (i.e. combinatorial entailment and transformation of stimulus function; Kirsten & Stewart, 2021; Kirsten et al., 2021, 2022; Mulhern et al., 2017).

Combinatorial Entailment: The More the Merrier! Combinatorial entailment involves the combination of two or more relationships of mutual entailment using contextual cues. For instance, if you are told that Stimulus A is the same as Stimulus B (mutual entailment relationship (1) and that Stimulus B is the same as Stimulus C (mutual entailment relationship (2), these two mutually entailed relationships combine to offer an additional relationship between Stimulus A and C. The derivation of the relationship between Stimulus A and Stimulus C (i.e. of sameness) is a demonstration of combinatorial entailment. Again, you are probably scratching your head and thinking, “This seems very similar to transitivity in Stimulus Equivalence!”, and again, you wouldn’t be entirely wrong. As previously outlined, transitivity only refers to relationships of equivalence or sameness, while combinatorial entailment refers to a derivation of relationships amongst two or more mutually entailed relations involving any relational frame (i.e. hierarchy, comparison, opposition, etc.). Furthermore, as with mutual entailment, combinatorial entailment is also concerned with unidirectional relationships. Put simply, combinatorial entailment is the phenomenon whereby two or more stimulus relations are combined to derive an additional relation. For example, if we can see that Calli is taller than Mary, and Mary is taller than Melissa, we can derive that Calli is taller than Melissa and that Melissa is shorter than Calli. This derivation is combinatorial entailment as we have combined the first mutually entailed relation (i.e. Calli is taller than Mary) with the second mutually entailed relation (i.e. Mary is taller than Melissa) to form a new relation (i.e. our derivations between Calli and Melissa). Importantly, combinatorial entailment is not confined to two relations (or three stimuli) alone and can contain any number of stimuli and relations. For example, we could extend this relationship to include further stimuli and relations  – Melissa is taller than Tiia, and Tiia is taller than Lucy. Again, these mutually entailed relations can combine to provide us with further derived relations – Melissa is taller than Lucy; Lucy is shorter than Melissa – and once we combine these relations with the previous example, we can derive a host of additional relationships between the stimuli outlined (e.g. Calli is taller than Mary, Melissa, Tiia and Lucy; Lucy is shorter than Calli, Mary, Melissa and Tiia; Tiia is shorter than Mary; etc.). It is important to note that combinatorially entailed relationships are not confined to one type of relationship or relational frame alone and can actually include a mix of different relationships. For example, if we also outline that Mary and Elena are the same height (i.e. a relational frame of sameness), this can also be combined with our previous relationships to provide further information that we can derive (e.g. Elena is taller than Melissa, Tiia and Lucy; Elena is shorter than Calli; etc.). This

Transformation of Stimulus Function

31

indicates the complexity with which the human population is able to relate stimuli to one another, and although this example is again non-arbitrary in nature, this capacity to combinatorially entail relations can also extend to arbitrary stimuli and relations – particularly once a non-arbitrary repertoire has previously been established (Berens & Hayes, 2007; Mulhern et al., 2018).

Transformation of Stimulus Function This is the final component of relational framing and is arguably one of the most crucial components of language and cognition as it is the means by which language can influence our behaviour. Although stimulus equivalence has parallels with RFT in relation to mutual entailment and combinatorial entailment, there is no such equivalent to transformation of stimulus function; although there are early studies within stimulus equivalence which examine this phenomenon (e.g. Auguston et al., 2000; Auguston & Dougher, 1997; Dougher et al., 1994), there was no specific label attributed to this phenomenon within stimulus equivalence research. If two or more arbitrary stimuli (e.g. A, B and C) are part of a relational frame network with one another and one of these stimuli has a specific psychological function (e.g. that A is a category of poison containing Stimuli B and C), then the function of the stimulus A may be transformed in accordance with this relationship of hierarchy. For example, after you derive that A is a category containing both Stimuli B and C and you are then informed that all A’s are poisonous, and you are asked if you want to eat either Stimuli B or C, even without seeing these stimuli and without receiving any additional feedback or instruction, you may reply that you do not want to ingest Stimuli B and C as they are poisonous. As a result of this response, we can now say that the functions of the Stimuli B and C are transformed via the derived relation with A (see, e.g. Barnes-Holmes et al., 2004). Transformation of stimulus function is an incredibly powerful phenomenon within language and cognition, and potentially one of the more interesting manifestations of this phenomenon has been seen with the recent coronavirus crisis and some of the misinformation surrounding this. For example, there was a common misconception that the association between the alcoholic beverage Corona and the virus corona (a non-arbitrary relationship of sameness – non-arbitrary as the names share formal similarity) was the factor which resulted in a decrease in sales of the beverage. This would mean that the psychological function of the virus (i.e. it is aversive and unwanted) transformed the psychological function of the beverage Corona due to the derived relation of sameness between the stimuli. Although this makes an interesting case for the importance of transformation of stimulus function as a psychological phenomenon, this case was untrue, and sales were actually hampered by peoples’ limited ability for movement across locations and inability to celebrate public occasions such as Chinese New Year and St. Patrick’s Day which are linked to high sales of alcohol. Nevertheless, I find it to be an interesting (and

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topical) example – we’ll just skip past the lack of evidence on this one (I won’t do it again, I promise)! There are many examples in everyday life in which stimuli (such as specific phrases) acquire psychological functions. Although these stimuli may begin as relatively neutral, due to a learning history (shaped, as always, by consequences and antecedents), these stimuli acquire psychological functions. For example, the phrase “We need to talk” seems to be relatively innocuous; however, for a lot of people reading this paragraph, it may have stirred up some feelings of dread and possible anxiety. Maybe this sort of statement results in a plummeting feeling within the stomach, a sense of dread and an intense desire to escape the situation. Presumably, small children will not have such a reaction to this phrase, meaning that the psychological function for this has been transformed over time. To further illustrate how transformation of stimulus function develops, I will provide you with the following self-involved example. If my partner approached me and told me that he had purchased a “billi” for me, and that it was waiting inside the house, I would probably be confused, as I do not know what that word refers to. However, if he proceeded to outline that a “billi” is the same as a cat, my feelings towards this stimulus changes (i.e. the psychological function of this stimulus has been transformed). For those who know me, they will be aware that I am an ardent lover of cats; therefore, I would likely rush inside to seek out the “billi” and cuddle it. This previously neutral stimulus of “billi” has now been transformed into an appetitive stimulus for me within this context. On the other hand, if I told my friend Méabh that a “billi” was in her house and outlined the relationship between “billi” and cat, this would have a major impact on her behaviour due to her cat allergies (likely increasing the appetitive properties of antihistamines), demonstrating the far-reaching consequences of this aspect of relational framing. Interestingly, it is this aspect of responding that really distinguishes RFT from that of stimulus equivalence. Although previous research within the field of stimulus equivalence have examined this phenomenon (e.g. Auguston et al., 2000; Auguston & Dougher, 1997; Dougher et al., 1994; Rodríguez Valverde et al., 2009), this is not a characteristic of stimulus equivalence initially proposed by Sidman in 1971, or in later revisions. In fact, even the American Psychological Association’s own dictionary (2020) outlines the three core properties of stimulus equivalence as reflexivity, symmetry and transitivity, neglecting the inclusion of transformation of function. RFT, however, outlines that this phenomenon is a defining feature of relational framing.

RFT: Is It Just a Fancy Stimulus Equivalence? Put simply? No, as previously alluded to, RFT extends upon the research of stimulus equivalence, considering even more complex relationships between stimuli than that of sameness. RFT considers a multitude of patterns of derived relational responding, including coordination (e.g. “same as”, “equal to”; Belisle et al., 2020;

RFT: Is It Just a Fancy Stimulus Equivalence?

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Cassidy et  al., 2011), opposition (e.g. “opposite to”; Alonso-Álverez & Pérez-­ González, 2018; Cassidy et al., 2016), distinction (e.g. “different to”; Rehfeldt & Barnes-Holmes, 2009), comparison (e.g. “more than/less than”; McLoughlin et al., 2021; Zagrabska-Swiatkowska et al., 2020), temporality (e.g. “before/after”; Brassil et  al., 2019; Kirsten & Stewart, 2021), deictics (e.g. “I-You, Here-There, Now-­ Then”; García-Zambrano et  al., 2019; Montoya-Rodríguez et  al., 2017), containment (e.g. “contains”; Ming et al., 2018; Mulhern et al., 2017), hierarchy (e.g. “part of”, “belongs”, “type of”; Mulhern et al., 2017, 2018) and analogy (e.g. “Big is to large, as small is to tiny”; Kirsten et al., 2021, 2022). RFT, therefore, goes beyond the realm of sameness and considers the complexities of human language and thought, and the remaining chapters of this book will consider the extent to which RFT addresses these areas. TLDR Cheat sheet Relational frame theory (RFT)

A functional contextual approach to language and cognition that posits that these behavioural repertoires are deeply rooted in our ability to relate objects, events and stimuli to one another based on contextual cues alone (e.g. same as, different to, bigger than, smaller than, etc.) Operants These are voluntary behaviours which operate on the environment and are influenced by consequences. Common examples include mands, tacts, echoics and intraverbals Derived relational A pattern of responding which involves the derivation of new untaught responding (DRR) relationships between stimuli and events from a previously established or acquired relation (these can be directly taught or acquired). For example, if I outline that a Maine Coon is bigger than a ragdoll, you might then derive that a ragdoll is smaller than a Maine Coon. You have ascertained this relationship without being explicitly taught or informed that a ragdoll is smaller than a Maine Coon; instead you have (hopefully) determined their relationship based upon the relationship that was outlined to you previously (i.e. a Maine Coon is bigger than a ragdoll) This refers to responding based upon the relationship between stimuli that Arbitrarily applicable relational is based on contextual cues alone and is an abstract form of responding. responding (AARR) With AARR, the relationship is not necessarily one in which there is a clear physical relationship between them, but instead is based on the contextual cue alone. For example, within the euro currency, although a 50 cent piece is physically larger than a 1 euro piece in terms of its diameter, a 1 euro piece is worth more than a 50 cent piece – This relationship is an arbitrary one and is not based on physical properties. Therefore, if I were to ask you which coin you would prefer, if you selected the 1 euro coin, your response would be an example of AARR. This is because you based your selection on the outlined relationship between these stimuli that was not a physical one, but was instead an arbitrary or abstract one Contextual cue This is a stimulus which outlines the relationship between two or more stimuli/events and is the stimulus which outlines the relational frame which comes to bear on the included stimuli. For example, for the relational frame of distinction, the contextual cues which may be included are “different”, “unlike”, “dissimilar”, “distinct”, “disparate”, etc. (continued)

34 Non-arbitrarily applicable relational responding (NAARR)

Mutual entailment

Combinatorial entailment

Transformation of stimulus function

2  What Is Relational Frame Theory? This refers to responding based upon the physical relationship between stimuli. With NAARR, the organism’s responding is based on the physical properties of stimuli including colour, height, size, etc. for example, if you were presented with two plates of biscuits, one of which holds five biscuits and the other has two biscuits, and you were asked which plate had the most – You would respond by saying the plate with five biscuits. This is because you can see the physical relationship between the stimuli and are basing your response on this rather than any verbal communication provided to you. This level of responding forms the cornerstone of much more complex responding within human development This refers to the relationship between two stimuli and is a component of all relational frames (and is the first pattern of relational responding to emerge in each relational frame). Mutual entailment applies when in a specified context, Stimulus 1 is related in a characteristic way to Stimulus 2, and as a result Stimulus 2 is now related in another characteristic way to Stimulus 1. For example, if you are told that a flamingo is the same as a plameniak, you would then derive that a plameniak is the same as a flamingo, indicating a mutually entailed relationship This refers to the relationship between three or more stimuli which occurs when two or more mutually entailed relationships combine. Combinatorial entailment applies when in a specified context Stimulus 1 is related in a characteristic way to Stimulus 2 and 3, and as a result a relationship between Stimulus 2 and 3 is combinatorially entailed. For example, if you are told that aaloo is the same as potato and práta, you would then derive that a potato is the same as a práta, making the relationship between práta and potato one of combinatorial entailment (and coordination) This refers to the modification or transformation of the stimulus functions (e.g. appetitive, aversive, discriminative, etc.) of stimuli based on their participation in relational frames – This applies to both mutually entailed and combinatorically entailed relationships across all relational frames. This occurs when the function(s) of a stimulus changes the function(s) of another stimulus as a result of the derived relationship between these stimuli, and this should occur without additional training. For example, if I told my friend Anna that I had cáis in the fridge and asked her would she like some, she would probably be unsure of how to respond – Meaning that the stimulus cáis is neutral. However, if I then tell her that cáis is the same as cheese, she will now have a very definitive aversive response to this stimulus as she is lactose intolerant. The stimulus cáis has now been transformed from a neutral stimulus to an aversive one due to its relationship of sameness with the stimulus cheese. This is a terribly cheesy example of transformation of stimulus function (continued)

References Unidirectional

Bidirectional

35 This refers to a relationship which operates in one direction only and is a characteristic of the relationship between stimuli across relational frames. For example, if I outline that my purse contains money, this is a unidirectional relationship because my purse can contain money, but money cannot contain my purse (unless we have entered a fantastical realm) – This relationship cannot be reversed, and the contextual cue of “contain” can only operate in one direction; similarly, the idea that the money is inside the purse also is a unidirectional relationship such that the contextual cue of “inside” only operates in one direction. Therefore, unidirectional relationships are those in which the relationship between stimuli may operate in one direction but may not necessarily operate in the same way in the other direction This refers to a relationship which operates in two directions (i.e. the relationship goes both ways, but is not necessarily symmetrical) and is a characteristic of the relationship between stimuli across several relational frames. Bidirectionality maintains that if Stimulus A is related to Stimulus B, then Stimulus B is related to Stimulus A, irrespective of the form of that relationship. For example, if I outline that Darcy is bigger than Cinnamon, there is a bidirectional relationship between Darcy and Cinnamon such that Darcy is related to Cinnamon in relation to the comparison of size and Cinnamon is related to Darcy based on the comparison of size

References Alonso-Álverez, B., & Pérez-González, L.  A. (2018). Analysis of apparent demonstrations of responding in accordance with relational frames of sameness and opposition. Journal of the Experimental Analysis of Behavior, 110(2), 213–228. https://doi.org/10.1002/jeab.458 American Psychological Association. (2020). APA Dictionary of Psychology: Stimulus equivalence. Retrieved from: https://dictionary.apa.org/stimulus-­equivalence Auguston, E. M., & Dougher, M. J. (1997). The transfer of avoidance evoking functions through stimulus equivalence classes. Journal of Behavior Therapy and Experimental Psychiatry, 28(3), 181–191. https://doi.org/10.1016/S0005-­7916(97)00008-­6 Auguston, E. M., Dougher, M. K., & Markham, M. R. (2000). Emergence of conditional stimulus relations and transfer of respondent eliciting functions among compound stimuli. The Psychological Record, 50(4), 745–770. https://doi.org/10.1007/BF03395381 Barnes-Holmes, Y., Hayes, S.  C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Advances in Child Development and Behavior, 28, 101–138. Barnes-Holmes, D., Barnes-Holmes, Y., & McHugh, L. (2004). Teaching derived relational responding to young children. Journal of Early and Intensive Behavior Intervention, 1(1), 3–12. http://psycnet.apa.org/doi/10.1037/h0100275 Belisle, J., Paliliunas, D., Lauer, T., Giamanco, A., Lee, B., & Sickman, E. (2020). Derived relational responding and transformations of function in children: A review of applied behavior-­ analytic journals. Analysis of Verbal Behavior, 36(1), 115–145. https://doi.org/10.1007/ s40616-­019-­00123-­z Berens, N. M., & Hayes, S. C. (2007). Arbitrarily applicable comparative relations: Experimental evidence for relational operants. Journal of Applied Behavior Analysis, 40, 45–71. https://doi. org/10.1901/jaba.2007.7-­06

36

2  What Is Relational Frame Theory?

Brassil, N., Hyland, J., O’Hora, D., & Stewart, I. (2019). Reversing time and size: Mutual entailment of nonarbitrary temporal and magnitude relational responding. The Psychological Record, 69, 95–105. https://doi.org/10.1007/s40732-­018-­0323-­y Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61, 173–198. https://doi. org/10.1007/BF03395755 Cassidy, S., Roche, B., Colbert, D., Stewart, I., & Grey, I. (2016). A relational frame skills training intervention to increase general intelligence and scholastic aptitude. Learning and Individual Differences, 47, 222–235. https://doi.org/10.1016/j.lindif.2016.03.001 Dougher, M.  J., Auguston, E., Markham, M.  R., Greenway, D.  E., & Wulfert, E. (1994). The transfer of respondent eliciting and extinction functions through stimulus equivalence classes. Journal of the Experimental Analysis of Behavior, 62(3), 331–351. https://doi.org/10.1901/ jeab.1994.62-­331 Fletcher, L., & Hayes, S. C. (2005). Relational frame theory, acceptance and commitment therapy, and a functional analytic definition of mindfulness. Journal of Rational-Emotive and Cognitive-­ Behavior Therapy, 23(4), 315–336. https://doi.org/10.1007/s10942-­005-­0017-­7 Frank, A.  J., & Wasserman, E.  A. (2005). Associative symmetry in the pigeon after successive matching-to-sample training. Journal of the Experimental Analysis of Behavior, 84, 147–165. https://doi.org/10.1901/jeab.2005.115-­04 García-Zambrano, S., Rehfeldt, R. A., Hertel, I. P., & Boehmert, R. (2019). Effects of deictic framing and defusion on the development of self-as context in individuals with disabilities. Journal of Contextual Behavioural Science, 12, 55–58. https://doi.org/10.1016/j.jcbs.2019.01.007 Giurfa, M., Zhang, S., Jenett, A., Menzel, R., & Srinivasan, M. V. (2001). The concepts of “sameness” and “difference” in an insect. Nature, 410, 930–933. https://doi.org/10.1038/35073582 Harmon, K., Strong, R., & Pasnak, R. (1982). Relational responses in tests of transposition with rhesus monkeys. Learning and Motivation, 13, 495–504. https://doi. org/10.1016/0023-­9690(82)90006-­6 Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001a). Relational frame theory: A post-­Skinnerian account of human language and cognition. Kluwer Academic Publishers. Hayes, S.  C., Fox Fox, E., Gifford, E., Wilson, K., Barnes-Holmes, D., & Healy, O. (2001b). Derived relational responding as learned behaviour. In S.  C. Hayes, D.  Barnes-Holmes, & B. Roche (Eds.), Relational frame theory: A post-Skinnerian account of human language and cognition (pp. 21–50). Plenum Press. Hughes, S., & Barnes-Holmes, D. (2016). Relational frame theory: The basic account. In R.  D. Zettle, S.  C. Hayes, D.  Barnes-Holmes, & A.  Biglan (Eds.), The Wiley hand book of contextual behavioral science. Wiley. Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record, 72, 221. https://doi.org/10.1007/s40732-­021-­00457-­y Kirsten, E. B., Stewart, I., & McElwee, J. (2021). Testing and training analogical responding in young children using a relational evaluation procedure. The Psychological Record, 72, 353. https://doi.org/10.1007/s40732-­021-­00468-­9 Kirsten, E.  B., Stewart, I., & McElwee, J. (2022). Testing and training analogical relational responding in children with and without autism. The Psychological Record, 1. https://doi. org/10.1007/s40732-­021-­00493-­8 Luciano, C., Becarra, I. G., & Valverde, M. R. (2007). The role of multiple-exemplar training and naming in establishing derived equivalence in an infant. Journal of the Experimental Analysis of Behavior, 87(3), 349–365. https://doi.org/10.1901/jeab.2007.08-­06 McLoughlin, S., Tyndall, I., Pereira, A., & Mulhern, T. (2021). Non-verbal IQ gains from relational operant training explain variance in educational attainment: An active-controlled feasibility study. Journal of Cognitive Enhancement, 5, 35–50. https://doi.org/10.1007/ s41465-­020-­00187-­z Ming, S., Mulhern, T., Stewart, I., Moran, L., & Bynum, K. (2018). Training class inclusion responding in typically-developing children and individuals with autism. Journal of Applied Behavior Analysis, 51(1), 53–60. https://doi.org/10.1002/jaba.429

References

37

Montoya-Rodríguez, M. M., Molina, F. K., & McHugh, L. (2017). A review of relational frame theory research into deictic relational responding. The Psychological Record, 67, 569–579. https://doi.org/10.1007/s40732-­016-­0216-­x Mulhern, T., Stewart, I., & McElwee, J. (2017). Investigating relational framing of categorization in young children. The Psychological Record, 67(4), 519–536. https://doi.org/10.1007/ s40732-­017-­0255-­y Mulhern, T., Stewart, I., & McElwee, J. (2018). Facilitating relational framing of classification in young children. Journal of Contextual Behavioral Science, 8, 55–68. https://doi.org/10.1016/j. jcbs.2018.04.001 O’Toole, C., Barnes-Holmes, D., Murphy, C., O’ Connor, J., & Barnes-Holmes, Y. (2009). Relational flexibility and human intelligence: Extending the remit of Skinner’s verbal behaviour. International Journal of Psychology and Psychological Therapy, 9(1), 1–17. Rehfeldt, R.  A., & Barnes-Holmes, Y. (2009). Derived relational responding: Applications for learners with autism and other developmental disabilities. Context Press, New Harbinger Publications. Rodríguez Valverde, M., Luciano, C., & Barnes-Holmes, D. (2009). Transfer of aversive respondent elicitation in accordance with equivalence relations. Journal of the Experimental Analysis of Behavior, 9(21), 85–111. https://doi.org/10.1901/jeab.2009.92-­85 Sidman, M. (1971). Reading and auditory-visual equivalences. Journal of Speech and Hearing Research, 14(1), 5–13. https://doi.org/10.1044/jshr.1401.05asp0-­az`0 Stewart, I. (2018). Derived relational responding and relational frame theory: A fruitful behavior analytic paradigm for the investigation of human language. Behavior Analysis: Research and Practice, 18(4), 398–415. https://doi.org/10.1037/bar0000129 Yamazaki, Y., Saiki, M., Inada, M., Iriki, A., & Watanabe, S. (2014). Transposition and its generalization in common marmosets. Journal of Experimental Psychology: Animal Learning and Cognition, 40, 317–326. http://psycnet.apa.org/doi/10.1037/xan0000027 Zagrabska-Swiatkowska, P., Mulhern, T., Ming, S., Stewart, I., & McElwee, J. (2020). Training class inclusion responding in individuals with autism: Further investigation. Journal of Applied Behavior Analysis, 9999, 1–14. https://doi.org/10.1002/jaba.712

Chapter 3

Relational Frames of Coordination and Sameness

For those of us who work within applied practice, the importance of establishing programmes which assess, teach and support the derivation of relations of sameness is something which forms the foundation of our early applied training days. For example, as part of their task list, organisations such as the Behavior Analyst Certification Board (BACB) have asserted that accreditations such as the BCBA (i.e. Board Certified Behavior Analyst) or BCaBA (i.e. Board Certified assistant Behavior Analyst) cannot be pursued unless a candidate “use[s] equivalence-based instruction” and thereby demonstrates a capacity to formulate programmes based on the facilitation of derived relations of sameness amongst our service users (BACB, 2017, p. 4; BACB, 2020, p. 4). As such, it will come as no surprise to the reader that the argument that the capacity to derive sameness is a critical skill to function within the everyday environment is one which has been safely put to bed within applied practice and research for quite some time (e.g. Barnes, 1994; Barnes et al., 1990; Devany et al., 1986; Horne & Lowe, 1996). This behavioural repertoire even forms the basis of a number of assessment and training tools within the area of applied behaviour analysis. This includes tools such as the VB-MAPP (Verbal Behaviour: Milestones Assessment and Placement Program; Sundberg, 2008), the ABLLS-R (Assessment of Basic Language and Learning Skills – Revised; Partington, 2010) and the various PEAK (i.e. Promoting the Emergence of Advanced Knowledge) assessment and training tools (Dixon, 2014a, 2014b, 2015, 2016). For example, the VB-MAPP typically focuses on the assessment and training of these relationships of sameness via matching-to-sample (MTS) procedures. For example, at its most basic, MTS may involve matching the letter “A” to an identical letter “A”, but MTS may also be more abstract and complex – such as matching (or relating) the word “pug” to its German counterpart of “mops”. The first of these examples is NAARR of coordination, while the second example is AARR of coordination. Each of these aforementioned tools directly focus on the measurement of identity matching beginning with NAARR and culminating in AARR, with only the PEAK curriculum explicitly outlining its relationship with RFT and focusing on the components of relational framing overall. © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_3

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Show Me the Data! The majority of research which has focused on the derivation of sameness or coordination has done so through the lens of stimulus equivalence (for a review, see Sidman, 1994, 2000, 2009), with a considerable amount of published RFT research focusing on frames of coordination – at least in the Journal of Applied Behavior Analysis (see Rehfeldt, 2011, for a compelling breakdown of derived relational research published in the annals of the journal between 1992 and 2009). Belisle et al. (2020) extended the analysis of Rehfeldt (2011) and provided a review of 123 published research studies across a number of behaviour analytic journals, which examined training procedures to facilitate derived relational responding and transformation of stimulus function amongst children. They showed a similar pattern to that of Rehfeldt (2011), with 80% (n = 101) of the included studies focusing on the development of derived relations of coordination, with the majority of these studies focusing on the utilisation of culturally relevant relations (i.e. those used in society on an everyday basis) as opposed to arbitrary relations (i.e. those who have no relevant cultural context). Given the wealth of research exploring the applications of relational frames of coordination, it is difficult to provide an exhaustive list of the behavioural repertoires which coordinate training programmes have facilitated – but I shall endeavour to do so as best as I can by considering three core areas – education, functional living skills and vocational skills. Published research has indicated that employing relational frames of coordination have facilitated educational skills including maths (Dixon et al., 2016; Henklain & Carmo, 2013; Lynch & Cuvo, 1995; McGinty et al., 2012; Ninness et al., 2006; Ninness et al., 2009), reading (Joyce & Wolking, 1989; Matos et al., 2006; Miguel et al., 2013), spelling (Matos et al., 2006), second languages (Haegele et al., 2011; Joyce et al., 1993; Petursdottir & Hafli∂adóttir, 2013), chemistry (César & Moroz, 2018), braille literacy skills (Toussaint & Tiger, 2013), US geography (LeBlanc et al., 2003), religious literacy (Ferman et al., 2020), piano/ music skills (Hayes et al., 1989; Hill et al., 2019) and receptive emotional labelling (Noro, 2005). Research has also indicated the utility of functional everyday living and social skills programmes founded on establishing relational frames of coordination and/or stimulus equivalence across adults, children, individuals with developmental disorders and individuals with traumatic brain injuries. This research includes the identification of appropriate portion sizes amongst undergraduate students (Hausman et al., 2014; Trucil et al., 2015), the identification of the nutritional content of food amongst adults (Arntzen & Eilertsen, 2020), teaching healthy food choices (Nastally et al., 2010), self-management skills to children with autism (Pierce & Schreibman, 1994), supermarket shopping skills for individuals with intellectual disabilities (Taylor & O’Reilly, 2000), name-face matching to adults with brain injuries (Cowley et al., 1992), emotion recognition to adults with brain injuries (Guercio et al., 2003), manual signs to college students (Longo et al., 2022) and adults with intellectual disabilities and hearing impairments (Elias et al., 2008), teaching young children

Relational Frames of Coordination: They’re All the Same!

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their caregivers’ contact information (LaFond et al., 2020), language interventions for individuals with language disabilities (Carr & Felce, 2000), teaching children to recycle and compost (Bolanos et al., 2020) and teaching children to accurately disclose child abuse (Keenan et al., 2000). Relational frames of coordination have even been used to facilitate vocational-­ specific skills including inferential statistics and statistical variability (Albright et  al., 2015; Critchfield, 2014; Critchfield & Fienup, 2010; Fields et  al., 2009; Fienup & Critchfield, 2010, 2011; Sandoz & Hebert, 2017), hypothesis decision-­ making skills (Fienup & Critchfield, 2010), brain anatomy and function (Fienup et al., 2010; Fienup et al., 2015; Fienup et al., 2016; Pytte & Fienup, 2012; Reyes-­ Giordano & Fienup, 2015), research design (Lovett et al., 2011; Sella et al., 2014; Walker & Rehfeldt, 2012), causes and supports for disabilities (Alter & Borrero, 2015; Walker et al., 2013), verbal operants (O’Neill et al., 2015), operant functions of behaviour amongst graduate students in ABA (Albright et al., 2016) and generic and proprietary names of drugs in addition to drug class training (Zinn, 2002; Zinn et al., 2015). Given the wide range of skills, and the varied populations, that have been and can be targeted using relational frames of coordination and/or stimulus equivalence, it should come as no surprise that this forms the basis of most early interventions and assessment tools (e.g. VB-MAPP, ABLLS-R and PEAK), and this is potentially why this frame has received considerable research attention (see Belisle et al., 2020; Rehfeldt, 2011).

Relational Frames of Coordination: They’re All the Same! As previously outlined in Chap. 2, the components of each relational frame are, rather ironically, the same (i.e. mutual entailment, combinatorial entailment and transformation of stimulus function), thereby providing us with a useful and relatively simple framework for the assessment and facilitation of these behavioural repertoires. So, why do we begin by focusing on relational frames of coordination? We do so because the research indicates that this is one of the first relational frames to emerge (e.g. Kirsten & Stewart, 2021; Lipkens et al., 1993) and is also considered to be the building block of other relational frames (Hayes et al., 2001; Kent et al., 2017). Coordination itself focuses on relationships of sameness or similarity – it is important to remember that for this relational frame, the stimuli involved do not have to be identical. In fact, the stimuli within these frames can just bear a passing resemblance to each other (not unlike purchasing an item online and having your expectations challenged by the reality in front of you). The Mad Hatter’s question of “Why is a raven like a writing desk?” potentially provides us with such an example of relational similarity. Ravens share no resemblance to writing desks (at least not physically), but we might consider them to be the same in terms of their functions – both of these stimuli are capable of producing notes. Are these stimuli the same? No – but they are similar (even if it is a tenuous similarity).

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Some Prerequisites.. At this point, I have hopefully sold you on the utility of an RFT programme; however, before we apply the framework, it is important that we do not forget the valuable information that we have garnered from the field of behavioural psychology overall. For example, Greer and Keohane (2005) and Greer and Ross (2008) provide a comprehensive overview of verbal milestones which we may also consider as necessary prerequisite behavioural repertoires before commencing on an RFT-based programme. Specifically, the behavioural repertoires that we must consider to be fully established before commencing with an RFT programme are those of pre-­ listener components (i.e. visual tracking, capacity for “sameness” across senses, compliance based on visual contexts and caregivers as a source of reinforcement) and some basic listener skills (i.e. conditioned reinforcement for voices and the capacity to discriminate between words and sounds that are not words). If these behavioural skillsets have not yet been established, it is unwise to pursue an RFT-­ based programme. However, if these prerequisites have been met, then you are sufficiently equipped to begin.

Selecting Your Methodology Within both the assessment and teaching phase, it is imperative to utilise a variety of contextual cues which correspond to the relational frame in question (see Table 3.1 for a brief list of contextual cues for the relational frame of coordination). This has typically been addressed within the research and applied settings using a matching-to-sample (MTS) format (e.g. Elias et al., 2008; McGinty et al., 2012; Ninness et al., 2009). Within an MTS procedure, teaching trials begin by presenting an individual with a sample stimulus; then two or more choice stimuli are presented either while the sample remains present or after it has disappeared (i.e. delayed MTS; see Fig. 3.1 for an example of MTS). If the individual selects the appropriate choice stimulus contingent on the sample, this section results in reinforcement (Doughty & Saunders, 2009), while an incorrect selection may be extinguished. This procedure has been used extensively within stimulus equivalence research (e.g. Arntzen et  al., 2010; Boelens et  al., 2000; Sidman et  al., 1986) and typically is Table 3.1  A brief list of contextual cues for the relational frame of coordination Contextual cues for coordination Is Is the same as Is similar to Is like Duplicates Is a duplicate of Is synonymous Is akin to Equivalent to Is congruent Doubles as Dupes

Means Is identical to Corresponding Resembles Matches Is a dupe of

Is equal to Corresponds to Is interchangeable Twins Is homogenous :

Parallels Is analogous to Is comparable to Mirrors Coordinates =

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Fig. 3.1  Example of MTS procedure In this example, an individual’s selection of the centre stimulus (i.e. circle) would be reinforced as this choice stimulus matches the sample stimulus. As a keen reader may have realised, this is an example of NAARR (as the selection is based on the physical characteristics of the stimuli, rather than an arbitrary or abstract relationship – this is where the foundation of contextual cues begins)

combined with multiple-exemplar training (MET), which involves the use of a number of different stimuli when conducting training programmes in order to provide the participant with multiple examples or opportunities of learning and to promote generative responding. Within the context of an MTS framework when teaching coordination, an individual may be taught to select (or match) the sample Stimulus 1 to the choice Stimulus 2, rather than selecting the comparison Stimulus B. Similarly, the participant may also be taught to match the sample Stimulus A to the choice Stimulus B, rather than selecting the comparison Stimulus 2, thereby establishing the relations of 1–2 and A-B, respectively. An individual may be taught further relationships between stimuli thereby establishing further coordinate relations (e.g. 2–3 and B-C). If this seems familiar to you – it should, as this forms the basis of Sidman’s early work (e.g. Sidman, 1971). Additional variations of the MTS procedure exists including the many-to-one (MTO) and one-to-many (OTM) procedures – particularly in relation to stimulus equivalence. As part of the MTO procedure, using the above example, teaching would involve the selection of Stimulus 2 when presented with Stimulus 1 and teaching an individual to select Stimulus 3 when presented with Stimulus 1 – equivalence testing would assess the relationship between Stimulus 2 and 3. Again using the above example, the OTM procedure involves teaching an individual to select Stimulus 1 when presented with Stimulus

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2 and teaching the selection of Stimulus 1 when presented with Stimulus 3 – equivalence testing would again assess the relationship between Stimulus 2 and 3. Arguably, MTS is a methodology which is best suited for studies of equivalence or coordinate relations (Hayes & Barnes, 1997) and therefore may not be appropriate for more complex relational frames. As previously outlined, MET has been used to establish relational framing repertoires. For example, Luciano et al. (2007) taught a 15-month-old child coordinate mutually entailed relations (i.e. object-sound/sound-object relations) using MET. Within the study, the child was presented with an object (i.e. Stimulus A) and was labelled (i.e. Stimulus B) by the experimenter – thereby presenting A-B relations. Following this, the child was provided with training to select the object when presented with its label (i.e. B-A relations). From this training, when the child was presented with novel objects and provided with their label, they were then able to select the appropriate object when provided with its label – thereby demonstrating derived mutually entailed coordinate relations. MET has also been combined with natural environment teaching (NET). For example, Lipkens et al. (1993) outline the findings of a case study which follows the early language development of a neurotypical child. They outlined that by 17 months, the child was able to derive mutually entailed picture-name relations and by 24 months was able to combinatorially entail name-sound relations. The facilitation of this relational frame of coordination has occurred via a combination of naturalistic learning opportunities (e.g. a child may be taught to look at a particular stimulus when presented with a specific word – child looks at cat when presented with the word cat) and multiple examples of such relationships. Initially, a child must be taught each symmetrical relation in both directions (e.g. see “cat”, say “cat”, i.e. a tact; hear “cat”, look at cat, i.e. a listener repertoire). Initially, a child must be taught each symmetrical relation in both directions (e.g. see “cat” – say “cat”- i.e. a tact; hear “cat” – look at cat – i.e. a listener repertoire); however, following multiple exemplars of this bidirectional teaching and learning within the natural environment, generalisation occurs, meaning that a child can now derive relations of sameness in an untrained direction (McHugh & Reed, 2008). For example, if a child is taught that when they hear “pug”, they then look at the pug, due to the previous bidirectional learning history, they may then derive that when they look at the pug, they then say the word “pug”. More recent research has focused on the utilisation of the relational evaluation procedure (REP; see Barnes-Holmes et al., 2001; Hayes et al., 2016; Stewart et al., 2004), which is a methodology which was developed to assess and teach relational framing repertoires under controlled laboratory conditions. This methodology was developed as a reaction to dissatisfaction with the limitations of MTS and has been used as the basis of a number of research programmes, including the SMART (Strengthening Mental Abilities with Relational Training; Cassidy et al., 2011) protocol, the IRAP (Implicit Relational Assessment Procedure; see Hussey et al., 2015) and the RCP (Relational Completion Procedure; e.g. Walsh et al., 2014). This methodology is recommended for those pursuing an RFT-based programme for scientific publication, as it allows the individual to produce a response other than mere selection (e.g. Barnes-Holmes et al., 2001) and to provide a method that more clearly

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models and analyses natural language performances. This procedure also provides the participant/student with the opportunity to consider or describe the stimulus relations or the relational frames that are presented to them within a learning trial (e.g. Stewart et al., 2004), typically by providing a confirmation or disconfirmation response (e.g. “Yes” and “No”), such that a participant may confirm or deny the applicability of specific stimulus relations to other sets of stimulus relations (i.e. are the stimuli presented actually “the same”; see Stewart et al., 2004). For example, Stewart et  al. (2004) employed an REP framework to facilitate relational frames of coordination and distinction. The initial step of this procedure involved establishing the relational functions of coordination and distinction for arbitrary stimuli (i.e. these stimuli now function as the contextual cues for “same” or “different”; see Fig. 3.2 for an example of these stimuli) while also establishing the functions of “yes” and “no” for two additional arbitrary stimuli. Such a procedure allows a participant to somewhat elaborate on the response that they have given  – thereby providing us with much more rich data! During an assessment phase, stimuli in a specific relationship with each other (e.g. two stimuli which are the same colour or shape serve as a relationship of coordination, while two stimuli which hare different shapes or colour serves as a relationship of distinction) are presented in addition to a contextual cue (i.e. one of the arbitrary shapes established as “same” and “different”) and the cues for “yes” and “no” (see Fig.  3.3 for an example). Stewart et al. (2004) found that when the relationship between the objects corresponded with the contextual cue (i.e. the objects were the same and were presented with the contextual cue for same), the participants selected the “yes” comparison and chose the “no” comparison when it did not. Such a methodology provides a potentially useful framework for the facilitation of more complex frames, as the work of Stewart et al. (2004) also indicated that it was possible to generate multiple relatively complex relational networks. Although the REP framework may seem complex and initially may not seem amenable for use with individuals with a limited relational framing repertoire, there Fig. 3.2  An example of arbitrary stimuli serving as contextual cues within REP. These shapes serve as contextual cues and provide us with a working model for the establishment of contextual cues

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Fig. 3.3  An example of the initial stages of REP assessment and training Please note that for the purpose of clarity and ease of communication, the text of “Same as” and “different to” were included; however, in REP work, this would typically not be included

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Fig. 3.3 (continued)

is evidence to suggest that such a procedure can be used to assess and shape relational framing repertoires. For example, within their first study, Hayes et al. (2016) indicated that an REP framework could be used to assess relational frames of coordination and distinction to children between the ages of 2 and 5. Their second study also found that children who failed to demonstrate responding in the early stages of the REP (i.e. Level 1 of the assessment which assessed non-arbitrary distinction and coordinate relations) were successfully taught NAARR coordinate and distinction responding. Within this level, two pictures (either identical or non-identical) were presented on the screen with an auditory prompt (e.g. “Are these the same, or different?”). The children were then required to select either the “same” or the “different” button in response (see Fig. 3.4 for clarification of Levels 1 to 3 of the REP). The children within this study (aged between 3 and 4 years) successfully acquired these non-arbitrary relational frames, and interestingly, within the fourth study by Hayes et al. (2016), two children (aged 33 and 35 months old) who had evidenced lower levels of responding than the children in Study 2 were also successfully non-­ arbitrary coordinate and distinction relations. Their third study extended on the previous findings by recruiting those children who failed to demonstrate Level 2 responding – at this level, children showed difficulties in responding “yes” or “no” to non-arbitrary coordinate and distinction relations. This training procedure was also successful in establishing further NAARR for frames of coordination and distinction with the use of “yes”/“no” comparison or confirmation/disconfirmation response. Although the majority of work in relation to the REP has been conducted with adults with a, presumably, established repertoire of relational framing, this study points towards the utility of this procedure to facilitate relational framing repertoires and may offer a more comprehensive framework than that of MTS, which has primarily focused on relational frames of coordination and stimulus equivalence. Furthermore, although the REP is a computer-based programme, it is also possible to run a similar teaching programme using tabletop stimuli.

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Fig. 3.4  Illustration of REP levels of training (1–3) utilised in Hayes et al. (2016) Hopefully, the above illustration will also provide some inspiration/indication as to how you could adopt this teaching paradigm within applied practice and utilise this paradigm without the need for incorporating computers and technology (which can be costly)

The SMART online protocol (e.g. Cassidy et al., 2011) also offers a more complex organisation of relational networks and builds upon the REP framework by providing a systematically organised set of REP trials which assess and train the relational frames of coordination, opposition and comparison at varying levels of complexity (this online training is available via Raise Your IQ). Each level includes a training and a test phase, and each trial involves the presentation of one to three statements, in addition to a question that is presented under the statements. The response options “yes” and “no” also appear on the bottom of the screen – the position of which changes across trials. For example, within SMART, a participant may be presented with the following statement on the top line of text, “HAQ is the same as FOK”, followed by “FOK is the same as YUW” on the second line and “YUW is the same as PIQ” on the third line. This is then followed by the question “Is HAQ the same as PIQ?” on the bottom line of text. The participant would then select “Yes” as a response. This online protocol is similar to that of REP as it involves presenting the participant/learner with contextual cues (i.e. “same as”, “opposite”, “more than”, “less than”) which specify the relationship between stimuli and also includes the foundation of novel stimulus relations. However, the SMART protocol employs contextual cues which have already been established (unlike the REP which seeks to establish contextual cues prior to training) to asses and train relational framing. As such, this protocol may also not be suitable for early learners as they require some existing knowledge of contextual cues and basic reading skills.

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However, more recently, Raise Your IQ has also released a KidStarter SMART training programme which has been developed for younger users (aged 4 and upwards) and addresses the issues of reading repertoires by incorporating non-­ arbitrary stimuli rather than the “random” syllables used in SMART training. This programme requires a child to be guided in the learning process by a caregiver or teacher who should aim to facilitate the learning session (Raise Your IQ XE "IQ" , 2022). Such a programme may be beneficial to the facilitation of relational frames of coordination – particularly those of a non-arbitrary nature. The IRAP is a computer-based procedure which has received considerable attention within the field of RFT (e.g. Hussey et al., 2015) and is readily available online as the GO-IRAP.  This procedure allows the researcher to assess the relationship between stimuli. For example, on an IRAP trial, participants might be presented with one of two sample words (e.g. “Shellina” or “Lois”) at the top of the computer screen. Underneath this sample word is a target stimulus (e.g. the word snake or the word dog). Participants are then required to determine the relationship between the sample word and the target stimulus by selecting one of two options (i.e. “It matches” or “It doesn’t match”) which are presented at the bottom of the screen (see Fig. 3.5 for an illustration). In order to progress onto further trials, the participant must select in accordance with a specific relational frame (e.g. when provided with the target word “Lois” and the sample word “snake”, the relational option “it matches” is selected), while on other trials, progression is dependent on the participant selecting an inconsistent relational response (e.g. when provided with the target word Lois and the sample word “snake”, the relational option “it doesn’t match” is selected). The difference in response latencies across these consistent and inconsistent trials provides a metric to assess for implicit responses. Although the IRAP has predominantly been designed to assess established relational networks (e.g. measuring and detecting changes in implicit associations towards the elderly; Edwards et al., 2017), it should also be considered as a potential tool for both assessment and teaching. For example, Kilroe et al. (2014) adapted the IRAP software (known as the Teacher-IRAP; T-IRAP) to teach the relational frames of coordination, comparison and opposition to autistic children. Furthermore, Murphy and Barnes-Holmes (2017) outline the promise of the GO-IRAP for teaching a number of relational frames. As such, this should be considered as a potential tool within early assessment and teaching – particularly as it is a free resource! The RCP is a further extension of the REP and has early roots in the examination of the transformation of stimulus functions in accordance with relational frames of coordination and opposition amongst adult populations (e.g. Dymond et al., 2007, 2008); however, interestingly, it was first developed as a functional analytic model of reading and responding to sentence-completion tasks (see Federmeier & Kutas, 1999). Using this procedure, Dymond et  al. (2007, 2008) sequentially presented stimuli to the participants, beginning with the sample stimulus which was then followed by a contextual cue, a blank space and up to five comparisons. Participants were then asked to “complete the sentence” by selecting one of the comparisons, placing it into the blank space and confirming their selection by selecting to finish

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Fig. 3.5  An illustration of IRAP trial types Within this scenario, a participant must determine whether the target word (i.e. Shellina or Lois) is consistent (i.e. it matches) or is inconsistent (i.e. it doesn’t match) with the sample word (i.e. dog or snake). For the purpose of clarity and ease of communication, the text “target word”, “sample word” and “response options” were included; however these are not typically present on an IRAP trial

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Fig. 3.5 (continued)

the trial or to start the trial again. Within training trials, participants were then given feedback (i.e. correct or incorrect), while no feedback was provided for assessment trials (see Fig. 3.6 for example of non-arbitrary relational training of coordination). For instance, within a non-arbitrary relational training trial, a participant may be presented with a triangle as the sample stimulus, followed by the contextual cue for “same” and three or more comparison stimuli; the participant would then be expected to select the triangle from the comparison stimuli and drag it to the blank space and confirm the trial was finished (or that they wished to wipe their response and start again). Upon doing this (and emitting a correct response), this behavioural chain would then be reinforced. The arbitrary relational training and testing were similar to that of the non-arbitrary trials; however, in the place of stimuli which bore a physical resemblance (or dissimilarity) to each other, they instead employed arbitrary stimuli (e.g. trigrams). Based upon their results, Dymond et al. (2007, 2008) posited that by presenting stimuli in this manner (which bears a resemblance to established reading repertoires and history of learning), such a procedure might facilitate relational framing repertoires relative to MTS as they had found across both studies that participants required fewer trials to meet criterion during non-arbitrary training and testing than that which is typically observed in MTS tasks. This hypothesis was later tested in further studies comparing the utility of the RCP to that of MTS in relation to the facilitation of arbitrary relational repertoires (see Dymond et al., 2013 and Dymond & Whelan, 2010), which indicated an accelerated acquisition rate for relational framing repertoires via RCP when compared to MTS. Using this methodology, Walsh et al. (2014) applied the RCP, combined with MET, to facilitate relational framing repertoires of coordination amongst nine autistic boys (aged 5–18) who had verbal repertoires (with the exception of one participant) but had evidenced moderate to severe language delays in both receptive and expressive language. The results indicated that seven of the nine participants passed tests for derived relations. In a second study, Walsh et al. (2014) then employed the same procedure to establish derivation of relations of coordination in three children without any diagnosed developmental conditions (aged 5–6) and five further autistic children (aged 10–11) who, with the exception of one participant, had no history of language delay. They

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Fig. 3.6  Illustrated example of an RCP of three stimuli and sequence of presentation Please note that the placement of the target stimulus would change on each trial

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Fig. 3.6 (continued)

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found that all three children without a diagnosis successfully acquired the four-­ member equivalence class, as did four of the five autistic children. Such results provide an encouraging foundation for future research based on RCP and its applications within RFT and the behavioural sciences more generally. As a keen reader may have observed, the “finish trial” and “start again” confirmatory responses within the RCP are similar to that of the “yes” and “no” functions within the REP and are again focused upon the evaluation of stimulus relations within the given trial. However, in contrast to the REP, the RCP has a drag-and-drop response requirement prior to the confirmatory response which is not present in the REP. Furthermore, the RCP also relies on the utilisation of previously established cue functions – such as the English words “finish trial” and “start again” within both the assessment and training of relational frames. These subtle (yet important) differences may play a role in the selection of the methodology most suited towards your research question or applied project.

The Initial Steps of Teaching Now that we have waded through the murky depths of RFT methodology (and you have selected which one best suits your purpose), let’s consider how to embark upon a training programme to facilitate relational frames of coordination. If you perused Chap. 2, then it should come as no surprise that the initial steps of an RFT programme are concerned with the assessment and the establishment of NAARR across the three components of any frame (i.e. mutual entailment, combinatorial entailment and transformation of stimulus function; see Fig. 3.7 for representation of two forms of non-arbitrary frame of coordination).

Let’s Talk Stimuli: Non-arbitrary Training of Coordination You may begin the very basis of NAARR coordination by relating completely identical stimuli (e.g. matching a red block to another red block which is of identical shape and size). An applied example of NAARR of mutual entailment is that of the first phase of PECS (Picture Exchange Communication System; Frost & Bondy, 1994) training, in which individuals are taught to relate a picture to a corresponding physical item and then learn to exchange this picture for this item (i.e. use as a manding device). We must first begin with mutual entailment and ensure that we are teaching bidirectionally (i.e. in both directions; see Fig. 3.8 for an example of teaching), with a variety of contextual cues, and are using multiple exemplars in order to facilitate the NAARR of coordination. As this is the very beginning stages of acquisition, carefully consider the prompts that you may employ to facilitate learning and ensure an adequate ratio of reinforcement. While teaching it is also important to assess for acquisition of derived mutual entailment – to do this, you must employ

Let’s Talk Stimuli: Non-arbitrary Training of Coordination

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Fig. 3.7  Illustration of non-arbitrary relational frame of coordination The first example is a traditional representation of non-arbitrary coordination, as we can see a clear relationship between the stimuli (i.e. they are all squares outlined in black). The second example is more subtle, but still functions as a type of non-arbitrary relational frame, because the words bear a physical similarity to each other – e.g. all begin with the letter “c”, while the words “chair” and “chaise” bear four letters in common and have the same number of syllables, making it more likely that we may relate these stimuli as similar on this basis. As such, if we placed these stimuli as part of AARR training, we could not say with certainty that an individual’s responses are based solely on contextual cues, as they may instead be based on the physical properties of those stimuli, thereby giving us inaccurate results. Remember, just because you are using verbal stimuli does not mean that it is automatically arbitrary (the concept of onomatopoeia also applies here!)

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Fig. 3.8  Teaching non-arbitrary mutual entailment of coordination Remember to train in both directions (i.e. A is the same as B and B is the same as A)

novel stimuli and teach the relationship of coordination in one direction (e.g. A is the same as B) and then assess the derivation of coordination (i.e. assess whether the individual can derive that B is the same as A; see Fig. 3.9 for an example of assessment). Once mastery of this has been achieved, you may then move on to employing stimuli that are not identical, but still bear physical similarity (e.g. matching a blue button to a red button). Afterall, NAARR coordination is not just about identical stimuli, but is about physical similarity between and across stimuli. If a student is struggling with mutually entailed coordination against these similar (but non-­ identical items), again begin by bidirectionally training these relationships and again probing for the derivation of coordination using novel stimuli. Once derivation of mutually entailed non-arbitrary coordinate relations has been observed, you are now in the position to begin to teach combinatorial entailment. If you recall from Chap. 2, combinatorial entailment is a combination of two or more mutually entailed relationships  – however, let’s not get overly ambitious  – let’s remain with just two mutually entailed relationships when teaching the basics of NAARR coordination (and your ambition can grow over time). As your student is now able to derive relationships of mutual entailment, you no longer will need to teach bidirectionally in this respect (however, we are all likely to be data nerds, so keeping some record of this is always useful). Instead, our bidirectional training is now concerned with combinatorial entailment. We can now begin by employing stimuli that are similar to one another (they do not need to be physically identical) and outlining the mutually entailed relationships (e.g. A is the same as B; B is the same as C), again using a variety of contextual cues and multiple exemplars. You should also select prompting levels and reinforcers based upon the needs and/or interests of your learner. Bidirectional training again comes into play  – but is

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Fig. 3.9  Assessing NAARR mutual entailment of coordination Please note that when assessing NAARR of mutually entailed coordination, you may teach the relationship between the novel stimuli in one direction (i.e. A is the same as B). However, it is important that you do not train this bidirectionally; instead, assess for derivation of sameness for the untrained relation (i.e. have the individual derive that B is the same as A without being explicitly taught this relationship)

Fig. 3.10  Illustrated example of teaching combinatorial entailment of NAARR coordination Within this illustration, the relationship of coordination is being taught between the white triangle and the gradient triangle (i.e. mutual entailment); however it is not being taught bidirectionally as the student has already demonstrated acquisition of mutual entailment of NAARR coordination previously. The student is further taught relationships of coordination between the gradient triangle and the triangle with a pattern (i.e. mutual entailment). The combinatorial entailment of NAARR coordination is taught between the white triangle and the patterned triangle bidirectionally (i.e. the white triangle is the same as the patterned triangle and the patterned triangle is the same as the white triangle)

concerned with the relationship of combinatorial entailment (i.e. the A – C and C – A relationship; see Fig. 3.10 for an illustration of this). As with mutual entailment, in order to determine a learner’s progress and acquisition of combinatorial entailment, it is important to assess the derivation of combinatorial entailment to avoid (a)

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boring a student by keeping them at a level that is too simple for them or (b) frustrating a student by repeated exposure to a behavioural repertoire that is not yet feasible for them to acquire (and if this is the case, it is important to revert to the previous level of training to ensure mastery). For this assessment piece, the bidirectional training portion is omitted, such that the student is taught A is the same as B (mutual entailment) and B is the same as C (mutual entailment) using novel stimuli – and their capacity to derive combinatorially entailed relationships is then evaluated (i.e. is A the same as C, is C the same as A?; see Fig. 3.11 for an illustration). Once an individual has demonstrated a capacity to derive combinatorial relations across two mutually entailed relationships, it is possible to then assess and train combinatorial entailment across three or more mutually entailed relations of NAARR coordination. Transformation of stimulus function is the final characteristic of a relational frame that we have to explore and is best divided into two parts – transformation of stimulus functions across mutually entailed relations and transformation of stimulus functions across combinatorially entailed relations. When we speak of transformation of stimulus functions, this actually relates to many functions that a stimulus may have. For example, this may mean an unconditioned elicited function (e.g. dark chocolate tastes bitter), a conditioned elicited function (e.g. blinking when a puff of air is introduced to the eye), a discriminative function (e.g. stopping at a stop sign), a consequential function (e.g. receiving penalty points for speeding may be punishing) or an extinction function (e.g. when presented with a faulty pay and display machine, we may give up trying to pay for parking). This is not an exhaustive list,

Fig. 3.11  Example of assessment of combinatorially entailed NAARR coordination When assessing NAARR of combinatorially entailed coordination, you may teach the relationship between the novel stimuli in one direction (i.e. A is the same as B; B is the same as C). However, it is important that you do not train the combinatorial entailment element of this relationship, and you must instead evaluate derived responding in relation to A and C (i.e. is A the same as C; is C the same as A), again without explicit instruction. Furthermore, for those who are very interested in data collection, it may also be recommended to assess the derivation of mutual entailment (similar to that outlined in Fig. 3.9)

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but should provide some inspiration for teaching in relation to transformation of stimulus function. We will first begin by considering the facilitation of transformation of stimulus functions of non-arbitrary mutually entailed relations of coordination. As previously outlined, PECS training provides an exemplary indication of this element of coordination. Within PECS, a picture acts as a referent for an object or activity which can be exchanged to gain access to this stimulus. As such, through PECS training, this pictorial stimulus changes its psychological function by becoming potentially more appetitive as it can be used to mand for items or activities – meaning, that this stimulus has transformed from being a neutral stimulus to an appetitive one that is used for manding. When teaching transformation of stimulus function of mutually entailed NAARR coordination, we could begin by establishing a relationship of coordination between two stimuli (e.g. a picture of a dog and a cuddly toy dog). By this point, the learner has already established derived mutually entailed NAARR coordinate relations so should be able to derive that the picture of the dog is the same as the cuddly toy dog after being taught that the toy dog is the same as the picture of a dog. But where does transformation of function come in? In this scenario, we could also teach the learner that the toy dog feels soft and furry – they may experience this themselves by physically manipulating the stimulus. We can then assess and teach the transformation of stimulus functions by presenting the learner with several pictures (e.g. a dog, a cup and a television) and ask them to select which of the stimuli is also soft and furry. Early responses may need to be prompted and/or shaped and should result in positive reinforcement. An additional example may include teaching a learner to relate a toy apple to a real apple in a mutually entailed NAARR coordinate relation. The learner may then be taught that the apple tastes sweet (again by direct manipulations and sampling the apple). We can again assess and teach the transformation of stimulus functions in this context by presenting the learner with several toys (e.g. a toy hot dog, toy apple and toy egg – with the target stimulus in different locations on each presentation) and asking them which one tastes sweet (at which point, the learner should select the toy apple – either independently or via prompts). As with the previous elements of relational framing, it is also important to assess the acquisition of transformation of stimulus function by employing novel stimuli and assessing the learner’s responding. We now stumble forward onto the final element of NAARR coordinate training – transformation of stimulus functions of combinatorially entailed relations. For this step of teaching, we again establish two mutually entailed relationships across physically similar stimuli (e.g. a bowl of ice cream is the same as a picture of ice cream. The picture of ice cream is the same as a plastic toy ice cream cone). At this point in training, a learner should have established NAARR mutual entailment and combinatorial entailment repertoires for coordination. The learner may then be taught that the bowl of ice cream is cold – this can be done by manipulating the ice cream and feeling the temperature. You can then assess and teach transformation of stimulus functions of combinatorially entailed relationships by presenting the learner with a number of stimuli (e.g. a toy strawberry, a toy bowl of spaghetti and a toy ice cream

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cone) and asking the learner to select the one that is cold. You may again employ prompting and reinforcement techniques to facilitate this repertoire. When teaching this repertoire, it is important to use a variety of contextual cues in addition to multiple exemplars of stimuli across a number of psychological functions. For example, a further way in which this could be taught and assessed is by establishing a relationship of sameness between a toy car without wheels and a picture of a car with deflated tyres (mutual entailment) and a relationship of coordination between a picture of a car with deflated tyres and a cartoon of a car without wheels (mutual entailment). The learner can then be taught that the toy car without wheels is unable to drive and is therefore broken (again, this can be done via a process of manipulation). Combinatorially entailed transformation of function can then be assessed and taught by presenting the learner with a number of stimuli (e.g. a cartoon car without wheels, a cartoon bicycle and a cartoon moped) and asking the learner which one is broken/which one is unable to drive. It should come as no surprise that throughout the teaching of this phase, you should continue to assess for the derivation of NAARR coordinate combinatorially entailed transformation of stimulus function for novel stimuli. Once a learner has established all aspects of NAARR coordination (i.e. mutual entailment, combinatorial entailment and transformation of stimulus function), they have now mastered the necessary steps to commence AARR coordination training and assessment.

Arbitrary Relating and Coordination Before beginning an AARR programme, it is important to ensure that all aspects of NAARR coordination have been established as any deficits in these repertoires may impact the acquisition of AARR (e.g. Berens & Hayes, 2007). One of the most typical forms of AARR that we encounter is that of reading as a written word may not share any physical similarity to its referent (e.g. the word elephant does not bear any physical resemblance to an actual elephant). However, AARR is not limited to a reading repertoire alone and is also concerned with language and cognition more broadly and is (as we have previously discussed) fundamental to a number of complex behavioural repertoires. As with NAARR, when teaching AARR coordination, we begin by intervening on and teaching mutually entailed relationships, in contrast to NAARR; however, we are now relating stimuli that bear no physical resemblance to each other. For example, when teaching AARR mutual entailment of coordination, we may relate a blue object (e.g. a blue block) to the written word “blue”. These stimuli bear no resemblance, but in order to establish mutual entailment, we would train bidirectionally (e.g. teach the learner to match the blue block to the word blue and to match the word blue to the blue block). A technique that is often utilised in applied practice is that of stimulus prompts (i.e. a cue that makes the discriminative stimulus for the target stimulus more prominent) and prompt fading

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(i.e. the systematic removal of these prompts). In this instance, we may take the established NAARR coordinate frame and teach the learner to relate the blue block to the written word blue (which is presented in blue font; a type of stimulus prompt). By presenting the written text in blue font, this is more likely to occasion a correct response (and we are using existing NAARR repertoires to establish AARR repertoires), and this can be gradually be faded by changing the font of the word from blue to navy to black. In order to avoid the learner establishing relationships of false equivalence (i.e. all four-letter words must be blue), it is important to again use a varietal of targets and exemplars in addition to contextual cues. A further applied example of teaching and assessing AARR coordination is that of phonics. With phonics, a learner is taught to relate the letter “B” to a “buh” sound, and this is again trained bidirectionally. For example, a learner may be presented with the letter “B” and asked “what sound does this make?”, and they may reply “buh”. They may also be presented with a number of different letters and asked to find the letter that makes a “buh” sound and correctly respond by selecting the letter “B”. While teaching AARR coordination, it is important to continue to assess for the derivation of mutually entailed relationships using novel stimuli in a process that is almost identical to that of NAARR (the only real distinction is in the stimuli used and the fact that they do not bear a physical relationship to each other). Once a learner has established AARR mutually entailed coordination, it is now suitable to begin teaching and assessing combinatorial entailment of coordination. When we are doing this, we again must ensure that we are employing arbitrary stimuli that bear no physical relationship to each other. For example, if we were to teach a learner that the colour blue was the same as the written word “blue” and that the written word “blue” was the same as the written French word “bleu”, this wouldn’t really qualify as AARR as the words “blue” and “bleu” are physically very similar (i.e. same number of letters, same letters and even sound similar), making this relationship a hybrid of AARR and NAARR (or an RFT Frankenstein). Now that we have dealt with that cautionary tale of AARR, let’s proceed with considering how best to teach and assess AARR combinatorial entailment of coordination! In this scenario, we could outline that the number “5” is the same as the written word “five” and that the written word “five” is the same as the spoken word “five”. By now, our learner has derived mutual entailment so should be able to derive that the written word “five” is the same as the number “5” and that the spoken word “five” is the same as the written word “five”. We again teach bidirectionally in this context by presenting the learner with the number “5” and asking them to say what word it is (again, prompting can be used including full or partial verbal prompts) and by presenting the learner with a variety of written numbers (e.g. “7”, “9”, “5”) and asking them to find the number five (thereby teaching combinatorial entailment). A further example of teaching combinatorial entailment in this context is that of playing and producing music. For example, an early harpist may learn that “E” string is the same as the musical note or sound “E” and that this musical note or sound “E” is the same as the musical notation “E” on a staff. As such, teaching combinatorial

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of coordination in this scenario involves teaching the student that when they are presented with the musical notation “E” on a staff, they should play the “E” string on the harp and when they are asked to match the “E” string to its corresponding note on the staff, they select the musical notation of E. With combinatorial entailment AARR of coordination, continue to teach and assess this repertoire until the learner shows derivation of combinatorial entailment across untrailed and novel stimuli. Finally, we move on to transformation of stimulus function of AARR coordination, and hopefully you can now see how wonderfully straightforward RFT and its applications actually are! We will continue by considering the assessment and teaching of transformation of stimulus functions of mutually entailed relations. For example, we may teach a learner that the spoken word “stop” is the same as the written word “stop”; at this stage of learning, the learner should be able to derive that the written word “stop” is the same as the spoken word “stop”, and if they are unable to do so, then this stage of teaching is not appropriate for them. If we then teach this student to stop whatever activity they are doing when the spoken word “stop” is emitted (i.e. a discriminative function), a test of transformation of stimulus function of mutual entailment in this context might be to present the written word “stop” to a student and assess whether they have stopped their activity (and if not, prompt them to do so). It is at this point that it should be noted that RFT should not be a tabletop activity and there should be opportunities for NET. For example, in this context the learner could play statues (a movement game in which the learner dances and moves about freely but must freeze when the word “stop” is yelled), and the discriminative stimulus of the vocal word “stop” could be swapped for the written word “stop”. Always remember that RFT has real-world applications and is acquired and learned within the everyday environment. In an additional example, we may teach a learner to equate the spoken word “break” with the Irish sign language for “break” and that they can request a break in work by verbalising the word “break”. In this instance, a transformation of stimulus function would be observed if the learner spontaneously emitted the Irish sign language for “break” in a request for a break in an activity. Finally, once a learner has demonstrated transformation of function of mutually entailed AARR, we may now begin teaching and assessing transformation of function of combinatorially entailed coordinate relations. We may teach a student that the physical alkali metal of sodium is the same as the written word “sodium” and that the written word “sodium” is the same as the chemical symbol Na. We may then teach a student that the sodium metal is highly reactive to water and results in explosions when the two stimuli meet (maybe not via physical demonstration  – let’s remember the confines of our professional boundaries). We can then assess for derivation of transformation of stimulus function of combinatorial entailment by presenting the student with chemical symbols (e.g. Ag, Au, Cu, Na and Pb) and asking them to select the element that is reactive to water and is likely to explode. We can teach this via prompting and again using multiple exemplars in training in addition

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to a variety of contextual cues (hopefully that recommendation is not a surprise to you at this stage of your RFT journey). We may also teach a student that Lindt™ is similar to Milka™ and Milka™ is similar to Dairy Milk™. The student may know that Dairy Milk™ tastes sweet but has no prior exposure to Milka™ or Lindt™ – we can assess transformation of stimulus function in this scenario by asking the student what Lindt™ might taste like. In an attempt to provide further (rather unusual) multiple exemplars, a parent or caregiver may outline a list of restricted words to their child after they began to swear in school (e.g. Swear Word A is equivalent to Swear Word B and Swear Word B is similar to Swear Word C). Upon emitting Swear Word A, the child’s behaviour is punished (e.g. a verbal reprimand of positive punishment), thereby decreasing the future frequency of Swear Word A. We would say that a transformation of stimulus function has occurred in this instance if the frequency of Swear Words B and C also decreased (as these stimuli had transformed to have an aversive effect) or if the child was asked what consequences they might expect if they said Swear Words B and C. As with all of our previous examples of training, it is critical to assess for derivation of transformation of stimulus function throughout the training process to determine when to cease training due to acquisition or deficits in responding.

Future Directions for Research and Applications? Although the majority of research that has been conducted in the field of RFT directly relates to coordination (see Belisle et al., 2020; Rehfeldt, 2011), we are far from exhausting material in this area – especially when considering the many potential applications for RFT and coordination. Obvious suggestions include programmes focusing on the facilitation of language (including early language, sign language and secondary language skills) and potentially in the preservation and acquisition of endangered languages. Relational framing programmes of coordination may be further applied to academic subjects including mathematics, science, art, music, literature and many others. For example, AARR programmes could focus on the facilitation of music skills such as sight reading or musical notation. A further emphasis on everyday skills using RFT of coordination would be a beneficial direction for researchers and applied practitioners – for example, coordination-­ based programmes could potentially be employed to aid individuals in the recognition of facial emotions, to increase independent living skills (e.g. following recipes) and to facilitate social skills (e.g. recognition of sarcasm and appropriate responses) and the ability to administer basic first aid (e.g. what is the appropriate treatment for minor burns). I hope that this chapter serves as a potential inspiration for future research and applications of coordination research as appears to be an abundance of research opportunities in this field.

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TLDR Cheat Sheet Matching-to-­ Within behavioural psychology, MTS refers to a procedure in which a Sample (MTS) stimulus is presented to an individual (e.g. the word “Cruella”) and they are subsequently taught to match this to a secondary stimulus (e.g. a picture of Cruella). When these stimuli are correctly matched, this selection behaviour is reinforced Multiple exemplar This is a teaching procedure that aims to promote the generalisation of training (MET) responding outside of the training programme itself. It does this by using multiple examples when teaching and by employing a variety of stimuli and response outcomes. This mode of instruction allows the student to employ several response topographies which in turn aid in the acquisition of appropriate response forms and increases response generalisation (i.e. the emergence of untrained topographies). For example, if teaching the tact “cat” using MET, an instructor may use several pictures of different cats, cuddly toys, cartoon cats, figurines of cats and maybe even an actual cat (i.e. a variety of stimuli). Further, with MET, the instructor may teach a variety of response topographies – For example, they may be taught to tact “cat”, “kitty”, “feline”, “kitten”, “pussycat”, “mouser”, “moggie”, “tabby”, “floof” and “fur baby” (i.e. a variety of response outcomes) when presented with a cat. As a result of MET, an individual is more likely to tact “floof”, “kitty” or “fur baby” when they see a novel cat Natural This teaching method incorporates learning opportunities into everyday environment activities (e.g. highly preferred activities) and the natural environment. This teaching (NET) methodology involves following the motivations and interests of the student within that moment and looks less structured and more organic than discrete trial training. In essence, this methodology focuses on capturing learning opportunities when they arise. For example, a student may be learning colours as part of their lessons, but their mother has recently returned from a shopping trip with groceries; while unpacking these items, there are opportunities to focus on receptive and expressive language in relation to colour (e.g. “hand me the red apples please”; “these bananas are ...”; “what colour is this?”). This learning opportunity is organic and has seized on the opportunity to explore this behavioural repertoire Picture exchange This is an alternative augmentative communication device in which the communication speaker communicates their needs, preferences or social interactions via the system (PECS) exchange of pictures which act as referents for objects/activities, etc. Stimulus prompt This is a form of prompt in which a temporary change is made to physical stimuli to facilitate the target behaviour (e.g. making the target stimulus bigger, placing it closer to the learner, changing the background behind the stimulus, etc.) Prompt fading This is the process of systematically and gradually reducing and removing prompts which have been employed to facilitate learning so that the learner may engage in independent forms of the target response. For example, if a stimulus prompt had been employed such that the target stimulus was always bigger than the comparison stimuli, prompt fading would involve gradually reducing the size of the target stimulus until it was the same size as the comparison stimuli

References

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References Albright, L., Reeve, K. F., Reeve, S. A., & Kisamore, A. N. (2015). Teaching statistical variability with equivalence-based instruction. Journal of Applied Behavior Analysis, 48(4), 883–894. https://doi.org/10.1002/jaba.249 Albright, L., Schnell, L., Reeve, K.  F., & Sidener, T.  M. (2016). Using stimulus equivalence-­ based instruction to teach graduate students in applied behavior analysis to interpret operant functions of behavior. Journal of Behavioral Education, 25, 290–309. https://doi.org/10.1007/ s10864-­016-­9249-­0 Alter, M. M., & Borrero, J. C. (2015). Teaching generatively: Learning about disorders and disabilities. Journal of Applied Behavior Analysis, 48(2), 376–389. https://doi.org/10.1002/jaba.211 Arntzen, E., & Eilertsen, J. M. (2020). Using stimulus-equivalence technology to teach skills about nutritional content. Perspectives on Behavior Science, 43, 469–485. Arntzen, E., Halstadtro, L., Bjerke, E., & Halstadtro, M. (2010). Training and testing music skills in a boy with autism using a matching-to-sample format. Behavioral Interventions, 25(2), 129–143. https://doi.org/10.1002/bin.301 Barnes, D. (1994). Stimulus equivalence and relational frame theory. The Psychological Record, 44(1), 91–124. Barnes, D., McCullagh, P., & Keenan, M. (1990). Equivalence class formation in non-hearing impaired children and hearing impaired children. Analysis of Verbal Behavior, 8, 1–11. Barnes-Holmes, D., Hayes, S. C., Dymond, S., & O’Hora, D. (2001). Multiple stimulus relations and the transformation of stimulus functions. In S. C. Hayes, D. Barnes-Holmes, & B. Roche (Eds.), Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer Academic: Plenum Publishers. Behavior Analyst Certification Board. (2017). BCBA task list (5th ed.). Behavior Analyst Certification Board. Behavior Analyst Certification Board. (2020). BCaBA task list (5th ed.). Behavior Analyst Certification Board. Belisle, J., Paliliunas, D., Lauer, T., Giamanco, A., Lee, B., & Sicman, E. (2020). Derived relational responding and transformations of function in children: A review of applied behavior-­ analytic journals. The Analysis of Verbal Behavior, 36(1), 115–145. https://doi.org/10.1007/ s40616-­019-­00123-­z Berens, N. M., & Hayes, S. C. (2007). Arbitrarily applicable comparative relations: Experimental evidence for a relational operant. Journal of Applied Behavior Analysis, 40(1), 45–71. https:// doi.org/10.1901/jaba.2007.7-­06 Boelens, H., Van Den Broek, M., & Van Klarenbosch, T. (2000). Symmetric matching to sample in 2-year-old children. The Psychological Record, 50, 293–304. Bolanos, J. E., Reeve, K. F., Reeve, S. A., Sidener, T. M., Jennings, A. M., & Ostrosky, B. D. (2020). Using stimulus equivalence-based instruction to teach young children to sort recycling, trash and compost items. Behavior and Social Issues, 29, 78–99. https://doi.org/10.1007/ s42822-­020-­00028-­w Carr, D., & Felce, D. (2000). Application of stimulus equivalence to language intervention for individuals with severe linguistic disabilities. Journal of Intellectual and Developmental Disability, 25(3), 181–205. https://doi.org/10.1080/13269780050144262 Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61, 173–198. César, M. A., & Moroz, M. (2018). Teaching chemistry based on the stimulus equivalence model. Paidéia (Ribeirão Preto), 28(2838), 1–10. https://doi.org/10.1590/1982-­4327e2838 Cowley, B. J., Green, G., & Braunling-McMorrow, D. (1992). Using stimulus equivalence procedures to teach name-face matching to adults with brain injuries. Journal of Applied Behavior Analysis, 25(2), 461–475.

66

3  Relational Frames of Coordination and Sameness

Critchfield, T.  S. (2014). Online equivalence-based instruction about statistical inference using written explanation instead of match-to-sample training. Journal of Applied Behavior Analysis, 47(3), 606–611. https://doi.org/10.1002/jaba.150 Critchfield, T. S., & Fienup, D. M. (2010). Using stimulus equivalence technology to teach statistical inference in a group setting. Journal of Applied Behavior Analysis, 43(4), 763–768. https:// doi.org/10.1901/jaba.2010.43-­763 Devany, J. M., Hayes, S. C., & Nelson, R. O. (1986). Equivalence class formation in language-­ able and language-disabled children. Journal of the Experimental Analysis of Behavior, 46(3), 243–257. https://doi.org/10.1901/jeab.1986.46-­243 Dixon, M.  R. (2014a). The PEAK relational training system: Direct training module. Shawnee Scientific Press. Dixon, M.  R. (2014b). The PEAK relational training system: Generalization module. Shawnee Scientific Press. Dixon, M.  R. (2015). The PEAK relational training system: Equivalence module. Shawnee Scientific Press. Dixon, M.  R. (2016). The PEAK relational training system: Transformation module. Shawnee Scientific Press. Dixon, M. R., Belisle, J., Stanley, C. R., Daar, J. H., & Williams, L. A. (2016). Derived equivalence relations of geometry skills in students with autism: An application of the PEAK-E curriculum. The Analysis of Verbal Behavior, 32(1), 38–45. https://doi.org/10.1007/s40616-­016-­0051-­9 Doughty, A. H., & Saunders, K. J. (2009). Decreasing errors in reading-related matching to sample using a delayed-sample procedure. Journal of Applied Behavior Analysis, 42(3), 717–721. https://doi.org/10.1901/jaba.2009.42-­717 Dymond, S., & Whelan, R. (2010). Derived relational responding: A comparison of match-to-­ sample and the relational completion procedure. Journal of the Experimental Analysis of Behavior, 94(1), 37–55. https://doi.org/10.1901/jeab.2010.94-­37 Dymond, S., Roche, B., Forsyth, F. P., Whelan, R., & Rhoden, J. (2007). Transformation of avoidance response functions in accordance with same and opposite relational frames. Journal of the Experimental Analysis of Behavior, 88(2), 249–262. https://doi.org/10.1901/jeab.2007.88-­249 Dymond, S., Roche, B., Forsyth, F. P., Whelan, R., & Rhoden, J. (2008). Derived avoidance learning: Transformation of avoidance response functions in accordance with same and opposite relational frames. The Psychological Record, 58, 269–286. Dymond, S., Ng, T.  C., & Whelan, R. (2013). Establishing arbitrarily applicable relations of same and opposite with the relational completion procedure: Selection-based feedback. The Psychological Record, 63, 111–130. Edwards, D. J., McEnteggart, C., Barnes-Holmes, Y., Lowe, R., Evans, N., & Vilardaga, R. (2017). The impact of mindfulness and perspective-taking on implicit associations towards the elderly: A relational frame theory account. Mindfulness, 8(6), 1615–1622. https://doi.org/10.1007/ s12671-­017-­0734-­x Elias, N. C., Goyos, C., Saunders, M., & Saunders, R. (2008). Teaching manual signs to adults with mental retardation using matching-to-sample procedures and stimulus equivalence. The Analysis of Verbal Behavior, 24(1), 1–13. https://doi.org/10.1007/BF03393053 Federmeier, K.  D., & Kutas, M. (1999). A rose by any other name: Long-term memory structure and sentence processing. Journal of Memory and Language, 41(4), 469–495. https://doi. org/10.1006/jmla.1999.2660 Ferman, D.  M., Reeve, K.  F., Vladescu, J.  C., Albright, L.  K., Jennings, A.  M., & Domanski, C. (2020). Comparing stimulus equivalence-based instruction to a video lecture to increase religious literacy in middle-school children. Behavior Analysis in Practice, 13(2), 360–374. https://doi.org/10.1007/s40617-­019-­00355-­4 Fields, L., Travis, R., Roy, D., Yadlovker, E., de Aguiar-Rocha, L., & Sturmey, P. (2009). Equivalence class formation: A method for teaching statistical interactions. Journal of Applied Behavior Analysis, 42(3), 575–593. https://doi.org/10.1901/jaba.2009.42-­575

References

67

Fienup, D. M., & Critchfield, T. S. (2010). Efficiently establishing concepts of inferential statistics and hypothesis decision making through contextually controlled equivalence classes. Journal of Applied Behavior Analysis, 43(3), 437–462. https://doi.org/10.1901/jaba.2010.43-­437 Fienup, D.  M., & Critchfield, T.  S. (2011). Transportability of equivalence-based programmed instruction: Efficacy and efficiency in a college classroom. Journal of Applied Behavior Analysis, 44(3), 435–450. https://doi.org/10.1901/jaba.2011.44-­435 Fienup, D. M., Covey, D. P., & Critchfield, T. S. (2010). Teaching brain-behavior relations economically with stimulus equivalence technology. Journal of Applied Behavior Analysis, 43(1), 19–33. https://doi.org/10.1901/jaba.2010.43-­19 Fienup, D.  M., Wright, N.  A., & Fields, L. (2015). Optimizing equivalence-based instruction: Effects of training protocols on equivalence class formation. Journal of Applied Behavior Analysis, 48(3), 613–631. https://doi.org/10.1002/jaba.234 Fienup, D. M., Mylan, S. E., Brodsky, J., & Pytte, C. (2016). From the laboratory to the classroom: The effects of equivalence-based instruction on neuroanatomy competencies. Journal of Behavioral Education, 25(2), 143–165. https://doi.org/10.1007/s10864-­015-­9241-­0 Frost, L., & Bondy, A. (1994). The picture exchange communication system training manual. Cherry Hill Publishing. Greer, R. D., & Keohane, D. D. (2005). The evolution of verbal behavior in children. Behavioral Development Bulletin, 12(1), 31–47. https://doi.org/10.1037/h0100559 Greer, R. D., & Ross, D. E. (2008). Verbal behavior analysis: Inducing and expanding new verbal capabilities in children with language delays. Pearson. Guercio, J. M., Podolska-Schroeder, H., & Rehfeldet, R. A. (2003). Using stimulus equivalence technology to teach emotion recognition to adults with acquired brain injury. Brain Injury, 18(6), 593–601. https://doi.org/10.1080/02699050310001646116 Haegele, K. M., McComas, J. J., Dixon, M., & Burns, M. K. (2011). Using a stimulus equivalence paradigm to teach numerals, English words, and Native American words to preschool-age children. Journal of Behavioral Education, 20, 283–296. Hausman, N. L., Borrero, J. C., Fisher, A., & Kahng, S. (2014). Improving accuracy of portion-size estimations through a stimulus equivalence paradigm. Journal of Applied Behavior Analysis, 47(3), 485–499. https://doi.org/10.1002/jaba.139 Hayes, S. C., & Barnes, D. (1997). Commentary: Analysing derived stimulus relations requires more than the concept of stimulus class. Journal of the Experimental Analysis of Behavior, 68(2), 235–270. Hayes, L.  J., Thompson, S., & Hayes, S.  C. (1989). Stimulus equivalence and rule following. Journal of the Experimental Analysis of Behavior, 52(3), 275–291. Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer Academic Publishers. Hayes, J., Stewart, I., & McElwee, J. (2016). Assessing and training young children in same and different relations using the relational evaluation procedure (REP). The Psychological Record, 66, 547–561. https://doi.org/10.1007/s40732-­016-­0191-­2 Henklain, M. H. O., & Carmo, J. S. (2013). Stimulus equivalence and increase of correct responses in addition and subtraction problems. Paidéia (Ribeirão Preto), 23(56), 349–358. https://doi. org/10.1590/1982-­43272356201309 Hill, K. E., Griffith, K. R., & Miguel, C. F. (2019). Using equivalence-based instruction to teach piano skills to children. Journal of Applied Behavior Analysis, 53(1), 188–208. https://doi. org/10.1002/jaba.547 Horne, P. J., & Lowe, C. F. (1996). On the origins of naming and other symbolic behavior. Journal of the Experimental Analysis of Behavior, 65(1), 185–241. Hussey, I., Barnes-Holmes, D., & Barnes-Holmes, Y. (2015). From relational frame theory to implicit attitudes and back again: Clarifying the link between RFT and IRAP research. Current Opinion in Psychology, 2, 11–15. https://doi.org/10.1016/j.copsyc.2014.12.009 Joyce, B. G., & Wolking, W. D. (1989). Stimulus equivalence: An approach for teaching beginning reading skills to young children. Education and Treatment of Children, 12(2), 109–122.

68

3  Relational Frames of Coordination and Sameness

Joyce, B.  G., Joyce, J.  H., & Wellington, B. (1993). Using stimulus equivalence procedures to teach relationships between English and Spanish words. Education and Treatment of Children, 16(1), 48–65. Keenan, M., McGlinchey, A., Fairhurst, C., & Dillenburger, K. (2000). Accuracy of disclosure and contextual control in child abuse: Developing procedures within the stimulus equivalence paradigm. Behavior and Social Issues, 10, 1–17. Kent, G., Galvin, E., Barnes-Holmes, Y., Murphy, C., & Barnes-Holmes, D. (2017). Relational responding: Testing, training, and sequencing effects among children with autism and typically developing children. Behavioral Development Bulletin, 22(1), 94–110. https://doi.org/10.1037/ bdb0000041 Kilroe, H., Murphy, C., Barnes-Holmes, D., & Barnes-Holmes, Y. (2014). Using the T-IRAP interactive computer program and applied behavior analysis to teach relational responding in children with autism. Behavioral Development Bulletin, 19(2), 60–80. https://doi.org/10.1037/ h0100578 Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record. https://doi.org/10.1007/s40732-­021-­00457-­y LaFond, T.  R., Reeve, K.  F., Day-Watkins, J., Reeve, S.  A., Vladescu, J.  C., & Jennings, A. M. (2020). Using stimulus equivalence-based instruction to teach young children their caregivers’ contact information. Behavioral Interventions, 36(1), 105–125. https://doi.org/10.1002/ bin.1742 LeBlanc, L.  A., Miguel, C.  F., Cummings, A.  R., Goldsmith, T.  R., & Carr, J.  E. (2003). The effects of three stimulus-equivalence testing conditions on emergent US geography relations of children diagnosed with autism. Behavioral Interventions, 18(4), 279–289. https://doi. org/10.1002/bin.144 Lipkens, R., Hayes, S. C., & Hayes, L. J. (1993). Longitudinal study of the development of derived relations in an infant. Journal of Experimental Child Psychology, 56(2), 201–239. https://doi. org/10.1006/jecp.1993.1032 Longo, A., Reeve, K. F., Jennings, A. M., Vladescu, J. C., Reeve, S. A., & Colasurdo, C. R. (2022). Comparing stimulus equivalence-based instruction to self-study of videos to teach examples of sign language to adults. Behavioral Interventions, 1–19. https://doi.org/10.1002/bin.1871 Lovett, S., Rehfeldt, R. A., Garcia, Y., & Dunning, J. (2011). Comparison of a stimulus equivalence protocol and traditional lecture for teaching single-subject designs. Journal of Applied Behavior Analysis, 44(4), 819–833. https://doi.org/10.1901/jaba.2011.44-­819 Luciano, C., Becerra, I. G., & Valverde, M. R. (2007). The role of multiple-exemplar training and naming in establishing derived equivalence in an infant. Journal of the Experimental Analysis of Behavior, 87(3), 349–365. https://doi.org/10.1901/jeab.2007.08-­08 Lynch, D.  C., & Cuvo, A.  J. (1995). Stimulus equivalence instruction of fraction-decimal relations. Journal of Applied Behavior Analysis, 28(2), 115–126. https://doi.org/10.1901/ jaba.1995.28-­115 Matos, M. A., Avanzi, A. L., & McIlvane, W. J. (2006). Rudimentary reading repertoires via stimulus equivalence and recombination of minimal verbal units. The Analysis of Verbal Behavior, 22, 3–19. McGinty, J., Ninness, C., McCuller, G., Rumph, R., Goodwin, A., Kelso, G., Lopez, A., & Kelly, E. (2012). Training and deriving precalculus relations: A small-group, web-interactive approach. The Psychological Record, 62, 225–242. McHugh, L., & Reed, P. (2008). Using relational frame theory to build grammar in children with autistic spectrum conditions. The Journal of Speech-Language Pathology -Applied Behavior Analysis, 3(1), 60–77. https://doi.org/10.1037/h0100233. Miguel, C.  F., Yang, H.  G., Finn, H.  E., & Ahearn, W.  H. (2013). Establishing derived textual control in activity schedules with children with autism. Journal of Applied Behavior Analysis, 42(3), 703–709. https://doi.org/10.1901/jaba.2009.42-­703

References

69

Murphy, C., & Barnes-Holmes, D. (2017). Teaching important relational skills for children with autism spectrum disorder and intellectual disability using freely available (GO-IRAP) software. Austin Journal of Autism and Related Disabilities, 3(2), 1041–1046. Nastally, B., Dixon, M. R., McKeel, A., & Fleming, M. (2010). Teaching healthy food choices through stimulus equivalence. Journal of Behavioral Health and Medicine, 1(2), 119–126. Ninness, C., Barnes-Holmes, D., Rumph, R., McCuller, G., Ford, A. M., Payne, R., Ninness, S. K., Smith, R. J., Ward, T. A., & Elliott, M. P. (2006). Transformations of mathematical and stimulus functions. Journal of Applied Behavior Analysis, 39(3), 299–321. https://doi.org/10.1901/ jaba.2006.139-­05 Ninness, C., Dixon, M., Barnes-Holmes, D., Rehfeldt, R. A., Rumph, R., McCuller, G., Holland, J., Smith, R., Ninness, S. K., & McGinty, J. (2009). Constructing and deriving reciprocal trigonometric relations: A functional analytic approach. Journal of Applied Behavior Analysis, 42(2), 191–208. https://doi.org/10.1901/jaba.2009.42-­191 Noro, F. (2005). Using stimulus equivalence procedures to teach receptive emotional labelling to a child with autistic disorder. The Japanese Journal of Special Education, 42(6), 483–496. O’Neill, J., Rehfeldt, R. A., Ninness, C., Muñoz, B. E., & Mellor, J. (2015). Learning Skinner’s verbal operants: Comparing an online stimulus equivalence procedure to an assigned reading. The Analysis of Verbal Behavior, 31(2), 255–266. https://doi.org/10.1007/s40616-­015-­0035-­1 Partington, J.  W. (2010). ABLLS-R: The assessment of basic language and learning skills: An assessment, curriculum guide, and skills tracking system for children with autism or other developmental disabilities. Behavior Analysts, Inc. Petursdottir, A.  I., & Hafli∂adóttir, R.  D. (2013). A comparison of four strategies for teaching a small foreign-language vocabulary. Journal of Applied Behavior Analysis, 42(3), 685–690. https://doi.org/10.1901/jaba.2009.42-­685 Pierce, K.  L., & Schreibman, L. (1994). Teaching daily living skills to children with autism in unsupervised settings through pictorial self-management. Journal of Applied Behavior Analysis, 27(3), 471–481. Pytte, C. L., & Fienup, D. M. (2012). Using equivalence-based instruction to increase efficiency in teaching neuroanatomy. Journal of Undergraduate Neuroscience Education, 10(2), 125–131. Raise Your IQ. (2022). KidStarter Brain Training: A tool to accelerate the development of basic relational skills in kids. https://www.raiseyouriq.com/kidstarter-­smart-­training Rehfeldt, R. A. (2011). Toward a technology of derived stimulus relations: An analysis of articles published in the Journal of Applied Behavior Analysis, 1992–2009. Journal of Applied Behavior Analysis, 44(1), 109–119. https://doi.org/10.1901/jaba.2011.44-­109. Reyes-Giordano, K., & Fienup, D. M. (2015). Emergence of topographical responding following equivalence-based neuroanatomy instruction. The Psychological Record, 65, 495–507. https:// doi.org/10.1007/s40732-­015-­0125-­4 Sandoz, E.  K., & Hebert, E.  R. (2017). Using derived relational responding to model statistics learning across participants with varying degrees of statistics anxiety. European Journal of Behavior Analysis, 18(1), 113–131. https://doi.org/10.1080/15021149.2016.1146552 Sella, A. C., Ribeiro, D. M., & White, G. W. (2014). Effects of an online stimulus equivalence teaching procedure on research design open-ended questions performance of international undergraduate students. The Psychological Record, 64, 89–103. Sidman, M. (1971). Reading and auditory-visual equivalences. Journal of Speech and Hearing Research, 14 (1), 5–13. DOI: http://dx.doi.org/https://doi.org/10.1044/jshr.1401.05asp0-­az`0. Sidman, M. (1994). Equivalence relations and behaviour: A research story. Authors Cooperative. Sidman, M. (2000). Equivalence relations and the reinforcement contingency. Journal of the Experimental Analysis of Behavior, 74(1), 127–146. https://doi.org/10.1901/jeab.2000.74-­127 Sidman, M. (2009). Equivalence relations and behavior: An introductory tutorial. The Analysis of Verbal Behavior, 25(1), 5–17. https://doi.org/10.1007/BF03393066 Sidman, M., Willson-Morris, M., & Kirk, B. (1986). Matching-to-sample procedures and the development of equivalence relations: The role of naming. Analysis and Interventions In Developmental Disabilities, 6(1–2), 1–19, https://doi.org/10.1016/0270-­4684)86)90003-­0.

70

3  Relational Frames of Coordination and Sameness

Stewart, I., Barnes-Holmes, D., & Roche, B. (2004). A functional-analytic model of analogy using the relational evaluation procedure. The Psychological Record, 54(4), 531–552. https://doi. org/10.1007/BF03395491 Sundberg, M. L. (2008). VB-MAPP verbal behaviour milestones assessment and placement program: A language and social skills assessment program for children with autism or other developmental disabilities. Guide, AVB Press. Taylor, I., & O’Reilly, M. F. (2000). Generalisation of supermarket shopping skills for individuals with mild intellectual disabilities using stimulus equivalence training. The Psychological Record, 50, 49–62. Toussaint, K.  A., & Tiger, J.  H. (2013). Teaching early braille literacy skills within a stimulus equivalence paradigm to children with degenerative visual impairments. Journal of Applied Behavior Analysis, 43(2), 181–194. https://doi.org/10.1901/jaba.2010.43-­181 Trucil, L. M., Vladescu, J. C., Reeve, K. F., DeBar, R. M., & Schnell, L. K. (2015). Improving portion-size estimation using equivalence-based instruction. The Psychological Record, 65, 761–770. Walker, B. D., & Rehfeldt, R. A. (2012). An evaluation of the stimulus equivalence paradigm to teach single-subject design to distance education students via blackboard. Journal of Applied Behavior Analysis, 45(2), 329–344. https://doi.org/10.1901/jaba.2012.45-­329 Walker, B. D., Rehfeldt, R. A., & Ninness, C. (2013). Using the stimulus equivalence paradigm to teach course material in an undergraduate rehabilitation course. Journal of Applied Behavior Analysis, 43(4), 615–633. https://doi.org/10.1901/jaba.2010.43-­615 Walsh, S., Horgan, J., May, R.  J., Dymond, S., & Whelan, R. (2014). Facilitating relational framing in children and individuals with developmental delay using the relational completion procedure. Journal of the Experimental Analysis of Behavior, 101(1), 51–60. https://doi. org/10.1002/jeab.66 Zinn, T. E. (2002). Using stimulus equivalence to teach drug names: A component analysis and drug name classification procedure. Auburn University. Zinn, T. E., Newland, M. C., & Ritchie, K. E. (2015). The efficiency and efficacy of equivalence-­ based learning: A randomized controlled trial. Journal of Applied Behavior Analysis, 48(4), 865–882. https://doi.org/10.1002/jaba.258

Chapter 4

Relational Frames of Opposition and Distinction

The current chapter aims to consider an RFT approach to the facilitation of the relational frames of distinction and opposition. Why have I grouped these relational frames together? The relational frames of distinction and opposition each pose their own unique challenges to practitioner and researcher alike, so it seems fitting to pair them. Furthermore, these relational frames have received little attention within the research so are excitingly novel, comprising an exciting adventure for researchers within the field.

 nd Now for Something Completely Different: A Frame A of Distinction It should come as no surprise to the reader that before the relation of difference (or distinction) develops, the relationship of coordination must first be established. Although it may be tempting to believe that the acquisition of relational repertoires of sameness predisposes us to being able to engage in relational framing of difference, this is not the case. For example, the extant literature indicates that an identity matching repertoire does not necessarily correlate with accurate oddity matching, while an ability to engage in oddity matching is also not related to identity matching (e.g. Lowenkron & Colvin, 1992; Mackay et al., 2002; Soraci et al., 1987; Stromer & Stromer, 1989). As such, it appears that the repertoire of distinction must instead be explicitly targeted, and appropriate contingencies for its development must be considered. The relational frame of distinction is quite unique within RFT as, unlike other relational frames which we have explored (and will explore), the growth of such a relational network is limited. For example, if I tell you that A is different to B and B is different to C, the most that we can truly (and factually) derive from this is that B is different to A (mutual entailment) and that C is different to B (mutual entailment). © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_4

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In this scenario, you might notice that it isn’t possible to derive any relationship of combinatorial entailment, such that the relationship between A and C is largely unknown. This makes the assessment and facilitation of combinatorial entailment in the context of distinction to be a unique and interesting challenge (and one which we will explore further within this chapter). This issue of combinatorial entailment and distinction largely applies to AARR, as the reader may be familiar with NAARR whose responding is largely based on the physical characteristics of the stimuli rather than the contextual cues alone (see Fig.  4.1 for an illustration of NAARR distinction and Fig. 4.2 for an illustration of AARR distinction). Furthermore, the dimension on which this relationship of difference exists (e.g. are the stimuli different in size, shape, colour?) is not usually outlined. For example, if I outline to you that a ragdoll cat is different to a Maine Coon cat – you can only really derive that they are different to each other (even though they are different on a number of dimensions including size, temperament and colouring). However, the knowledge of the dimension on which these adorable cats (or any other stimuli) differ is not a

Fig. 4.1  An illustration of NAARR of distinction As you may see from the first illustration (i.e. NAARR Example 1), although the relationship between the untrained stimuli is not outlined, within NAARR an individual can physically see the relationship between these stimuli and derive that Stimulus A is indeed different to Stimulus C. However, as is also the case from the second illustration (i.e. NAARR Example 2), an individual can again see the physical relationship between the untrained stimuli and can see in this instance that Stimulus A bears a similarity to Stimulus C (i.e. they are identical, thereby deriving coordination). In the final illustration (i.e. NAARR Example 3), an individual can again see the physical relationship between the untrained stimuli; however, in this instance, they may see that Stimulus A is similar to that of Stimulus C (i.e. thereby deriving sameness due to their similar shape), but they may also notice elements of difference (i.e. thereby also deriving distinction due to the difference in colour). Such an illustration aims to provide an indication of the complexity of the frame of distinction and provide mindful consideration for training and conceptualisation of future framework

And Now for Something Completely Different: A Frame of Distinction

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Fig. 4.1 (continued)

distinguishing component of AARR (our previous points of mutual entailment, combinatorial entailment and transformation of stimulus function being the defining components of relational framing still remains). As we explored within Chap. 3, our consideration of appropriate contextual cues within assessment and training is important. When considering the relational frame of distinction, it is important to employ appropriate contextual cues, with some research somewhat equating non-equivalence (i.e. not the same) with distinction (e.g. Hayes et al., 2016). This addition of negation provides a further rich backdrop and additional complexity for our assessment and training and should be considered when formulating a catalogue of contextual cues for this frame (see Table 4.1 for additional inspiration for distinction contextual cues).

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Fig. 4.2  An illustration of AARR of distinction When employing AARR assessment and training, it is important to remember that we cannot see a physical relationship between these arbitrary stimuli (so that they remain truly arbitrary). In this example, it is not possible to combine the mutually entailed relationships presented and form any reliable conclusion regarding their relationship to one another, so the only real conclusion which can be derived in this scenario is that we do not know the relationship between Stimuli A and C. Instead, it is recommended to combine this with relational frame with others (e.g. coordination) to further explore characteristics such as combinatorial entailment and transformation of stimulus function Table 4.1  A brief list of contextual cues for the relational frame of distinction Contextual cues for distinction Different to Diverges from Distant to Is differentiated from Is dissimilar to

Contrasts Deviates from Is distinguishable from Is not the same Is unlike

Distinct from Disparate to Is discriminable from Is unalike ≠

What About the Research? As previously outlined, this relational frame has received comparably less attention than that of coordination. However, an early study within RFT focused on this relational frame (i.e. Steele & Hayes, 1991). Steele and Hayes recruited nine participants aged between 3 and 17 within Experiment 1. In the initial stages of their experiment brought the participants responding to non-arbitrary stimulus relations under contextual control of coordination, opposition and distinction. Four of these participants received the same and opposite pretraining; three received the same and different training, while the remaining two participants acted as control participants and were provided with arbitrary MTS training (without the pretraining element).

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As you may expect, within the non-arbitrary coordination phase, the selection of a comparison stimulus that matched (or was similar to) the sample stimulus was reinforced. Within the non-arbitrary distinction phase, the selection of any comparison stimulus other than the sample stimulus was reinforced, while in the non-arbitrary opposition phase, the selection of a comparison stimulus that was as physically far from the sample stimulus along any physical dimension was reinforced. Following this non-arbitrary training, participants were then provided with arbitrary MTS training in the context of these contextual cues (i.e. same, different and opposite). Four participants received coordination and opposition AARR training; three received coordination and distinction AARR training, while the remaining two control participants received coordination, opposition and distinction AARR training (without having received any pretraining). The results indicated that all participants demonstrated derivation of relational responding in accordance with the frames of coordination, distinction and opposition. However, although it may be tempting to conclude that MTS has proven itself to be a suitable framework for the facilitation of AARR, it is also important to note that the participants within this study already had an established AARR repertoire and a (presumably) extensive learning history of relational framing given their age. Such results should be regarded tentatively within the context of application and training. Dixon and Zlomke (2005) employed the precursor to the REP (a computerised training procedure) to establish AARR in accordance with coordination, distinction and opposition amongst 15 adults. Within the first phase of this study, participants were presented with two stimuli on the screen and were asked to select one of two coloured response options (which functioned as contextual cues for same, opposite or different – a tactic which has been used in applied research also). Relations of coordination, opposition and distinction were established between these stimuli, and participants were then assessed for derived symmetrical relations. The results indicated that all participants demonstrated derived responding with the trained stimuli and with novel stimuli. As outlined in Chap. 3, much research on the foundation of such relational repertoires has been based on an MTS framework; however, Dixon and Zlomke (2005) indicate the potential utility of using a computerised framework. As with Steele and Hayes (1991), this study also employed adult participants with presumably established relational framing repertoires, so the claim that such a computerised framework may be used to establish frames of distinction, opposition and coordination in populations with deficits in responding cannot be made with any great confidence on the basis of these results. Corbett et al. (2017) assessed the utility of the REP for the assessment and facilitation of non-arbitrary relational frames of coordination and distinction with nine autistic children (aged 7–11; see Chap. 3 for full outline of REP). All participants were assessed using the three levels of the REP which focused on non-arbitrary coordination and distinction. Of these participants, six failed all three levels, while three participants passed Level 1, but failed Levels 2 and 3. These children were then recruited for the training phase of the study which focused on Level 2 responding of the REP (i.e. confirmation or disconfirmation of sameness/difference of stimuli presented) in the context of a concurrent multiple baseline design. The training

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intervention was also presented on a computer screen and correct responding was reinforced with auditory feedback, visual imagery, praise and tokens (exchangeable as part of a token economy). Incorrect responses were met with auditory feedback (i.e. “Wrong”) and the programme automatically stopped to allow the experimenter to provide feedback for incorrect responding. This corrective feedback involved the repetition of the auditory question prompt (i.e. “Are these the same/different?”) accompanied by a gesture and/or vocal prompt to indicate the correct yes or no response. All three participants acquired Level 2 non-arbitrary coordination and distinction responding. To avoid repetition, within Chap. 3, Hayes et al. (2016) were also referenced as having employed REP to assess and establish non-arbitrary frames of coordination and distinction amongst typically developing children with similar results. Although this indicates the potential utility of the REP for the assessment of relational responding, the programme does not automatically include a training component and requires human intervention so may not be the most comprehensive training procedure for relational framing. As such, the REP is likely best combined with other methodologies in this context. A further study which may have greater implications for those within the applied setting is that of O’Connor et al. (2011) who assessed and taught arbitrarily applicable mutually entailed relations of distinction (and coordination) to autistic children and children without a diagnosis. In the first experiment, eight children between the ages of 6 and 9 were recruited and assessed for mutually entailed AARR of distinction and coordination. The first phase involved explicit name training, while in Phases 2 and 3 of this study, participants were presented with written nonsense syllables (e.g. VUG) and their corresponding spoken stimuli (e.g. “vug”). Cardboard circles (red and blue) were also employed as contextual cues. Within a coordination trial, participants were presented with the blue circle (to signify this was the contextual cue for coordination) and two written words (e.g. VUG and LUP) and asked to select the card that they thought was correct once they heard the spoken word (e.g. if the word “vug” was spoken, the participant was expected to select VUG). Within the distinction trial, participants were presented with the red circle as the contextual cue for distinction and two written words and were again asked to select the correct card once they heard the spoken word (e.g. if the word “vug” was spoken, the participant was expected to select LUP). Within testing trials, selection responses were not reinforced; however, during the training phase, their selection of the correct target stimulus was reinforced. Within the fourth phase, participants were provided with a new set of abstract stimuli (i.e. shapes that bore no similarity to one another) and provided with conditional discrimination MTS training, with the final phase assessing coordination and distinction responses under contextual control. Interestingly, the results indicated that across all phases of the experiment (which also included tests for generalised responding), participants produced high levels of accuracy throughout without the need for additional training. The results indicated that children of this age may already have an established mutually entailed AARR repertoire of distinction and coordination and that such a paradigm may be helpful to assess these repertoires.

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The second experiment focused extending the assessment and training procedures within Experiment 1 to ten autistic children (aged 6–9), categorised as readers/writers with emergent levels of self-editing skills with high levels of verbal ability. Within this experiment, participants were provided with the same stimulus sets from Experiment 1; however, in order to promote the acquisition of AARR, MET was employed involving the addition of a further eight stimulus sets. Two of these stimulus sets included nonsense syllables similar to those outlined in Experiment 1; two of these stimulus sets included abstract shapes similar to those in Experiment 1, while the remaining four stimulus sets included familiar stimuli (e.g. HORSE and “horse”) which were only employed if difficulties arose with the arbitrary stimuli. The basic procedure was identical to Experiment 1 (with the exception of the addition of MET) and also included corrective feedback and reinforcement in the form of tokens. The results indicated that four children required no intervention (similar to the results of the children from Experiment 1) and three required MET using the arbitrary stimuli, while the final three participants required MET using both the arbitrary stimuli and the familiar stimuli to acquire mutually entailed AARR of coordination and distinction. In their final experiment, five autistic children were provided with a variation on the previous training procedures. The experiment included nonsense syllables and abstract shapes as used in Experiments 1 and 2; however, Experiment 3 included the addition of new stimuli which included familiar and nameable pictures to the participants (i.e. pictures of cars, pencils, chickens, etc.). The same contextual cues were employed as in Experiments 1 and 2, while Phases 1 to 5 were also identical to that of the previous experiments; however, an additional four levels of training were included and followed after the original Phase 2. In the first level, participants were taught to emit either the correct or incorrect naming response during a task (designed to establish the basis of distinction responding). For example, when presented with a picture of a spoon, participants were told “What is it? Give me the wrong answer”, and participants were expected to provide an incorrect tacting response (e.g. “tractor”). Level 2 was similar to the previous level, however, focused on selection responses. For example, participants were presented with an array of five pictures and were then told “Give me something. Don’t give me a tractor” or “Give me something. Give me a tractor”. Level 3 involved the reintroduction of contextual cues. During these trials, a cue was placed on the table above the middle picture (either blue or red circle). When presented with the blue circle, the participant was asked only questions such as “Give me something. Give me a ball”. In contrast, when presented with the red circle, the participants were only asked questions such as “Give me something. Don’t give me a horse”. In the final level, stimuli were presented within an MTS format (in order to mimic Phase 4 of training) involving identity matching. Participants were presented with two identical pictures (one of which was the sample stimulus, while the other was a comparison stimulus) and two additional pictures to serve as comparison stimuli. One of the contextual cues was then placed above the sample. When presented with the blue circle, participants were expected to select the comparison stimulus that matched the sample stimulus, while when presented with the red circle, participants were expected to

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select a comparison stimulus that was not identical to the sample stimulus; however, no verbal antecedent was provided, meaning that all responses were based upon the contextual cue (i.e. blue or red circle) alone. Following the completion of Level 4 of training, participants then proceeded to Phases 3 to 5 (as outlined in Experiments 1 and 2). The addition of Levels 1–4 was successful in facilitating mutually entailed AARR coordination and distinction with autistic children. Although O’Connor et al. (2011) focused only on mutually entailed AARR of distinction and coordination, this study still provides us with a potentially useful framework for establishing these frames in more complex ways. Newsome et al. (2014) investigated the utility of an RFT-based framework combined with precision teaching to facilitate reading comprehension using the contextual cues of “same” and “different” with five children (aged 9–12) with a range of diagnoses (including autism, Down syndrome, foetal addictions and seizures) and a history of poor reading comprehension. Participants were provided with hierarchical relational training which involved participants correctly identifying the categories, features and functions of a variety of common stimuli. Following this phase of training, participants were then provided with relational training using the contextual cues of “same” and “different”. Within this phase, there were nine relational tasks (five sets which were presented in conjunction with the cues of “same”, while the remaining four sets were presented with the cues of “different”). These sets varied according to experimental history with the stimuli (i.e. stimuli had been presented in the hierarchical relational training phase), stimulus modality (i.e. presented visually or auditorily) and relational complexity of the stimuli. For example, within this phase of training, participants were asked questions such as “How is a bus the same as a taxi?” or “How is a bus different to a taxi?”. The participants were also asked questions relating to activities, such as “How is cooking like [or different from] painting?” The researchers found that this MET relational framing procedure facilitated reading comprehension for all five participants indicating that a relational framing paradigm can be employed to facilitate generalised operants outside of AARR alone (e.g. reading). Dunne et al. (2014) conducted a comprehensive study which focused on establishing repertoires of coordination, opposition, distinction and comparison amongst children with autism. Within their third study, they focused on establishing frames of distinction and coordination with two autistic children (aged 4–5) and did so by initially focusing on non-arbitrary coordination and distinction repertoires. Within Stage 1, the participants were assessed and trained in these repertoires by presenting them with three picture cards (of which two were identical and one was different; e.g. two squares and one circle) and asking the participant to select the pictures that are the same or the picture that is different across a total of 30 trials. Stage 2 involved further assessment and training of non-arbitrary coordination and distinction relations across four target stimulus dimensions including colour, length, texture and shape across 32 trials. During these trials, participants were presented with stimuli that were either identical on the target dimension or that differed on the target dimension (e.g. two red circles versus a red and yellow circle). Stage 3 involved mutually entailed coordination and distinction relations across a 12-trial block.

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Within trials of coordination, the researcher presented two identical stimuli and also verbally outlined the relationship of sameness between them and subsequently asking participants if the stimuli are the same or different. Trials of distinction were similar, however involved the presentation of non-identical stimuli, the verbal outline of the relationship of difference between the stimuli and questions regarding whether the stimuli were the same or different. Finally, Stage 4 directed assessment and training towards combinatorially entailed relations again involving physically identical stimuli; although the paper outlines that the “trials assessed arbitrary responding combinatorially entailed AC relation” (Dunne et al., 2014, pp. 43 – 44), this can only be true for distinction relations as the stimuli were themselves identical cups labelled A, B and C. Within this stage, there were 12 trials in total which consisted of 3 trial types (repeated four times): (1) A is the same as B; B is the same as C – Is A the same or different to C? (2) A is the same as B; B is different to C – Is A the same or different to C? And (3) A is different to B; B is the same as C – Is A the same or different to C? Within the four repetitions of each of the three trial types, the question involved a relation of coordination in two of these trials, while the remaining two focused on distinction. Although the study fails to progress from non-arbitrary responding to arbitrary responding in the instance of mutual entailment, it does progress to consider combinatorial entailment in the context of arbitrary distinction. Given the success of both participants with the combinatorially entailed element of distinction, the study indicates that it is worthwhile to consider probes during training in order to avoid unnecessary exposure to training  – we should always aim to streamline our programmes. As you may have surmised, there is a dearth of published research which considers the facilitation of distinction repertoires amongst populations who evidence deficits in this repertoire (particularly when juxtaposed against the frame of coordination); as such, this section is primarily theoretical and is certainly open to revision (or an opportunistic second edition). However, the following section aims to provide a basis for assessing and teaching the frame of distinction.

Teaching Distinction Relational Responding We may take for granted that distinction repertoires emerge without explicit training; however, there are many learning opportunities within the everyday environment which facilitates such a repertoire, for example, games such as spot the difference, snap (although this reinforces the matching of identical stimuli, this also negatively reinforces the non-selection of non-matching or different stimuli) and Sesame Streets “One of These Things” (in which the viewer is encouraged to identify the object that is not the same as the others). As with coordination, any programme focusing on the facilitation of distinction repertoires should also consider how best to integrate learning opportunities within games and the natural environment.

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When establishing non-arbitrary relations of distinction, it is important to consider the salience of the stimuli involved, as the more salient the difference is between the stimuli, the greater the likelihood is that this will facilitate responding in accordance with contextual cues of difference (e.g. see Soraci et al., 1991, who varied stimulus saliency in oddity matching tasks to facilitate correct responding). As accurate responding increases with these salient stimuli, the salience of these stimuli can be reduced to allow a more smooth transition to AARR. Furthermore, I would also recommend interspersing distinction trials amongst previously acquired relational repertoires (i.e. coordination) to facilitate more flexible responding. As was the case with frames of coordination, a variety of stimuli should be employed (e.g. auditory, visual, olfactory, etc.) when teaching distinction.

Non-arbitrary Distinction Beginning with non-arbitrary mutual entailment of distinction, it is advisable to commence teaching and assessment with two stimuli which are markedly dissimilar (e.g. a leaf and a teddy bear). These stimuli are different across a number of dimensions (e.g. colour, size, texture, shape, category and function) making the relation of distinction potentially more salient. However, the salience of difference should be decreased across trials as accurate responding increases. For example, in early teaching and assessment trials, begin by using stimuli that that are different across five dimensions before systematically decreasing the dimensions along which the stimuli differ. When assessing non-arbitrary distinction, present both stimuli (across a number of modalities) in addition to the contextual cue (e.g. different, dissimilar, unalike). For instance, present a leaf and a teddy bear, and while pointing/holding the relevant stimuli, outline their relationship (e.g. “This leaf is different to this teddy bear”; an A-B relationship). Mutual entailment can then be evaluated by assessing A-B (e.g. “What is a leaf different to?”; “Show me what is different to this leaf.”; “Is the leaf different to the teddy bear?”) and B-A responding (e.g. “What is different to this teddy bear?”; “Is the teddy bear the same or different to the leaf?”). When teaching, ensure that the relations are taught in both directions (see Fig. 4.3 for an example) with multiple exemplars and a variety of contextual cues. This stage of teaching should also consider the utilisation of contextual cues of negation (e.g. X is not the same as Y) and be interspersed with trials of coordination (as you may see from Fig. 4.3, it is possible for the student to outline that the physical relationship between the stimuli operates on the relational frame of coordination and distinction). The assessment of derivation of non-arbitrary mutually entailed distinction should also be conducted alongside training, such that if taught that a novel object A (e.g. cheese) is different to novel object B (e.g. fish), the student is then tested on the relationship between B and A (e.g. “Is a fish different to cheese?”; “Complete the sentence: Fish is different to ____”; “Show me something that is different to a fish”). An additional example which could be explored is one of auditory stimuli. For example, it could be possible to programme two BIGmack buttons to play two

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Fig. 4.3  Teaching non-arbitrary mutual entailment of distinction Ensure that when you are training NAARR mutually entailed distinction relations that bidirectional training is employed (e.g. A is different to B; B is different to A). Notice in the second set of examples, the stimuli are not as noticeably dissimilar to each other (e.g. a bouquet of flowers versus a pot of flowers), while the third example bears greater physical similarity to each other but are different on the dimension of colour/outline. By varying the stimulus sets in this manner and systematically decreasing the salience of distinction, training with such stimulus sets may promote greater reflexive responding. Distinction trials should also be interspersed with previous acquired coordinate trials to allow for more complex responding. For example, with the third stimulus set, a student could be told that Stimulus A is the same as Stimulus B but they are also different. This sets the foundation of a more complex relational network

different sounds (e.g. Button 1 could play bird song, while Button 2 could play death metal music  – arguably, a greater distinction between stimuli could not be made). These BIGmack buttons also come in different colours (adding an additional dimension of salience to distinction in this scenario). We could then press BIGmack Button 1 (to emit the sound as an example) and BIGmack Button 2 while outlining their relationship (i.e. “Button 1 is different to Button 2”). Mutual entailment could then be evaluated by assessing the derivation of the relationship between Button 2 and Button 1 (e.g. “Does Button 2 sound the same as/different to Button 1?”; “What is different to Button 2?”; Show me something that is unlike Button 2″). Following the acquisition of non-arbitrary mutually entailed distinction (I shall avoid recommending a specific mastery criterion in order to allow for the individualisation of a training programme), we may now progress to the combination of mutually entailed relations. This is where the frame of distinction gets a little bit complex, as the combination of these mutually entailed relationships adds a greater complexity to the task at hand. For example, if I present the following stimuli and outline that “An elephant

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Fig. 4.3 (continued)

is different to a laptop and a laptop is different to a lemonade”, apart from presenting us with a potentially messy training facility, any questions regarding the relationship between the elephant and lemonade would be derived based upon their physicality alone. For instance, we may conclude that the relationship which exists between these stimuli is one of difference – this is not based on the contextual cues provided, but on the physical relationship we know to exist between these stimuli. This relationship of difference is not the inevitable conclusion for all

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combinatorially entailed relations of distinction (particularly those which are abstract – which we will cover soon – just remember that patience is a virtue). For example, if we again focus on the non-arbitrary aspect of distinction, if presented with the following statement and its accompanying stimuli “An orange is different to a flamingo, and a flamingo is different to a satsuma”, if assessed regarding the relationship between an orange and a satsuma, an adamant citrus lover might outline that they are similar, but distinct, whereas a person without any knowledge of citrus fruits may simply say that these stimuli appear to be similar – meaning that the derivation of combinatorially entailed relations of distinction is a complex one with a number of potential responses (a stark contrast to that of coordination – a much more straightforward relational frame). Within Fig.  4.1, I have outlined a number of examples of the many different responses that may be produced. For example, in NAARR Example 1, we may present Stimuli A, B and C to a student accompanied by the statement “A is different to B and B is different to C”. From previous teaching, a student can now derive that B is different to A and C is different to B, and as such, training on these characteristics are no longer necessary. However, training in regard to the A to C and C to A relationship is now required (e.g. “Is this [A] different to [B]?”; “Show me something that is dissimilar to A?”). In this scenario, a relationship of difference is physically visible between Stimuli A and C. In NAARR Example 2, however, the relationship between Stimuli A and C are those of coordination as we can see a physical similarity between these stimuli, while in NAARR Example 3 the relationship between Stimuli A and C are both of sameness (i.e. same shape) and of difference (i.e. different colour). As such, incorporating stimuli such as these within the assessment and training of the combinatorial entailment of distinction may allow for the facilitation of responding (when incorporated with appropriate corrective feedback, response prompts and reinforcement contingencies). However, it is also useful to consider combining mutually entailed relations of distinction and coordination in order to incorporate acquired relational responding and expand relational networks for the student and move beyond potentially ambiguous combinatorially entailed relationships – an important consideration for future AARR (see Fig. 4.4 for an illustrated example, including that of an extended relational network). In an effort to further complicate the relational frame of distinction, we now consider the characteristic of transformation of stimulus function (again, this offers us an opportunity to consider teaching and assessing across various sensory modalities). Beginning with mutually entailed distinction relations (which should already be established), we could begin by presenting a student with two stimuli. For example, we may take advantage of a naturally occurring event and present a student with an orange and allow them to manipulate it (e.g. including smelling the peel of the orange) and also present them with another stimulus (e.g. a rose). If it is outlined that an orange is different to a rose, the student should derive that the rose is different to the orange. We may then teach the student that the orange smells zesty (we can do this via direct manipulations) and smells different to a rose and subsequently assess for the transformation of stimulus function for the second stimulus (i.e. the rose). It is crucial that the dimension along which these stimuli can be differentiated

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Fig. 4.4  Combining coordination and distinction for NAARR combinatorial entailment By combining mutually entailed relations of coordination and distinction within this context, this may form the basis of a more rich relational network while also providing a platform for less ambiguous AARR responding of this nature. Furthermore, by extending the network to a greater number of stimuli (such as in the third example), this allows for additional learning opportunities and the further derivation of combinatorially entailed relations

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Fig. 4.4 (continued)

is explicitly outlined (e.g. they smell different, they feel different, they look different), or responding and assessing becomes unwieldy. For example, a student might be asked “Does a rose smell different to an orange?” or “What smells different to an orange?” or “Show me something that smells different to an orange”. If this derivation and transformation of stimulus function is absent, we can then teach this via prompting and exposure (e.g. presenting the rose and orange and asking the student to smell both stimuli) and representing the discriminative stimulus. In a further lunchtime example, we might provide a student with a glass of milk and a separate glass of apple juice and outline that the glass of milk tastes different to the glass of apple juice, with transformation of stimulus function being assessed by asking the learner if the apple juice tastes different to/the same as milk. However, it should not be assumed that the answer for transformation of stimulus function is always clear-­ cut (and unfortunately, there is a dearth of research considering transformation of stimulus function in regard to distinction). For instance, if presented with a cup of tea and a mug of hot chocolate and also told that they were different – the extent to which they are different (particularly in relation to transformation of stimulus function) may vary, meaning that responses for questions of transformation of stimulus function may vary as a result. If told that hot chocolate was sweet and subsequently asked if tea was also sweet or different (although, this may actually depend on the cup of tea involved), it may be both correct and incorrect to say that it is different (a Schrödinger’s cat if you will). To further illustrate my point, if it was then outlined that hot chocolate is warm (which is again presented as a stimulus in a frame of distinction with tea) and subsequently asked if tea was also warm (or not), it becomes a more difficult question to respond to. If they were truly different stimuli, then surely the tea should not be warm; however, a learning history with tea would indicate that it is likely to be warm (with the exception of iced tea). If, however, I outline that tea tastes different to hot chocolate, a derivation of distinction of taste

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may be assessed (e.g. “Does hot chocolate taste different to tea?”) that leaves little room for uncertainty. It is therefore, imperative to be explicit in relation to the dimension(s) along which these stimuli may differ. Furthermore, when considering the programming of transformation of stimulus function, it is also important to consider the appropriateness of “I don’t know” as a response while also considering the dimensions along which stimuli may be different or, indeed, similar. Put simply? Plan your stimuli, training and assessment programmes carefully! The complexity of transformation of stimulus function continues when we consider combinatorial entailment (an already murky field in the arena of distinction). As previously outlined, many potential responses may apply when considering NAARR combinatorial entailment of distinction, and we must once again recognise the role of coordination in this context. Therefore, the selection of stimuli for this particular question becomes quite complex – as does the selection of discriminative stimuli in the assessment and training of such responses. For example, if a learner was provided with the following stimuli (e.g. a skirt, a jacket and jeans) and told that “A skirt is different to a jacket, and a jacket is different to jeans”, although these are all different in appearance, they may share a common function (i.e. they can all be worn as pieces of clothing) – thereby complicating the very issue at the core of transformation of stimulus function and distinction. If, however, we outline that the skirt is woollen (and the learner can feel the coarseness of the fabric against the skin) and feels different to the leather jacket (again, the learner can feel the smoothness of the material) and that the leather jacket feels different to the jeans (again allowing the learner to manipulate and feel the fabric of the clothing), the assessment of the relationship between the skirt and the jeans in relation to the sensation of the fabric (whether it is distinction or coordination – or a mixture of both – e.g. “Does the skirt feel the same as/different to the jeans?”) may become a little more straightforward (as much as such a sartorial scenario may be). When faced with the case of transformation of stimulus function and combinatorial entailment, we must once again consider the stimuli that we employ and further revise the stimulus relations and responses within previous combinatorial entailment distinction assessment and training trials (and when in doubt, consult with peers in relation to the stimuli and discriminative stimuli that you employ within assessments and training). Furthermore, when studying this relational framing characteristic, it is advisable to again employ the combination of mutually entailed relations of coordination with mutually entailed relations of distinction which may serve to eliminate some of the ambiguity of responding, for example, if presented with the following stimuli – Coke, Pepsi and Fanta (all of which have a very clear physical relationship of similarity and difference with one another) – in addition to the statement “Coke tastes the same as Pepsi and Pepsi tastes different to Fanta”. Upon sampling each drink, the learner may then be able to accurately respond to questions assessing transformation of function (e.g. “Does Coke taste the same as/different to Fanta?”;“Which one of these tastes different to Coke?”; “Can you tell me anything that tastes different to Fanta?”; “Which one of these is not the same as Coke?”; etc.), thereby providing us with a slightly more simplistic scenario for assessing NAARR of distinction.

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 ARR and Distinction: Conceptual A and Theoretical Considerations This may be the point where we are somewhat thankful for the reintroduction of arbitrary stimuli, as the use of non-arbitrary stimuli (and the prior learning history we have with them) within this context make difficult to produce simple “copy-and-­ paste” programmes within RFT. For ease of communication, we shall return to the example of reading and phonics when considering arbitrary stimuli. For instance, the letter “D” bears no physical similarity or relationship to its phonic counterpart “duh” and thus constitutes a prime example of arbitrary coordination. We may assess AARR of mutually entailed distinction by again incorporating existing coordination responses within this framework (as complex relational responding often involves a relational network in which relational frames are combined). For example, the relationship between the written letter “D” and the spoken sound “buh” may be outlined as different to the learner. We may then present the learner with several letters (e.g. B, b and D) and assess mutual entailment by asking the learner to “Select” the one that is different to “buh” (an example of potential oddity matching). This could be assessed and trained across a number of phonic-letter combinations (as illustrated in Fig. 4.5). Bidirectional training must again be employed (i.e. A is different to B; B is different to A) while simultaneously assessing the derivation of mutual entailment across distinction relations. Traditionally within RFT, to avoid prior learning histories with stimuli which may influence responding, arbitrary stimuli are employed (e.g. nonsense syllables, abstract shapes, etc.) to assess and train AARR. For example, if presented with the stimuli VUG and TORK and the contextual cue “different”, we may assess mutual entailment of distinction by presenting TORK as the sample stimulus and ask the learner to identify the stimulus that is different to TORK from the comparison

Fig. 4.5  Example of the assessment of mutually entailed AARR distinction relation

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stimuli (e.g. VUG, FLUV, MEQ). In this scenario, the selection of the stimulus VUG should be based on the previously outlined relationship of distinction (i.e. VUG is different to TORK). However, AARR does provide us with a conundrum – how can we be sure that responding is truly arbitrary? Even if we employ stimuli without a learning history, there is a possibility that some aspect of responding is rooted in NAARR (e.g. VUG is visually dissimilar to TORK, and it would not technically be incorrect to respond by saying that FLUV and MEQ are different to TORK – as they again are visually dissimilar). This is where we must consider an elaboration of responses – and assess why the learner has selected the stimuli they have within this context (we must also consider the role of familiarity here). This can be done by simply asking the learner why they have made this response. However, as the reader may be aware, there is limited research when considering the relational frame of distinction, so we have somewhat entered the realm of concept and theory to some degree. It seems fitting that we now delve into further uncertainty (namely, the appropriateness of “I don’t know” as a response to relationships between stimuli) when addressing combinatorial entailment of distinction. If it is outlined that a MEQ is different to a SBI and a SBI is different to an AFIM, although we may derive that a SBI is different to a MEQ and that an AFIM is different to a SBI (based on an established mutually entailed repertoire of distinction), the relationship between an AFIM and a MEQ is ambiguous (i.e. we do not know if they are different to one another or whether they are the same). This leads us to a potential issue within programming as given the above example, a learner might outline that a MEQ and an AFIM are different based upon NAARR (i.e. the stimuli themselves look or sound different). Additionally, a learner may incorrectly derive that an AFIM and a MEQ are different as previous training trials of AARR combinatorial entailment of coordination involves the application of the relevant contextual cue to all stimuli outlined within the relational network, indicating that this response may originate from an overgeneralisation of responding. This again indicates the importance of determining the rationale behind an individual’s responding – an aspect which should be incorporated into training and assessment programmes. When teaching the combinatorially entailed response to these stimuli, it is important to present “I don’t know” as an option  – however, in order to avoid receiving an “I don’t know” for every combinatorial entailment trial, it is important to intersperse previously acquired combinatorial entailment trials of coordination while also combining mutually entailed relations of distinction and coordination (as we explored within NAARR). For example, we might outline that a “XIK is the same as a PLUQ while a PLUQ is different to a WIJ”. In this context, we may derive the relationship between XIK and WIJ (i.e. combinatorial entailment) as one of distinction, thereby relieving us of the ambiguity we have experienced so far. If we again return to the example of phonics, we might outline that written letter M is the same as the spoken sound “mmm” and “mmm” is different to the spoken sound “kuh” and that the sound “kuh” is the same as the written letter K. We may assess the derivation of combinatorial entailment in the following ways. Firstly, we may present a number of written letter stimuli (e.g. K, M and k) and ask the student to identify the letter which is different to “kuh”.

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Secondly, the learner could be presented with further letter stimuli (e.g. M, m and K) and asked to select the one that is different to “kuh”. The reader may also notice that we could also present the learner with the sample stimulus K and comparison stimuli (e.g. K, k and M) and ask the student to identify the one which is different (however, again, we are faced with potential NAARR responding in relation to this particular combinatorially entailed relation). It is again important to consider evaluating the responses themselves (i.e. determine the dimensions along which responding is based). The issues of ambiguous responding again transfer (rather ironically) to the characteristic of transformation of stimulus function when applied to the frame of distinction. When assessing and teaching transformation of stimulus function, we must again begin by considering mutual entailment. Within this context we may present two arbitrary stimuli verbally and outline their relationship (e.g. “A SILA is different to a NINEA”), while presenting a characteristic of one stimuli (e.g. “SILAs smell sweet”), we may then test for derivation of difference by asking the learner “Does a NINEA smell different to a SILA?”. The conservative (but ultimately correct) answer is “I don’t know” – however, in this context, it becomes unclear if an “I don’t know” response is based upon an understanding that it is ultimately not possible to determine if they are different along the dimension of scent (unless it is later clarified and made explicit) or if the learner is more generally unsure. As such, when assessing and training for transformation of stimulus function with this frame, it becomes again important to consider the discriminative stimuli (or questions) employed and the information that is provided to the learner (i.e. the dimensions along which the stimuli differ). If we return to the above example, and I outline that “A SILA smells different to a NINEA”, it is now possible to provide an accurate response to the question “Does a NINEA smell different to a SILA?”. As you might expect, the issue of transformation of stimulus function becomes increasingly complex once the issue of combinatorial entailment is included – as this denotes a truly ambiguous relationship. For instance, in the previous example of MEQ, SBI and AFIM, if it is outlined that MEQ is poisonous and potentially lethal, the derivation of the relative safety of SBI (mutual entailment) and AFIM (combinatorial entailment) is not certain, and a response which outlines this is perhaps the safest to derive in this context. Even when attempting to adjust for this ambiguity by combining mutually entailed relations of coordination and distinction, such as in the example of XIK, PLUQ and WIJ above, ambiguity remains, such that if told that a XIK is edible (and has a relationship of coordination with PLUQ and a relationship of distinction with WIJ as outlined previously), we cannot confidently derive whether PLUQ (mutual entailment) or WIJ (combinatorial entailment) are edible. It is hoped that such examples clarify (albeit awkwardly) the issues regarding the transformation of stimulus component of distinction while providing both a tentative example of teaching and assessment and an indication of a relevant area of potential research. Of course, within the field of behavioural psychology, we must always consider the relevance and social validity of the programmes that we put in place (e.g. Baer et al., 1968, 1987), and it is left to each practitioner to determine the

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potential utility of including (or excluding) the characteristic of transformation of function when examining the frame of distinction.

Future Directions for Research Within Distinction? It should be quite plain to the reader that the area of distinction remains a relatively untapped wealth of potential research and educational applications. Although preliminary research has focused on the facilitation of mutually entailed distinction relations at an AARR and NAARR level amongst populations evidencing deficits in these areas (e.g. Corbett et al., 2017; Hayes et al., 2016; O’Connor et al., 2011), research has yet to extend beyond this characteristic of relational framing. However, the lack of research on other characteristics of distinction (i.e. combinatorial entailment and transformation of function) may lie in the theoretical technicalities and ambiguities of this frame for both NAARR and AARR. As such, further theoretical and experimental work is necessary within this domain to tease out the complexities of distinction across both arbitrary and non-arbitrary stimuli. The issue of transformation of function in the domain of distinction for both AARR and NAARR repertoires also provides us with a novel challenge in the area of both assessment and teaching, and it is one which I hope is addressed by researchers far more intelligent than I (although I do encourage you to adopt some suggestions within this chapter and assess their utility both within the applied setting and in the context of research). Furthermore, the question of the arbitrary nature of the stimuli employed within AARR of distinction must also be examined as it is difficult to generate stimuli that do not differ on at least one dimension, meaning that some element of NAARR may be at play in this respect. For instance, even if we presented stimuli that are identical and outlined that they are in a relational frame of distinction with one another, we may regard them as different simply due to their location within our visual field or the timing of their presentation to the learner. This poses an interesting challenge to those within experimental behaviour analysis. It is clear that close attention must be paid when formulating assessments, generating stimulus sets and confirming correct/appropriate target responses, and the reader should be aware that an RFT-based distinction programme should not be undertaken lightly (or without due thought as it is a truly different terrain).

The Relational Frame of Opposition Although it may not seem as though there is a natural segue from distinction to opposition (and that I am instead attempting to shoehorn these repertoires together), these relational frames have been paired together for a reason. For instance, both relational frames have received considerably less attention within peer-reviewed research and are usually studied in combination within the same research or with

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other relational frames (e.g. Dunne et al., 2014; Dixon & Zlomke, 2005; Dymond & Barnes, 1996). This may be due to each frame’s unique complexities in the areas of application and assessment. For example, when employing frames of distinction and opposition, we must consider the dimensions along which these stimuli may be differentiated (e.g. size, shape, colour, temperature, texture, etc.). This has been outlined in the case of distinction above and bears a similar role in that of opposition and the ways in which we present stimulus relations. Within opposition, although responding is based on contextual cues such as “is opposite to” (however, a limited number of contextual cues exist for opposition, potentially due to its limited utilisation in everyday life when compared to relational frames such as comparison), responding becomes difficult unless it is outlined along which dimensions the stimuli oppose one another. For example, if presented with the following statement: “Eve is opposite to Lavinia and Lavinia is opposite to Rachel”, apart from being a rather awkward and somewhat unnatural statement, if we are asked to derive the relationship between Eve and Rachel, it becomes a little uncertain as it is unclear in what ways they are opposite. If, however, the statement is adjusted to outline that “Eve is hilarious – a complete opposite to Lavinia. Lavinia’ humour is opposite to Rachel”, it becomes much more clear that there is a derivation of opposition (and coordination) across these stimuli; a point of reference is required. Relational framing in accordance with distinction and opposition, therefore, bears a great similarity to one another, however differ dependent on the specific dimensions of the stimuli outlined (Rehfeldt & Barnes-Holmes, 2009) in addition to the contextual cues involved. It is at this point that the reader may also notice that opposition and distinction have similarly complex patterns of combinatorial entailment. Specifically, in the context of opposition and the previous example, the relationship between Eve and Rachel is that of coordination – meaning a relationship of sameness is derived for combinatorial entailment. This indicates that the capacity to derive sameness is a necessary precursor for the successful derivation of opposition (as was also the case with distinction). Finally, addressing the context of combinatorial entailment, both distinction and opposition are some of the first relational frames to demonstrate an interaction amongst relational frames  – thereby forming the basis of increasingly complex relational networks.

Opposition: The Research Although a limited number of studies investigating the relational frame of opposition exist, when we compare the studies of opposition to that of distinction, these studies (arguably) explore the frame of opposition much more extensively than studies which have tackled the frame of distinction. For instance, where research on the frame of distinction largely fails to address transformation of function, a number of studies have examined this relational frame characteristic in both basic and applied research offering insightful approaches to the assessment of this relational

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framing characteristic (e.g. Dymond et al., 2007, 2008; Stewart et al., 2015; Whelan & Barnes-Holmes, 2004a). In a recent study by Stewart et al. (2015), adult participants were recruited to investigate the transformation of thought suppression functions in accordance with frames of opposition and coordination using a computer programme. Within their first experiment, 11 participants (aged 22–30) were exposed to 5 phases of assessment and training. The first phase involved establishing two arbitrary stimuli (astrological signs) as contextual cues for coordination (i.e.) and opposition (i.e. ) via non-arbitrary relational training and testing using an MTS procedure. On a computer screen, participants were presented with the arbitrary stimulus (i.e. the contextual cue for same, , or opposite, ), followed by a sample stimulus and finally three comparison stimuli. The sample stimulus and the target stimulus of the comparison stimuli bore a physical relationship with one another, such that in the case of coordination, the target stimulus from the comparison stimuli was physically similar to the sample stimulus, while in the case of opposition, the target stimulus was the physical opposite of the sample stimulus (e.g. a short line versus the long line of the sample stimulus). No feedback was provided during testing; however, during training, participants were given visual feedback on screen (i.e. “Correct” or “Wrong”). The second phase involved the assessment and training of coordination and opposition AARR. This employed the contextual cues established within the first phase to assess and train relations of coordination and opposition with a mixture of real words (e.g. Bear) and nonsense words as stimuli. Instructions and MTS within this phase were similar to the previous phase but were composed of two distinct stages. Within both stages a relational network was established which included a to-be-suppressed (target) word in addition to a non-target network (e.g. in one relational network the target word to be suppressed was Bear or Stimulus B1). Within the first stage of training, stimuli from the non-target network were primarily employed to support training of the target network; this element of training was designed such that participants would not be taught to always select B1 and C1 during trials of sameness or select B2 and C2 during trials of opposition, thereby ensuring greater stimulus control. For example, in this stage, the participant was presented with the contextual cue for opposite (i.e. ), the sample stimulus (e.g. A1) and three comparison stimuli (e.g. B2, B1 and N1 – a stimulus from the non-target network). In this way, mutually entailed relations between A1 and other stimuli on the basis of opposition (i.e. A1 was trained as opposite to B2 and C2) and coordination (i.e. A1 was trained as the same as B1 and C1) were established. Subsequently, derived combinatorial entailment relations of both opposition (i.e. C1 is opposite to B2, and B1 is opposite to C2) and coordination were assessed (i.e. B1 is the same as C1 and B2 is the same as C2). Following mastery of Stage 1, participants proceeded to Stage 2 of Phase 2. The second stage was similar to that of Stage 1; however, this focused primarily on the non-target network. The third phase was designed to familiarise participants with the suppression task and involved asking participants to suppress all thoughts of the word “Bear” (i.e. Stimulus B1) for 5  minutes. If, however, participants did think of the word

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“Bear”, they were also instructed to press the spacebar on the computer. This was followed by the fourth phase of the experiment  – cognitive load induction. This phase provided the participant with a “cognitive load” in the form of being asked to remember a nine-digit number and reproduce it (via writing) after a period of 25 s. This cognitive load was included to increase the rebound effects of attempted thought suppression. This was followed by the final experimental phase – the suppression task. During this phase, participants were again asked to suppress the thought from the previous part of the study (i.e. do not think of the word “bear”), while they were also presented with a word on the computer screen every 10 seconds. Participants were also instructed that if they were “not happy with a word being on the screen then you can remove it by pressing the spacebar” (Stewart et al., 2015, p. 382). 28 words in total were presented on screen and were a combination of previously seen words (i.e. the nonsense and real words from the two trained and tested relational networks) in addition to previously unseen words. These were presented in random order, and all words were presented a total of four times (i.e. 112 words in total). Of the 11 participants who began this experiment, a total of 10 completed all phases of the experiment. The findings suggested more frequent and faster removal of the target word (i.e. Bear) than other words (which we might expect), but the findings also indicated that there was also more frequent and faster removal of words within the target network than other words (i.e. the unseen words). The findings, rather interestingly, indicated that participants were more likely to remove the target and any words related to the target (whether in a frame of opposition or coordination) than to remove words from outside that relational network. Typically within the frame of opposition, it must be outlined along which dimension the stimuli in question are in opposition to one another (i.e. size, colour, etc.) or responding becomes ambiguous. As the experiment in question did not outline the dimensions along which these stimuli opposed one another, the results generated from the first experiment within this study may have occurred due to this potential relational ambiguity. Nevertheless, the findings from this experiment indicated a marginally smaller (although ultimately statistically non-significant) frequency of word removals for the two derived opposite words (M = 2.7; SD = 1.57) when compared to the derived same word (M  =  3.00; SD  =  1.33), indicating a potential distinction in responding between these stimuli that requires further examination. For example, the response in question focused on the removal of a stimulus (specifically, the target stimulus); however, if the stimuli presented were in true opposition, these would be stimuli that a participant would want greater exposure to (i.e. lengthen the period of time which they were on screen). If the experiment had included an additional and/or alternative response option to elongate word exposure time, this may have provided some additionally thought-provoking data  – although the participant’s inaction relative to the stimuli within a frame of sameness should have also provided such data within this experiment. Instead, a derivation of sameness appeared to have been established in relation to transformation of stimulus function. However, the complexity of thought suppression in itself adds an additional layer of interest to this particular question – as a failure to engage in thought suppression indicates that

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while stimuli may indeed be in a frame of opposition in some contexts, they may instead be placed in a frame of coordination when placed in the context of thought suppression. This experimental phenomenon is not unlike the following everyday example. Imagine going through a bad romantic breakup and finding all thoughts of your former paramour to be incredibly upsetting – this leads you to attempt to purge all thoughts of them from your mind. You then go on a date with a person who is the opposite of your former partner; however, despite them bearing no similarity to your previous love interest, you can’t help but think of them. This again brings us back to our previous point in regard to the deceptive complexity of opposition – it is not one to be underestimated! Within their second experiment, Stewart et al. (2015) predominantly focused on relations of opposition within the relational networks. This experiment bore great procedural similarity to that of Experiment 1; however, in this case the target stimulus (i.e. Bear) assumed a new position in the target relational network (i.e. that of B2 in the previous experiment). In this experiment, the target stimulus of Bear (or B2) was tested and trained in opposition to the Stimulus A1, which is in contrast to Experiment 1, in which the target stimulus of Bear (or B1) was tested and trained in coordination to the Stimulus A1. This change meant that a new set of both trained and derived relations were expected to emerge in addition to new and corresponding changes in thought suppression functions. Their findings produced a similar, but weaker, pattern to that of Experiment 1. Finally, Experiment 3 was designed to examine the possibility of demonstrating transformation of stimulus functions that is more cohesive with a frame of opposition while simultaneously assessing and demonstrating a transformation of stimulus functions in accordance with coordination with this relational network. This adaptation to the previous experimental procedures aimed to demonstrate that the stimuli did operate in a way that conforms with a frame of opposition in specific contexts rather than coordination alone. The first phase (i.e. initial function training and testing using MTS) was different to the previous experiments, such that participants were presented with one of three textual stimuli on screen (i.e. X1, Sackol; B2, Bear, which acted as a target stimulus; X2, Wilfop), followed by comparison stimuli which were three red squares which appeared in three randomly chosen corners of the screen. These comparison stimuli were presented (one at a time) with each stimulus being presented in conjunction with an auditory stimulus (i.e. one chime, two chimes or three chimes). Participants received visual confirmation of a correct response when they selected the “one chime” comparison square for the target stimulus Bear (i.e. B2 stimulus), the “two chime” comparison square for Sackol (i.e. X1) and the “three chime square” for Wilfrop (i.e. X2). Following mastery of this section of training, participants were then tested using a similar format. However, the sample array now included the Stimuli A1 (i.e. Casors), B2 (Bear), C2 (Vartle), B1 (Lorald) and C1 (Heittler) and did not include reinforcement or feedback for responding. In a further variation to the previous experiments, the second phase of the experiment employed an RCP training and testing paradigm (see Chap. 3 for further information on this training methodology) conducted across two four-stage cycles. The

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first cycle focused on the target arbitrary relational network, while the second cycle was concerned with the control arbitrary relational network. Stage 1 of Cycle 1 involved non-arbitrary training (not unlike the first phase of Experiments 1 and 2, however delivered via RCP), with the second stage consisting of non-arbitrary relational testing. Stage 3 focused on arbitrary relational training of opposition and coordination with Stage 4 then testing arbitrary relations. Stages 1 and 2 of Cycle 2 were identical to that of Cycle 1, with Stages 3 and 4 also bearing similarity to Cycle 1 but with different relational network. The third phase (i.e. follow-up function training and testing) was identical to initial function training and testing. Because Phase 2 successfully established a relation of opposition between B2 and A1 and a number of derived relationships (e.g. a relation of opposition between B2 and B1 and B2 and C and a relation of coordination between B2 and C2) and the stimulus B2 were trained to have an auditory stimulus function of “1 chime”, it was hypothesised that when provided with a choice between one, two and three chimes, the option of three chimes might function as opposite to one chime. Specifically, Stewart et al. (2015) predicted that B2 would be in a relationship of opposition with A1, B1 and C1 (i.e. three chimes) and a relationship of coordination with C2 (i.e. one chime). The remaining stages of training were identical to that of Experiments 1 and 2 and involved the phases of suppression induction, cognitive load induction and the suppression task. Their findings replicated those demonstrated in Experiment 2; however, they also indicated that the transformation of stimulus function relevant to opposition was observed when utilising a context other than thought suppression. The authors of this study themselves outline that this protocol (both assessment and training) could be considered by some to include some relational framing elements of comparison rather than strict opposition. However, although the stimuli did vary along a physical dimension such as size and quantity and the selection of a larger/smaller or more/less comparison was reinforced in the presence of an opposition contextual cue, the patterns of responding emitted by participants were more consistent with responding associated with opposition than comparison. This self-identified critique by the authors highlights a potential testing and assessment issue in relation to stimulus sets which may arise, and it is one that we would do well to take note of. One of the earliest studies (and arguably one of the most theoretically robust) to examine the facilitation of relational framing in accordance with opposition was conducted by Barnes-Holmes et  al. in 2004 in which three children (aged 4–6) served as participants. The study specifically focused on establishing AARR opposition responding with its participants and ensured that the stimuli employed were those with which the participants had no prior learning history. Arbitrary stimuli were employed in the form of paper coins which were the same size but different colours – totalling 57 blue, 57 red and 56 green coins. These were then used to construct 17 sets of coins, with 10 coins in each set (in each set there were three blue coins, three red coins, three green coins and one additional coin which was blue, green or red), with only 1 set of coins being used at a time. The coins in each set were labelled as A, B, C, etc.; however, these labels were not visible to the participants and were only known to the experimenters. The study also assessed for

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generalisation of responding (i.e. the capacity to derive opposition and sameness for novel stimuli without explicit training). Coloured beads were used as reinforcers, in addition to children’s stickers and sweets. Within baseline (which obviously included no feedback), participants were tested for opposite relations amongst four coins (i.e. A, B, C and D) which were positioned horizontally from left to right from A to D. The children were then presented with a scenario, in which they were told that they would play a “birthday game”. As outlined previously, it is important to specify along which dimension stimuli are in opposition with one another to avoid ambiguity in responding and this was taken into consideration with the instructions included which specified a relationship of opposition based on value. Participants were told the following: I want you to imagine that it is your birthday today and you have to go to the shop to get sweets for your birthday party. If I tell you that this coin (e.g., experimenter pointed to coin A) buys many (or few) sweets, and this coin (experimenter still pointing to coin A) is opposite to this coin (experimenter pointed to coin B), and this coin (experimenter still pointing to coin B) is opposite to this coin (experimenter pointed to coin C), and this coin (experimenter still pointing to coin C) is opposite to this coin (experimenter pointed to coin D), which would you take to buy as many sweets as possible? (Barnes-Holmes et  al., 2004, p. 564)

These instructions were edited on future trials to only include the information regarding the stimuli in question and their relationship with one another (i.e. the first sentence was omitted). This baseline included four trial types across eight trials in total, presented in random order (see Barnes et  al., 2004 for further information regarding trial types employed). For each trial, there were two stimuli whose selection was considered as constituting correct responses, and experimenters outlined that failure to select both stimuli for each trial type represented incorrect responding. In order to pass a block of test trials, a participant was required to produce seven out of eight correct responses within a session. As outlined within this chapter, the arbitrary nature of the stimuli must be carefully considered – how arbitrary are these stimuli? This was something which was considered carefully by the researchers and even included mindful planning regarding the physical layout of the stimuli within the study. Although Barnes-Holmes et al. (2004) initially presented the stimuli in horizontal order within the baseline phase, once the children completed that phase of testing, they were again presented with the coins; however, these were now placed in random positions. This presentation of stimuli (i.e. beginning with a horizontal position presentation before progressing to a random position presentation) occurred throughout the study. By doing this, the experimenters sought to eliminate stimulus control by physical location alone, but were also considering the potential role of faulty NAARR (e.g. potentially responding to the stimuli as being physically opposite to one another). As outlined in the case of distinction, the careful planning, assessment and presentation of stimuli are critical for the accurate training and evaluation of responding – something which is exemplified in the study by Barnes-Holmes et al. (2004). The training procedure for this relational repertoire was similar to that of the baseline procedure; however, it involved the addition of positive reinforcement (i.e.

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both praise and a bead which operated as part of a token economy and could be exchanged for stickers or sweets) to increase correct responding and a response cost element. The punishment component included feedback (i.e. “No, that is not correct”), which functioned as positive punishment, and the removal of a bead (i.e. negative punishment) which aimed to decrease incorrect responding. Children were considered to have mastered this phase of training if they demonstrated derivation of responding using a novel stimulus set and were considered ready for the next phase of training (i.e. relations amongst five coins). In the case of Participant 1, however, they produced only 3 correct responses across 16 trials and indicated that they wished to stop training. This is where the study indicates the importance of flexible and individualised programming, as the experimenters simplified the training trials within the next session by using only two coins from Set 1 (i.e. focusing on the foundation of mutually entailed relations of opposition). Within this phase of training, the participant was provided with two blocks of training. The first block of training focused on the relationship of opposition between A and B across eight trials. The coins A and B were presented to the participant, and the relationship between these stimuli was outlined (e.g. “Coin B boys many sweets and is opposite to coin A. Which would you choose to buy as many sweets as possible?”). Mastery of this block of training was required before progression to the second block of training which was concerned with Stimuli B and C (see Barnes-Holmes et al., 2004 for training trials for mutual entailment of opposition). Once the participant passed this phase of training, their generalisation of mutually entailed responding was then assessed using novel stimuli. The participant was then provided with combinatorially entailed AARR opposition training with three coins. This involved presenting the participant with three coins (i.e. A, B and C) and outlining the relationship between them (e.g. “Coin C buys few sweets and is opposite to Coin B. Coin B is the opposite to Coin A. Which would you choose to buy as many sweets as possible?”). The selection of one coin (or two) depended upon the relationship specified between the stimuli as in certain contexts the selection of one coin alone was correct, while in others the selection of two coins was necessary to constitute a full and correct response. In order to further facilitate this repertoire, the relational frame of coordination was also employed to establish combinatorially entailed relations of opposition. Following the successful completion of this phase of training (and the demonstration of mastery), this pattern of testing and training were repeated with the next two phases of training which included testing and training opposite relations amongst five coins and amongst six coins. When discussing distinction, we outlined the importance of utilising negation (e.g. contextual cues such as “not the same”), and this is a recommendation which also applies to that of opposition. This additional complexity was also included within the training paradigm by Barnes-Holmes et al. (2004). Once participants had successfully met mastery criterion on the previously outlined stages, they were then assessed on their capacity to respond in accordance with “would” and “would not”. During this testing phase, the children were instructed as follows:

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4  Relational Frames of Opposition and Distinction This time, I will sometimes ask which coin would you take to buy as many sweets as possible, and other times I will ask which coin would you not take to buy as many sweets as possible? (Barnes-Holmes et al., 2004, p. 566)

By including the “would” and “would not” element of assessment, the experimenters provided a novel (yet wonderfully simple) method of evaluating transformation of stimulus function across mutually entailed and combinatorially entailed relations of opposition. This phase of testing employed six coins and consisted of eight trials which were randomly presented. If a child failed this six-coin “would” or “would not” assessment, they reverted to the previous phase of training; however the elements of “would” and “would not” were included within training. Contingency reversals were then introduced such that children were expected to respond away (or in opposition) to the coin selection(s) which were reinforced previously. For example, when provided with the relation “A buys many sweets. A is opposite to B, B is opposite to C, and C is opposite to D”, the selection of the coins B and D was reinforced (as opposed to the previously reinforced A and C). This functioned as Reversal 1, with a second reversal put into place following the participants’ mastery of Reversal 1. The second reversal involved a reinstatement of the reinforcement contingencies previously employed. Testing concluded by assessing the derivation of opposite relations amongst eight, nine and ten coins. Although a complex and rather exhaustive study, Barnes-Holmes et al. (2004) provide an incredibly useful and comprehensive paradigm with which to both train and assess relations of opposition while considering all aspects of a relational frame (i.e. mutual entailment, combinatorial entailment and transformation of function). Ultimately, all three participants demonstrated a derivation of opposition across all stages (including contingency reversals) and across multiple stimulus sets. This study also provides an excellent example of the potential problem-solving nature of RFT and the adaptability of an RFT framework to teach and assess. Importantly, this demonstrates that a systematic approach to relational framing is necessary and that the acquisition of these repertoires appears to be a somewhat stepwise progression in which a deficit in responding in one area (e.g. mutual entailment) ultimately impacts responding across all other areas of this frame. Dunne et al. (2014) further extend the work of Barnes-Holmes et al. (2004) by establishing relations of opposition with four autistic children (aged 3–5) and primarily focused on the facilitation of non-arbitrary and arbitrary mutual entailment. Children who had been provided with training with the frame of coordination served as participants. Participants were first tested for yes/no responding using ten familiar pictures. Within this phase, the experimenter held up the picture and asked “Is it a [correct/incorrect name of item]?”. Block 1 required all yes responding (as the correct item was presented), and Block 2 required all no responding (the incorrect item was presented), while Block 3 was a random mix (five yes and five no trials). Stage 2 required the participants to identify non-arbitrary dimensions of the stimuli and employed the ten familiar pictures from Stage 1 and a corresponding picture (i.e. 20 pictures in total). These ten familiar picture pairs differed along one of ten physical dimensions (i.e. big/small; long/short; wet/dry; hot/cold; happy/sad; c­ lean/

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dirty; empty/full; dark/light; rough/smooth; heavy/light). Each trial began by presenting the picture pairs side by side and asking the participant to select the stimulus that matched the specified non-arbitrary dimension (e.g. “Show me the big one”), and the initial ten-trial test block targeted only the big/small dimension. For participants who failed to identify the big/small pictures, they received explicit training on this dimension. Participants were tested and trained on each of the specified dimension until they met mastery criterion for all ten dimensions (remember that when evaluating the frame of opposition, the dimension along which the relationship of opposition is based is an important consideration, so this element of training aimed to intervene on this relational precursor). The third stage included testing and training opposite relations with big/small, with Stage 4 including the assessment and teaching of non-arbitrary relations of opposition across all ten dimensions. During Stage 4, which was comprised of 120 mixed trials (i.e. 12 trials per dimension), participants were tested on yes/no responding (e.g. “Is this one big?”), their abstraction of non-arbitrary dimensions (e.g. “Show me the big one.”) before testing the opposite relations (e.g. “Show me the opposite of big.”). The final stage of testing was identical to the previous one; however this focused on arbitrary relations such that the stimuli employed were physically identical to one another. Ultimately, all participants completed all five stages of training demonstrating acquisition of AARR mutually entailed opposition. Although this study only considers one characteristic of the relational frame of opposition (i.e. mutual entailment) at both an arbitrary and non-arbitrary level, it provides further exemplars of an RFT-based framework to facilitate this repertoire and also shows its potential efficacy for teaching with neurodivergent populations.

Teaching Opposition: A Non-arbitrary Approach When teaching and assessing opposition, it has been previously outlined that the dimension of opposition should be defined to prevent ambiguous responding. Therefore, when beginning with NAARR mutual entailment, it is important to employ suitable stimulus sets which capture this aspect of opposition. I would recommend ensuring that the non-arbitrary sample stimuli employed may be held in a frame of opposition with several other stimuli (but not necessarily simultaneously) to promote flexible (rather than rote) responding. To further illustrate and hopefully clarify my point, in Fig. 4.6 the sample stimulus is a black square that may be considered to have a relationship of opposition with all of the comparison stimuli below it. For example, it is in a relationship of opposition of colour with Stimulus A (black is opposite to white) and in a relationship of opposition of width with Stimulus B and a relationship of opposition of height with stimulus C. By assessing and teaching an individual’s capacity to select the appropriate comparison stimulus when the relevant dimension of opposition (e.g. height, width or colour) is outlined, we may be more confident in concluding that a correct selection is indeed based on the relationship of opposition rather “learning off” that the sample stimulus is always in a

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Fig. 4.6  Example of Training Across Dimensions of Opposition In the above example, Stimulus A may be considered to be non-arbitrarily opposite to the sample stimulus on the dimension of colour, while Stimulus B may be considered as non-arbitrarily opposite to the sample stimulus on the basis of width, while Stimulus C may also be considered as nonarbitrarily opposite to the sample stimulus on the basis of height. As such, responding on the basis of the contextual cue of opposite in addition to the dimension of opposition is necessary for correct responding

relationship of opposition with Stimulus A.  As with previous relational frames, when teaching mutually entailed relations, we must begin with bidirectional training with the stimulus sets selected (i.e. A is opposite to B across a specified dimension; B is opposite to A across a specified dimension). It is also important to again seize upon naturally occurring learning opportunities to facilitate this relation (e.g. “This closed door is opposite to this open door”; “The empty glass is opposite to this full glass”; “This hot tea is the opposite temperature of the ice-cold water”) and to select a variety of response options (e.g. “Is this open door opposite to this closed door?”; “Show me something that is opposite to this full glass”; “What is the opposite temperature of ice-cold water?”). As you may have gathered from the previous work within this chapter, the characteristic of combinatorial entailment is a complex one when applied to the frame of opposition. Specifically, when two mutually entailed opposition relations combine, they form a derived relation of coordination, while three mutually entailed opposition relations form a relation of opposition when they are combined and so on and so forth. This characteristic of combinatorial entailment of opposition is something which must be taken into account when selecting a stimulus set for this component of NAARR testing and training (see Fig. 4.7 for an example across three and four stimuli in the context of combinatorial entailment). This means that in certain contexts, when teaching and assessing combinatorial entailment, a derivation of sameness or opposition may be correct  – and as such, NAARR coordination or

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Fig. 4.7  Examples of NAARR opposition combinatorial entailment of three and four stimuli In the first example, Stimulus A is in a relation of opposition of width with Stimulus B, which is in a relationship of opposition with Stimulus C. Although Stimulus A and C are different colours, they share a similarity or a relationship of sameness along the dimension of width. Within the second example, Stimulus A is in a relation of opposition of colour with Stimulus B, which is in a relation of opposition of colour with Stimulus C which is in a further relation of opposition with Stimulus D. Within this example, Stimuli A and C are similar, and B and D are similar, while A is opposite to B and D

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opposition training may be required for these stimuli. It is at this point that I would also ask the reader to again consider the potential ambiguity between stimuli. For example, what if it is outlined that Stimulus A is opposite in colour to Stimulus B, and Stimulus B is opposite in height to Stimulus C – in this context, it is difficult to derive any accurate relationship between A and C, meaning that an accurate response in this context would be “I don’t know”. Although this consideration applies more to AARR, it is one that we should also consider within NAARR training. For instance, if it is outlined that an elephant is opposite in size to a mouse and a mouse is opposite in their noise production to a sperm whale, we shouldn’t be able to derive a relationship based on that information alone between an elephant and a sperm whale as within this context, these mutually entailed relations (i.e. elephant and mouse opposite size; mouse and sperm whale opposite noise production) cannot be combined along these dimensions. However, due to a learning history between these stimuli, we may actually derive a relationship of sameness between these stimuli as they coincidentally are quite large. In a further example, if it is outlined that a violin is opposite in size to a double bass, and a double bass is opposite in texture to sandpaper, within this context, we cannot derive any relationship between a violin and a sandpaper given the information provided, and in this context, we certainly cannot derive a relationship of sameness. As such, this is an aspect that may need to be incorporated into early training – namely, the response of “I can’t tell based on the information provided”. However, this is complicated in NAARR as the physical relationship between stimuli can be seen and is something that requires further conceptual and theoretical consideration. Transformation of stimulus function may again require bidirectional training across both mutually entailed and combinatorially entailed relations of opposition (and technically, coordination). However, as suggested by Stewart et  al. (2015), thought suppression may not be the most suitable psychological function to employ for this particular relational frame. We are again best-placed to consider everyday learning opportunities when teaching this aspect of relational framing. For instance, we might teach a learner that a green light is opposite to a red light and green means “go”; we would then assess for derivation of transformation of stimulus function across this mutually entailed relationship by measuring whether the learner stops when presented with the red light. In the event that they have not derived this relationship of opposition, we would then teach a learner to stop when presented with the red light. While doing laundry, we might outline that the dirty clothes smell opposite to clean clothes and that dirty clothes smell stale and aversive to be around (personally, I wouldn’t stick my nose into dirty laundry). If we derived a relationship of opposition between dirty and clean clothes, the transformation of function that may occur is that we may derive that clean laundry has a pleasant smell and may be an appetitive stimulus (in contrast to dirty laundry, this is something I would be quite happy to smell). Transformation of stimulus function and combinatorial entailment combined offer the same elements of complexity as both characteristics in isolation and, as such, should be approached with due consideration for stimulus sets and dimensions outlined. For example, we may have a learner that loves spicy food, and they love jalapeno peppers – we may outline that jalapeno peppers are

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opposite in spice level to cottage cheese, and cottage cheese is opposite in spiciness to kimchi jjigae. Given their love of jalapeno peppers (which acts as an appetitive stimulus), we could determine the derivation of sameness and transformation of stimulus function by asking the learner whether they wanted to try kimchi jjigae (of course, such an example would not work so well with a picky eater like myself, but may be worth considering as a slightly different way of approaching teaching this characteristic of opposition). As with all other characteristics of relational frames, it is recommended that if an individual evidences deficits in this realm, MET and bidirectional training (with appropriate individualised prompts) are employed.

 ARR and Opposition: Teaching and Directions A for Future Research Given the example provided by Barnes-Holmes et al. (2004), it is recommended that when considering a training or assessment programme of this relational frame, a similar approach to the experimenters may be adopted. At this point in your relational frame journey, you will notice that it will become a little bit more difficult to find arbitrary stimuli to employ within a programme. This is because any learners who have reached this stage already (should) have an established AARR coordination repertoire with corresponding relational networks. For example, such a learner may have already established that the textual stimulus of “cheese” is related to the physical object of cheese (and are aware of the physical attributes of cheese) and also be aware that the textual stimulus of “chalk” is related to the real-world item of chalk, meaning that if the relationship of opposition is outlined between cheese and chalk, the learner may establish the relationship of opposition on the basis of non-­ arbitrary cues rather than arbitrary stimuli alone. It is for this reason that from this point onwards truly arbitrary stimuli (e.g. nonsense syllables, identical shapes, etc.) should be employed within testing and training (e.g. Cassidy et al., 2016; Colbert et al., 2018; Hughes & Barnes-Holmes, 2016). The potential ambiguity of combinatorial entailment that was previously discussed should also be addressed during AARR testing and training. For example, if we teach a learner that an IXLA is opposite in height to a DANAMA and a DANAMA is opposite in brightness to an IBRANA and we then ask a learner if an IBRANA is opposite in brightness to an IXLA, based on the relations outlined, it is not possible to accurately derive such a relationship. As such, the only way to accurately respond is to state that no relationship can be derived (e.g. “I can’t tell.”; “I don’t know”; “It’s impossible to say”). This may be a worthwhile addition to AARR combinatorially entailed opposition programmes to facilitate more accurate and flexible responding. As yet, no existing research (that I am aware of) has executed this within opposition research and may be a lucrative avenue for research and application. This of course should be taught in combination with combinatorially entailed opposition relations which are possible to derive (i.e. the dimensions of

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opposition are outlined). Furthermore, these relations should be assessed and taught with at least four stimuli in combination (i.e. A is opposite to B, B is opposite to C, and C is opposite to D; see Fig. 4.8). When considering how best to teach and assess AARR transformation of stimulus function, it may be most appropriate to adopt a similar approach as that within the NAARR phase of training (with the exception of the utilisation of arbitrary stimuli instead of non-arbitrary stimuli) or employing a similar framework to that of Barnes-Holmes et al. (2004). For instance, a learner may be presented with the following statement “RULAA is opposite to YILKE” in addition to the information that RULAAs are scary. A transformation of stimulus function may have occurred if a learner correctly responds to questions such as “Is a YILKE scary?”, “No”, and “Is a YILKE safe to be around?”, “Yes”. Deficits in responding could be facilitated via MET, corrective feedback and individualised prompting procedures. In the case of transformation of function and combinatorially entailed relations, this should be taught across three and four stimuli (e.g. Fig.  4.8). A learner may be told that a XELSIA is quiet (following training on this four-member network) and transformation of stimulus function may be assessed by evaluating derivations of sameness and opposition between stimuli within this relational network. For example, “If a XELSIA is quiet, what else is quiet?”, “A ZAHEKI”; “Is a PEHISO quiet?”, “No”; “If a XELSIA is quiet, what is loud?”, “A PEHISO and an AISVIL”; “Is a ZAHEKI quiet?”, “Yes”; “Which one of these should you not bring to a library?”, “A PEHISO and an AISVIL”. In the case of deficits in responding with this relational frame characteristic, MET, corrective feedback, positive reinforcement and prompting procedures may be used to establish this final component of this relational repertoire. Transformation of stimulus function as it relates to both mutually entailed and combinatorially entailed opposition relations has been examined within the research

Fig. 4.8  Examples of testing and training of AARR combinatorial entailment of opposition

References

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and considers some interesting psychological functions such as consequential functions (i.e. stimuli were established as punishers or reinforcers; Whelan & Barnes-­ Holmes, 2004a), formative augmenting (i.e. establishing particular consequences as reinforcers or as punishers; Whelan & Barnes-Holmes, 2004b) and avoidance learning (Dymond et al., 2008). However, as outlined there are interesting manifestations of transformation of stimulus function when the relational frame of opposition is in effect (as evidenced by Stewart et al.’s 2015 experiment with thought suppression), meaning that further empirical work may yield more thought-provoking insights into the frame of opposition, its application and the field of RFT more broadly. TLDR Cheat Sheet Oddity This procedure bears a similarity to MTS; however, in this scenario when the matching participant is provided with a sample stimulus and comparison stimuli, their selection of the comparison stimulus that does not match the sample stimulus is reinforced. For example, if provided with a handbag as a sample stimulus and three comparison stimuli (handbag, horse and dog), the selection of the stimuli horse and dog would be reinforced, while the selection of the matching handbag would be extinguished. Precision This is a systematic individualised method of instruction which focuses on fluent teaching responding and does so by monitoring the frequency of behaviour across a defined period of time using a standard celebration chart and making decisions based on this performance regarding progression of individual goals. BIGmack This is a large single button, primarily used as a means of alternative augmentative communication, which when pressed emits a recording and can be used as a means of verbal behaviour

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 Barnes-Holmes, Y., Barnes-Holmes, D., & Smeets, P. (2004). Establishing relational responding in accordance with opposite as generalised operant behavior in young children. International Journal of Psychology and Psychological Therapy, 4(3), 559–586. Cassidy, S., Roche, B., Colbert, D., Stewart, I., & Grey, I. M. (2016). A relational frame skills training intervention to increase general intelligence and scholastic aptitude. Learning and Individual Differences, 47, 222–235. https://doi.org/10.1016/j.lindif.2016.03.001 Colbert, D., Tyndall, I., Roche, B., & Cassidy, S. (2018). Can SMART training really increase intelligence? A replication study. Journal of Behavioral Education, 27(4), 509–531. https://doi. org/10.1007/s10864-­018-­9302-­2 Corbett, O., Hayes, J., Stewart, I., & McElwee, J. (2017). Assessing and training children with autism spectrum disorder using the relational evaluation procedure (REP). Journal of Contextual Behavioral Science, 6, 202–207. https://doi.org/10.1016/j.jcbs.2017.02.007

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Dixon, M. R., & Zlomke, K. M. (2005). Using the precursor to the relational evaluation procedure (PREP) to establish the relational frames of sameness, opposition and distinction. Revista Latinoamericana de Psicología, 37(2), 305–316. Dunne, S., Foody, M., Barnes-Holmes, Y., Barnes-Holmes, D., & Murphy, C. (2014). Facilitating repertoires of coordination, opposition, distinction and comparison in young children with autism. Behavioral Development Bulletin, 19(2), 37–47. https://doi.org/10.1037/h0100576 Dymond, S., & Barnes, D. (1996). A transformation of self-discrimination response functions in accordance with the arbitrarily applicable relations of sameness and opposition. The Psychological Record, 46(2), 271–300. Dymond, S., Roche, B., Forsyth, J. P., Whelan, R., & Rhoden, J. (2007). Transformation of avoidance response functions in accordance with same and opposite relational frames. Journal of the Experimental Analysis of Behavior, 88(2), 249–262. https://doi.org/10.1901/jeab.2007.22-­07 Dymond, S., Roche, B., Forsyth, J. P., Whelan, R., & Rhoden, J. (2008). Derived avoidance learning: Transformation of avoidance response functions in accordance with same and opposite relational frames. The Psychological Record, 58, 269–286. https://doi.org/10.1007/BF03395615 Hayes, J., Stewart, I., & McElwee, J. (2016). Assessing and training young children in same and different relations using the relational evaluation procedure (REP). The Psychological Record, 66, 547–561. https://doi.org/10.1007/s40732-­016-­0191-­2 Hughes, S., & Barnes-Holmes, D. (2016). Relational frame theory: The basic account. In R. D. Zettle, S. C. Hayes, D. Barnes-Holmes, & A. Biglan (Eds.), The Wiley handbook of contextual behavioral science. Wiley Blackwell. Lowenkron, B., & Colvin, V. (1992). Joint control and generalised nonidentity matching: Saying when something is not. The Analysis of Verbal Behavior, 10, 1–10. https://doi.org/10.1007/ BF03392870 Mackay, H. A., Soraci, S. A., Carlin, M. T., Dennis, N. A., & Strawbridge, C. P. (2002). Guiding visual attention during acquisition of matching-to-sample. American Journal of Mental Retardation, 107(6), 445–454. https://doi.org/10.1352/0895-­8017(2002)1072.0.CO;2 Newsome, K. B., Berens, K. N., Ghezzi, P. M., Aninao, T., & Newsome, W. D. (2014). Training relational language to improve reading comprehension. European Journal of Behavior Analysis, 15(2), 165–197. https://doi.org/10.1080/15021149.2014.11434512 O’Connor, J., Barnes-Holmes, Y., & Barnes-Holmes, D. (2011). Establishing contextual control over symmetry and asymmetry performances in typically developing children and children with autism. The Psychological Record, 61, 287–312. https://doi.org/10.1007/BF03395761 Rehfeldt, R.  A., & Barnes-Holmes, Y. (2009). Derived relational responding: Applications for learners with autism and other developmental disabilities. New Harbinger Publications. Soraci, S. A., Deckner, C. W., Baumeister, A. A., Bryant, J. T., Mackay, H. A., Stoddard, L. T., & McIlvane, W. J. (1991). Generalised oddity performance in preschool children: A bimodal training procedure. Journal of Experimental Child Psychology, 51(2), 280–295. https://doi. org/10.1016/0022-­0965(91)90037-­S Soraci, S. A., Deckner, C. W., Haenlein, M., Baumeister, A. A., Murata-Soraci, K., & Blanton, R.  L. (1987). Oddity performance in preschool children at risk for mental retardation: Transfer and maintenance. Research in Developmental Disabilities, 8(1), 137–151. https://doi. org/10.1016/0891-­4222(87)90044-­8 Steele, D., & Hayes, S.  C. (1991). Stimulus equivalence and arbitrarily applicable relational responding. The Journal of Experimental Analysis of Behavior, 56(3), 519–555. https://doi. org/10.1901/jeab.1991.56-­519 Stewart, I., Hooper, N., Walsh, P., O’Keefe, R., Joyce, R., & McHugh, L. (2015). Transformation of thought suppression functions via same and opposite relations. The Psychological Record, 65, 375–399. https://doi.org/10.1007/s40732-­014-­0113-­0 Stromer, R., & Stromer, J. B. (1989). Children’s identity matching and oddity: Assessing control by specific and general sample-comparison relations. Journal of the Experimental Analysis of Behavior, 51(1), 47–64. https://doi.org/10.1901/jeab.1989.51-­47

References

107

Whelan, R., & Barnes-Holmes, D. (2004a). The transformation of consequential functions in accordance with the relational frames of same and opposite. Journal of the Experimental Analysis of Behavior, 82(2), 177–195. https://doi.org/10.1901/jeab.2004.82-­177 Whelan, R., & Barnes-Holmes, D. (2004b). Empirical models of formative augmenting in accordance with the relations of same, opposite, more-than and less-than. International Journal of Psychology and Psychological Therapy, 4(2), 285–302.

Chapter 5

The Relational Frame of Comparison

A wise philosopher once said “We’re gonna need a bigger boat...” – and this seems to be the case with comparative relational frames, which are potentially the most expansive of relational frames that we will consider within this current text. While distinction frames consider the relationship between stimuli across specified dimensions, it does not exactly quantify the relationship or provide information on a qualitative dimension as is the case with comparison. For example, in the case of distinction, we might outline that “X is a different shape to Y” – in this scenario, we do not know exactly how they are different (e.g. is X a circle and Y a square?), just that a distinction of shape exists – this may be a subtle distinction (an isosceles triangle versus an equilateral triangle) or a marked one (e.g. a rhombus versus a circle). In the case of comparative frames, an individuals’ responding is based on a quantitative or qualitative relationship that is specified along a particular dimension. For instance, when provided with the following relationship: “A is worth more than B”, a frame of comparison has been applied specifically considering the dimension of value. In this case, comparison is slightly more akin to opposition; however, it is more appropriate for cases where there are no “absolutes”. For instance, while a relationship of opposition might outline that black is opposite to white, a relationship of comparison might outline that pink is lighter than red. As such, the relationship of comparison provides us with a greater depth of detail and specificity regarding the stimuli within our environment. Given the fact that we can make comparisons between stimuli across a number of possible dimensions, it should come as no surprise that there are an almost inexhaustive list of contextual cues for this frame (see Table 5.1 for a list of contextual cues for comparison). For each specified dimension (e.g. height, size, weight) that is considered within the frame, it must be noted that there are a minimum of two contextual cues which are employed that consider the bidirectional and unidirectional aspect of this frame. For example, if it is outlined that an elephant is heavier than a mouse, there is a bidirectional relationship between elephant and mouse in this context as they are related to each other across the dimension of weight. However, the relationship between these stimuli is also unidirectional in that we can © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_5

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Table 5.1  A brief list of contextual cues for the relational frame of comparison Contextual cues for comparison Bigger/Smaller More than/Less than Warmer/Colder Dearer/Cheaper Harder/Softer

Heavier/Lighter Brighter/Darker Faster/Slower Higher/Lower Cleaner/Dirtier

Taller/Shorter Broader/Thinner Richer/Poorer Rougher/Smoother Newer/Older

only say that the elephant is heavier than the mouse, but we cannot apply the contextual cue of “heavier” in the other direction (i.e. it would not be correct to say that the mouse is heavier than the elephant) as this is not a symmetrical relationship. As such, we must employ two contextual cues in this context (i.e. heavier and lighter) to account for this unique relationship.

Nothing Compares to... Research You may remember that Barnes-Holmes et al. (2004a) conducted a study applying RFT to the facilitation of opposition relational repertoires with young children and did this by employing identically sized paper coins as arbitrary stimuli in addition to the relevant contextual cues (see Chap. 4 for a summation). In a further study conducted by Barnes-Holmes et al. (2004b), they further indicated that the primary distinction between each relational frame is the contextual cues involved within training. Within this study, the researchers intervened with young children (aged 4 to 6) and again employed identically sized paper coins as arbitrary stimuli but focused on the frame of comparison in this instance. The dimension of comparison examined within this study was based on a relationship of quantity and employed the contextual cues of “more than” and “less than”. Within the experiment, 45 coloured paper coins of identical size (15 blue, 15 red and 15 green coins) were each marked with a unique pattern and formed the basis of 15 stimulus sets, each containing 3 coins. These coins were designated as A, B and C (the labels of which were known only to the experimenter and were not visible to the participants). These coins were placed on a white A4 paper, and during some trials, this sheet of paper contained one or two black arrows, pointing either left or right, between the coins. Each arrow was also accompanied with a printed phrase placed above it (e.g. “BUY MORE”, “BUY LESS”). For instance, when presented with the coins A, B and C on this sheet of paper, one arrow was placed between coins A and B, with a printed phrase placed above (e.g. “BUY MORE” or “BUY LESS”), and another arrow was placed between B and C also accompanied by a printed phrase (e.g. “BUY MORE” or “BUY LESS”). In instances with three stimuli and therefore two arrows, the same phrase was employed across stimuli (i.e. either “BUY MORE” or “BUY LESS” was used within that trial). Both the arrows and phrases were systematically removed following the acquisition of AARR (specifically after the acquisition of “would”

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and “would not” responding as we will describe later). As with their previous experiment, a response-cost token economy was employed with a fixed-ratio exchange of 8 (i.e. after collecting eight beads, the children could then select a backup reinforcer), with correct responses reinforced by the addition of a bead and verbal praise and incorrect responses punished by the removal of a bead from the jar and verbal feedback indicating an incorrect response. Baseline testing first involved determining the participants capacity to respond to the stimuli based on the contextual cues of “more than” and “less than” using the three coins in the first stimulus set across a total of 24 trials which consisted of 12 trial types (see Barnes-Holmes et al., 2004b for further information regarding trial types). Baseline testing was then followed by teaching mutually entailed AB comparative relations. Within this phase, children were provided with coins A and B across a total of eight trials. Coin A was consistently placed on the left-hand side of the stimulus sheet, while Coin B was placed on the right side of the sheet. Participants were then told that they were going to play the “birthday game” in which participants were told that they were to imagine that the coins provided were to be used to buy sweets at the shop, before the experimenter outlined the mutually entailed relationship between the stimuli (e.g. “If I tell you that this coin [Coin A] buys more sweets than this coin [Coin B], which would you take to buy as many sweets as possible?). This training phase involved two “less than” and two “more than” trial types (see Barnes-Holmes et al., 2004a for further information regarding trial types), with incorrect coin selection resulting in corrective feedback and the loss of a token. Following mastery of the mutually entailed AB relations, the participants were then introduced to mutually entailed BC trial types which were identical to those of AB comparative relations. Training of combinatorially entailed relations (i.e. ABC) involved the use of all three coins and a total of four trial types presented across eight training trials. Within this phase, children were again provided with instructions for the “birthday game” (e.g. “If this coin [Coin A] buys less sweets than this coin [Coin B], and if this coin (Coin B) buys less than this coin [Coin C], which would you take to buy as many sweets as possible?”). Following the acquisition of mutually entailed and combinatorially entailed comparative relations, participants were again assessed on mutually entailed and combinatorially entailed relations (identical to baseline settings) with a new set of coins and were not provided with feedback on their responses. If participants failed to demonstrate generalised mutually entailed and combinatorially entailed comparative relations with an untrained stimulus set, they returned to training phases using a new stimulus set, while those who passed this phase proceeded to the assessment of comparative responding in accordance with “would” and “would not” (again, similar to Barnes-Holmes et al., 2004a). This phase of testing combined the relational frame of comparison with that of distinction, such that “more than” and “less than” functioned as contextual cues for comparison, while “would” and “would not” were contextual cues for distinction. Within these trials, children were told “This time, I will sometimes ask which would you take to buy as many sweets as possible, and other times I will ask which would you not take to buy as many sweets as possible?” (Barnes-Holmes et al., 2004b,

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p. 169). This assessment of would/would not trials was conducted across a total of 24 trials assessing both mutually entailed and combinatorially entailed relations (including 12 total trial types – specifically, 4 AB trials, 4 BC trials and 4 ABC trials) with half of these trials assessing “would” and half assessing “would not” relations. Following assessment, participants were then introduced to “would/would not” comparative training which involved feedback until they reached mastery criterion. As previously outlined, the visual stimuli of arrows and text which designated the direction of the relationship had been used within earlier phases of training; however, following acquisition of “would/would not” responding, these visual stimuli were then removed, and children were again assessed and trained for this repertoire. All stages of training and assessment had included the horizontal presentation of stimuli (i.e. the presentation of stimuli A, B and C from left to right); however, the final stage of assessment and training involved the vertical presentation of these stimuli (i.e. presenting Stimulus A at the top, B in the middle and C at the bottom). This phase of assessment and training was conducted to ensure that responding was not dependent on the physical location of the stimuli. In the context of an ABA reversal design, the previously outlined stages constituted the A phase of this design. In order to demonstrate experimental control, Barnes-Holmes et al. (2004b) then introduced a contingency reversal (which constituted phase B). Within this phase, participants were now required to respond away from the coin that they would have been reinforced for selecting in the previous A phase of training. For example, when provided with the statement “B is worth more than A”, the selection of the coin A was now reinforced, while selection of the coin B was reinforced in the previous A phase. In ways, this contingency reversal somewhat parallels opposition responding, such that the participant had to respond in the opposite direction of their previous selections. Phase B further involved a reintroduction to all previous phases of training contained within Phase A, however included this contingency reversal. Following the completion of Phase B, participants were exposed to the final phase of the ABA reversal design which involved a second contingency reversal. This contingency reversal involved reinstating the original reinforcement contingency, such that when told that “B is worth more than A”, the selection of the coin B was reinforced as it was in the previous A phase. The reintroduction of this A phase again involved exposing participants to all previous phases of testing and training. Although some participants demonstrated difficulty with generalisation tests and therefore required additional re-exposure to training, ultimately, all participants demonstrated the acquisition of AARR comparative relations. The complexity of the ABA reversal design further indicates the experimental control of the study, but its implementation (particularly that of Phase B) served to assess and teach flexible responding in accordance with comparison. Barnes-­ Holmes et  al. (2004b) undoubtedly present a robust and useful framework for assessing and teaching AARR comparison; however, as previously outlined, there are a multitude of potential dimensions to comparison with “more than/less than” comprising a small section of this expansive repertoire. As such, it is difficult to determine whether the participants within this study acquired a total comparative repertoire or just a subsection of this. Furthermore, the study approached the

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assessment and training of combinatorial entailment, but only did this using three stimuli, extending this to a greater relational network of potentially four or five stimuli within a comparative frame. Finally, the study also presented the comparative relationship within a linear fashion (e.g. “A is more than B, B is more than C”), rather than a non-linear fashion (e.g. “B is more than C, A is more than B”) or a mixed manner (e.g. “A is smaller than B, B is bigger than C”). By considering the way in which the relationship between stimuli is presented, a more complex and potentially more flexible comparative repertoire may be established. Berens and Hayes (2007) also offer an interesting framework for the assessment and facilitation of AARR comparative responding with four children (aged 4 to 5) in the context of a combined multiple baseline design (across behaviours and across participants) and a multiple probe design. As with Barnes-Holmes et al. (2004b), Berens and Hayes also considered the “more than/less than” dimension of comparison and employed a reinforcement (e.g. token economy) and MET paradigm; however, they also considered the inclusion of mixed non-linear trials within their teaching and assessment. The arbitrary stimuli included three sets of three paper pictures which depicted different coloured pictures (e.g. heart, sun, smiley face) and had different coloured borders (e.g. red, blue, orange), all of which were used within training and assessment; as with Barnes-Holmes et al. (2004b), these stimuli were designated as A, B or C; however these labels were not visible to the participants. As with Barnes-Holmes et al. (2004b), the correct selection of a stimulus was reinforced with praise and a token; however, Berens and Hayes (2007) did not include a response-cost element to the consequential procedure and instead relied on differential reinforcement of correct responding (i.e. withholding a token for incorrect responses), and feedback did not include an error correction or prompting procedure (i.e. children were told “No, that is not it” for incorrect responses but were prompted in selecting the correct response). Participants could exchange tokens for backup reinforcers; however, with each trial block, a goal was established such that if a participant emitted one correct response more than the previous trial block (they were told what number they had to meet at the beginning of each trial block), they gained access to an additional larger prize that they could choose themselves. The experimenters also embedded non-contingent reinforcement within the training paradigm to accommodate the young (and early) learners within the training environment. Both training and assessment sessions began with the experimenter outlining that they were going to play a game in which the child was expected to select the picture that would buy them the most candy. Each trial consisted of 8–40 trials which consisted of 4–20 different trial types. For each of these trial blocks, the experimenter had a data sheet that functioned as a script for the session, and this was constructed by randomly selecting the order of the presentation of the trial types. This included an outline of the arrangement of the stimuli, the relation between them, the order in which the relation was to be specified and the correct selection response. The inclusion of this pre-made data sheet not only simplified the data collection and training procedure, but it also served to provide randomisation of trials, thereby minimising the possibility that participants may simply learn the responses to the order of questions, rather than the questions themselves.

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As in Barnes-Holmes et al. (2004b), Berens and Hayes (2007) began by assessing and training mutually entailed relations within Phases 1 and 2 and presenting stimuli and the relationship between them in a linear manner, with Phase 1 solely focusing on the training of “more than” mutually entailed relations, while Phase 2 trained “more than” and “less than” mutually entailed relations. Interestingly, the researchers also employed a component analysis to determine the impact of training on specific relational components and did this by exposing participants to probes of all 20 trial types following the mastery of each phase (mastery of each phase involved 100% accuracy for two consecutive trial blocks), meaning that Phases 1, 2, 3, 4 and 5 were all followed by probe trials. Phases 3 and 4 were also linear trials; however, they focused on the assessment and facilitation of arbitrary “more than” and “less than” relations. In contrast to Barnes-Holmes et al. (2004b), Berens and Hayes (2007) included mixed non-linear trials within their fifth phase of training, which included a mixture of both “more than” and “less than relations” (e.g. “C is less than B and A is more than B”), the addition of which generated a further layer of complexity and relational flexibility to the arbitrary training. Interestingly, within Berens and Hayes (2007), not all four participants were initially successful in their arbitrary comparison training, with only two of the four participants proceeding through all phases of training with relative ease (i.e. Sally and Laura), while the remaining two participants evidenced difficulties in this domain (i.e. Valerie and Emma). As we have previously discussed in earlier chapters of this work, non-arbitrary repertoires must be established prior to the training of AARR, and it was hypothesised by the researchers that a potential deficit in NAARR comparison repertoires may be the basis for the participants’ difficulty in acquiring AARR comparison. It should also be noted at this point that of all the non-arbitrary repertoires, there is recent evidence to suggest that this is the only non-arbitrary relation that is significantly correlated with IQ and other relational framing abilities, thereby indicating that this non-arbitrary repertoire may form the basis of arbitrary relational framing more generally and may also be a crucial component in intellectual and linguistic development (see Kirsten & Stewart, 2021). As such, focusing on non-arbitrary comparison more generally may be a fruitful exercise for practitioners and researchers alike. Berens and Hayes (2007) then developed a non-arbitrary comparison training procedure, which employed the same consequential procedures as those outlined for arbitrary comparison training; however, the training procedures were slightly different for both participants. Valerie was the first to be introduced to non-arbitrary comparison training which included the same training stimuli employed within the arbitrary comparison training; however, the experimenters included pennies within Phase 1.1 which  served as the non-arbitrary (or visual) element of training. For instance, the pennies were placed on the pictures to indicate the relationship of quantity between the stimuli such that there was a visible and obvious comparison in terms of the amount of pennies placed on each stimulus, therefore indicating a non-arbitrary comparative relationship between the stimuli (e.g. picture A had eight pennies, while picture B had two pennies and the relationship of comparison is more visible). Phase 1.2 was a slight modification of the previous stage and was

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designed to facilitate responding from non-arbitrary to arbitrary stimuli. This involved presenting the participant with a large and small pile of pennies and asking them “Which is more?”; following this, the stimuli from Stimulus Set 1 were then placed under the pennies, and participants were then presented with a series of questions including (1) again asking participants “which one is more?”, (2) “which one would you use to buy candy?” and (3) “If this [the large pile of pennies] is more than this [smaller pile of pennies], which one would you use to buy candy?”. The position of the piles of pennies and pictures was then switched, and the participant was again asked the final question previously outlined. Following mastery of this phase, participants were then reintroduced to the first phase of arbitrary comparison training and once this phase of training was mastered, they were introduced to the next phase of non-arbitrary comparison training. Phases 2.1 and 2.2 were similar to that of Phase 1.1 and 1.2; however, they were focused on the “less than” relationship between stimuli in addition to the “more than” relationship. Once Valerie reached 100% correct, the contextual cues were systematically faded, and the participant was introduced to Phase 2.3. Within this phase, the participant was again presented with different-sized piles of pennies and was asked a total of seven questions: (1) [while pointing to one of the piles of pennies] “Is this more or less?”, (2) [while pointing to the other pile of pennies] “Is this more or less?”, (3) “Which one has more?”, (4) “Which one has less?”, (5) “Which one would you use to buy candy?”, (6) “If this [points to a pile of pennies] is more than this [points to the other pile], which would you use to buy candy?” and (7) “If this [points to a pile of pennies] is less than this [points to the other pile], which would you use to buy candy?” If the participant was unsuccessful in these questions, these were repeated until mastery was achieved, and they then proceeded to Phase 2 of arbitrary comparison training. Phase 2 of arbitrary comparison training was followed by Phase 3.1 of non-arbitrary comparison training and was identical to that of Phase 2.3; however, it included three piles of pennies and only focused on the training and assessment of “more than” relations. Upon completion of Phase 3.1 of non-arbitrary comparison training, Valerie then entered Phase 3 of arbitrary comparison training followed again by a return to non-arbitrary comparison training. Phase 4.1 was identical to that of Phase 3.1; however, it included the addition of “less than” relations, while Phase 4.1 made a minor modification in relation to instructions (i.e. “If this one has more pennies than this one which would you use to buy more candy?”). The participant then successfully proceeded to Phases 4 and 5 of arbitrary comparison training with no further need for non-arbitrary comparison training and ultimately acquired AARR in accordance with comparison. The second participant (Emma) who required non-arbitrary comparison training began her training by examining mutually entailed “more than” relations (i.e. Phase 1.1 for Emma, which was different to Phase 1.1 for Valerie), and this was done by presenting the participant with different-sized piles of pennies in a procedure similar to that of Phase 2.3 with the participant Valerie. Presumably, this variation in non-arbitrary comparison training arose from deriving the training procedures which successfully facilitated non-arbitrary responding with Valerie. Ultimately, however, this Phase of training did not prove successful with Emma, and she was

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entered into a subsequent training phase. Phase 1.2 was identical to that of Phase 1.1 of Valerie’s early training; however, this phase sought to emphasise the word more within the questions posed. For example, “If this one [points to the larger pile of pennies] is more [said both louder and longer] than this one [points to the smaller pile of pennies] which one would you use to buy more candy?” Following this phase of instruction, Emma then proceeded onto Phase 1.3 which was similar to that of Phase 1.2; however, the experimenter only pointed to the stimulus that was “more”. Emma then returned to overall arbitrary comparison training with no further need for non-arbitrary comparison training and successfully progressed through Phases 1–5 of arbitrary comparison training previously outlined. The difference in training procedures (and amount of training) needed for both participants to acquire arbitrary comparative responding raises some important points. Firstly, the study emphasises the importance of individualised instruction and also highlights the difficulty of generating a one-size-fits-all RFT programme (despite our very best efforts to do so, we must always remember each individual’s unique learning history may predispose them to certain procedures). Secondly, Berens and Hayes also demonstrate the importance of frequent probes and assessments during training phases – if these probes had not been conducted, in the case of Emma, she would have been exposed to unnecessary training and an otherwise avoidable use of resources. Finally, the study also points to the importance of assessing and training non-­ arbitrary repertoires prior to the assessment or training of arbitrary repertoires. Dunne et al. (2014) is the only published study to date which considers the facilitation of arbitrary comparison amongst developmentally disabled populations. Within the fourth study of their published work, two autistic children (aged 4–5) served as participants who received both non-arbitrary training (i.e. using items where the relationship of comparison was visible to the participant) and arbitrary training (i.e. using non-identical coin-shaped objects) and again focused on the comparative dimension of “more than”/“less than”. Stage 1 consisted of 12 trials testing and training non-arbitrary “more than” and “less than” relations, with half of the trials focusing on “more than” and half focusing on “less than” relations. The participants were presented with two stimuli, each of which contained items (e.g. one container may have two chocolate sweets, while the other container might have nine chocolate sweets), thereby presenting participants with a non-arbitrary mutually entailed relationship between these two stimuli. Participants were then asked “Which has more?” and “Which has less?”. Following successful completion of non-arbitrary mutually entailed comparison training, participants then proceeded with non-arbitrary combinatorially entailed “more than” and “less than” testing and training. This was conducted across 24 trials and was similar to that of the previous non-arbitrarily mutually entailed trials and now involved three containers with a different number of stimuli (e.g. three sweets in one container, ten sweets in one container and five sweets in the final container). Across all trials, the participants were asked about the combinatorically entailed A-C relation (i.e. “Is A more than or less than C?”) across the relationships presented to the participants, which either outlined that A is less than B and B is less than C or A is more than B and B is more than C. If participants failed on this step of training, they were provided with a new

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set of stimuli and explicit training which is unfortunately not outlined in the paper itself, and it is left to the reader to determine exactly what training consisted of. The subsequent phase of testing and training involved mutually entailed arbitrary “more than” and “less than” relations across 24 trials consisting of a total of four trial types; (1) A is more than B, (2) B is less than A, (3) B is more than A, and (4) A is less than B. Within this third stage of training, the participants were presented with two identical coins (thereby ensuring the arbitrary nature of training), and after being told the relationship between the stimuli, the participants were then asked, “Which has less” or “Which has more”. As with the previous stage, if participants evidenced difficulty with acquisition of the target relations, they were then provided with (undefined) explicit training using a novel set. The final stage of testing and training involved arbitrary combinatorial entailment of “more than” and “less than” relations. The final stage of testing and training involved arbitrary combinatorially entailed “more than” and “less than” relations across a total of 24 trials and two trial types; (1) A is less than B and B is less than C, and (2) A is more than B and B is more than C. Interestingly, however, the researchers did not test and train in both directions with the stimuli involved (i.e. they did not test and train (a) C is more than B and B is more than A or (b) C is less than B and B is less than A), which may have impacted flexible responding. Again, participants were presented with arbitrary stimuli (i.e. three identical coins), were informed of the relationship of comparison between the stimuli and were then questioned on the combinatorially entailed AC relation with the question “Is A more than or less than C?”. It is possible that by only presenting one question on this AC relationship rather than also assessing the CA relationship (e.g. “Is C more than or less than A”), this may have limited the participants’ flexibility of derivation of comparative relationships. Both participants successfully acquired both non-arbitrary and arbitrary mutually entailed and combinatorially entailed “more than” and “less than” relations. Although the study provides a useful framework for the assessment of “more than” and “less than” frames within the applied setting, there is limited information regarding the process of training in this instance and unfortunately provides a limited guide in terms of teaching these frames. Furthermore, although this study presents an additional example of assessment within the realm of comparison, it again only considers this from the dimension of “more than” and “less than”, which is a very narrow and limited portion of the frame of comparison overall. A number of experimental studies have focused on assessing and training comparative relations with a focus on transformation of stimulus function (e.g. Dougher et al., 2007; O’Hora et al., 2002; Vitale et al., 2008; Whelan et al., 2006); however, all of these studies have focused on adult populations with presumably established comparative relations and all (with the exception of Dougher et  al., 2007 who addressed “largest” versus “smallest” as the dimension of comparison) focusing on “more than” and “less than” dimensions of comparison. Dougher et  al. (2007) examined transformation of stimulus function of “smaller than” and “larger than” relations within a three-member network with eight undergraduate university students (aged 19–27) serving as experimental participants and seven students serving as control subjects. Before beginning relational training, the skin conductance of the

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participants was measured to determine their suitability for the experiment (i.e. were they skin conductance responders?), and they then entered the shock-selection procedure in which they selected a shock level that was “uncomfortable but not painful” for use within a later stage of the experiment. Participants then entered relational training, which was comprised of an arbitrary MTS procedure, and were told that a symbol (i.e. A, B or C) would be presented on the computer screen along with three symbols (which were identical in form but differed in size) which were displayed below the first symbol. The samples A, B and C each represented specific contextual cues (i.e. A = pick the smallest; B = pick the medium selection; C = pick the largest) which when presented would specify the appropriate selection of three comparison stimuli (whose form differed across trials). Participants were provided with written feedback on their responses (i.e. “Correct” or “Wrong”), which remained on the computer screen for 2 seconds. Participants were required to meet a mastery criterion of 96% accuracy of responding before beginning the next experimental phase. In the next phase of testing and training, the participants were asked to press the spacebar of the computer keyboard when they were presented with the B stimulus (i.e. the contextual cue for medium), and once a (self-determined) steady rate of responding was established for that stimulus, they were then presented with the Stimuli A and C and were also asked to determine an appropriate rate of spacebar pressing. The results indicated that the responses per second were lowest for the A stimuli, medium for the B stimuli and highest for the C stimuli across all participants, thereby indicating the first transformation of stimulus function within the experiment. This pattern of responding generally did not appear in the control participants with the exception of two of the seven control participants. The final phase of testing and training was labelled as the respondent conditioning phase, and this involved the pairing of the B stimulus (a previously neutral stimulus which becomes a conditioned stimulus) with the unconditioned stimulus of electric shock and the measurement of the participants’ skin conductance change (i.e. the unconditioned response to electric shock and the eventual conditioned response to the B stimulus). During this phase of the study, no operant responses were required from the participants, and participants were exposed to a total of six conditioning trials with the B stimulus (this decision was based on previous research by Dougher et al., 1994). Ninety seconds after the presentation of the B stimulus, the participants were then presented with the A stimulus on the screen which was also accompanied by an electric shock which was half the voltage of that of the B stimulus. The A stimulus was presented with an electric shock so that participants did not establish a frame of distinction between the B stimulus and the Stimuli A and C (i.e. only one of these is accompanied by an electric shock). During this time, skin conductance of the participants was measured throughout. Ninety seconds after the presentation of the A stimulus, the participants were then presented with the C stimulus; however this was not presented with a shock, and the C stimulus was only presented once within the study to prevent extinction of respondent conditioning. The results indicated that skin conductance rates were lowest for the A stimulus and medium for the B stimulus but were greatest for the C stimulus across six of the eight experimental

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participants – while the same pattern was only observed in one of the seven control participants. The results indicated that the psychological function of the C stimulus had been transformed without exposure to the electric shock, but instead occurred due to the relationship of comparison which had been derived. As you may have derived from this section (I know, I judge myself for the use of this pun), RFT has adequately considered the “more than”/“less than” dimension of comparison; however, relatively little of other dimensions of this frame have been considered within peer-reviewed research (e.g. brighter/darker, warmer/colder, bigger/smaller). The focus on “more than”/“less than” is of course relevant to the applied setting as it is an extremely frequent comparison to make and future research within this area should certainly not be discouraged. Furthermore, it is arguably easier to assess and train “more than”/“less than” when considering more complex aspects of relational framing such as transformation of stimulus function than that of other dimensions of comparison such as “brighter”/“darker”. Given the broad scope of this particular relational frame, it is not unjustified to consider that this specific aspect of relational framing has a wealth of research and applied potential that has yet to be discovered and fully realised.

Comparison and NAARR The foundation of AARR comparison is built firmly on NAARR comparison (Berens & Hayes, 2007), and of all of the non-arbitrary repertoires to focus on in teaching and assessment, it can be argued that this may be one of the most important to include (see Kirsten & Stewart, 2021). Given the many possible dimensions of comparison, it is important to consider the dimensions to include within assessment and training. For instance, it is no coincidence that the majority of RFT research which has considered comparison has primarily focused on the “more than”/“less than” dimension of this frame, and as such, this should undoubtedly be considered for inclusion within any comparison assessment or training programme (additional dimensions should be considered by the individual assessor or trainer for their suitability for inclusion). For example, relevant dimensions to consider may include size, weight, height, breadth, temperature, speed, etc. with consideration of their cultural or individual relevance to the student. Beginning with mutual entailment, it is advisable to include several dimensions within an MET and assessment paradigm. For example, we may consider the dimensions of “more than”/“less than”, “bigger”/“smaller” and “brighter”/“darker” for inclusion within a mutually entailed non-arbitrary comparison programme (see Fig. 5.1 for examples of assessment and Fig. 5.2 for example of training). Within teaching, bidirectional training should be employed with the selected stimulus sets (i.e. “A is more than B” – “B is less than A”; “A is bigger than B” – “B is smaller than A”; etc.). It is also recommended that when training and assessing comparative relations, a variety of responses are considered rather than merely selection of the stimulus. For example, in addition to asking the student to select the stimulus which

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Fig. 5.1  Examples of mutually entailed non-arbitrary comparison assessment Please note that in order to accurately assess these dimensions of comparison, it is important to have an equal number of trials assessing A-B and B-A comparisons. Further, this is not a definitive example of all potential dimensions of non-arbitrary comparison to assess

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Fig. 5.2  Examples of mutually entailed non-arbitrary comparison training The above examples are very simple constructions for use within an MTS; however, RFT training and assessment should not be confined to MTS alone

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is bigger than or smaller than A or B, further questions could include “Is this bigger or smaller than A/B” which would constitute a yes or no response or “Tell me what is bigger or smaller than A/B” which would involve a verbal response. It is also important that we again seize upon learning opportunities in the environment when considering the facilitation of this frame. For example, when putting away items from a shopping bag, we might outline the relationship that “This litre of milk is heavier than this apple. The apple is lighter than this litre of milk” and subsequently ask the student to identify the heavier or the lighter item. An additional example of comparison is that of the dimension of temperature, while eating dinner we may outline that “The glass of water is colder than the baked potato. The baked potato is hotter than the glass of water” and then ask the student is the baked potato colder than the glass of water. With comparison, there are many opportunities for learning and assessment throughout the typical day, so it is best to consider how best to capture those opportunities. Stimulus sets for establishing combinatorially entailed non-arbitrary comparison relations should again consider the multiple dimensions of comparison and should expand on the training from the previous mutual entailment phase (see Fig. 5.3 for an MTS training example). As with mutual entailment, the possibility to provide multiple response forms is important in this phase of training – as is bidirectional training and natural environment training. When teaching or assessing non-arbitrary comparison, we do not have to rely on visual stimuli alone – we could also consider stimuli which may be presented auditorily, olfactorily, gustatorily or tactilely. For example, if teaching the comparison of “louder”/“quieter”, we could use a speaker system to play music at different volumes while outlining the relationship between stimuli (e.g. “Song A is louder than Song B, Song B is louder than Song C” – “Song C is quieter than Song B, Song B is quieter than Song A”) and then presenting the student with questions to assess and train combinatorial entailment, such as (1) “Is Song A louder/quieter than Song C?”, (2) “Is Song C louder/quieter than Song A?”, (3) “What is louder/quieter than Song A?” or (4) “What is louder/quieter than Song C?”. Of course, it is important that Songs A, B and C are counterbalanced, so one is not always the loudest, medium or quietest. We might also consider teaching the comparison of “softer” versus “rougher” by presenting a student with three samples of fabric (e.g. pashmina fabric, jean and tweed) and allowing them to manipulate the samples. The student could then be told the relationship of comparison between the stimuli (i.e. “Pashmina is softer than jeans, jeans are softer than tweed” or “Tweed is rougher than jeans, jeans are rougher than pashmina”). Again, students could be assessed for combinatorial entailment via their selection responses, confirmation/ disconfirmation and/or verbal responses. As with previous frames such as opposition and distinction, it is also recommended to combine comparison relations with previously established relational frames to generate relational networks which mimic the complexity of relational networks within the natural environment. For instance, assessments and training could include presenting a relationship of coordination and comparison to a student such that A and B are in a relationship of coordination, while B and C are in a relationship of comparison. Tests of combinatorial entailment could then be conducted to determine the relationship between A

Comparison and NAARR

Fig. 5.3  Examples of training non-arbitrary combinatorial entailment of comparison

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and C (e.g. “A satsuma is the same as an orange. Oranges taste sweeter than kiwis.” – “Does a satsuma taste sweeter than a kiwi?”). Transformation of stimulus function should once again be taught and assessed across both non-arbitrary mutual entailment and combinatorial entailment of comparison using MET and bidirectional training. The dimension of “more than” and “less than” has been employed within RFT work as it is quite logically linked to appetitive and aversive responses and can be captured readily within the daily environment. For example, if presented with two plates – one of which contains two biscuits and another which contains a single biscuit  – and we ask an individual which plate they want (presuming that they have not been previously satiated and find biscuits appetitive), they may be more inclined to select the plate with two biscuits. However, we could also train and assess transformation of non-arbitrary comparison across other dimensions. For example, after a brisk walk outside in Winter, we could return indoors and give the learner an option of two drinks – cold water and hot tea – while outlining that “Tea is warmer than this water” and ask the learner “Which one of these would make you feel warmer?”. Their selection of tea would constitute a transformation of stimulus response, while a selection of the option of water when asked “Which one of these drinks would make you feel colder?” would also comprise a correct response for transformation of stimulus function of mutually entailed non-arbitrary comparison. The assessment and training of transformation of stimulus functions for combinatorially entailed comparison relations would be similar to that of mutual entailment but would employ a greater number of stimuli. For example, we might present a learner with three different desk lamps (each with a different wattage of bulb) and outline that Lamp A is brighter than Lamp B (and demonstrate) and that Lamp B is brighter than Lamp C. We could then assess for transformation of stimulus function by asking the student which lamp would be best suited to allow you to read clearly. Their selection of Lamp A in this context would serve as an exemplar of transformation of stimulus function. We could also present a learner with three different fabric samples (as before) and outline that “pashmina is softer than jeans, jeans are softer than tweed” and then ask which fabric would be the best to use as a pillow. An answer of pashmina would demonstrate transformation of stimulus function (in  addition to expensive tastes). As was the case with combinatorial entailment, when considering transformation of stimulus function, comparison should again be combined with other relational frames to form a larger relational network. As previously stated, this section of RFT training and assessment should be considered carefully (and should certainly not be overlooked or rushed through) when we consider the implications that this repertoire has for arbitrary comparison, other relational framing repertoires and intellectual potential more generally (Berens & Hayes, 2007; Kirsten & Stewart, 2021).

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It’s All Arbitrary: Comparison, Assessment and Training Barnes-Holmes et al. (2004b) and Berens and Hayes (2007) present incredibly useful frameworks for the assessment and training of the dimension of “more than” and “less than” for arbitrary comparison, and I would strongly suggest employing these examples for training and assessment of this dimension. Of course, as with NAARR, AARR comparison is also comprised of several dimensions (other than more than and less than), and this should also be included as part of a comprehensive programme. Beginning with mutual entailment, it is important to ensure that the dimension of comparison which is being explored has already been established on a non-arbitrary basis before pursuing an arbitrary programme. For example, in an effort to consider the “warmer” and “colder” dimension of comparison, we may review the weather forecast in the area for the last several days, but without a non-­ arbitrary basis in this repertoire, acquisition of this dimension of comparison may be more difficult, so simply stating that “Thursday the 3rd of May was warmer than Friday the 4th of May” may be too abstract of a concept to communicate to the student (and may instead need to be textually or visually presented in addition to temperature readings to facilitate responding). However, assessing a truly arbitrary “warmer”/“colder” mutually entailed relation might involve telling a student that “32°Fahrenheit is colder than 3° Celsius” and assessing mutual entailment by asking “Is 3°Celsius warmer or colder than 32°Fahrenheit?” or “Which is warmer – 32°Fahrenheit or 3°Celsius?” Bidirectional training and MET should be employed to facilitate this repertoire (see Fig.  5.4 for examples). In the example posed in Fig. 5.4, a student would be taught that Stimulus A is colder than Stimulus B in the first example and subsequently taught that Stimulus B is warmer than Stimulus A. This would then be repeated across exemplars. We could also introduce the arbitrary comparison of cleaner/dirtier when discussing Ireland’s Tidy Towns competitions (which, I can assure the reader is an actual thing that occurs in this country). A learner could be presented with the following statement “Westport is tidier/cleaner than Ballina” (based on 2021 Tidy Towns reports) and assessed for mutual entailment by asking the student to name a town that is tidier than Ballina (no offence to my hometown) or asking them if Ballina is tidier than Westport. Combinatorial entailment programmes should seek to extend on the dimensions explored within arbitrary comparison mutual entailment and again involve bidirectional training, feedback and MET. Examples of “more than” and “less than” arbitrary comparison training and assessment are already available and should undoubtedly be included in training and assessment programmes due to their comprehensive nature and peer-reviewed status (I’m not so arrogant as to think that I can improve on the work of Barnes-Holmes et  al. or Berens and Hayes). Taking the dimension of “taller”/“shorter”, we could present the three-member comparative network in Fig. 5.5 to a learner. Without having met the individuals involved in this scenario, a learner responding should be based on the arbitrary relations alone. Combinatorial entailment could be assessed via selection (e.g. “Choose who is shorter than Briana” – in this context, the selection of both Katie and Wilma would

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Fig. 5.4  Example of training arbitrary comparison (warmer/colder) mutually entailed relations The above trials have been (somewhat) balanced such that there are instances where the Fahrenheit example is warmer than the Celsius example to prevent “warmer” or “colder” responses being consistently associated with Fahrenheit alone. The above example also includes instances where the same number (i.e. 102) is presented so that responding is not based on the numerical presentation alone (i.e. consistently responding to the higher or lower number)

Fig. 5.5  Example of training arbitrary comparison (taller/shorter) combinatorially entailed relations

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be correct), a confirmation or disconfirmation response (e.g. “Is Briana taller than Wilma?”) or a verbal response (e.g. “Name somebody taller than Wilma” – again, in this context, the response of Katie and Briana would constitute a correct response). Combinatorial entailment of course does not have to be limited to relational networks of three stimuli alone and can (and should) be extended to four or more members within a relational network across both training and assessment. When considering the dimension of “richer”/“poorer” (a particularly fun endeavour when considering the current economic climate), we could potentially assess and train this dimension of arbitrary comparison by employing the Forbes Billionaires list. For instance, a learner could be presented with the following statement: “Elon Musk is richer than Jeffrey Bezos, Jeffrey Bezos is richer than Bill Gates and Bill Gates is richer than Mark Zuckerberg”, and apart from lamenting the lack of general inclusivity within this “richest list”, we could assess combinatorial entailment again using selection responses, confirmation/disconfirmation responses or verbal responses. For example, a learner could be asked “Mark Zuckerberg is richer than Elon Musk – is this True or False?” or “Who is richer than Bill Gates?” A wealth of examples of teaching transformation of stimulus function of arbitrary comparison can be included within everyday examples. For example, “more than” and “less than” is possibly the most relevant to include within training. Beginning with mutual entailment, we could present a learner with a 50 cent coin and a 1 euro coin (although the 50 cent coin is larger in size than a one euro coin, this does not reflect their arbitrary relationship with one another) and outline their relationship with one another (i.e. A one euro coin is worth more than a 50 cent coin). Transformation of stimulus function could then be assessed by asking the learner which coin could be used to buy more sweets in a shop. Combinatorial entailment could then be introduced by adding a 1 pound coin into the relational network (this is the same size as a one euro coin) and outlining that “A one pound coin is worth more than a one euro coin, and a one euro coin is worth more than a 50 cent coin”; transformation of stimulus function could then be assessed by asking the learner which coin would buy them the most sweets. The inclusion of transformation of function in this context could be a useful addition to an educational programme which considers finances (again indicating the everyday utility of an RFT programme). The dimension of “warmer” and “colder” could also be employed when assessing transformation of function of mutually entailed and combinatorially entailed relations. For example, we could outline that “Egypt is warmer than France” and ask the student which destination would be better for a sun holiday and which destination may be better if you did not like a sun holiday (hopefully the reader will see that this is similar to the “would”/“would not” phase of training and assessment outlined within Barnes-Holmes et al., 2004b). This could be extended to capture combinatorially entailed relations (e.g. “Egypt is warmer than France, France is warmer than Ireland”) and posing similar questions to the learner. The dimension of older/newer could also be included within transformation of function assessment and training and combined with other relational frames. For instance, if we had a learner that was interested in technology, we could outline that “Laptop A is older than Laptop B, Laptop B is older than Laptop C. Laptop C is similar to Laptop D

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which is a top-of-the line gaming laptop” and ask questions to assess transformation of function such as “Which laptop (excluding Laptop D) would you like the most for gaming?” or “Would you prefer to use Laptop A or Laptop B?”. These are limited examples, but it is hoped that these scenarios provide some inspiration for a broad and individualised RFT programme.

 he Future of Arbitrary Comparison: Where Do T We Go from Here? Although the area of comparison has received some attention within RFT research, there is still scope for development and exploration of this frame. For example, existing SMART research has focused on a packaged programme including coordination, opposition and comparison (“more than” and “less than”) training which has been successful in increasing intellectual potential and academic ability (e.g. Cassidy et al., 2011; Hayes & Stewart, 2016; McLoughlin et al., 2021), and an interesting direction for future research may include an analysis to determine the contribution of comparison training alone to intellectual potential and academic attainment compared to the overall training package. Additionally, future SMART training could integrate additional dimensions of comparison into training to determine if a broader conceptualisation of comparison in this scenario may positively impact and potentially enhance training outcomes. Research which has focused on transformation of stimulus function has primarily focused on adult populations who have a (presumably) already-established arbitrary comparison repertoire (e.g. Dougher et al., 2007; O’Hora et al., 2002; Vitale et al., 2008; Whelan et al., 2006); as such a potentially fruitful avenue for research may include examining the development of this relational framing characteristic amongst younger populations (while again considering a number of dimensions of comparison). Given the variety of potential psychological functions which may be examined within transformation of function, it would also be beneficial to consider further aspects of this when exploring arbitrary comparison if employing adult participants. Dougher et  al. (2007) examined transformation of stimulus function of arbitrary comparison using skin conductance measures, and future research could extend upon this avenue of research by assessing additional physiological responses such as pupil dilation, heart rate and blood pressure. Although one study has examined the utility of an RFT programme to facilitate arbitrary comparison repertoires amongst autistic individuals (i.e. Dunne et  al., 2014), this study provided limited information regarding the training protocol employed and had a limited sample size (two participants in total). As such, additional research is necessary to determine the feasibility of an RFT programme with

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a more diverse population while also considering real-world outcomes and transfer of training to functional living skills. For instance, research could examine whether training on “more than” and “less than” arbitrary comparison transfers to money management and exchange responses within novel retail settings (e.g. if a student is taught that €50 is more than €20, and €20 is more than €10, when provided with a bill of €25.67, will the student correctly select €50 as the appropriate amount to give the retail assistant when provided with the previous three monetary amounts). Given the breadth of arbitrary comparison, there remains a great breadth of research and an untapped wealth of potential educational applications that has yet to be explored (and may in fact be achieved by a reader of this work). TLDR Cheat Sheet Fixed-ratio This is a schedule of reinforcement wherein reinforcement is delivered after the completion of a previously specified number of responses ABA This is a single subject experimental design which aims to demonstrate a reversal functional relationship between the behaviour of interest and the intervention. design Typically, within an ABA reversal design, participants are exposed to condition A (this is usually a baseline) and then proceed to condition B once stable responding has been observed in condition A. condition B generally involves the introduction of the intervention until the behaviour of interest reaches a stable level or is observed to clearly diverge from that of the baseline level. Following this, condition B is withdrawn, and participants are reintroduced to condition A. an additional variation of this design is the ABAB reversal design – Which is typically considered more ethical as it ends with the participant being exposed to the intervention Multiple This is a single subject experimental design in which two or more behaviours, baseline participants or behaviours across specific settings are assessed to determine their design baseline (or initial) stable level of responding. After stable responding is observed in one setting, behaviour or participant, the intervention is then introduced to that participant, behaviour or setting while the remaining participant(s), behaviour(s) or setting(s) remain in baseline condition. Once the condition that is exposed to the intervention demonstrates a change (e.g. increase or decrease to behaviour), the next behaviour/participant/setting which evidences a stable baseline responding is then introduced to the intervention. This is then repeated across the included participants/behaviours/settings. By successively introducing an intervention across these contexts, this simultaneously controls for confounding variables and also serves to demonstrate replication of the experimental effect Multiple This is a single subject experimental design which is a combination of multiple probe baseline and probe procedures. Within this design, there are intermittent measures design or probes of the target behaviour during baseline. This may be conducted across multiple behaviours, multiple participants or across multiple settings Component This is a systematic assessment of two or more components of a training package analysis in order to identify and isolate the components of the training package which are responsible for behaviour change (see Ward-Horner and Sturmey (2010) for further information)

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References Barnes-Holmes, Y., Barnes-Holmes, D., & Smeets, P.  M. (2004a). Establishing relational responding in accordance with opposite as generalized operant behavior in young children. International Journal of Psychology and Psychological Therapy, 4, 559–586. Barnes-Holmes, Y., Barnes-Holmes, D., Smeets, P.  M., Strand, P., & Friman, P. (2004b). Establishing relational responding in accordance with more-than and less-than as generalized operant behavior in young children. International Journal of Psychology and Psychological Therapy, 4, 161–189. Berens, N. M., & Hayes, S. C. (2007). Arbitrarily applicable comparative relations: Experimental evidence for a relational operant. Journal of Applied Behavior Analysis, 40(1), 45–71. https:// doi.org/10.1901/jaba.2007.7-­06 Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61, 173–198. Dougher, M. J., Auguston, E., Markham, M. R., Greenway, D. E., & Wulfert, E. (1994). The transfer of respondent eliciting and extinction functions through stimulus equivalence classes. The Experimental Analysis of Behavior, 62(3), 331–351. Dougher, M. J., Hamilton, D. A., Fink, B. C., & Harrington, J. (2007). Transformation of the discriminative and eliciting functions of generalized relational stimuli. Journal of the Experimental Analysis of Behavior, 88(2), 179–197. https://doi.org/10.1901/jeab.2007.88-­179 Dunne, S., Foody, M., Barnes-Holmes, Y., Barnes-Holmes, D., & Murphy, C. (2014). Facilitating repertoires of coordination, opposition, distinction and comparison in young children with autism. Behavioral Development Bulletin, 19(2), 37–47. https://doi.org/10.1037/h0100576 Hayes, J., & Stewart, I. (2016). Comparing the effects of derived relational training and computer coding on intellectual potential in school-age children. British Journal of Educational Psychology, 86(3), 397–411. https://doi.org/10.1111/bjep.12114 Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record. https://doi.org/10.1007/s40732-­021-­00457-­y McLoughlin, S., Tyndall, I., Pereira, A., & Mulhern, T. (2021). Non-verbal IQ gains from relational operant training explain variance in educational attainment: An active-controlled feasibility study. Journal of Cognitive Enhancement, 5, 35–50. O’Hora, D., Roche, B., Barnes-Holmes, D., & Smeets, P.  M. (2002). Response latencies to multiple derived stimulus relations: Testing two predictions of relational frame theory. The Psychological Record, 52, 51–75. Vitale, A., Barnes-Holmes, Y., Barnes-Holmes, D., & Campbell, C. (2008). Facilitating responding in accordance with the relational frame of comparison: Systematic empirical analyses. The Psychological Record, 58, 465–390. Ward-Horner, J., & Sturmey, P. (2010). Component analyses using single-subject experimental designs: A review. Journal of Applied Behavior Analysis, 43(4), 685–704. https://doi. org/10.1901/jaba.2010.43-­685 Whelan, R., Barnes-Holmes, D., & Dymond, S. (2006). Transformation of consequential functions in accordance with the relational frames of more-than and less-than. Journal of the Experimental Analysis of Behavior, 86(3), 317–335. https://doi.org/10.1901/jeab.2006.113-­04

Chapter 6

The Relational Frame of Temporality

To date, temporality has commonly been combined with other relational frames and has rarely been targeted as a relational frame in isolation within applied research with children and populations for whom this relational repertoire may be deficient. Nevertheless, temporality is cited as a core relational frame in much published work within the field of RFT (e.g. Cullinan & Vitale, 2009; Hayes et al., 2001; Hendriks et al., 2016a). Given the frequency with which temporality is cited within the introduction of published RFT work (and indeed, the importance of the concept of time itself), it is surprising that there remains a dearth of literature which focuses on temporality alone. This may be because the frame of temporality itself is often intermingled and subsumed within that of deixis (or perspective-taking) which includes spatial, temporal and interpersonal relational repertoires (e.g. Hendriks et al., 2016b; McHugh & Stewart, 2012) and is also a component of rule-following and rule-­ governed behaviour (e.g. Stapleton, 2020). As such, gaining an understanding of the development and assessment of temporality alone is difficult meaning that portions of the current chapter will be theoretical and therefore rather tentative and philosophical in nature. The role of temporal relational responding in complex behavioural repertoires has received renewed attention in the last few years. For instance, O’Hora et  al. (2014) also examined the role of temporal relational responding in instruction-­ following and found that instruction-following involved the derivation of coordination, distinction and temporal relations. This study provides an outline of the relational repertoires necessary for such a behaviour and again indicates the potential utility of RFT within the applied setting. More. recent research from Tyrberg et  al. (2021) has examined the role of temporal framing in executive function. Their findings indicate that temporal framing, in combination with deictic framing, is employed at a greater rate than other relational frames when engaged in tasks requiring a greater level of executive functioning. While temporal relational framing has applications within academic scenarios (e.g. the Great Irish Famine happened after the Irish Rebellion, telling the time, etc.) and everyday life (e.g. executive functioning skills, planning and coordinating events © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_6

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and being able to arrive at events at a specified time), there is also some evidence to suggest that temporal responding forms a basis of mental health, including positive and negative future thinking (Kosnes et al., 2013), meaning that this relational frame may have great implications for the field of mental health (e.g. Hendriks et  al., 2016a, b). Cullinan and Vitale (2009) also provide a suggestion that the capacity to distinguish temporal framing from spatial relational framing may form the basis of the corrections of speech errors in young children. For instance, early language may involve poor distinction between temporal events (i.e. before and after) and spatial events (e.g. in front of or behind), thereby resulting in speech errors such as “Can I go outside behind nap time?” rather than the correct “Can I go outside after nap time?” – a pattern of speech errors traditionally explored by cognitive psychologists such as Dr. Steven Pinker (e.g. Pinker, 1991, 2003, 2009, 2015). RFT researchers would argue that such errors decrease due to increased exposure to contextual cues, thereby becoming more refined and distinct over time (which indicates a level of distinction responding is necessary before embarking on temporal responding overall). Temporal relational framing involves an individual responding to stimuli or events in relation to their temporal displacement from other stimuli or events, therefore sharing some similarity to the relational frame of comparison, such that temporal relations specify the relative locations between stimuli on the dimension of time. For example, if the following finishing positions in a race are outlined “Keziah finishes before Daniella, and Daniella finishes before Chris” and an individual is posed with the following question “Does Chris finish before or after Keziah”, their response of “after” constitutes combinatorially entailed temporal responding. Temporality in and of itself is quite abstract – for instance, how do we present the future within training and assessment? (Unfortunately, I do not have the resources for either a Tardis or a DeLorean as part of my toolkit.) Although we have focused on unidirectionality as it pertains to comparison in our previous chapter, the issue of unidirectionality is also pertinent to that of temporality (obviously, if A comes before B, B cannot then come before A) and is somewhat more unique as this greatly impacts the presentation of stimuli as when considering time itself, we can only present stimuli within a unidirectional sequence of change (e.g. Hayes et al., 2001; Kirsten & Stewart, 2021). Indeed, Hayes et al. (2001) hypothesise that this sequence of change may be related to other relations (specifically that of comparison), indicating the once-again crucial role of comparative responding to overall relational framing. Although it is tempting to consider temporality as an extension of comparison (and that is certainly an argument for greater minds than my own), O’Hora and Maglieri (2006) argue that temporality is distinct from that of comparison, particularly when the element of transformation of stimulus function is introduced. For instance, the transformation of function in accordance with comparison typically involves a change in the properties of a response along a specified dimension (e.g. demonstrating greater desire to earn £100 than £5), while transformations in accordance with temporality involve the occurrence or not of the overall response (e.g. dessert is consumed after dinner, not before).

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What’s in a Contextual Cue? One of the defining characteristics of temporal framing is that, like comparative framing, it is not unidirectional, meaning that a minimum of two contextual cues are required when examining this frame, which is in direct contrast with relational frames of coordination, distinction and opposition. For instance, the statement “Thursday is before Friday” cannot be reversed as “Friday is before Thursday”; instead an alternative contextual cue must be employed (i.e. “Friday is after Thursday”). The distinction between these contextual cues has been explored in research, specifically examining the difference in response latencies for the cues “before” and “after”. Hyland et al. (2012) examined the relative effects of the contextual cues of “before” and “after” on temporal order judgements of 20 university students. The first experiment involved a total of five phases examining sequential responding. Participants were randomly assigned to one of two groups – either the before-after (BA) or the after-before (AB) group which dictated the sequence of training and assessment phases. For participants within the group, the first phase was labelled as “Before Training” in which participants were asked to attend to a sequence of two shapes at the top of the computer screen. One shape (e.g. a circle, square, triangle or cross) appeared at the centre of the screen for 1 s; the screen was then clear for 1 s (i.e. a white screen was now visible), followed by the second shape which appeared for 1 s, followed by a blank white screen for 1 s, and finally a grey message box which contained the words “Click Here” in the centre of the screen. Upon clicking the message box, the screen cleared, and a black line appeared above the bottom quarter of the screen. Under the black line, two stimulus arrays consisting of four shapes each (i.e. circle, square, triangle and cross) were displayed on the bottom right- and bottom-left quarter of the screen, with the contextual cue “BEFORE” positioned between both arrays. Participants were required to select the first stimulus they had observed within the trial from the array at the bottom left-­ hand side of the screen and then select the second stimulus they had observed within the trial from the array at the bottom right-hand side of the screen. Participants were provided with visual feedback (i.e. “Correct” in green writing and “Wrong” in red writing following correct and incorrect responses, respectively). This phase involved 12 trials in total with participants requiring a mastery criterion of 11 out of 12 before moving onto the next phase (failure to meet this mastery criterion resulted in re-­ exposure to this first phase of training). Phase 2 was labelled as the “Before Probes” phase and was identical to the previous phase with the exception that this phase did not provide participants with feedback. Phase 3 involved the introduction of the contextual cue of “after” and classified as the “After Training” phase. This phase was similar to Phase 1; however, in this context, the contextual cue of “before” which was placed between the stimulus arrays was now replaced with the contextual cue of “after”. Participants were now required to select the last stimulus they had observed in the trial from the array on the bottom-left side of the screen and then select the first stimulus they had seen from the trial from the array on the bottom-­right side of the screen (essentially in opposition to their actions in the

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previous two phases – which does make one wonder the extent to which relational frames of opposition may be in operation in this context). As this was a training phase, participants were provided with feedback on screen. The fourth phase was labelled the “After Probes” phase and was similar to the previous phase (i.e. “After Training” phase), but excluded feedback for participant performance. The fifth and final phase for both the BA and AB group was the “Mixed Probes” phase which was comprised of 24 trials with a mixture of before and after probes. As previously outlined, the AB group experienced a different order of experimental phases such that participants in this group were first exposed to “After Training”, followed by “After Probes”, “Before Training”, and “Before Probes”, before ending with the final phase of “Mixed Probes”. In addition to data regarding accurate performance, the participants’ response speeds for each trial were recorded across all phases. Experiment 2 replicated the procedure of the first study; however, it employed abstract stimuli rather than familiar stimuli and also had a slightly larger sample size (n  =  24). The results for both experiments indicated that across both groups, the participants’ response speeds were significantly faster for trials involving the contextual cue of “before” than “after”. Such a result may occur due to the relative exposure that humans have with the contextual cue of “before” versus “after” – we simply may have a greater number of learning opportunities in which we are exposed to the contextual cue of “before” because our natural environment only permits a unidirectional sequence of change (unless time travel has been made possible since this book has gone into print). The findings of Hyland et al. (2012) indicate that although temporal responding requires relational flexibility, this flexibility is not equal across the contextual cues of a relational frame. Hyland et al. (2014) extended on their previous research by considering whether a similar pattern of responding would be observed when the relationship between the stimuli was arbitrary rather than non-arbitrary (as was the case in their 2012 experiment). As in their previous study, the 24 adult participants were randomly assigned to either the BA or AB group. The experimental phases were similar to that of their 2012 study, even employing the same stimuli as in Experiment 1; however, the stimuli within the trials were no longer displayed in a non-arbitrary temporal sequence. For example, when engaged in a “Before Training” trial, the participant was presented with two shapes which appeared simultaneously underneath a black line with the contextual cue of “before” displayed between the shapes for 1 s. This was followed by a grey message box with the words “Click Here”, which when clicked resulted in the display of four shapes. Participants were then required to select the shapes in the order specified by the sequential instruction (e.g. when presented with “Cross BEFORE Triangle”, the participant was required to select cross followed by triangle). “After Training” was similar to that of “Before Training”; however the contextual cue of “before” was replaced with the contextual cue of “after” in the initial stimulus presentation. The assessment portion of the trial, however, remained the same as the “Before Training” section, which required the participant to derive the “before” relationship between stimuli, such that if presented with the instruction of “Square AFTER Triangle”, the participants were required to select triangle followed by square (i.e. deriving the “before” relationship between

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stimuli). Training phases resulted in feedback for both correct and incorrect responses as per their 2012 study. The results indicated that participants were faster and more reliable in their temporal responding when instructed to choose one stimulus before another, than when they were requested to choose one stimulus after another, such that participants demonstrated a faster and more accurate level of responding for derived relations which were identical to those trained than reversed order stimulus relations (i.e. B after A). The results also indicated that the participants’ relational responding was again more flexible for the contextual cue of “before” than that of “after”. These results were replicated by McGreal et al. (2016), who used a similar format of testing and training. Their results indicated that both older and younger adults demonstrated lower accuracy and reduced response speeds for the reversed “after” statements, with older adults demonstrating greater deficits in relational flexibility when compared to younger adults. Although it could be argued that these studies assessed arbitrary mutually entailed temporality (as there was no clear physical relationship between the stimuli on the basis of temporality), there is a possibility that participant performance was a combination of non-­arbitrary coordination (i.e. reproducing the shape, contextual cue and shape of the relations displayed on screen) and non-arbitrary opposition (i.e. again reproducing the shape, contextual cue and shape of the relations displayed, but in reverse – or opposite – order to that which was visually displayed). As such, it becomes difficult to determine the exact relational framing repertoire underpinning responses in this context. This is a methodological issue which plagues much of the more complex relational frames, such as temporality, hierarchy, containment and analogy, and is certainly an area that requires further attention within experimental and applied work.

 elational Inflexibility for Reversed Relations: Unique R to Temporal Relations? The findings of relational inflexibility for reversed-order relations (i.e. deriving relations in the reverse order in which they were trained) when compared to the derivation of relations for statements which retain the original order of stimulus presentation within research on temporal relational framing raised the question as to whether this behavioural phenomenon was unique to temporal relational responding or to relational framing more broadly. Brassil et al. (2019) addressed this question by examining the effect of reversal on magnitude statements (e.g. “B is bigger than A”) compared to the effect of reversal on temporal statements (e.g. “B is after A”) on the accuracy and response timings of 40 undergraduate psychology students. Participants were quasi-randomly assigned to one of two groups who received either temporal training and assessment first or magnitude training and assessment first. For both relational tasks, 25 Japanese symbols served as stimuli, while the contextual cues for the temporal tasks included “before” and “after”, and the magnitude relational task included the contextual cues of “bigger than” and “smaller than”. In

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the case of the magnitude relational task, the stimuli presented were of different font sizes to depict the non-arbitrary comparative relation between them (i.e. font size 40, 60 and 80). The temporal task was similar to that of previous non-arbitrary temporal experiments (e.g. Hyland et al., 2012) as participants were required to respond in accordance with the order in which the stimuli appeared in the observed sequence, while the magnitude task required participants to respond in accordance with the relative size of the stimuli displayed on screen. The results indicated that participants demonstrated faster acquisition of non-arbitrary comparative responding (along the dimension of magnitude), which provides further credibility to the argument that temporal relational framing acts as a separate and distinct relational repertoire to that of comparative relational framing. Brassil et al. (2019) also found that for both temporal and comparative relations, participants demonstrated less accurate and slower responding for the reversal of the order of stimuli, indicating that this relational flexibility is not unique to temporal relational responding, but is instead a more general relational effect, such as mutual or combinatorial entailment may be in operation. Such results indicate that training programmes which aim to promote relational flexibility may require increased exposure to learning opportunities with reversed-order relations when compared with learning opportunities for the derivation of relations which retain the original order stimulus presentation. Such a recommendation is rather straightforward when considering comparative relational framing but becomes much more complex when applied to non-arbitrary temporal framing.

Temporal Relations and Early Research One of the earliest studies which addressed the relational frame of temporality was that of O’Hora et al. (2004) – incidentally Dr. Denis O’Hora’s name is probably associated with all temporal research cited within this chapter to at least some extent, so he is most certainly a greater authority on the subject than I am! Within their first study, three undergraduate university students served as participants and were trained to respond in accordance with temporal relations followed by coordination and distinction relations. As in previous RFT research, arbitrary stimuli (in this case, four three-string characters including %%%,!!!, ()() and:::) served as the contextual cues for “before” (i.e. ()() acquired the function of “before”), “after” (i.e.::: served as the contextual cue for “after), “same” and “different”, while geometric shapes served as stimuli during relational pretraining and testing, while tests for instructional control involved four differently coloured squares and eight three-­ letter nonsense syllables. Participants were first provided with non-arbitrary pretraining and testing for temporal relational responding which involved the presentation of written instructions on a computer screen to participants. These instructions outlined that they would be presented with two sets of images, followed by another two sets of images, and that participants were required to select the stimulus set which was presented at the beginning of the trial. All stages of training

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and testing within this study involved the use of an REP procedure (see Chap. 3 for further information on this procedure). Participants were presented with one shape (e.g. circle) followed by an arbitrary contextual cue for before or after (i.e. () () or:::); this was then followed by another shape (e.g. square). Participants were then asked to select one of two stimulus sets presented, each of which comprised the previously viewed stimuli in addition to an arbitrary contextual cue for before or after between the stimuli within each set. The selection of the stimulus set which outlined the correct temporal relation between stimuli was reinforced via visual feedback on screen. A total of 16 pretraining trials for mutually entailed temporal relations were employed, and these also included arbitrary shapes; however, within this context, there were four “choice situations” for these stimulus pairs, such that if the trial included the relationship of “circle before square”, a participant would then be presented with the following four potential choices: (1) “circle before square” or “square before circle”, (2) “circle after square” or “square after circle”, (3) “circle before square” or “circle after square” and (4) “square before circle” or “square after circle”. Trials within this block were counterbalanced such that each question was asked an equal number of times that each arbitrary shape initially presented on trials was displayed an equal number of times and that the correct response option was displayed an equal number of times on either the left- or right-hand side of the screen. Following this pretraining phase, which required a mastery criterion of 14/16, participants then moved to test probes of novel stimulus pairs across two blocks (a total of 32 trials). All participants passed this phase of training and were subsequently exposed to non-arbitrary pretraining and testing for relations of coordination and distinction. This was similar to the previous pretraining of temporality; however, this involved arbitrary contextual cues of difference and sameness (i.e. %%% and!!!). Following the mastery of this stage (15 out of 16 correct responses), a test for instructional control was then administered across 36 instruction probes which also assessed networks of relational responding with the frames of coordination, distinction and temporality. This phase of testing employed the previously established contextual cues and nonsense syllables as stimuli. Within each probe, the nonsense syllables (labelled as B and C stimuli) were presented vertically and in random order, while the arbitrary contextual cues of “before” or “after” were presented in between each pair of nonsense syllables, leading to a total of 48 possible combinations of contextual cues (i.e. before and after) and the 4 nonsense syllable stimuli, with test blocks including 12 random samples of these 48 combinations. Participants were also assessed for further instructional control with the contextual cues of “same” and “different” using nonsense syllables and coloured squares (labelled A stimuli) in the following manner. Once presented with the C stimuli (i.e. nonsense stimuli) and the contextual cue of before or after, the computer screen then displayed A (i.e. coloured squares), B and C (i.e. nonsense syllables) in addition to the same or different contextual cues in the top third of the screen, providing a total of eight pairs of stimulus presentations. The left-hand side of the screen included four potential columns of stimuli which comprised a contextual cue for “same” relational responding, an A stimulus under this contextual cue and a further B

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stimulus placed beneath the A stimulus (i.e. reading upward B stimulus, A stimulus, contextual cue of same). The right-hand side of the screen also included four possible columns of stimuli; however, this was composed of either the “same” or “different” contextual cue which was placed above the B stimulus which was also above the C stimulus (i.e. reading downward SAME/DIFFERENT, B stimulus, C stimulus). For this set of probes, each of the eight pairs of previously outlined stimuli was displayed at random in one of the eight outlined positioned at the top of the computer screen. When presented with this relational network, participants were required to press as many coloured response keys as they wanted, in whatever order they selected, before pressing the return key. These coloured response keys were four computer keys coloured green, red, yellow and blue which corresponded to the A stimuli within this context. For each of these test probes, a specific four-key sequence was considered to constitute a correct response. For example, if presented with the relational network “C4 BEFORE C3 BEFORE C2 BEFORE C1” at the bottom of the computer screen (this was to be read upwards) in addition to the stimulus relations outlined on the top right-hand screen (e.g. reading upward; C4, B4, SAME; C3, B3, SAME; C2, B2, SAME; C1, B1, SAME) and the stimulus relations displayed on the top left-hand of the screen (e.g. reading upward; B4, A4-blue, SAME; B3, A3-yellow, SAME; B2, A2-red, SAME; B1, A1-green, SAME), the correct behavioural response would be to press the coloured response keys of blue, yellow, red and green. When presented with “different” contextual cues, no specific response was expected within the relational network provided. However, this does not mean that any possible random responses would constitute a correct response. For example, the following relational network may be presented: C4 BEFORE C3 BEFORE C2 BEFORE C1 at the bottom of the computer screen (again, this was presented so that participants read upwards) and provided with the stimulus relations on the top-right hand of the screen (e.g. reading upwards; C4, B4, DIFFERENT; C3, B3, DIFFERENT; C2, B2, DIFFERENT; C1, B1, DIFFERENT) and the relational network on the left hand of the screen (e.g. reading upward; B4, A4-blue, SAME; B3, A3-yellow, SAME; B2, A2-red, SAME; B1, A1-green, SAME). Within this context, the response which is specified is “not blue”, “not yellow”, “not red” and “not green”; therefore, any response other than blue, yellow, red and green (in this order) was considered correct. In total, the test for instructional control involved 3 blocks of 12 test probes: (1) same sequential probes, (2) same non-sequential probes and (3) different non-sequential probes. Sequential probes were designed to facilitate participants reading from bottom to top and also involved the presentation of the stimuli within a temporal relationship in a temporal sequence (constituting an element of non-arbitrary temporality). Non-sequential probes presented the contextual cues simultaneously and were therefore more arbitrary in nature. These probes were extremely complex in nature and involved the combination of several mutually entailed relationships into a larger relational network of temporality, coordination and distinction. Two of the three participants met mastery criterion within two exposures of the final phase of the experiment, while the third participant demonstrated a greater difficulty with this relational network requiring four exposures for the

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second phase of the same non-sequential probes while failing to meet mastery criterion for distinction prior to the termination of the study. The researchers hypothesised that the third participants’ difficulty with responding in this experimental phase may have resulted from the introduction of cues of distinction following the competition of test probes using contextual cues of coordination, as responding may become less sensitive to change once they have been established (a hypothesis based on the findings of Wulfert et al., 1994). As such, the second experiment by O’Hora et al. (2004) modified the experimental procedure by altering the stage at which contextual cues for distinction were introduced into training (i.e. they were now introduced following the fourth test probe within the test for instructional control). The researchers also included a further change to the initial experiment by including an assessment of generalisation upon completion of the initial test for instructional control including stimuli from a novel stimulus set. The second experiment was conducted with eight undergraduate university students between the ages of 19 and 23, and the procedure was similar to Experiment 1 with the exception of the previously outlined modifications. Their findings indicated that a further five of the eight participants who had demonstrated instructional control within the experiment also demonstrated generalisation of responding with untrained stimuli. The findings of both experiments in relation to instructional control generated further evidence for the utility of RFT as a model of generative verbal behaviour  – an issue which has plagued behavioural psychology since Chomsky’s infamous critique in 1959. Although the design of this experiment is somewhat complex (particularly when considering the expansive relational networks employed), it seems appropriate to focus on the facilitation of temporality within an overall relational network within applied work to model such complex patterns of behaviour. Therefore, an applied version of such a training and assessment programme with populations who are deficient in these repertoires should not be shied away from and should in fact be encouraged within the field of behaviour analysis.

Temporal Framing and Intellectual Potential Relational framing research has considered the relationship between this behavioural repertoire and cognitive functioning since its inception. Interestingly, temporal framing is potentially one of the relational frames which has been most closely examined in regard to its relationship with intellectual potential. For instance, O’Hora et al. (2005) extended upon their 2004 research and provided evidence for the role of temporal relations in cognitive functioning by examining the relationship between relational responding (including a model of instructional control as outlined in their 2004 study) and subtests of the WAIS-III (Wechsler Adult Intelligence Scale, 3rd edition; Wechsler, 1997). The participants included 75 university students as participants between the ages of 18 and 54. Participants were first assessed for language comprehension using the Spanish Language Comprehension Assessment which was developed by the research team. Participants were subsequently

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categorised as monolingual (n = 26) or bilingual (n = 49; specifically Spanish and English) participants. Participants were then exposed to the relational task which was identical to the empirical model of instructional control within O’Hora et al.’s previous study in 2004 involving six stages in total: (1) pretraining for temporal relational responding, (2) testing for temporal relational responding, (3) pretraining for coordination and distinction relational responding, (4) testing for coordination and distinction relational responding, (5) test for instructional control and (6) test for generalisation. Following the completion of the relational task, participants were finally assessed across three subtests of the WAIS-III: (1) the vocabulary subtest involved participants defining a series of 33 words (presented orally and textually), (2) the arithmetic subtest included 20 mathematical problems which were to be solved mentally and answered verbally within a specified time limit, and (3) the digit-symbol-coding subtest involved presenting participants with numbers paired with arbitrary symbols and then asking the participant to draw the symbols for as many numbers as possible within a 2 min period. The results indicated that participants who successfully completed the relational task (n = 31) outperformed those who failed to complete the task (n = 44) on WAIS-III subtests of vocabulary and arithmetic; however, no significant difference existed for digit-symbol encoding subtest scores between these two groups. No difference in performance on the relational task or the WAIS-III subtests was found between monolingual and bilingual participants. Upon further analysis, post hoc tests indicated a significant correlation between a specific phase of the relational task and performance on vocabulary and arithmetic subtest scores. Specifically, a significant correlation was found between the vocabulary and arithmetic subtest and the number of correct responses during the first phase of the relational task (i.e. temporal relational training). Given the relationship between temporal relational responding and these measures of cognitive functioning, this early study provided a convincing rationale to examine temporality and indeed offered a strong base upon which to consider the importance of relational framing to cognitive and intellectual functioning overall. A further follow-up study by O’Hora et  al. (2008) examined the relationship between temporal relational responding more specifically and further indices of cognitive and intellectual functioning with 81 undergraduate students between the age of 18 and 48. A temporal relational task was first presented to the participants which involved 12 blocks of 16 trials which was similar to the first stage of the relational task employed in their 2004 and 2005 studies (i.e. the 2008 study omitted the previous elements of coordination and distinction that were included in their earlier relational tasks). Participants were classified as either having passed or failed the task following these 12 training blocks, which was the first measure of temporal relational responding, and were also assessed on the percentage of trials correct during training  – the second measure of temporal relational responding which was included to ascertain the speed and flexibility with which participants could identify the temporal relations of the arbitrary stimuli. Participants were then assessed for their WAIS-III performance. In contrast to their earlier 2005 study, the researchers assessed participants along a greater number of subtests (i.e. 13 of the 14 subtests within the WAIS-III assessment) and obtained full-scale intelligence scores from

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the sample (these were above average, which is to be expected when considering the demographic profile of the participants included). The WAIS-III assessment included the previously explored subtests of vocabulary, arithmetic and digit-­ symbol coding from their 2005 study, but also involved the addition of subtests of comprehension, similarities, information, digit span, block design, matrix reasoning, picture arrangement, picture completion, letter-number sequencing and symbol search (only omitting the subtest of object assembly as it did not contribute to IQ scores or indices). The indices examined within the study included verbal comprehension (i.e. combination of vocabulary, similarities and information subtest scores), perceptual organisation (i.e. a combination of block design, matrix reasoning and picture completion subtest scores), working memory (i.e. a combination of participant scores for arithmetic, digit span and letter-number sequencing subtests) and processing speed (i.e. a combination of symbol search and digit-symbol coding performances). The results of the temporal relational task indicated that 45 of the 81 participants reached the mastery criterion within 12 blocks of training (the first measure of temporal responding) with average correct temporal responding standing at 62.8% (the second measure of temporal responding). Successful completion of the temporal relational task was associated with full-scale, verbal and performance IQ, such that participants who had passed the temporal relations task demonstrated a significantly higher full-scale, performance and verbal IQ. Furthermore, the results also indicated that successful completion of the temporal relational task was also associated with greater performances on the verbal comprehension and perceptual organisation indices; however, no relationship was observed between mastery of the relational task and performance on working memory or processing speed indices of the WAIS-­ III. Further analyses investigating the relationship between participants’ percentage of correct trials during the temporal task also revealed that this measure was positively (and moderately) related to full-scale, verbal and performance IQ. Significant moderately strong correlations were also found between percentage of correct temporal responding and scores on the indices of verbal comprehension and perceptual organisation but were not present for the indices of working memory or processing speed. Upon further investigation, percentage of correct relational responding was found to be significantly related with performance on five subtests of the WAIS-III (specifically, vocabulary, similarities, information, block design and symbol search). The results of O’Hora et al. (2005, 2008) provide a strong argument for the incorporation of temporal relational framing into academic and applied programming and call for further exploration of procedures specifically designed to establish this repertoire. O’Toole and Barnes-Holmes (2009) employed an alternative methodology to examine the relationship between temporal relational responding and intelligence. Within their study, 55 undergraduate students aged between 18 and 55 years participated in 2 experimental sessions. Within the first session, participants completed 1 IRAP protocol of temporality and another IRAP protocol which addressed coordination and distinction (see Figs. 6.1 and 6.2 for example of IRAP temporal protocols for congruent and incongruent trials) across a total of 32 trials per protocol.

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Fig. 6.1  Example of IRAP temporal protocol for congruent trials

Fig. 6.2  Example of IRAP temporal protocol for incongruent trials

Within both IRAP protocols, participants were first assessed for their speed of relational responding on consistent trials (across sameness, distinction and temporality), followed by their speed of relational responding on inconsistent trials (which required participants to respond against pre-established verbal relations). Participants’ measure of relational flexibility was subsequently calculated by subtracting participants’ response latencies for consistent trials from their reaction times for inconsistent trials. The second session involved the assessment of IQ using the Kaufman Brief Intelligence Test (KBIT, Kaufman & Kaufman, 1990) which began by assessing expressive vocabulary and concluded with matrices. The

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findings indicated that greater relational flexibility (i.e. faster response times for changes in the relationship between stimuli) across temporality, coordination and distinction was associated with higher IQ and extended upon the previous research of O’Hora et al. (2005, 2008) while also providing potential evidence for the role of relational flexibility as a predictor of intelligence and cognitive functioning. In a more recent study conducted by Kirsten and Stewart (2021), the relationship between temporal framing repertoires (and a number of other relational framing repertoires) and IQ scores was examined in a sample of 24 young children aged 3 to 7 years. This study provides one of the most comprehensive assessments of relational framing repertoires to date and also includes an assessment of both non-­ arbitrary and arbitrary relational repertoires. The relational assessment involved four stages, each of which was comprised of five specific substages assessing coordination, comparison, opposition, temporality and hierarchy relational repertoires. Each stage of the relational assessment became increasingly complex beginning with non-arbitrary repertoires and culminating in arbitrary analogical relations within the fourth stage of the assessment (a complex relational frame which involves relating relations and will be explored in greater detail in Chap. 8). For instance, in the case of Stage 1 non-arbitrary temporality (which was presented on an iPad Air using Apple Keynote software), participants were asked to direct their attention to the tablet screen which displayed sequentially appearing shapes (thereby illustrating the non-arbitrary nature of temporality), such that one shape would appear 0.5 s following the commencement of a new trial, while the second stimulus appeared 1 s after the appearance of the first stimulus. Participants were then assessed for mutually entailed NAARR temporality across a variety of verbal responses (e.g. “Is the orange star after the purple star?”, “No”; “Which colour is before the other colour?”, “purple”; “Which shape is before the other shape?”, “Triangle”). Stage 2 was also presented using an iPad and Keynote software but focused on the assessment of non-arbitrary analogical relations. Across all substages of this phase of assessment, a compound sample stimulus (which bear a relationship of coordination, distinction, opposition temporality or hierarchy with one another) was displayed at the top of the screen, while two comparison compound stimuli were displayed on the lower half of the screen (each depicting a specific non-arbitrary relationship). Each of these compounds included two stimuli which appeared either simultaneously or 0.5 s apart on screen. In this stage, the participant is asked to select the compound stimulus which is like the one displayed at the top of the screen. In the case of non-­ arbitrary temporal analogical relations substage, each of these compounds included two stimuli which appeared either simultaneously or 0.5  s apart on screen. For example, when the sample compound stimulus displayed at the top of the screen involves the simultaneous appearance of both components of this stimulus, while the bottom half of the screen displays the options of comparison Stimulus A (in which one component of the stimulus is presented before the other) and comparison Stimulus B (in which both components of the stimulus are presented simultaneously), the selection of comparison Stimulus B in this instance constitutes a correct response. Stage 3 was presented on a Chromebook using Microsoft PowerPoint

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software and was an adaptation of an REP format. Within this stage (and the various substages), arbitrary stimuli in the form of monochromatic shapes (e.g. rectangles, triangles, circles) were displayed on screen accompanied by a single Latin letter which signified the contextual cue (e.g. B for “before”, A for “After”, S for “Same”, etc.) and relational frame in operation between the displayed stimuli. A corresponding audio icon which produced an audio recording of the contextual cue was also included within all substages. This stage focused on the assessment of mutual and combinatorial entailment across a number of relational frames and, in the case of coordination, distinction and opposition, also included the assessment of transformation of stimulus function. The final stage within this relational assessment was similar to Stage 3; however, it focused on the assessment of arbitrary analogical relations. The sequence in which participants were assessed using the Stanford-­ Binet fifth edition (SB5; Roid, 2003) or the relational assessment task was randomly determined. The results of Kirsten and Stewart (2021) potentially provide one of the most useful applied RFT studies to date, as they provide a rudimentary account of the developmental sequence of relational frame acquisition, with stronger performance on all stages and substages of the relational assessment being associated with age. For example, when focusing on temporality, the results indicate that NAARR of temporality is the last relational frame to emerge of the five relational frames examined within the substages of Stage 1 (i.e. coordination, comparison, opposition, hierarchy and temporality) and also is one of the final frames combined within a non-arbitrary analogical relational frame as measured across the substages of Stage 2 (the data indicated that it was the fourth of these five frames to emerge in this context). Similar results were also observed within arbitrary stages of assessment, with temporal relational responding being identified as the fourth relational frame to emerge across both Stages 3 and 4. The relationship between relational repertoires and IQ was also explored within this study, and as outlined in Chap. 5, the only non-arbitrary relational frame associated with IQ (total score, non-verbal and verbal scores) was that of comparison. However, all arbitrary relational frames (including that of temporality) were found to have a significant positive relationship with that of overall IQ, verbal and non-verbal IQ as measured by the SB5, thereby replicating the previous findings of O’Hora et al. (2005). Given the findings of this study and that of previous research in this field, it is tempting to conclude that temporal relational framing plays a role in the manifestation of intelligent behaviour; however, we must always interpret the findings of such studies with caution and encourage the advancement of research within this field. Within their study, Kirsten and Stewart (2021) demonstrated the feasibility of assessing relational repertoires at varying levels of complexity with a young sample and offer an exceptionally useful framework for applied practitioners in this sense. The relational assessment tool used within their study could potentially be integrated with existing assessment protocols and curriculums with relative ease and minimal use of resources.

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Temporality and Applied Practice? Although it has not been stated within research to date, it is possible that some element of temporal relational responding is responsible for behaviour which operates in accordance with the Premack principle (Premack, 1959), which is also known as the “First/Then” contingency within the applied field (e.g. Herrod et  al., 2022). “First/Then” contingencies have received considerable attention within applied practice and operate by outlining the behavioural contingency which exists between the “first” (and specified target) behaviour and the “then” behaviour to an individual (Mechner, 2008). This “then” behaviour is a high-probability behaviour (or reinforcing behaviour) for the individual and is made available to the individual contingent on their performance of the “first” behaviour (initially a low-probability behaviour). This has typically been used within applied and educational practice for scenarios in which a demand is placed on an individual (e.g. the completion of a mathematical worksheet) and its execution results in access to a reinforcing activity (e.g. playtime outside; Trump et al., 2018). But where do temporal relations possibly operate within the Premack principle? Potentially, it is that when given the scenario “First Activity A, then Activity B”, the word “then” may operate as a contextual cue specifying the temporal displacement between Activity A and B, indicating that performance of Activity A is required before access to Activity B (which may constitute a mutually entailed transformation of stimulus function in accordance with temporality). While this relationship may be arbitrary (i.e. there is no indication regarding the physical relationship between the stimuli), non-arbitrary elements such as visual supports in the form of a “First/Then” board or a visual schedule have been employed (e.g. Warren et al., 2021), potentially involving non-arbitrary coordination with arbitrary temporality. However, it could also be argued that a degree of causal relations is in operation in this context, and as outlined at the beginning of this chapter, there is an element of murky uncertainty and speculation with this relational frame  – as there is much more to explore and would certainly be an interesting avenue of research.

Temporality: Training and Assessment of NAARR and AARR As previously outlined, we are treading tentatively into the realm of hypotheticals as, to date, there is no research which has focused on the facilitation of temporal relations amongst individuals who demonstrate deficits in this repertoire. However, the assessment tools of Hyland et al. (2012, 2014) and Kirsten and Stewart (2021) provide a potentially useful avenue with which to consider this process, including presentation platforms (e.g. Keynote or PowerPoint) and in-app animation options to display the temporal relationship between stimuli, providing an example of non-­ arbitrary temporal framing to a student. Further, given the results of Hyland et al. (2012, 2014) and McGreal et al. (2016), careful attention must be brought to the

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issue of reversed-order relations when commencing with the training of mutually entailed temporal relations, with explicit planning for additional trials for these relations. For example, if presenting the statement “A before B” to a learner, it is possible that a greater number of questions assessing and training “B after A” are required to teach that aspect of derivation than questions which assess and train “A before B”. The issue of bidirectional training is more complex when applied to temporal relations as there is no way in which we can physically demonstrate the “after” relation (even rewinding an event on video would only confuse the matter and is likely unviable as a solution), meaning that due to exposure alone, the contextual cue and relation of “before” is more salient. This unbalanced salience may underscore why non-arbitrary temporality is one of the last relational frames to emerge in development (Kirsten & Stewart, 2021). As with the previous relational frames we have discussed so far, it may be possible to assess and teach these relational within the context of tabletop instruction using relational assessments such as those employed by Kirsten and Stewart (2021). Assessment and training should also focus on a variety of response forms such as selection (e.g. “Point to which one comes after”), confirmation or disconfirmation (e.g. “Does X come after?”; “Y is after Z, is this true?”) and verbal responses (e.g. “Tell me what is before?”; “What’s the relationship between X and Y?”). Naturally occurring events may also be utilised to teach and assess this repertoire. For instance, when playing with toy cars that are engaged in a race, we may verbalise the physical relation between the stimuli (e.g. “The red car has finished before the blue car”; “The blue car finished after the red car”) and then assess for derivation of mutual entailment (e.g. “Which car finished before the other one?”) and represent the temporal relation with the verbal statement in the event of incorrect responding. Temporal relations could also be interspersed with intraverbal training to provide further exposure to temporal contextual cues (e.g. “What comes after C?”; “What number is before 5?”). In further applied examples, an analogue clock could also be used to demonstrate the relationship between two temporal events (e.g. “6:15 is before 6:30”) – although this verges on the more abstract concept of time, the visual and spatial distinction between the clock hands may provide a more physically clear indication of the relationship between timepoints while also facilitating a more abstract relational repertoire over time. Furthermore, the analogue clock also allows a user to manipulate the events in question by physically altering the placement of the clock hands. Auditory stimuli could also be used to assess and teach mutually entailed (and even combinatorially entailed) temporal relations. In the scenario of music class, students may listen to Queen’s “Bohemian Rhapsody” several times, and their derivation of mutually entailed temporal relations could be assessed with questions such as “Which comes before/after the other – ‘is this the real life?’ or ‘is this just fantasy?’” or “What’s after ‘Mama, life had just begun’?” Of course, a more simplistic version of this (that does not require the same amount of short-term memory – or obsession with Queen) may be to use single distinct musical notes such as “doh” and “soh”, demonstrate their temporal relationship to one another and

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subsequently assess derivation of mutual entailment. However, it is of course recommended that the interests of the learner are considered when programming this – socially meaningful stimuli should be incorporated into training (even if that does include listening to Queen many, many times). NAARR combinatorially entailed temporal relations could again be assessed using a tool similar to that of Kirsten and Stewart (2021) – however, in the original study, only mutually entailed NAARR temporal relations were assessed. Watching Olympic sports may also serve as a relevant example of combinatorial entailment. For instance, the 2020 Summer Olympic’s women’s 100 m might serve as an appropriate example in which Elaine Thompson-Herah placed first, Shelly-Ann Fraser-­ Pryce placed second and Shericka Johnson placed third. While watching the race (and potentially the award ceremony), the relationship between these individuals could be outlined using contextual cues “Shericka finished after Shelly-Ann and Shelly-Ann finished after Elaine” and subsequently assessing combinatorial entailment, with teaching trials providing feedback. Instruction and assessment should also consider the combination of NAARR temporality with more arbitrary relational repertoires such as coordination or comparison. For instance, in music class, the learner may be presented with a sheet of music as in Fig. 6.3 which includes arbitrary coordination, non-arbitrary distinction and spatial and temporal relations. Using this example, we could subsequently assess a learners’ derived NAARR temporal responding with questions such as “What note(s) comes after E♭?” or “What note is before C?” Of course, this is not a perfect example as the extent to which NAARR of spatial relations and temporality are combined becomes quite muddied; nonetheless, it provides us with a relatively functional and socially acceptable method of training and assessing a complex relational network. Transformation of stimulus function for both mutually entailed and combinatorially entailed temporal relations could again be incorporated into the everyday environment. As previously discussed, an element of temporality may potentially underscore “First/Then” responding (a hypothesis which would be useful to investigate); however, everyday actions could also be used to facilitate NAARR temporal

Fig. 6.3  Example of musical sheet employing non-arbitrary and arbitrary relational networks Illustrated above is a musical sheet which provides an example of arbitrary coordination, non-­ arbitrary distinction and non-arbitrary spatial and non-arbitrary temporal relations. The arbitrary elements include the music notes (i.e. a minim is equivalent to two musical beats) whose relative placement on the staff equates to a musical note (i.e. E♭, E♭, C, C, B♭ and B♭). Non-­arbitrary distinction coupled with non-arbitrary spatial elements include the difference in the placement of the notes on the staff, while non-arbitrary temporal elements (when reading from left to right in music) indicates that E♭ is before E♭, while the second E♭ is before C and so on

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responding. For instance, when getting dressed to go outside, this repertoire could be assessed by drawing on the discriminative function of stimuli. The learner could first be told the correct sequence of dressing (e.g. “Socks before shoes”; “Coat after shirt”) and asking the learner “Do you put your shoes on before or after you put on your socks?” or “Do you put your shirt on before or after your coat?” Any attempts to put a sock on over a shoe or a shirt on over a coat is unlikely to be reinforced, while the appropriate and correct temporal sequencing of stimuli would result in reinforcement. Similarly, when considering the temporal relationship between stimuli needed to make a crisp sandwich (i.e. bread before butter, before crisps), the transformation of function of combinatorially entailed temporality could also be assessed and trained in this way, as any order other than that specified is unlikely to result in a whole crisp sandwich. Arbitrarily applicable responding in accordance with temporality would be facilitated in a similar way to that of NAARR, including an emphasis on MET and reversed-order relations, while also considering the social meaningfulness of the stimuli and behaviours involved. Of course, AARR now considers the relationship between arbitrary stimuli such as written text or verbal statements, which may of course be combined with other relational repertoires. For example, AARR of temporality could be assessed via the history curriculum by providing a student with statements such as “The Great Irish Famine occurred before the Easter Rising” and assessing for mutual entailment by asking “Did the Famine happen after the Easter Rising?”. This initial statement could be extended by adding that “The Easter Rising took place in 1916”, and combinatorial entailment could be assessed by asking the student “Did the Famine occur before or after 1916?”. As we previously discussed within this chapter, an aspect of rule – or instruction-following and rule-governed behaviour is dependent on a temporal relational repertoire (O’Hora et  al., 2014; Stapleton, 2020); as such, a potentially useful way in which to assess and teach arbitrary temporality may be via rule-governed behaviour. For instance, in a school-­ based environment, transformation of function could also be taught and assessed by outlining that the student may leave the class “after” the bell rings – their exit from the classroom following the ringing of the bell constituting a transformation of stimulus function, such that exiting the class after the bell rings will result in reinforcement, while exiting the class before the bell rings may result in punishment. Moving away from rule-governed behaviour, a further element of transformation of function within language could also be assessed. For instance, within France the greeting “bon jour” is appropriate before 6 pm, while “bon soir” is the acceptable greeting after 6 pm. If a learner has been taught a complex relational network, such that “bon jour” is similar to “bon soir” as a form of greeting and is also told that “bon soir” is only acceptable after 6 pm while “bon jour” is the correct term before 6 pm, we may assess a learners’ transformation of stimulus function based upon the French greeting that they select before or after 6 pm. These are brief (and entirely theoretical) examples of teaching temporal responding, as unfortunately, there is a lack of data in this realm.

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 he Totally Not Ironic Future of Temporal Relations: T Directions for the Future? The lack of published research which focuses on the facilitation of non-arbitrary and arbitrary temporal relations with populations deficient in this repertoire indicates a substantial gap in the area which future research should aim to resolve. As this has been achieved with other relational frames (notably coordination and comparison as explored in our previous chapters), it is entirely feasible that such a training and assessment protocol could be developed and adapted for socially meaningful and functional living skills. For instance, executive function and its links with temporal relational responding have been demonstrated in previous research (Tyrberg et al., 2021) indicating that deficits in this relational repertoire may be linked with deficits in executive function. There are several populations which struggle with executive function, such as autism and attention deficit hyperactivity disorder (Demetriou et al., 2019; Lee et al., 2020); it is proposed, therefore, that RFT may offer a potentially useful framework to facilitate temporal relational repertoires which may positively impact executive function abilities. Recent publications have also considered the applications of temporal relational repertoires in the area of mental health, such as the remediation of depression and anxiety (e.g. Hendriks et al., 2016a, b). This comprises a useful and socially relevant avenue of research which should be encouraged within the field, and it is anticipated that a greater wealth of research may evolve from this domain of research, potentially incorporating procedures from acceptance and commitment therapy (a sibling of RFT). Cullinan and Vitale (2009) also postulated that temporal relations may underpin some of the complexities of grammar that have historically been studied by cognitive psychology; research should therefore determine whether exposure to a curriculum training temporal relations may also facilitate correct grammatical responding. Experimental work in the area of temporal relations has shed some light on the complexity of reversed-order relations, providing relevant information which can generalise to establishing these relational repertoires – a finding which is not isolated to temporality alone. A potential avenue for research in this area may include research which evaluates the relative proportion of reversed-order training to original-­order training which is required to establish flexible temporal relational responding. Furthermore, in previous chapters, we have explored the considerable contributions of experimental analysis to the understanding of transformation of stimulus function across relations such as coordination and opposition (Dymond et al., 2007) and comparison (Dougher et al., 2007); however, there are no studies which have examined transformation of stimulus function in accordance with temporal relations, which may be a useful direction to further our understanding of temporal responding. Finally, a rather tentative and entirely hypothetical area of research for temporal relational responding may lie in the field of criminal behaviour and rehabilitation as previous research (e.g. O’Hora et  al., 2014; Stapleton, 2020) have outlined a

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potential link between temporal relational repertoires and rule-governed behaviour; it may be worthwhile to consider the application of a programme focused on future-­ thinking (rooted in temporal relations) for at-risk youth to determine the viability of an RFT-based programme in this field. Given the dearth of research relating to temporal responding, there is a host of potential research that is yet to be conducted, and I remain hopeful that there is much more to come in this field. TLDR Cheat Sheet Deixis A relational frame comprised of temporal (i.e. now-then), spatial (here-there) and interpersonal (I-you) relational responding which forms the basis of perspective-­ taking from an RFT perspective. For a more in-depth view of this frame (and perspective-taking more generally), it is highly advisable to read McHugh & Stewart’s, 2012 book on the topic Rule-­ This is behaviour that is driven by, or is controlled by, a verbally mediated rule governed which describes contingencies (e.g. “if you ingest rat poison you will die”) and is behaviour not actually shaped by direct exposure to or experience of these contingencies. For instance, many of us may obey the laws of the land (e.g. avoiding physically harming another human being) not because we have a direct experience of punishment for engaging in these behaviours, but because of the law (or verbal rule) that such behaviour results in serious sanctions and punishments Executive This is a term used to describe a broad set of cognitive abilities (e.g. working function memory, reasoning, impulse inhibition, etc.) and mental processes that when combined serve to allow humans to engage in goal-directed behaviours such as the management of time, organisation of tasks and problem-solving Arbitrary Although this is explored in greater depth in Chap. 8, a simple definition of analogical analogical relational responding is provided within this section, such that RFT relations considers repertoires of analogy to be a complex form of relational framing – Namely, the ability to relate relations. For example, the analogy cat is to kitten as dog is to puppy involves three relations. Relation 1 is the relationship which exists between cat and kitten, which is a comparative relation. Relation 2 is the relationship between dog and puppy, which is also of comparison. Finally, relation 3 involves determining the relationship between the stimuli in relation 1 (i.e. cat and kitten) and the stimuli in relation 2 (i.e. dog and puppy) to be that of sameness as both relation 1 and 2 are concerned with the relational frame of comparison of age. Therefore, this third relation requires an individual to relate the relationships between presented relations, ultimately resulting in analogical responding Premack Also known as “first/then” or “Grandma’s rule”, the Premack principle maintains principle that behaviours which are more probable may be used to reinforce behaviours which occur at a lower frequency. In this scenario, the reinforcer is not a stimulus, but is instead a behaviour or activity. For instance, if I were to take the high probability behaviour of online shopping for myself and juxtapose that against a low probability behaviour of mine such as writing, I could increase the frequency of my writing by making access to online shopping contingent on the completion of three pages of writing (this may or may not be based on the current book-­ writing scenario), thereby using my high probability behaviour (online shopping) to increase the future probability of my initially low probability behaviour (i.e. writing)

References

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References Brassil, N., Hyland, J., O’Hora, D., & Stewart, I. (2019). Reversing time and size: Mutual entailment of nonarbitrary temporal and magnitude relational responding. The Psychological Record, 69, 95–105. https://doi.org/10.1007/s40732-­018-­0323-­y Chomsky, N. (1959). Review: Verbal behaviour by B. F. Skinner. Language, 35(1), 26–58. Cullinan, V., & Vitale, A. (2009). The contribution of relational frame theory to the development of interventions for impairments of language and cognition. The Journal of Speech and Language Pathology – Applied Behavior Analysis, 4(1), 132–145. https://doi.org/10.1037/h0100254 Demetriou, E. A., DeMayo, M. M., & Guastella, A. K. (2019). Executive function in autism spectrum disorder: History, theoretical models, empirical findings, and potential as an endophenotype. Frontiers in Psychiatry, 10(753), 1–17. https://doi.org/10.3389/fpsyt.2019.00753 Dougher, M. J., Hamilton, D. A., Fink, B. C., & Harrington, J. (2007). Transformation of the discriminative and eliciting functions of generalized relational stimuli. Journal of the Experimental Analysis of Behavior, 88(2), 179–197. https://doi.org/10.1901/jeab.2007.88-­179 Dymond, S., Roche, B., Forsyth, F. P., Whelan, R., & Rhoden, J. (2007). Transformation of avoidance response functions in accordance with same and opposite relational frames. Journal of the Experimental Analysis of Behavior, 88(2), 249–262. https://doi.org/10.1901/jeab.2007.88-­249 Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer Academic. Hendriks, A.  L., Barnes-Holmes, Y., McEnteggart, C., De Mey, H.  R. A., Janssen, G.  T. L., & Egger, J.  I. M. (2016a). Understanding and remediating social-cognitive dysfunctions in patients with serious mental illness using relational frame theory. Frontiers in Psychology, 7, 143. https://doi.org/10.3389/fp-­syg.2016.00143 Hendriks, A.  L., Barnes-Holmes, Y., McEnteggart, C., De Mey, H.  R. A., Witteman, C.  L. M., Janssen, G. T. L., & Egger, J. I. M. (2016b). The relationship between theory of mind and relational frame theory: Convergence of perspective-taking measures. Clinical Neuropsychiatry, 13(2), 17–23. Herrod, J.  L., Snyder, S.  K., Hart, J.  B., Frantz, S.  J., & Ayres, K.  M. (2022). Applications of the Premack Principle: A review of the literature. Behavior Modification, 1–28. https://doi. org/10.1177/01454455221085249 Hyland, J. M., O’Hora, D. P., Leslie, J. C., & Smyth, S. (2012). Sequential responding in accordance with temporal relational cues: A comparison of before and after. The Psychological Record, 62, 463–484. https://doi.org/10.1007/BF03395814 Hyland, J. M., Smyth, S., O’Hora, D. P., & Leslie, J. C. (2014). The effect of before and after instructions on the speed of sequential responding. The Psychological Record, 64, 311–319. https://doi.org/10.1007/s40732-­014-­0026-­y Kaufman, A.  S., & Kaufman, N.  L. (1990). The Kaufman brief intelligence test. American Guidance Service. Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record. https://doi.org/10.1007/s40732-­021-­00457-­y Kosnes, L., Whelan, R., O’Donovan, A., & McHugh, L. A. (2013). Implicit measurement of positive and negative future thinking as a predictor of depressive symptoms and hopelessness. Consciousness and Cognition, 22, 898–912. https://doi.org/10.1016/j.oncog.2013.06.001 Lee, R. R., Ward, A. R., Lane, D. M., Aman, M. G., Loveland, K. A., Mansour, R., & Pearson, D.  A. (2020). Executive function in autism: Association with ADHD and ASD symptoms. Journal of Autism and Developmental Disorders, 1–13. https://doi.org/10.1007/ s10803-­020-­04852-­2 McGreal, C., Hyland, J., O’Hora, D., & Hogan, M. (2016). Mutual entailment of temporal relations in younger and older adults: Reversing order judgments. The Psychological Record, 66, 419–428. https://doi.org/10.1007/s40732-­016-­0182-­3 McHugh, L., & Stewart, I. (2012). The self and perspective-taking: Theory and research from contextual behavioral science and applied approaches. New Harbinger Publications.

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Mechner, F. (2008). Behavioral contingency analysis. Behavioural Processes, 78(2), 124–144. https://doi.org/10.1016/j.beproc.2008.01.013 O’Hora, D., & Maglieri, K.  A. (2006). Goal statements and goal-directed behaviour: A relational frame account of goal setting in organisations. Journal of Organizational Behavior Management, 26(1–2), 131–170. https://doi.org/10.1300/J075v26n01_06 O’Hora, D., Barnes-Holmes, D., & Stewart, I. (2014). Antecedent and consequential control of derived instruction-following. Journal of the Experimental Analysis of Behavior, 102(1), 66–85. https://doi.org/10.1002/jeab.95 O’Hora, D., Barnes-Holmes, D., Roche, B., & Smeets, P. (2004). Derived relational networks and control by novel instructions: A possible model of generative verbal responding. The Psychological Record, 54, 437–460. O’Hora, D., Peláez, M., & Barnes-Holmes, D. (2005). Derived relational responding and performance on verbal subtests of the WAIS-III. The Psychological Record, 55, 155–175. https://doi. org/10.1007/BF03395504 O’Hora, D., Peláez, M., Barnes-Holmes, D., Rae, G., Robinson, K., & Chaudhary, T. (2008). Temporal relations and intelligence: Correlating relational performance with performance on the WAIS-III. The Psychological Record, 58(4), 569–584. https://doi.org/10.1007/BF03395638 O’Toole, C., & Barnes-Holmes, D. (2009). Three chronometric indices of relational responding as predictors of performance on a brief intelligence test: The importance of relational flexibility. The Psychological Record, 59, 119–132. https://doi.org/10.1007/BF03395652 Pinker, S. (1991). Rules of language. Science, 253, 530–535. Pinker, S. (2003). The language instinct: How the mind creates language. Penguin. Pinker, S. (2009). Language learnability and language development: With new commentary by the author (volume 7). Harvard University Press. Pinker, S. (2015). Words and rules: The ingredients of language. Basic Books. Premack, D. (1959). Toward empirical behavior laws: I.  Positive reinforcement. Psychological Review, 66(4), 219–233. https://doi.org/10.1037/h0040891 Roid, G. H. (2003). Stanford-Binet intelligence scales (5th ed.). Riverside Publishing. Stapleton, A. (2020). Choosing not to follow rules that will reduce the spread of COVID-19. Journal of Contextual Behavioral Science, 17, 73–78. https://doi.org/10.1016/j. jcbs.2020.07.002 Trump, C.  E., Pennington, R.  C., Travers, J.  C., Ringdahl, J.  E., Whiteside, E.  E., & Ayres, K.  M. (2018). Applied behavior analysis in special education: Misconceptions and guidelines for use. Teaching Exceptional Children, 50(6), 381–393. https://doi. org/10.1177/0040059918775020 Tyrberg, M.  J., Parling, T., & Lundgren, T. (2021). Patterns of relational framing in executive function: An investigation of the Wisconsin card sorting test. The Psychological Record, 71, 411–422. https://doi.org/10.1007/s40732-­021-­00459-­w Warren, T., Cagliani, R. R., Whiteside, E., & Ayres, K. M. (2021). Effect of task sequence and preference on on-task behavior. Journal of Behavioral Education, 30(1), 112–129. https://doi. org/10.1007/s10864-­019-­09358-­1 Wechsler, D. (1997). WAIS-III administration and scoring manual. Psychological Corporation. Wulfert, E., Greenway, D.  E., Farkas, P., Hayes, S.  C., & Dougher, M.  J. (1994). Correlation between a personality test for rigidity and rule-governed insensitivity to operant contingencies. Journal of Applied Behavior Analysis, 27(4), 659–671. https://doi.org/10.1901/ jaba.1994.27-­659

Chapter 7

The Relational Frames of Containment and Hierarchy

Classification has been described as the capacity to organise stimuli or events into specified classes or categories due to their shared physical features or similar functions, while the groups that contain these stimuli are labelled as classes or categories (Astley et  al., 2001; Zentall et  al., 2002). Hierarchical classification is a slightly more complex form of classification in which classes are further categorised into higher order classes (Greene, 1994). For instance, we may classify a chardonnay as a wine, while also classifying wine as an alcoholic beverage, with lower order categories becoming more specific (e.g. chardonnay and wine) and higher order categories being more broad and general in their scope (e.g. alcoholic beverages include other categories under this label such as beers and spirits). Our ability to navigate the human environment and determine behaviourally appropriate responses for stimuli is based partly on our ability to classify (Freedman & Assad, 2006; Markman, 1989). For example, if I am informed that a Scottish Fold is a type of cat, I would adjust my behaviour to this novel stimulus (i.e. Scottish Fold) based on its membership to the category of cat, deriving that it is likely to have physical characteristics of that group (e.g. fur and claws) and similar behaviours (e.g. interesting and somewhat dramatic reactions when exposed to catnip) and should likely not be initially approached with a bunch of catnip. Without the capacity to categorise and classify stimuli, when presented with novel or unfamiliar events, we would be required to respond to each novel stimulus from the bottom-up which would be a cognitively exhausting experience (Bott et al., 2006), meaning that classification is an exceptionally important skill in facilitating everyday life. The ability to categorise stimuli into progressively more and more specific and complex groupings allows an individual to adjust their behaviour in a strategic manner for more effective and efficient performance (Bornstein & Mash, 2010; Furrer & Younger, 2008; Proffitt et  al., 2000). Classification has a number of practical applications, including everyday living skills (e.g. sorting laundry; Bock, 1994, 1999), thinking and concept learning (Lakoff, 1987) and academic scientific thinking. For example, hierarchical classification is required to organise taxonomies within scientific disciplines such as biology or chemistry. This means that the capacity to respond in accordance with the © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_7

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contextual cues of hierarchy may be responsible for more complex scientific thinking and that this pattern of responding may also be responsible for further complex repertoires such as abstraction and concept formation (Dixon & Stanley, 2020). Hierarchical classification (and classification more broadly) has traditionally garnered attention from the field of cognitive psychology (e.g. Blewitt, 1994; Deneault & Ricard, 2006; Inhelder & Piaget, 1964). The field of Relational Frame Theory (RFT) considers this repertoire to be underpinned by a combination of containment and hierarchical relational frames (McLoughlin et  al., 2019; Mulhern et  al., 2017, 2018). Containment relational framing involves the capacity to relate stimuli using contextual cues such as “in”, “inside”, “contains” and “holds” and, as with other relational frames, is theorised to owe its origins to non-arbitrary or physically visible relationships. For instance, a child may learn containment relations by initially seeing that the toy car is in the box, establishing the contextual cue “in” and via MET (i.e., multiple exemplar training) and this contextual cue becomes abstracted for use in more arbitrary terms. This non-arbitrarily applicable relational responding (NAARR) of containment is also considered to form the basis of hierarchical relational responding as there is some overlap in regards to the contextual cues employed. Hierarchical relational framing involves responding to stimuli on the basis of categorical membership (e.g. “part of”, “type of”), class containment/inclusion and class attributes. For instance, “Stimulus A is a type of Stimulus B and Stimulus B is a type of Stimulus C”, the derivation of the relationship between Stimulus A and C is now possible which specifies that Stimulus A is a type of Stimulus C and that Stimulus C is a class that contains Stimulus A. However, not all relationships of hierarchy are as straightforward as the example outlined. For example, when considering members of a class it is difficult to determine their relationship with one another, leading to a relationship of ambiguity within this relational network. Consider the following example: Stimulus A1/A2 (A1  =  tangerine; A2 = racoon) is a type of Stimulus B1/B2 (B1 = fruit; B2 = animal) and that Stimulus C1/C2 (C1 = orange; C2 = bear) is a type of Stimulus B1/B2 (B1 = fruit; B2 = animal). The response to the question for the stimuli A1 and C1 (i.e. “Is A1 [i.e. tangerine] a type of C1 [i.e. orange]?”) is yes, while the response to the same question for the stimuli A2 and C2 (i.e. “Is A2 [i.e. racoon] a type of C2 [i.e. bear]?”) is no. In this scenario, our response is not actually based upon the relationship outlined to us, but is instead based on information external to this. If this scenario is made into one of true arbitrary responding in which an individual is told that “Stimulus A is a type of Stimulus B, Stimulus C is a type of Stimulus B” and asked “Is A a type of C?”, the correct response is “It’s not possible to say”. Such a scenario exemplifies the complexities of assessing and training an AARR (arbitrarily applicable relational responding) hierarchy repertoire accurately and precisely. Furthermore, such a scenario indicates the potential pitfalls of NAARR when facilitating this aspect of hierarchical responding as curriculums that do not consider this aspect of hierarchical relational responding may inadvertently teach inaccurate or faulty AARR. Figure 7.1 provides an example of a limited hierarchical relational network in which an individual, if taught this hierarchical relational network, would respond to dairy,

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Fig. 7.1  Example of an everyday hierarchical relational network The above example of a hierarchical relational network using everyday stimuli is incomplete as it omits information regarding the relationship between the category (i.e. food) and lower levels of the category (e.g. butter, potatoes, sausage, etc.) and vice versa. The relationship between the mid-­ level stimuli (i.e. dairy, vegetables and meat) is also undefined, as is the relationship between the lower levels of the category (e.g. the relationship between butter and cheese). Despite these omissions, it becomes clear that this pattern of relational framing is complex and can become unwieldy if appropriate attention is not given to the selection of appropriate stimulus sets for assessment and training

vegetables and meat as belonging to the category of food, while also responding to butter and cheese as belonging to dairy, potatoes and onions as belonging to vegetables and sausage and chicken as belonging to meat. However, the issue of the unidimensional relationships is again relevant to the frame of hierarchy. In this scenario, a correct hierarchical response would include the response that “Not all potatoes are food, and not all food is potatoes”, meaning that the function of categorical membership only operates in one direction (i.e. top-down rather than bottom-up) within hierarchical relational framing.

 ierarchy, Containment and the Link to Cognitive H and Linguistic Potential Given the complexity of hierarchical relational responding and containment framing, it has been theorised that these relational repertoires may be related to linguistic and cognitive abilities. This hypothesis formed the basis of my doctoral dissertation and one of the first studies that I published on this topic. In our 2017 paper, we assessed the non-arbitrary containment responding, arbitrary containment and arbitrary hierarchical relational responding of 50 children between the ages of 3 and 8 without any known diagnoses. Children were also assessed for their class inclusion

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responding, categorisation ability (using the Children’s Category Test [CCT]; Boll, 1993), linguistic ability (using the Peabody Picture Vocabulary Test, fourth edition [PPVT-4]; Dunn & Dunn, 2007) and IQ (using the Stanford-Binet Intelligence Scales, fifth edition [SB5]; Roid, 2003). To determine their inclusion for the study, participants were evaluated for their capacity to tact colour and engage in yes–no responding as these were behavioural repertoires necessary to engage in the remaining assessment procedure. Following this, participants were exposed to the first relational responding test of the assessment, which involved assessing participants for non-arbitrary containment repertoires. This involved using square boxes of different sizes (large, medium and small) and different colours (red, yellow, green, blue, purple, orange, black, white and pink), which were manipulated to demonstrate the physical relationship between the stimuli. NAARR containment was assessed across a total of 32 questions, of which 16 addressed the characteristic of mutual entailment, while the remaining questions assessed combinatorial entailment (see Mulhern et al., 2017 for trial types for mutual entailment and combinatorial entailment NAARR containment). During each trial, the experimenter described and demonstrated the relationship between the stimuli by manipulating the stimuli (e.g. when providing the description of “a green box is inside a purple box”, the experimenter would then place a green box inside the purple box), while participants were required to provide a “yes” or “no” response. Participants were then assessed for AARR containment repertoires using same-sized circles of differing colours (e.g. red, yellow, green, blue, purple, orange, black, white and pink) across 32 questions that assessed mutual entailment and combinatorial entailment. The statements and the accompanying statements were similar to that of the NAARR containment phase; however, they focused on identically sized circles as stimuli within both statement and questions. The final phase of the relational test assessed arbitrary hierarchical relational responding using nonsense words as stimuli, which were presented on a laptop screen across a total of 64 questions employing the contextual cues of “type of” and “contains”. For each trial, the participant was presented with an on-screen textual description of the relationship between the stimuli, which was read aloud by the experimenter. Questions within this assessment considered the potentially ambiguous nature of hierarchical networks (e.g. “A quig is a type of donk. Quigs have purple tongues.” – “Do all donks have purple tongues?” – it is not possible to tell based upon the information provided) and also included questions assessing transformation of function of both mutually entailed and combinatorially entailed hierarchical relations. The questions within this section focused on the unidirectional nature of hierarchy whereby the function of belongingness flows top-down rather than bottom-up (e.g. “Are all biks animals?”; “Are all animals biks?”). Additionally, questions also focused on the derivation of relationships in the order in which they are presented (e.g. “A tol is a type of animal.” – “Is a tol a type of animal?” and the derivation of reversed-order relationships (e.g. “A quig is a type of animal.” – “Does the class of animals contain quigs?”). Throughout all three phases of relational assessment, the statements and questions were presented in random order to the participants. Following the completion of this phase of assessment, participants

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were assessed using the SB5 (Roid, 2003) for verbal, non-verbal and total IQ, linguistic ability using the PPVT-4 (Dunn & Dunn, 2007), categorisation ability using the CCT (Boll, 1993) and class inclusion responding. In order to determine the reliability of the relational assessment, the experimenters also assessed the test–retest reliability of the assessment by representing the relational assessment test to participants 2 weeks following their initial test. Minor modifications were made to each phase to endeavour to combat practice effects. The NAARR containment phase within the retest assessment was similar to that of the initial test, but employed triangular-­shaped boxes, while the AARR containment phase replaced the identically sized circles with identically sized triangles. AARR hierarchy replaced the nonsense syllables employed within test 1 with a set of new nonsense syllables and also provided a new set of characteristics for each stimulus (e.g. “A vink is a type of ropa. Vinks have claws.”). The results of this study provided a tentative outline of the developmental trajectory of NAARR containment and AARR of both containment and hierarchy, which suggested that these repertoires become established and strengthened over the course of development potentially via a process of repeated everyday exposure, reinforcement and feedback. Furthermore, the participants responses remained consistent across the initial relational test and the re-test 2 weeks later, indicating reliability of the measure. The results also indicated that the children’s total relational framing scores and the relational framing subsets (i.e. NAARR containment, AARR containment and AARR hierarchy) were positively correlated with performance on the CCT and class inclusion tests, providing some support for the hypothesis that hierarchical and containment framing form a component of classification responding. Additionally, the results also indicated that performance across all measures of relational framing, as well as total relational framing measured, was positively related to linguistic ability as measured by the PPVT-4, a finding that supports early RFT work that hypothesised that relational framing repertoires may play a part in the expression of language (e.g. Hayes et al., 2001). Finally, the results also indicated that overall relational framing, NAARR containment, AARR containment and AARR hierarchy were all positively related to verbal IQ, non-verbal IQ and overall IQ as measured by the SB5, a similar finding to that of O’Hora et al. (2005, 2008), who indicated that a positive correlation existed between overall IQ and temporal relational framing. Although this study does not provide a comprehensive overview of hierarchical classification (as it omits a number of relations that are likely to be observed within a hierarchical network such as coordination, distinction and comparison), the study provides a foundation for future research for the assessment of hierarchical and containment frames. Furthermore, although AARR hierarchy was assessed across a total of 64 trials that aimed to evaluate mutually entailed and combinatorially entailed (with and without transformation of stimulus functions), the trials were not even across all stimulus sets. For example, in the case of the first trial type of mutual entailment (i.e. “A tol is a type of animal”), there are only two questions that address this relationship (i.e. “Is a tol a type of animal?” and “Is an animal a type of tol?”), meaning that additional aspects of this relationship, such as the derivation of reversed-order relationships and the unidimensional nature of

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belongingness, were not evaluated for this stimulus set. Although these features of hierarchical classification and relational framing more broadly were addressed in subsequent questions across additional sets (e.g. “Are all animals quigs?”; “Does the class of animals contain quigs?”), a more comprehensive framework assessing all aspects of hierarchical classification and AARR hierarchy may be beneficial, particularly in the area of transformation of stimulus function. For example, in the first trial type of transformation of stimulus function of mutually entailed relations (i.e. “A tol is a type of gip. Gips have bones.”), there are only two questions that assess AARR (i.e. “Do all tols have bones?” and “Does the class of tols contain members without bones?”). However, there are a number of additional questions that could have been included within this test to assess the derivation of hierarchy across this stimulus set, such as “Does the class of gips contain members without bones?”, in addition to questions that address the potential ambiguity of hierarchy (e.g. “A tol is a type of gip. Gips have bones.” – “Do tols have scales?” – “It’s not possible to say.”). Furthermore, a more comprehensive AARR hierarchy assessment, although onerous in nature, may also offer an outline of the specific areas in which development of this repertoire may emerge (e.g. does derived reversed-order AARR hierarchy emerge prior to the ability to respond in accordance with the unidirectional dimension of belongingness?). It is clear that further research is required in the area of hierarchical classification and AARR hierarchy; however, our 2017 study provides an early attempt within the field to consider how best to assess this repertoire with a young participant pool. As we explored briefly in Chap. 6, Kirsten and Stewart (2021) examined the role of relational framing repertoires in regard to intellectual potential. In addition to assessing temporal relational frames (at both an arbitrary and non-arbitrary level), the researchers also evaluated non-arbitrary hierarchy, which they conceptualised as non-arbitrary containment and arbitrary hierarchy (as well as NAARR and AARR coordination, opposition, comparison and analogy – an overall incredibly impressive body of work). Twenty-four children between the ages of 3 and 7 participated in the study evaluating relational framing repertoires across four stages (with five substages) and IQ via the SB5. Stage 1 assessed non-arbitrary relations, with the final substage addressing non-arbitrary hierarchy. Using an iPad, participants were presented with images of differently coloured and differently sized boxes (either two boxes for trials assessing mutual entailment or three boxes for trials assessing combinatorial entailment), which depicted the relationship of containment/hierarchy between stimuli (e.g. a red box inside a green box). This was similar to Mulhern et al. (2017), but did not involve the direct manipulation of the stimuli as this was presented on screen. Stage 2 assessed non-arbitrary analogical relations, with the final substage evaluating analogy of hierarchical relations. Within this substage, participants were presented with a sample stimulus displayed at the top-half of the screen of a square inside another larger square with blue dots located in either the innermost or outermost square or outside the squares. The bottom-half of the screen displayed two comparison stimuli, which requires the participant to select the stimulus that corresponds to the sample stimulus. For instance, in Fig. 7.2, which provides an example of a substage of this assessment, a correct response would include the selection of the stimulus on the bottom right of the screen as this is the stimulus

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Fig. 7.2  Example of non-analogical hierarchy trial In the above example, the selection of the comparison stimulus on the right-hand side would constitute a successful execution of non-arbitrary analogy of hierarchical frames as this stimulus corresponds to the sample stimulus above (i.e. both contain dots on the innermost box, with no dots in the outermost box)

that most closely corresponds to the sample stimulus. Stage 3 assessed arbitrary relations, with the final substage evaluating arbitrary hierarchy by presenting the relational networks on a PowerPoint. In this substage, the relational network included coloured circles and the contextual cues inside (presented as the Latin letter I) and contains (presented as the Latin letter C), and was similar to the arbitrary containment stage of Mulhern et al. (2017). The experimenter told the participants that the coloured circles either contained or were inside each other. For instance, the participant saw Blue circle – I (contextual cue symbol) – Green circle, while the experimenter outlined the relationship (i.e. “The blue circle is inside the green circle”) before posing the question that assessed either mutual entailment or combinatorial entailment. Finally, Stage 4 examined arbitrary analogical relations, with the final substage assessing hierarchical relations. This was similar to the non-arbitrary stage, such that the sample stimulus outlined the relationship between stimuli, but this was an arbitrary nature (e.g. Red circle – I – Blue circle) and was displayed at the top half of the screen, while the bottom half of the screen displayed two response options or comparison stimuli, one of which corresponded to the relationship of containment/hierarchy. The results of Kirsten and Stewart (2021) provide a more thorough understanding of the developmental sequence of hierarchical/containment responding at both the arbitrary and non-arbitrary levels. The findings indicated that non-arbitrary hierarchy was the third relational frame to emerge following that of coordination and comparison and was subsequently followed by the emergence of opposition and temporality. The second stage of non-arbitrary analogy indicated that non-arbitrary analogical responding employing hierarchical frames was the second frame to

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emerge, preceded only by coordination. Interestingly, arbitrary hierarchy was the final arbitrary frame to emerge of the relational frames examined despite its early non-arbitrary emergence (which may be because the natural environment does not focus on relations of containment and hierarchy to the same extent as frames of coordination and comparison). Finally, arbitrary analogical responding in accordance with hierarchy was also the final of these frames to emerge. The researchers also found a positive correlation between the children’s performance on: (1) Stage 1 non-arbitrary hierarchy and verbal, non-verbal and overall IQ; (2) Stage 2 non-­ arbitrary analogy in accordance with hierarchy and verbal, non-verbal and overall IQ; (3) Stage 3 arbitrary hierarchy and verbal, non-verbal and overall IQ; (4) Stage 4 arbitrary analogy in accordance with hierarchy and verbal, non-verbal and overall IQ; (5) overall relational score on Stages 1, 2, 3 and 4 and verbal, non-verbal and overall IQ; and (6) overall relational score and verbal, non-verbal and overall IQ. These findings replicate and extend on previous research (e.g. Mulhern et al., 2017; O’Hora et al., 2005, 2008), providing further support for the hypothesis that relational framing repertoires are associated with intellectual potential. Of the non-­ arbitrary repertoires examined, only non-arbitrary hierarchy and comparison were associated with verbal, non-verbal and overall IQ, suggesting the importance of these non-arbitrary repertoires more generally. The assessment tool offered by Kirsten and Stewart (2021) provides a user-friendly method of assessing several relational frames; however, the incorporation of additional contextual cues across each of these substages (e.g. for hierarchy, the incorporation of contextual cues “type of”, “part of” and “belongs” may be a mindful inclusion) in future revisions of the tool may offer additional insight into these repertoires. Nevertheless, the findings of Kirsten and Stewart (2021) provide further rationale for the exploration of training procedures and assessment protocols for these relational repertoires.

 arly Research and a Search for a Model E of Hierarchical Classification Early research examining hierarchical relational repertoires primarily focused on adult populations (e.g. Gil et al., 2012, 2014; Griffee & Dougher, 2002; Slattery et al., 2011; Slattery & Stewart, 2014; Stewart et al., 2018) in an effort to explore and refine RFT understandings of classification repertoires, particularly in relation to transformation of stimulus function. Griffee and Dougher (2002) were among the first researchers to address the issue of hierarchical classification from an RFT and behaviour analytic lens and considered this repertoire to be rooted in hierarchical contextual control. The researchers employed stimuli that shared physical characteristics (i.e. all stimuli employed were triangles) and stimulus functions (including nonsense syllable labels associated with these triangles and response functions) to simulate naturally occurring categories. Contextual control over responding to four similar triangular stimuli (they differed along a continuum of base length) was established with five adult participants with coloured backgrounds signalling different contexts (e.g. green background = superordinate context; red background = intermediate context; yellow

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background = subordinate context) such that these stimuli were then placed in a hierarchical taxonomy. The researchers found that the participants’ differentiated their selection responses dependent on the context (i.e. their responding was brought under contextual control), as the stimuli, which were designated as the top of the hierarchy (i.e. the superordinate context), all evoked one shared response, while stimuli at the lower levels of the hierarchy (i.e. the intermediate and subordinate contexts) evoked different responses. The results of this early experiment demonstrated responding that was analogous to that of hierarchical classification, although in a non-arbitrary context. Although Griffee and Dougher indicated that four of the five participants demonstrated transitivity within their study, it was noted by Slattery et al. (2011) that this study failed to assess transitive class containment, asymmetrical class containment and unilateral property induction, which are features of hierarchical classification traditionally explored by cognitive and mainstream psychology. With that in mind, Slattery et al. (2011) sought to replicate and extend on the work of Griffee and Dougher (2002) by assessing transitive class containment with five adult participants. The first experiment involved a replication of the Griffee and Dougher (2002) protocol but employed stimuli that were physically dissimilar to those employed during training to assess for transitive class containment. Of the five participants included within this study, only two demonstrated responding consistent with transitive class containment, indicating that the model of hierarchical classification by Griffee and Dougher may not have captured the full scope of hierarchical classification and that further revisions may be necessary. In their second experiment, Slattery and colleagues posited that repeated exposure to the protocol may be correlated with transitive class containment and introduced further three participants to their extending training protocol. However, none of the three new participants demonstrated transitive class containment in their responding. A further modification was made to the protocol in their final experiment which involved the replacement of the previous stimuli employed in Experiments 1 and 2 with more arbitrary stimuli. This experiment yielded more promising results with all three new participants demonstrated responding in accordance with transitive class containment. The researchers themselves, however, highlighted three important points for consideration. The first was that although transitive class containment appeared to be present for some participants within the study, the researchers also argued that the pattern of responding that was observed could also be explained by a functionally simpler pattern of behaviour. The second was that it was unclear how the adapted version of the Griffee and Dougher (2002) protocol within their third experiment actually facilitated this apparent transitive class containment, ultimately positing that this inclusion of arbitrary stimuli may have cued a pattern of arbitrary hierarchical relational responding rather than leaving participants to solely focus on non-arbitrary aspects of the stimulus relations. Finally, the experimenters also acknowledged that if transitive class containment had, in fact, been demonstrated within their experiment, their study failed to assess the other dimensions of hierarchical classification (i.e. asymmetrical class containment and unilateral property induction). Slattery et  al. (2011) concluded their study with the recommendation that RFT be considered within future research as a potential framework for hierarchical classification.

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 etting Technical: RFT Explores the Fundamentals G of Hierarchical Classification The first study to model hierarchical responding as hierarchical relational framing was Gil et al. (2012), who examined this relational repertoire with ten participants aged 18–33. Phase 1 involved non-arbitrary relational training to establish arbitrary stimuli as contextual cues for hierarchical (i.e. “includes” and “belongs to”) in addition to coordination (i.e. “same”) and distinction (i.e. “different”) relations using MET. Following this non-arbitrary relational training, participants were then assessed on all four contextual cues. For instance, in a trial assessing the emergence of the contextual cue “includes” the participant is presented with a computer screen that displays a rhombus with two stimuli inside (e.g. a pencil and an umbrella), while other stimuli are displaced external to the rhombus (e.g. radio, trumpet, rose). This depicts the relationship of containment, such that the rhombus contains the stimuli pencil and umbrella. The screen is then replaced with the sample stimulus of the rhombus shortly followed by three comparison stimuli (e.g. umbrella, rose, trumpet) and finally the contextual cue for “includes”. In this scenario, the participant is required to select the stimulus “umbrella” in the presence of the contextual cue “includes” as it relates to the initial display at the beginning of the trial. Within Phase 2, participants were taught three four-member equivalence relations (which were comprised abstract shapes and nonsense syllables) via a one-to-many MTS (i.e., match-to-sample) procedure. For instance, participants were taught to relate the stimulus A1 to the stimuli B1, C1 and D1, respectively. The third phase employed the previously established contextual cues of “includes” and “belongs to” to teach the middle and top level of the hierarchies using stimulus pairing and MTS. Within this phase, some of the stimuli employed within Phase 2 (i.e. those used to establish three four-member equivalence classes) formed the bottom-most level of the hierarchy, while the middle and upper levels of the hierarchy were established using novel arbitrary stimuli. Phase 4 then established specific stimulus properties (or functions – e.g. “sweet” and “cold”) for specific stimuli within the hierarchical network. For instance, in the relational network “X contains X.1, X.1 contains A1 and B1”, the function of “cold” was established for the stimulus X.1. Rather interestingly, from the second phase of the experiment, the stimuli of A1 and B1 had been established in a frame of coordination with the stimuli C1 and D1 and the researchers found that not only did transformation of stimulus function occur with the stimuli A1 and B1 (i.e. the property of “cold” transferred from the stimulus X.1 to these stimuli), but the stimuli C1 and D1 also acquired the function of “cold” (as predicted by the researchers) when assessed for this relational network in the fifth and final stage of the experiment. Gil et  al. (2012) provided a novel approach to the study of hierarchical classification, even including multiple stimulus relations (i.e. hierarchy, coordination and distinction), which closely models that of hierarchical classification encountered in the natural environment. Gil et al. (2014) expanded on their earlier work by demonstrating further patterns of derived hierarchical relations with eight adult participants. This study employed a similar procedure to that

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outlined in their 2012 study; however, the protocol was now modified to use the relational cues “includes” and “belongs to” when establishing inclusion relations between the lower levels of the hierarchy and the middle level of the hierarchy (i.e. a modification to Phase 3). As in the previous study, specific stimuli were established as having specific characteristics or functions (e.g. “cold”, “heavy” and “sweet”) within the fourth phase, while Phase 5 assessed for the transformation of stimulus function using seven stimuli from both hierarchical networks, which had been established as part of the experiment. Of the six participants who reached the final phase of this study, five demonstrated patterns of responding consistent with hierarchical classification. The 2012 and 2014 studies conducted by Gil et al. offer a useful framework for the conceptualisation of a hierarchical network from the viewpoint of RFT and should be considered as a useful starting point for research and applied work seeking to establish these networks in populations that may be deficient in these repertoires. Slattery and Stewart (2014) endeavoured to again consider hierarchical classification from the perspective of RFT across two experiments. The researchers also incorporated the three core features of hierarchical classification as conceptualised by mainstream psychology (i.e. transitive class containment, asymmetrical class containment and unilateral property induction) within their assessment procedures. In the first experiment, four adults were exposed to non-arbitrary training in which arbitrary shapes were established as contextual cues for hierarchical relational responding (i.e. “includes” and “member of”). This phase was similar to Phase 1 of Gil et al. (2012, 2014) but employed a different set of non-arbitrary stimuli within training, including a set of coloured shape stimuli (17 multidimensional shapes in total) that could only be grouped together along specific physical dimensions. This phase was designed to provide the experimenters with sufficient control over patterns of responding consistent with non-arbitrary hierarchy, as the aforementioned multidimensional shape stimuli had been designed to be interrelated along specific physical dimensions, which was hypothesised to encourage participants to respond to these stimuli as formally interrelated classes and subclasses. The careful consideration of the non-arbitrary stimuli employed within this study to facilitate contextual cues of “includes” and “member of” also provides a template for applied work that may seek to facilitate non-arbitrary hierarchical repertoires. Phase 2 employed the arbitrary cues established from Phase 1 to train and assess a hierarchical relational network of three-letter nonsense syllables. Participants were subsequently taught that specific stimuli within these hierarchical networks possessed specific characteristics or functions, similar to the fourth phase of Gil et al. (2012, 2014), but training included the word “HAVE” during function training (and testing), which was hypothesised to function as a cue for a pattern of hierarchical relational responding in adults. Finally, the researchers assessed for transformation of stimulus function, while also assessing for transitive class containment, asymmetrical class containment and unilateral property induction. All four participants demonstrated mutually entailed and combinatorially entailed transformation of function in addition to patterns of responding consistent with transitive class containment, asymmetrical class containment and unilateral property induction. Experiment 2 sought

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to improve on the protocol outlined in the first experiment, specifically in relation to the function training protocol, which employed the word “HAVE” to facilitate the acquisition of transformation of function. Slattery and Stewart (2014) hypothesised that the inclusion of this cue may have been responsible for participant responding in this context, rather than the hierarchical contextual cues previously established in Phase 1. As such, Experiment 2 omitted the word “HAVE” within transformation of function training to provide a better controlled test of transformation of function and also included a simpler set of stimuli that could be classified along the dimension of spots. The findings of the second experiment were similar to the first, demonstrating all characteristics of relational framing repertoires in addition to all three characteristics of hierarchical classification. Technically precise work, such as those provided by Slattery and Stewart (2014), as well as the previous authors outlined within these chapters, provides valuable information regarding the exact mechanisms that may underpin complex repertoires and is a crucial component in furthering our understanding of RFT more broadly. As such, it is highly recommended that although it is tempting to delve into the world of application, the experimental field of RFT has more to offer. In more recent experimental work, Stewart et al. (2017) examined the part–whole dimension of hierarchical classification from the perspective of RFT. The part– whole dimension of hierarchical responding involves treating specific stimuli as parts of larger and more inclusive “wholes” (e.g. a “handle” is categorised part of a “door”, while a “door” is part of a “house”). Ten participants were exposed to Phase 1 of training, which involved non-arbitrary training to establish arbitrary stimuli as contextual cues hierarchical responding (i.e. “part of” and “includes”). Participants were subsequently entered into Phase 2 of the experiment (i.e. AARR training and testing in accordance with hierarchy) and employed the cues established in Phase 1 as contextual cues to train an arbitrary hierarchical relational network across six trigrams. Participants were then assessed for the emergence of derived hierarchical relations (mutual entailment and combinatorial entailment), with a response requirement of 92% or more correct required before moving onto the next stage of training, which involved training stimulus functions. This procedure was similar to the previous protocols for training stimulus function outlined (i.e. Gil et  al., 2012, 2014; Slattery & Stewart, 2014); however, half of the participants (i.e. Group 1) received training that established functions for the stimuli H1.1 and H2.1; these stimuli were selected as their placement within the hierarchical network meant that in the case of both of the trained functions, transformation of function either up or down the hierarchy could be discerned. The remaining participants (i.e. Group 2) received training that established functions for the stimuli H1.1.1 and H2; these stimuli were selected due to their placement within the hierarchical network to determine whether the trained function would transfer up from H1.1.1 or whether it would transfer down from H2. Finally, participants were tested for transformation of stimulus function across a number of patterns based upon experimental hypotheses: (1) downward unidirectional transfer in which the transformation of stimulus functions only moved from stimuli higher up in the hierarchy to the stimuli on the lower levels of the hierarchy; (2) bidirectional transfer in which the transformation of stimulus

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function could be observed from both directions; (3) upward unidirectional transfer in which transformation of stimulus function operated only from lower levels of the hierarchy to the higher levels and (4) an absence of transformation of function in either direction. Of the five participants in Group 1, one participant showed no pattern of transformation of function, one participant showed an inconsistent pattern across the two trained functions (upward transfer for one function and bidirectional transfer for the other), one participant demonstrated unidirectional transfer for both functions while the remaining two participants from this group demonstrated bidirectional transfer for both functions. One participant from Group 2 showed no pattern of transformation of stimulus function, two participants demonstrated unidirectional transfer (with one participant demonstrating downward transformation of function and the other evidencing upward transfer), while the remaining two participants demonstrated bidirectional transformation, ultimately demonstrating a similar pattern of results to that of Group 1. The results generated from this study indicates the need for further experimental research within this realm to identify the active components of arbitrary hierarchy training and assessment and potentially provide a framework for the accurate prediction of responses.

Training Deficient Repertoires of Hierarchy and Containment The previously outlined experimental work has provided the basis for more applied work, which aims to incorporate the findings of this research into applied curriculums. For example, Ming et al. (2018) examined the viability of an RFT approach to facilitating class inclusion responding with children without a known diagnosis and with autistic children. Class inclusion involves the ability to categorise stimuli into two or more categories simultaneously. For instance, if presented with two apples and five oranges, we may conceptualise these items as simultaneously belonging to the categories of apples and oranges, respectively, as well as belonging to the overarching category of fruit. This ability then impacts performance on subsequent questions, such as “Are there more oranges or fruit?”, with correct responses indicating “There are more fruit than oranges”. Previous research had indicated that this repertoire was related to containment and hierarchy repertoires (Mulhern et al., 2017), which formed the basis of this study. Three children without a diagnosis of autism (aged 3–4) and three autistic children (aged 8–19) served as participants within the context of two separate non-concurrent multiple baseline designs. Participants were first screened for pre-requisite behavioural repertoires before entering the experimental phase. These pre-requisite repertoires included: (1) the capacity to tact all stimuli, (2) tact their corresponding category, (3) identify the stimuli using yes/no responses, (4) tact quantities and (5) the capacity to perform non-arbitrary comparison. The stimuli included coloured flashcards (5.5 cm × 5.5 cm) of items from four different categories (i.e. animals, fruit, clothing and vehicles), with six exemplars per category (e.g. cat, horse, pig, sheep, cow and dog for the category of animals) and clear plastic containers (one large and two

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smaller containers) to represent the containment relationship between stimuli. These clear plastic containers were labelled using whiteboard markers with the larger plastic container serving as the “category box” and the smaller plastic containers for the exemplars (e.g. the “dog box” or the “cat box”). The stimuli used for each trial, along with the class inclusion trial types were randomised at the beginning of each trial. Trial types of class inclusion included: (1) More [category] or more [smaller subclass]; (2) More [category] or more [larger subclass]; (3) Less [category] or less [smaller subclass]; (4) Less [category] or less [larger subclass]; (5) More [smaller subclass] or more [category]; (6) More [larger subclass] or more [category]; (7) Less [smaller subclass] or less [category]; and (8) Less [larger subclass] or less [category]. These were designed in an effort to promote flexible and reversed-order responding, of course, it could be argued that the trial types 1, 3, 5 and 7 do not entirely assess class inclusion responding (with responses instead potentially being based on non-arbitrary comparison between both sub-categories – a correct response may in fact not be a correct class inclusion response), but were included to have equal more and less trials evaluating the larger and smaller subclass. These trials were also interspersed with trials concerned with non-arbitrary comparison between the subclasses (e.g. “Are there more dogs or more cats?”). Baseline testing involved assessing class inclusion responding across all four categories. Training employed MET of only the animal category and nested boxes to highlight the saliency of the containment relationship between stimuli (i.e. non-arbitrary containment was employed to facilitate more arbitrary containment/hierarchical responding), with training conducted across two phases. Phase 1 involved pre-trial prompting in which the experimenter described the larger box as the category box and then required the participant to tact the category of the flashcard stimuli (i.e. animals). For each trial, the participant was told that the specific stimuli used within that trial (e.g. five dogs, four sheep) were all animals (e.g. “Dogs and sheep are both animals”), belonged to the animal category and went inside the animal category box, with the words “inside” and “belongs” acting as contextual cues. The participant was then required to place the flashcards in two smaller boxes (i.e. the five dogs into one box and four sheep into the other box) and place these inside the larger category box. Participants were then asked to identify the box containing the stimulus type for the trial (e.g. if the trial type focused on the larger subclass, the participant was asked to identify the dog box) and the category box. Any errors at this phase in training were corrected by gesture prompts and a representation of the trial to provide participants with an opportunity to answer independently. The experimenter then presented the trial question (e.g. “Are there more dogs or more animals?”) while lifting up each of the boxes. Correct responses were reinforced by specific praise, while incorrect responses were met with the error correction procedure that involved repeating the requirement to select the stimulus type boxes (i.e. the smaller or larger subclass) and the category box and providing corrective feedback detailing the relation between the stimuli and the category while lifting the relevant boxes (e.g. “dogs and sheep are types are all types of animals, so they all go inside the big animal box. They all belong to the animal category, but only these are

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dogs, so there are more animals in the big animal category box than there are dogs in the dog box.”). The trial type was then repeated but used a new combination of stimuli (e.g. two horses and six cows) until the participant responded correctly on the first trial with new stimuli. The second phase of training aimed to reduce prompting and omitted the pretrial requirement to select the relevant boxes, with further modifications made to verbal feedback provided that eliminated reference to the size of the boxes (i.e. it was no longer referred to as “the big” category box) and omission of the description that subclass boxes “go inside” the category box. Following the completion of Phases 1 and 2, participants were then assessed for generalisation of class inclusion responding, with a return to baseline conditions (i.e. the boxes were no longer employed to demonstrate the containment relationship between stimuli) for the trained stimulus set and then for the remaining category types. In the case of children without a diagnosis, response maintenance was assessed 1 month following the cessation of training, while autistic children were assessed for maintenance 6–8  weeks following training. Both groups of children demonstrated acquisition of class inclusion responding and generalisation of responding to novel stimuli. However, one participant in the autistic group (named A3) required one further exposure to Phase 2 training before full generalisation of responding was observed. Furthermore, maintenance of performance was observed for all three children without a diagnosis 1 month following training. Two of the autistic participants also demonstrated maintenance of performance 6  weeks following the cessation of training; however, one participant (named A2) returned to a baseline level of responding 8  weeks following training and was subsequently returned to one further session of Phase 2 training. This resulted in the successful generalisation of class inclusion responding and also in the maintenance of responding at 6 weeks (although a slight dip in performance was observed at 2 weeks following the termination of training). Given the slight difficulties demonstrated by the autistic participants in acquiring this repertoire, it was hypothesised that a further revision to the protocol was necessary to streamline performance. As two autistic participants required further exposure to Phase 2 of the training procedure to demonstrate generalised and maintained class inclusion responding, it was theorised that Phase 2 alone may function as the active component in training. The class inclusion protocol was further refined by Zagrabska-Swiatkowska et al. (2020), who employed a concurrent multiple baseline design across participants to assess efficacy of the adjusted training protocol in training class inclusion responding with three autistic adults (aged 23–26). The stimulus sets, training stimuli and trial types were identical to those of Ming et al. (2018) and participants were screened using the same pre-screening criteria of the previous study. Participants were also assessed using the PPVT-4 to verify that their language age equivalent was greater than 3  years as it was hypothesised that a minimum of 3  years may facilitate acquisition of responding (a decision that was made due to the success of 3- and 4-year-old children with the class inclusion protocol of Ming et al.). Baseline conditions were identical to that of Ming et al. (2018) and assessed class inclusion responding across all four categories and included interspersal trials. Modifications were made to the training component and was reduced to a single phase of training

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that employed the animal stimulus set but continued to highlight the saliency of the containment relationship between the subclass stimuli and the overarching category and were similar to that of Phase 2 of the previous study. Participants were first asked to select the stimulus quantity card, which outlined the number of stimuli and specific subclasses employed within the trial and was then displayed on the tabletop by the experimenter. The experimenter then selected the trial type card (again, these were identical to those of Ming et al., 2018) and outlined to the participant that the stimuli within that trial (e.g. five pigs and two cats) were all animals (e.g. “Pigs and cats are both animals”), belonged to the animal category and went inside the animal category box. Participants were then asked to place the flashcards into the two smaller boxes and place the smaller boxes inside the larger box. The requirement to identify the subclass box and category box was eliminated from training. The class inclusion trial was then presented in which the experimenter provided the question while manipulating the boxes to increase the saliency of the containment relationship. Contingent feedback was provided for correct responses while again manipulating the relevant stimuli. Corrective feedback statements were provided following incorrect responses that were identical to that of Phase 2 in Ming et al. (2018). The major modification that was made to the training procedure was in the mastery criterion – which required participants to provide 100% correct responses across two consecutive sessions. This modification to the mastery criterion was made as Ming et al. (2018) found that only one additional exposure to Phase 2 training resulted in generalised and maintained responding. Upon successful completion of training, participants were then assessed for generalisation of class inclusion responding without the non-arbitrary element of training for the trained stimulus set (i.e. animals) and untrained categories. Generalisation of class inclusion responding was observed for all three participants with all participants demonstrating maintenance of gains 2  weeks following the cessation of training. Ultimately, the researchers were successful in providing a more streamlined and refined training protocol that is amenable to applied practitioners with limited resources (e.g. the training protocol and assessment procedures did not require the need for additional technologies). The study suggests the potential utility in employing non-arbitrary repertoires to facilitate more complex arbitrary repertoires among diverse populations and is one of the few RFT studies that addresses responding with neurodivergent populations. The final study, which we will explore, that sought to facilitate arbitrary containment and hierarchical responding was conducted by Mulhern et  al. (2018), with Experiment 1 assessing and training AARR containment repertoires and Experiment 2 addressing AARR hierarchy repertoires. Both experiments employed a combined multiple baseline design (i.e. it was a multiple baseline across three participants and a multiple baseline across four relational characteristics – mutual entailment, transformation of function of mutual entailment, combinatorial entailment and transformation of function of combinatorial entailment). This combined multiple baseline design was employed to enhance experimental control, replicate experimental effects and more accurately determine the impact of training on the relational repertoires in question. This was the first published study to employ a combined single subject research design of this nature. Within this design, all experimental participants were exposed to baseline sessions until a stable level of responding was

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observed. Following this, the first participant entered Phase 1 of training, while the remaining participants remained in baseline conditions. During each phase of training the remaining untrained relational components were probed during experimental sessions. The two remaining participants were exposed to baseline sessions until the first participant had completed the first phase of training. The second participant was then exposed to training once they had demonstrated stable rates of responding. After that, the second participant had completed the first phase of training and also demonstrated stable responding, and the final participant entered the training phase. Within Experiment 1, three children (aged 5–6) served as experimental participants, while three additional children (also aged 5–6) served as control participants. Participants were screened for NAARR containment repertoires in a procedure similar to that of Mulhern et al. (2017); however, this protocol also included transformation of stimulus function of mutually entailed and combinatorially entailed relations (e.g. “The [A] box is inside the [B] box. Brian likes the [A] box, and Sarah likes the [B] box.” – “Is there a box that Brian likes inside box [B]?” – “Yes”) and required a performance of 80% or higher to be included within the study. Participants were also assessed for AARR containment repertoires across four arbitrary stimulus sets (nonsense words – e.g. blorg, grap and plak) presented via PowerPoint (a performance of 60% or lower was necessary for participation eligibility). Mutual entailment and combinatorial entailment trial types were like those employed within Mulhern et al. (2017); however, instead of employing identically sized and differently coloured circles, the experimenters instead employed nonsense syllables displayed on a laptop screen. A further modification from the assessment protocols of the 2017 study included the assessment of transformation of function in accordance with mutually entailed and combinatorially entailed relations. Participants were also assessed for categorisation ability using the CCT, linguistic ability using the PPVT-4 and class inclusion reasoning. Following these assessments, all three experimental participants entered the baseline phase of the experiment. Training was conducted across four phases: (1) mutual entailment, (2) transformation of function of mutually entailed relations, (3) combinatorial entailment and (4) transformation of function of combinatorially entailed relations. Within each phase of training, the trials were presented as they were in baseline; however, participant responses were met with positive reinforcement, specific praise and a token (four tokens were exchanged for a sticker) in the case of correct answers. In the case of incorrect responses, participants were provided with corrective feedback (e.g. “That’s not it. A doesn’t contain B, because B contains A.”) and the trial was represented until a correct response was given. Furthermore, participants were told at the beginning of each session that meeting the goal of that session would result in an additional prize (e.g. rubbers, pencils and markers which the participants could self-select from a box). The goal for the first training session of each training phase was 50% or more correct, while the subsequent goal for each training session was for the participant to beat their score from the previous session by at least one more correct response (participants were informed of the score that they had to reach before beginning each session). Participants were deemed to have successfully completed a training phase if they achieved a score of 100% correct within one session, or 90% or more across two consecutive sessions. All three

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participants successfully completed the four phases of training and also demonstrated generalisation of responding with untrained stimulus sets, in addition to maintenance of responding assessed at 5 weeks after training. Six months after their initial assessment (this gap in time between testing was selected to decrease the possibility of practice effects), Experimental and Control participants were reassessed for their verbal ability using the PPVT-4, categorisation ability using the CCT and class inclusion responding and the raw scores of both groups were compared. The results indicated that while both the Experimental Group and the Control Group demonstrated gains in responding in each of the areas assessed, the average gains made by the Experimental Group were greater than those of the Control Group, but ­ultimately neither group demonstrated improvements in standardised scores or percentiles across these measures, meaning that these gains were not clinically significant. Experiment 2 aimed to facilitate arbitrary hierarchical relational responding among three children (aged 6–7) with a further three children serving as control participants. All participants were assessed for class inclusion responding, classification ability using the CCT, verbal ability using the PPVT-4 and arbitrary hierarchical responding across four arbitrary stimulus sets. Arbitrary hierarchy was assessed by presenting nonsense syllables as textual stimuli on a laptop screen using PowerPoint and all participants were assessed for mutual entailment, transformation of function of mutual entailment, combinatorial entailment and transformation of function of combinatorially entailed relations. The experimental design was identical to that of Experiment 1, and following baseline, each participant progressed through the four phases of training that were identical to that of Experiment 2 (with the exception of the contextual cues involved – i.e. “type of”). All participants successfully completed training, demonstrated generalisation of AARR hierarchical responding and maintained their training gains at five-week follow-up. Six months after the initial assessment, both the Experimental Group and the Control Group were reassessed using the CCT, PPVT-4 and for class inclusion responses. A similar pattern was observed within this experiment as that of Experiment 1, namely that both groups evidenced gains across all three measures, with the Experimental Group demonstrating a greater increase in gains than that of the Control Group (however, these gains were again not clinically significant). Although this study presents a successful example of the assessment and training of hierarchy, there is an undoubted need for refinement of the assessment protocol. For instance, for trials assessing and training transformation of function, the question “Does the class [A] contain members without [Property B]?” requires the response of “no” to constitute a correct response; however, it is possible that the word “without” may itself be a contextual cue for this response as it is not present in any other trials (i.e. there are no trials in which questions using the words “without” are met with a correct “yes” response). Furthermore, there is a disproportionate number of “yes” responses for transformation of function within this assessment, which may have resulted in inflated scores that may not truly reflect AARR hierarchy. Nevertheless, such a study indicates the feasibility of employing an RFT framework to assess and teach such repertoires.

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 eaching and Training Containment T and Hierarchical Repertoires Given the findings of previous research (e.g. Kirsten & Stewart, 2021; Ming et al., 2018; Mulhern et al., 2017, 2018; Zagrabska-Swiatkowska et al., 2020), it is likely that hierarchical responding is rooted in early NAARR containment relationships. Taking the findings of Ming et al. (2018) and Zagrabska-Swiatkowska et al. (2020) into account, an appropriate approach to the facilitation of non-arbitrary containment may be to use materials such as boxes or baskets to highlight the salience of the containment relations. For instance, when teaching non-arbitrary mutual entailment of containment, the teacher may place an apple inside a clear plastic container while vocally outlining the relationship between stimuli (e.g. “the apple is inside the box”). This relation could be bidirectionally trained by placing an object on a flat surface and placing a clear cup or box over the object while outlining the relationship of containment. Over time, the salience of these objects could be decreased (e.g. move from clear plastic containers to opaque containers) to facilitate a move towards more arbitrary repertoires. As always, MET is recommended to facilitate this repertoire. Combinatorial entailment could be achieved in a similar fashion (as per Ming et al., 2018 and Zagrabska-Swiatkowska et al., 2020) by employing nesting boxes. For instance, in the assessment protocol outlined by Mulhern et  al. (2017), one large box (e.g. red) could contain a further medium box (e.g. blue) containing a smaller box (e.g. yellow) and the instructor could demonstrate the relationship between these stimuli via physical manipulation (e.g. lifting and placing the boxes) while describing the relationship between them (e.g. “the yellow box is inside the blue box and the blue box is inside the red box”). Transformation of stimulus function could then be assessed and trained across both mutual entailment and combinatorial entailment by incorporating appetitive stimuli within the relations. For instance, a box could contain a preferred toy (and a non-preferred toy to avoid automatic responding) and questions assessing the transformation of function could be directed around this (e.g. “Is there something inside this box that you like?”; “Does the box contain something you can play with?”). The relationship of containment does not have to be confined to boxes alone and could be used with additional stimuli such as bags, purses, envelopes and in the scenario of transformation of function, a Jack-in-the-box may be an interesting stimulus to employ (dependent on the interests of the learner of course). AARR containment and AARR hierarchy bear some amount of overlap as both employ the same contextual cues (i.e. contains), but hierarchy is arguably somewhat more complex than that of containment in the contextual cues that it employs (e.g. “type of”, “part of”). The study outlined by Mulhern et al. (2018) provides a viable training and assessment protocol for arbitrary containment repertoires and could be employed to facilitate this repertoire. Of course, nonsense syllables are not necessary to employ as stimuli within this context – any arbitrary stimulus will suffice (e.g. identically sized and differently coloured circles and triangles were used by Mulhern et al., 2017), and a number of different stimuli should be employed within

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MET and bidirectional training. The work of Ming et  al. (2018) and Zagrabska-­ Swiatkowska et al. (2020) also indicates the utility of employing non-arbitrary repertoires to establish arbitrary repertoires, as such an additionally viable approach may be to include stimuli that are physically seen as operating in a relationship of containment and gradually altering this relationship to decrease the salience of this physical relationship, therefore shifting responding from the non-arbitrary to the arbitrary for both mutually entailed and combinatorially entailed relations. Transformation of function could also be assessed and trained in a similar manner to that of Mulhern et al. (2018); however, it is advised that additional functions are explored when teaching this to promote relational flexibility. Arbitrary hierarchy is arguably a more difficult relation to wholly capture and undoubtedly requires additional attention within research. However, the previously discussed research also provides a useful framework for assessing and training arbitrary hierarchy for mutual entailment and combinatorial entailment (e.g. employing nonsense syllables as stimuli, emphasising the contextual cues involved and providing corrective feedback and reinforcement; Mulhern et al., 2018) and is one that should be considered within the formulation of potential curriculums and assessments. Assessments should also consider the part–whole nature of hierarchy (e.g. Stewart et al., 2017) and the unidirectional dimension of belongingness (e.g. “all dogs are animals, but not all animals are dogs”) of this frame within all areas of training. As such, although the trial types employed for mutual entailment and combinatorial entailment posed by Mulhern et al. (2018) offer a useful framework for assessment and training, these are by no means exhaustive and require additional refinement to more accurately capture the complexities of arbitrary hierarchy. Transformation of stimulus function is a more complex aspect of this frame to consider (particularly when considering the unidirectional transfer of function); however, previous studies such as that of Slattery and Stewart (2014), Stewart et al. (2017) and Gil et al. (2012, 2014) may offer a more appropriate framework upon which to assess and train transformation of function across a hierarchical relational network. For more applied and educational programmes, applying AARR hierarchy to taxonomies such as the animal kingdom and the periodic table of elements may be a functional and useful avenue for assessing and establishing transformation of function. Training and assessment could begin with familiar stimuli such as cats and dogs, which belong to the category of animals. For example, a learner may be told that “A Bengal is a type of cat and a cat is a type of animal. All animals have blood, cats meow and Bengals are sweet and loving”. Mutually entailed transformation of stimulus function could be assessed by asking the learner questions such as: “Does the category of animals contain creatures that meow?”, “Do cats have blood?”, “Do Bengals meow?” and “Does the category of cats contain creatures that are sweet and loving?” The unidirectional transfer of function could also be trained and assessed with questions such as “Do all animals meow?” and “Are all cats sweet and loving?”, with further questions considering the part–whole dynamic of hierarchy, such as “Do some animals meow?” and “Are some cats sweet and loving?”. Similarly,

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combinatorially entailed transformation of stimulus function questions would address derived relations (e.g. “Do Bengals have blood?”), reversed-order relations (e.g. “Does the category of animals contain creatures that are sweet and loving?”), unidirectional transfer of function (e.g. “Are all animals sweet and loving?”) and part–whole hierarchy (e.g. “Are some animals sweet and loving?”). The stimuli employed within training and assessment could become more abstract over time to include unfamiliar creatures (or even imaginary creatures), with MET being an essential component to the acquisition of these repertoires.

The Future of Hierarchy and Containment Although considerable research has been conducted in the field of RFT and classification, there is still opportunity for further research and exploration. For instance, the earlier work of Slattery and Stewart (2014), which sought to isolate the cues responsible for transformation of stimulus function within a hierarchical network, has advanced our understanding of this relationship and the cues that may facilitate, or indeed hamper, these repertoires. However, more research is necessary to examine this further as there is a possibility (e.g. in the case of Mulhern et al., 2018) that the use of certain words (such as “without”) within the questioning phase may have cued specific responses rather than the outlined hierarchical relation itself, indicating a need for further revisions of such protocols. The exact nature of the transfer of function within hierarchy is also complex, as revealed by the results of Stewart et al. (2018), who indicated that participants trained on the same hierarchical network emitted dissimilar patterns of responding when assessed on transformation of function, indicating the need to further isolate the variables that impact responding. Research has also demonstrated the feasibility and the viability of utilising RFT framework to assess and train hierarchical responding among children and autistic populations, with the data from Mulhern et  al. (2018) also indicating a potential impact of training on measures of categorisation and language. Further research is necessary to determine the far-reaching impact of training outside of the isolated arbitrary repertoires of interest. For instance, what impact might AARR hierarchy and containment training have on academic tests and standardised measures when tested on a larger and more comprehensive scale? It would be interesting, for example, to include frames of hierarchy and containment within the SMART protocol and examine the impact of training on IQ as with Cassidy et  al. (2011, 2016). Although great advances have been made in the area of RFT to further understand how best to train and assess hierarchy and containment, there are still many opportunities for further growth and progress in the field.

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TLDR Cheat Sheet Class inclusion: Class inclusion was proposed by Piaget as a measure of a hierarchical classification within the concrete operational developmental period and refers to the capacity to classify and conceptualise a stimulus as simultaneously being part of one general category and a member of two specific categories. For instance, a dress belongs to the general category of clothing and a pair of trousers also belongs to the category of clothing, if presented with five dresses and three pairs of trousers and asked “Is there more dresses, or is there more clothes?”, a correct class inclusion response would be to state that there are more clothes, as both trousers and dresses (although each in their own distinct category) belong to the more general category of clothing. Superordinate: A label used to represent a broad category of stimuli within a hierarchical system of classification such as food, animals and clothing. Intermediate: A label used to categorise stimuli into more specific classes dependent on the context. For instance, an intermediate class within the larger superordinate category of food might include bread, while an intermediate class within the superordinate category of animals might include dog. This may be considered as a basic level of categorisation. Subordinate: This is a further category contained within the intermediate and superordinate classes and further specifies the stimuli within this category. For example, a subordinate class within the intermediate class of bread may include soda bread, while a subordinate class within the intermediate class of dog may include Chihuahua. Transitive class This refers to a pattern of responding such that if taught that stimulus A is a containment: type of stimulus B and is taught that stimulus B is a type of stimulus C, then an individual should respond to stimulus A as a member of stimulus C – a phenomenon that is almost analogous to combinatorial entailment, but entirely specific to hierarchy. Asymmetrical This refers to the phenomenon of the unidirectional dimension of class belongingness. For instance, if informed that class A is a type of class B, we containment: may derive that class A is a type of class B, but we cannot (and should not) derive that class B is a type of class A, as this is a relationship that operates in one direction only. Unilateral This is the final property of hierarchical classification that outlines that the property property of a superordinate class (e.g. animals) will transfer properties to a induction: lower class (e.g. intermediate or subordinate class; dogs and beagles), but that the properties of these lower classes do not necessarily transfer in a bottom-up direction. Again, this is similar to the unidirectional dimension of belongingness as applied to transformation of stimulus function. For example, if we know that the larger stimulus class of animals have the property of blood, we may derive that all members of this class have blood (including dogs and beagles); however, we may not derive that because the subordinate class of beagles barks, that this property of barking transfers to higher order classes such as animals more generally. Non-concurrent This is an experimental design which is related to the multiple baseline design multiple previously explored in Chap. 5. Unlike the traditional concurrent multiple baseline design: baseline design, which involves the observation and assessment of individuals across the same time points, the non-concurrent multiple baseline design involves the observation of different individuals at different times, such that participant 1 may be in baseline conditions in may, participant 2 may be in baseline in July and participant 3 may be in baseline in august.

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References Astley, S. L., Peissig, J. J., & Wassermann, E. A. (2001). Superordinate categorization via learned stimulus equivalence: Quantity of reinforcement, hedonic value and nature of the mediator. Journal of Experimental Psychology: Animal Behavior Processes, 27(3), 252–268. http://psycnet.apa.org/doi/10.1037/0097-­7403.27.3.252 Blewitt, P. (1994). Understanding categorical hierarchies: The earliest levels of skill. Child Development, 65, 1279–1298. https://doi.org/10.1111/j.1467-­8624.1994.tb00817.x Bock, M. A. (1994). Acquisition, maintenance, and generalization of a categorization strategy by children with autism. Journal of Autism and Developmental Disorders, 24(1), 39–51. https:// doi.org/10.1007/BF02172211 Bock, M. A. (1999). Sorting laundry: Categorization strategy application to an authentic learning activity by children with autism. Focus on Autism and Other Developmental Disabilities, 14(4), 220–230. https://doi.org/10.1177/108835769901400404 Boll, T. (1993). Children’s category test. Psychological Corporation. Bornstein, M.  H., & Mash, C. (2010). Experience-based and on-line categorization of objects in early infancy. Child Development, 81(3), 994–897. https://doi. org/10.1111/j.1467-­8624.2010.01440.x Bott, L., Brock, J., Brockdorff, N., Boucher, J., & Lamberts, K. (2006). Perceptual similarity in autism. The Quarterly Journal of Experimental Psychology, 59(7), 1237–1254. https://doi. org/10.1080/02724980543000196 Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61, 173–198. https://doi. org/10.1007/BF03395755 Cassidy, S., Roche, B., Colbert, D., Stewart, I., & Grey, I. (2016). A relational frame skills training intervention to increase general intelligence and scholastic aptitude. Learning and Individual Differences, 47, 222–235. https://doi.org/10.1016/j.lindif.2016.03.001 Deneault, J., & Ricard, M. (2006). The assessment of children’s understanding of inclusion relations: Transitivity, asymmetry, and quantification. Journal of Cognition and Development, 7(4), 551–570. https://doi.org/10.1207/s15327647jcd0704_6 Dixon, M. R., & Stanley, C. R. (2020). Relational frame theory: Basic operants. In M. Fryling, R. A. Rehfeldt, J. Tarbox, & L. J. Hayes (Eds.), Applied behavior analysis of language and cognition: Core concepts and principles for practitioners (pp. 174–197). Context Press. Dunn, L. M., & Dunn, D. M. (2007). Peabody picture vocabulary test, fourth edition (PPVT-4). Pearson. Freedman, D. J., & Assad, J. A. (2006). Experience-dependent representation of visual categories in parietal cortex. Nature, 443(7107), 85–88. https://doi.org/10.1038/nature05078 Furrer, S.  D., & Younger, B.  A. (2008). The impact of specific prior experiences on infants’ extension of animal properties. Developmental Science, 11(5), 712–721. https://doi. org/10.1111/j.1467-­7687.2008.00721.x Gil, E., Luciano, C., Ruiz, F. J., & Valdivia-Salas, S. (2012). A preliminary demonstration of transformation of functions through hierarchical relations. International Journal of Psychology and Psychological Therapy, 12(1), 1–19. Gil, E., Luciano, C., Ruiz, F. J., & Valdivia-Salas, S. (2014). Toward a functional analysis of hierarchical classification: A further experimental step. International Journal of Psychology and Psychological Therapy, 14(2), 137–153. Greene, T. R. (1994). What kindergartners know about class containment hierarchies. Journal of Experimental Child Psychology, 57, 72–88. https://doi.org/10.1006/jecp.1994.1004 Griffee, K., & Dougher, M. J. (2002). Contextual control of stimulus generalization and stimulus equivalence in hierarchical categorization. Journal of the Experimental Analysis of Behavior, 78(3), 433–447. https://doi.org/10.1901/jeab.2002.78-­433 Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer Academic Publishers.

176

7  The Relational Frames of Containment and Hierarchy

Inhelder, B., & Piaget, J. (1964). The early growth of logic in the child. Norton. Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record, 72, 221. https://doi.org/10.1007/s40732-­021-­00457-­y Lakoff, G. (1987). Women, fire and dangerous things: What categories reveal about the mind. University of Chicago Press. Markman, E. M. (1989). Categorization and naming in children: Problems in induction. MIT Press. McLoughlin, S., Tyndall, I., Mulhern, T., & Ashcroft, S. (2019). Technical notation as a tool for basic research in relational frame theory. The Psychological Record, 69(3), 437–444. https:// doi.org/10.1007/s40732-­019-­00344-­7 Ming, S., Mulhern, T., Stewart, I., Moran, L., & Bynum, K. (2018). Training class inclusion responding in typically developing children and individuals with autism. Journal of Applied Behavior Analysis, 51(1), 53–60. https://doi.org/10.1002/jaba.429 Mulhern, T., Stewart, I., & McElwee, J. (2017). Investigating relational framing of categorization in young children. The Psychological Record, 67(4), 519–536. https://doi.org/10.1007/ s40732-­017-­0255-­y Mulhern, T., Stewart, I., & McElwee, J. (2018). Facilitating relational framing of classification in young children. Journal of Contextual Behavioral Science, 8, 55–68. https://doi.org/10.1016/j. jcbs.2018.04.001 O’Hora, D., Peláez, M., & Barnes-Holmes, D. (2005). Derived relational responding and performance on verbal subtests of the WAIS-III. The Psychological Record, 55, 155–175. https://doi. org/10.1007/BF03395504 O’Hora, D., Peláez, M., Barnes-Holmes, D., Rae, G., Robinson, K., & Chaudhary, T. (2008). Temporal relations and intelligence: Correlating relational performance with performance on the WAIS-III. The Psychological Record, 58(4), 569–584. https://doi.org/10.1007/BF03395638 Proffitt, J. B., Coley, J. D., & Medin, D. L. (2000). Expertise and category-based induction. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(4), 811–828. https://doi. org/10.10371/0278-­7393.26.4.811 Roid, G. H. (2003). Stanford-Binet intelligence scales (5th ed.). Riverside Publishing. Slattery, B., & Stewart, I. (2014). Hierarchical classification as relational framing. Journal of the Experimental Analysis of Behavior, 101(1), 61–75. https://doi.org/10.1002/jeab.63 Slattery, B., Stewart, I., & O’Hora, D. (2011). Testing for transitive class containment as a feature of hierarchical classification. Journal of the Experimental Analysis of Behavior, 96(2), 243–260. https://doi.org/10.1901/jeab.2011.96-­243 Stewart, I., Slattery, B., Chambers, M., & Dymond, S. (2017). An empirical investigation of part-­ whole hierarchical relations. European Journal of Behavior Analysis, 19(1), 105–124. https:// doi.org/10.1080/15021149.2017.1416525 Stewart, I., Slattery, B., Chambers, M., & Dymond, S. (2018). An empirical investigation of partwhole hierarchical relations. European Journal of Behavior Analysis, 19(1), 105–124. https:// doi.org/10.1080/15021149.2017.1416525 Zagrabska-Swiatkowska, P., Mulhern, T., Ming, S., Stewart, I., & McElwee, J. (2020). Training class inclusion responding in individuals with autism: Further investigation. Journal of Applied Behavior Analysis, 53(4), 2067–2080. https://doi.org/10.1002/jaba.712 Zentall, T. R., Galizio, M., & Critchfield, T. S. (2002). Categorization, concept learning and behavior analysis: An introduction. Journal of the Experimental Analysis of Behavior, 78, 237–248. https://doi.org/10.1901/jeab.2002.78-­237

Chapter 8

Analogy: Relating Relations Elle Kirsten and Ian Stewart

Analogies are ubiquitous in daily language and cognition and lie at the core of intelligence and creativity (Gentner, 1983; Hofstadter, 2001; Holyoak et al., 2001; Holyoak & Thagard, 1995; Oppenheimer, 1956; Sternberg, 1977). Analogy is central to learning in both children and adults; teachers often recruit analogies to help teach unfamiliar concepts, for example, when introducing atomic structure by explaining that, “the atom is like a tiny solar system” (Alexander et al., 1989; Goswami, 1996; Morsanyi & Holyoak, 2010; Polya, 1945/2004; Richland & Simms, 2015; Stewart et al., 2020). Analogy is a key component of higher order language and cognition, including scientific and mathematical skills as well as problem-solving more generally, and it is commonly used as a metric of intellectual potential and as a measure to predict academic success, for example, the Law School Admissions Test (LSAT; see Lapiàna, 2004) (Goswami & Brown, 1989; Polya, 1945/2004; Sternberg, 1977). Reasoning by analogy is considered a critical skill for further knowledge acquisition and language generativity (Goswami, 1996; Matos & Passos, 2010). Furthermore, through analogy, we can construct convincing legal arguments based on set precedents, or convey complicated emotions through poetry and prose (Spellman & Schauer, 2005). For example, a literal explanation of a subject’s personal qualities such as kindness, charm and beauty would not evoke the same emotive behaviour as Shakespeare does when he writes: “Shall I compare thee to a summer’s day?” (Sonnet 18; Dancygier & Sweetser, 2014). “Emotional experiences are notoriously difficult or impossible to convey by literal language; but by connecting the relational pattern of a novel experience with that of a familiar, emotion-­laden one, analogy provides a way of recreating a complex pattern of feelings” (Holyoak et al., 2001, p. 5). Indeed, cultural records provide prolific examples of analogy in literature, religion and philosophy. E. Kirsten (*) Compassionate Behavior Analysis, PLLC, New York, NY, USA e-mail: [email protected] I. Stewart The National University of Ireland, Galway, Ireland © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_8

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What Is Analogy? The term analogy is borrowed from the Greek word analogia, a term used by Greek mathematicians to denote a similarity in proportional relationships (Hesse, 1965; Stewart & Barnes-Holmes, 2001). Aristotle first studied proportional analogies as a form of logical reasoning, as demonstrated by his classic syllogism, “All men are mortal; Socrates is a man; ergo, Socrates is mortal” (Hofstadter & Sander, 2013, p. 17). Aristotle’s classical four-term analogical structure A:B::C:D (read A is to B is the same as C is to D) depicts this equality of proportion. Mathematical in their precision, these proportional analogies are often included in intelligence tests but arguably do not include the more enlightening analogies inspiring scientific discoveries (e.g. penicillin), or facilitating complex concept explanation (e.g. atomic structure via a planet and sun analogue), or influencing creative design, poetry, humour, empathy, political debate and so forth (Holyoak, 2005; Holyoak et  al., 2001). Instead, analogies of attribution were another form of analogy identified by the Greeks in which the similarity of function between two analogues was inferred by a common property attributed in some way to each term (Stewart et  al., 2001). Essentially, terms are analogous if they have properties in common or when there is a similarity in relation (Hesse, 1965). Within the field of psychology itself, there is little agreement on reasoning by analogy between subdisciplines. This should come as no surprise considering the fundamental lack of unity in psychology wherein each subdiscipline offers its own theories and data analyses with limited generalisation of principles between theoretical approaches (Chiesa, 1994). Regarding analogy, the cognitive sciences have long been interested in analogy, particularly its development in young children. More recently, behaviour psychology, specifically Relational Frame Theory (RFT), has provided a functional analytic definition of analogy, and the development of analogy in young children has been investigated (Barnes et  al., 1997; Carpentier et al., 2002, 2003, 2004).

Cognitive Science Analogy became of interest to mainstream cognitive researchers when they realised that human reasoning does not always operate based on content-free general inference rules but rather is often related to particular bodies of knowledge and the context in which it occurs (Vosniadou & Ortony, 1989). Within the cognitive sciences, analogy is defined as an “inductive mechanism based on structured comparisons of mental representations” (Holyoak, 2005, p. 234). Two situations are analogous if they share a common pattern of relationships among their constituent elements despite the elements being different across the two situations (Holyoak, 2005). Identifying a common pattern requires a comparison of the two situations. In most cases, one analogue  – the source or base  – is more familiar than the other

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analogue – the target – in that prior experience or knowledge about functional relations within the source analogue are known; for example, understanding that certain properties of the source have causal, explanatory or logical connections to other properties (Hesse, 1996). The initial asymmetry in knowledge supports the process of analogical transfer, an inductive process, in which the source is used to generate inferences about the target (Holyoak, 2005). There is a general agreement that analogy requires a relational structure, normally applied in one domain to also function in another domain (Gentner, 1983); whole systems of connected relations are matched from a known domain that already exists in memory (i.e. the source, the base or the vehicle analogue) to another, unknown domain (the target) (Holyoak et al., 2001; Gentner et al., 2001; Vosniadou & Ortony, 1989). The general consensus among cognitive scientists is that analogical thinking can be deconstructed into several basic component processes, including: (1) one or more relevant analogues stored in memory must be accessed; (2) a familiar analogue must be mapped to the target analogue, and the corresponding parts of each analogue must be aligned; (3) analogical inferences are made from the mappings, allowing new knowledge to fill gaps in understanding; (4) the inferences are evaluated and possibly adapted to fit the unique requirements of the target; (5) new categories and schemas may be generated as a result of the analogical reasoning (Gentner & Holyoak, 1997; Holyoak et al., 2001; Vosniadou & Ortony, 1989). All cognitive theories of analogy include and emphasise one or more of these basic component processes. According to cognitive scientists, these component processes involve dynamic interactions of many interrelated systems and thus, as is characteristic of the cognitive science approach to dealing with complex information-­processing problems, computational simulations of analogical reasoning have been developed to test analogical theories (Vosniadou & Ortony, 1989). Artificial intelligence scientists and cognitive psychologists have created a number of computational models of analogy to provide theoretical illustrations of how humans compare representations, retrieve potential analogues from memory and learn from the results (Gentner & Forbus, 2011). Computational models of analogy include subsets of the basic components processes offered by cognitive science. However, computational models differ in their focus; some capture the range of analogical phenomena at the cognitive level, and others suggest how analogical processes might be implemented in neural systems. From a functional behaviour analytic perspective, a fundamental weakness shared by the cognitive models is that they do not have functional definitions for analogical reasoning but rely on information-processing concepts such as “mapping” and “knowledge transfer”. From a behavioural perspective, the use of psychological terms, such as matching and mapping, does not explain the core relational performances. Furthermore, despite connectionist models having advantages over the representational models, they are arguably more interesting as models of neurological rather than psychological functioning (Stewart et al., 2004). Regarding the computational models, these terms are better defined, but their similarity to the human psychological events can only be assumed (Stewart et al., 2001).

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Behavioural Science Research on analogy has been mostly the province of cognitive psychologists; however, during the last two decades, behavioural psychologists have also begun to research analogy and perhaps the most prominent such work has been by relational frame theorists (see, e.g. Stewart et al., 2009). Before the present era, behavioural attention to analogy was confined to the theoretical writing of B. F. Skinner. Skinner (1957) provided an interpretative account of analogy as a form of “metaphorical extension”, a subtype of the “extended tact” (Stewart et al., 2004). A tact is defined as “a verbal operant in which a response of a given form is evoked (or at least strengthened) by a particular object or event or property of an object or event” (Skinner, 1957, pp. 81–82). The tact is a verbal response that makes contact with non-verbal stimuli in the environment for which the speaker receives generalised reinforcement such as verbal praise. For example, a child sees a dog and says, “Dog!” and consequently receives praise from the listener, “That’s right, it’s a dog!”. The tact allows the speaker to infer something about his environment that has nothing to do with himself. The extended tact is a more complex verbal behaviour that occurs when a response is evoked by a novel stimulus that resembles a stimulus previously present when a response was reinforced. Metaphorical verbal behaviour is a subtype of the extended tact that occurs “because of the control exercised by properties of the stimulus which, though present at reinforcement, do not enter into the contingency respected by the verbal community” (p. 92). The following is an example of the Skinnerian interpretation of metaphorical extension that appears in “Verbal Behavior” (1957): When for the first time a speaker calls someone a mouse, we account for the response by noting certain properties – smallness, timidity, silent movement and so on – which are common to the kind of situation in which the response is characteristically reinforced and to the particular situation in which the response is now emitted. Since these are not the properties used by zoologists or by the lay community as the usual basis for reinforcing a response we call the extension metaphorical (p. 93).

Skinner conceptualises analogy as the abstraction, via the extended tact, of a common physical property, from two different types of environmental events. This conceptualisation initiated the study of analogy within the behavioural sciences, but details as to the behavioural processes underlying this phenomenon are required. For example, how does “A is to B as C is to D” develop from a (presumably) simpler repertoire of formal property abstraction? To answer this question an empirically based functional analysis of analogical responding is required and for this we turn to RFT.

Relational Frame Theory To work within an RFT framework, Barnes et al. (1997) provided the first functional analytic model of analogy as the derivation of an equivalence relation between derived relations and more specifically between two equivalence relations, which

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they referred to as “equivalence–equivalence” responding. For example, consider the simple analogy “apple is to orange as dog is to sheep”. In this case, “apple” and “orange” participate in an equivalence relation in the context of “fruit” and “dog” and “sheep” participate in an equivalence relation in the context of “animal”, and thus, because these are both equivalence relations, we can derive a further relation of equivalence between the relations themselves. To empirically model this phenomenon, Barnes et al. first trained and tested four three-member equivalence relations in adults and 9-year-old children. They used a matching-to-sample (MTS) procedure to train conditional discriminations among three-letter nonsense syllable stimuli (A1-B1, A1-C1, A2-B2, A2-C2, A3-B3, A3-C3, A4-B4, A4-C4) and then tested for the derivation of the following four untrained relations (B1-C1, B2-C2, B3-C3, B4-C4). After participants passed these equivalence tests, they were then tested for the derivation of equivalence relations between equivalence (and non-equivalence) relations themselves (i.e. equivalence– equivalence responding). This involved using compound stimuli comprising either two nonsense syllables that were equivalent (e.g. B1-C1) or two that were non-­ equivalent (e.g. B1-C2). Participants were required to choose an equivalent pair in the presence of an equivalent pair (i.e. equivalence–equivalence) and a non-­ equivalent pair in the presence of a non-equivalent pair (i.e. non-equivalence–non-­ equivalence). All participants related equivalence relations to other equivalence relations and non-equivalence relations to other non-equivalence relations, and thus this constituted a basic model of analogical reasoning. Stewart et al. (2001) extended Barnes et al. by demonstrating equivalence–equivalence responding based on the abstraction of common formal properties. The latter is a common aspect of analogical language. For example, in the analogy “apple is to orange as dog is to sheep”, the similarity in each of the two equivalence relations is based on physical similarity (i.e. between “apple” and “orange” in one case and between “dog” and “sheep” in the other). The fact that analogies are grounded in physical properties in this way is important because it allows the language user to learn about potentially important physical dimensions of the domains being related as opposed to simply deriving completely abstract relationships. In Stewart et al. (2001), participants were taught using MTS to choose a specific nonsense syllable in the presence of each of four blue and four red geometric shapes and then to choose a further nonsense syllable in the presence of each of the first eight. During testing, participants demonstrated equivalence responding based on the abstraction of colour by consistently matching nonsense syllables related to same-coloured shapes to each other. Participants also showed equivalence–equivalence responding in which equivalence relations from the previous part of the experiment were related to other equivalence relations, and non-equivalence relations were related to other non-equivalence relations. Another important aspect of analogical language is that analogy can lead to new insights or in RFT terms effective transformations of function. Stewart et al. (2002) showed that relating derived relations could allow for the discrimination of common physical similarities between relations and that this in turn could lead to a transformation of functions such that a desired pattern of behaviour might be produced.

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Tasks were designed such that equivalence–equivalence responding might allow participants to discriminate a physical similarity between the relations involved. Some participants (colour subjects) received only equivalence–equivalence tasks in which they may discriminate a colour relation, whereas others (shape subjects) were given tasks in which they might discriminate a shape relation. A control group received both types of tasks. Stewart et al. trained and tested adults for the formation of four three-member equivalence relations: A1-B1-C1, A2-B2-C2, A3-B3-C3 and A4-B4-C4. The B and C stimuli were three-letter nonsense syllables, and the A stimulus was a coloured shape. Participants subsequently showed equivalence– equivalence responding, which in turn allowed them to discriminate either colour or shape relations (depending on their experimental condition) and in a subsequent test for the discrimination of formal similarity, colour subjects consistently matched as required according to colour while shape subjects matched according to shape (and the controls showed no consistent pattern). Stewart et al. suggested that this modelled the experience of insight via analogy, whereby analogical responding facilitates a contextually effective response to the environment. Stewart et al. (2004) extended previous work by using a new RFT-based methodology, called the relational evaluation procedure (REP; see Chap. 3 for further information on this procedure), to enable training and testing of analogical relations in a potentially more efficient and generative way than using MTS. The experiment involved nine stages in which five participants completed a complex series of initial REP training and testing protocol after which all participants readily demonstrated multiple instances of analogical responding, each of which involved a completely novel set of stimuli. This was important because it modelled the kind of generativity in the context of analogy, which is a feature of natural language. Barnes-Holmes et  al. (2005) further extended the RFT model of analogy by investigating additional dependent variables in the context of analogy, namely reaction time and neurophysiological behaviour. Their study tested analogical reasoning based on the relating of derived sameness and derived difference relations as per previous work but added novel outcome measures. In Experiment 1, they recorded reaction time measures of similar–similar (e.g. “apple is to orange as dog is to cat”) versus different–different (e.g. “he is to his brother as chalk is to cheese”) derived relational responding, in both speed-contingent and speed-noncontingent conditions. In Experiment 2, they examined the event-related potentials (ERPs) associated with these two patterns of responding. Both experiments found similar–similar responding to be significantly faster than different–different responding. The behavioural and neurophysiological data suggest that similar–similar responding is simpler and functionally distinct from different–different analogical responding. Lipkens and Hayes (2009) examined analogy in the context of topography-based responses and additional relations (i.e. not just sameness and difference), including non-symmetrical relations (i.e. comparison). In Experiment 1, participants successfully recognised analogies among stimulus networks containing same and opposite relations. In Experiment 2, analogy was successfully used to extend derived relations to pairs of novel stimuli. In Experiment 3, the procedure used in the first experiment was extended to non-symmetrical comparative relations while in

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Experiment 4, the procedure used in Experiment 2 was extended to non-­symmetrical comparative relations. Lipkens and Hayes found the procedures occasioned relational responses consistent with an RFT account, including productive responding based on analogies. Ruiz and Luciano (2011) sought to further improve the ecological validity of analogy by modelling cross-domain analogy as relating relations among separate relational networks and they also correlated participant performance with a standard measure of analogical reasoning. In two experiments, adults were first administered general intelligence and analogical reasoning tests. Next, they completed computerised conditional discrimination training designed to establish two relational networks, each consisting of two three-member equivalence classes. Testing included a two-part analogical test in which participants had to relate combinatorial relations of coordination and distinction between the two relational networks. In both experiments, 65% of participants passed the analogical test on the first attempt, and results from the training procedure were strongly correlated with the standard measure of analogical reasoning. Ruiz and Luciano (2015) used the RFT model to investigate analogical “aptness”. Twenty participants were trained to respond to the structure of analogical tests, after which they were trained on two separate relational networks, each consisting of three equivalence classes (Network 1: F1-G1-H1, F2-G2-H2, F3-G3-H3; Network 2: M1-N1-O1, M2-N2-O2, M3-N3-O3). The node stimuli always appeared with colour spots on their backgrounds (F1 and M1: yellow; F2 and M2: red; F3 and M3: blue). During testing, participants were to select the more accurate response from two options: relating combinatorial relations of coordination with the same colour in the node stimuli (e.g. relating G1H1 to N1O1) versus relating combinatorial relations with different colours in the node stimuli (e.g. relating G1H1 to N2O2). The colours of the node stimuli did not appear on the test. Eighteen participants selected the analogies with common colour properties as the more correct ones. While most of the initial RFT research on analogy has focused on analogy, there is also an important stream of research examining analogy in children. Carpentier et  al. (2002) used the equivalence–equivalence paradigm to investigate the early acquisition of analogy by comparing performance on equivalence–equivalence tests across a range of age groups, including adults, 9-year-old and 5-year-old children. As in the original Barnes et al. study, they found that adults and 9-year-old participants readily showed equivalence–equivalence responding. In contrast, the 5-year-­ old children, while readily passing equivalence testing, initially failed to show equivalence–equivalence responding and required additional training before doing so. More specifically, they required training and testing with compound–compound-­ matching tasks with trained relations (e.g. A1B1-A3B3 and A1B2-A1B3) before they could successfully pass the derived compound relations (BC-BC) test. Carpentier et  al. (2003) extended this work by assessing whether this additional training could also facilitate the 5-year-old children’s ability to pass equivalence– equivalence tests before receiving the prior equivalence tests. This was something that Barnes et  al. had shown that adults and 9-year-old children could do, and Carpentier et  al. (2003) replicated this in adults. However, despite providing

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considerable additional training, only two of 18 of the 5-year-old participants were successful in this task. The Carpentier et  al. (2002, 2003) studies thus provided additional insight into the early acquisition of equivalence–equivalence responding as a functional analytic model of analogy. By providing a precise, functional analytic model of this behaviour, this work has arguably shed additional light on this phenomenon beyond that provided by mainstream, cognitive psychological work by not alone confirming a developmental divide in the analogical ability at a particular age but also suggesting how additional training might remediate in this respect. The acquisition of analogy in young children has been further investigated recently by Kirsten and Stewart (2021), who developed an REP multi-stage protocol that allowed testing of different types of relations across four levels of complexity, including (1) Stage 1 non-arbitrary relations, (2) Stage 2 non-arbitrary analogy, (3) Stage 3 arbitrary relations and (4) Stage 4 arbitrary analogy (see Figs. 8.1 and 8.2). Within each stage were five substages focused on particular relations, including beginning with coordination, comparison, opposition, temporality and concluding with hierarchy across each stage (i.e. non-arbitrary relations, non-arbitrary analogical relations, arbitrary relations and arbitrary analogical relations). Participants included 24 young children (14 females, 10 males) who ranged between the ages of 3 and 8 and their relational performance across and within all levels and frames was correlated with their age and intellectual performance, as assessed on a standardised test of intellectual functioning, namely the Stanford-Binet Intelligence Scales (5th Edition) for Early Childhood (SB5).

Fig. 8.1  Stage 1: non-arbitrary analogical relations substages

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Fig. 8.2  Stage 4: arbitrary analogical relations substages

The children’s relational performance across and within levels and frames was correlated with their age and intellectual performance. The total score in Stage 4 arbitrary analogy, as well as its individual substage scores, showed significant correlations with age, IQ score and total assessment scores. The total score for arbitrary analogical responding showed a slightly stronger correlation with IQ performance than basic Stage 3 arbitrary relations. In comparison, basic arbitrary relations showed a slightly higher correlation with age compared to arbitrary analogical relations. These data provide further evidence that analogical relations may be associated with intellectual potential. Arbitrary analogy scores revealed a marked difference between the 4- to 5-year-old cohort and the 5- to 6-year-old cohort. These findings thus also contribute to the extant RFT research, suggesting a developmental divide in the acquisition of analogical ability at around 5 years of age (Carpentier et al., 2002, 2003). Unlike the Carpentier et al. studies, however, Kirsten and Stewart (2021) examined both non-arbitrary (Stage 2) and arbitrary (Stage 4) analogical responding across five frames, providing further insight into the developmental sequence and acquisition of analogical responding. Total relational assessment scores for Stage 2 (non-arbitrary analogy) showed strong, significant correlations with age, IQ score and total assessment scores. Data were further analysed for patterns of responding by age group to identify at which age analogical responding is acquired. Stage 2 results showed a gradual improvement in scores by age and suggested the acquisition of analogy, at least in coordinate and difference relations, at 5 years of age. This was the first RFT study to focus on non-arbitrary analogy in addition to arbitrary analogy. In the domain of comparative psychology, more work has been done testing relating of non-arbitrary relations in nonhumans, and indeed, various species have been found to pass such tests. For example, chimpanzees (Gillan et al., 1981), crows (Smirnova et al., 2015) and baboons (Fagot & Maugard, 2013) have passed

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non-arbitrary analogical (i.e. relating relations) tasks. Additionally, cognitive-­ developmental researchers have also conducted such work (e.g. Christie & Gentner, 2014). Kirsten and Stewart bridged that gap in their RFT-based study of non-­ arbitrary analogy in young children. From an RFT perspective, of course, non-­ arbitrary analogy is not full analogy (i.e. deriving relations among arbitrary relations). However, it is an important repertoire and should be trained as a prerequisite skill before training arbitrary analogy. The strong correlations between non-­ arbitrary and arbitrary analogy total scores in the present study provide evidence for this analysis, and future researchers could further evaluate the effects of training non-arbitrary analogy if it is a weak or missing skill in young children. Furthermore, considering the significant correlation between analogical responding and IQ, relational curricula may be further strengthened by including analogical responding. Considering the relevance of analogy to intellectual potential, future researchers could investigate the generalised effects of training analogical responding on socially valid measures such as mainstream analogy tests, academic achievement tests or standardised tests of cognitive performance. In previous RFT research on intellectual performance and relational responding, Cassidy et al. (2011) and various follow-up studies (e.g. Hayes & Stewart, 2016; Cassidy et al., 2016) used the REP to assess and train derived relational responding and compared scores on pre- and post-training standardised intelligence tests. Participant scores on the intelligence tests increased significantly following the relational training. Future researchers could similarly investigate the effects of training analogy, with multiple different relations within the analogies, on intellectual performance. The protocol used in Kirsten and Stewart could be used to efficiently test and train analogies in young children and subsequently examine the effects of such training on intellectual potential. Furthering the REP-based protocol, Kirsten, Stewart, and McElwee (2021) assessed and trained analogical responding in young, typically developing children. Three 5-year-old children were assessed and trained in relating relations using the RFT-based REP protocol in a combination of multiple baseline designs across participants and a multiple probe designs across behaviours. The study included a relational pre-assessment to screen potential participants; a baseline condition in which analogy was tested; and a training condition in which analogical responding was trained and generalisation probe trials were presented (see Fig. 8.3). Following multiple exemplar training, correct responding increased to criterion levels for all three children, and both generalisation and maintenance were observed. The data from Kirsten et  al. support the Carpentier et  al. findings that 5-year-old children are capable of analogical responding. However, Kirsten et  al. extended Carpentier et  al. by directly training analogy through multiple exemplar training using a controlled multiple baseline design such that the participants of the study could thereafter demonstrate analogical responding without additional prompting Fig. 8.3 (continued) Analogical stimuli presented in colour, for example, yellow red (sample), blue red (sameness comparison), yellow green (difference comparison) Third panel: probe for combinatorially entailed relations with a variation in the relational network (the difference cue is no longer presented last in the relational network). Relational network presented in colour, for example, blue S yellow, yellow D green, red S blue. Analogical stimuli presented in colour, for example, green red (sample), red yellow (sameness comparison), blue green (difference comparison)

= same Relational Network S

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Fig. 8.3  Example of the assessment of analogical relations Note. First panel: probe for combinatorially entailed relations. Relational network presented in colour, for example, red S blue, blue S yellow, yellow D green. Combinatorially entailed sameness relation (presented in thought bubble) included red, blue, yellow. Analogical stimuli presented in colour, for example, green red (sample), red yellow (sameness comparison), blue green (difference comparison) Second panel: probe for directly presented, mutually entailed and combinatorially entailed relations. Relational network presented in colour, for example, red S blue, blue S yellow, yellow D green.

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procedures being needed. The results from the multiple baseline showed that the combinatorially entailed (CE) analogy training procedure was an effective intervention for training analogy and eliciting generative responding, as shown by the generalisation data. All participants passed baseline CE Probe Set 1 as well as novel CE Probe sets following CE analogy training. Furthermore, correct analogical responding generalised to the DMC Probes  (i.e., Directly presented/ Mutually entailed/ Combinatorially entailed analogy probes). Previous RFT work on relating relations (e.g. Barnes et al., 1997; Carpentier et al., 2002) typically involved testing and training at least two sets of combinatorially entailed relations. Kirsten et al. included directly presented, mutually entailed and combinatorially entailed relations to provide evidence that participants were generalising analogical responding across different types of relational derivation rather than limiting their responses to the CE relation only. Kirsten et al. (2022) further extended the work of Kirsten et al. (2021) by modifying the testing and training procedure implemented in the latter to include a larger array of stimuli. The relational networks included 16 monochromatic circles and the relational cue, S for same, to delineate the relations between circles. A larger array would more closely replicate the analogical work by Carpentier et  al. (2002) in which participants were trained and tested for equivalence–equivalence responding with nine arbitrary pictures. Kirsten et al. (2022) also administered a pre-assessment testing for participants’ relational and analogical responding. The pre-assessment tested and trained combinatorial entailment when it was weak or missing in the participants’ relational repertoire. Using small, coloured disks to correspond to the presented relational network, the 5-year-old participants were trained to derive arbitrary relations from the presented sameness relational networks. Following this training, participants combinatorially entailed relations from novel relational networks without further prompting or training, thus, meeting the pre-requisite criteria for participating in the study of analogical relations. In Experiment 1 of Kirsten et al. (2022), a multiple baseline across participants was used to test and train analogical responding. The study included a relational pre-assessment for screening potential participants; a baseline condition in which relating combinatorially entailed relations (CE analogy) was tested; a brief pre-­ training probe condition in which relating directly presented relations (DP analogy) was tested; and a training condition in which relating directly presented relations (DP analogy) was trained, and generalisation probe trials were presented (see Fig. 8.4). Two 5-year-old typically developing children were assessed and trained in relating relations in a multiple baseline design. Following training, both children successfully showed analogical responding during CE Probe sets, including the original CE Probe Set 1 used during baseline testing, a novel CE Probe Set 2, and the generalisation probe, CE + D Probe (see Fig. 8.5). Fig. 8.5 (continued) green, yellow S black, grey S pink, red S turquoise. Combinatorially entailed sameness relations (presented in thought bubble) included purple, red, turquois; yellow, black orange; pink, blue, grey; brown, green, white. Analogical stimuli presented in colour, for example, yellow orange (sample), white brown (sameness comparison), purple blue (difference comparison) Bottom panel: CE analogy with a distractor. Relational networks presented in colour, for example (from left to right), purple S red, brown S green, black S orange, pink S blue, white S green, yellow S black, grey S pink, red S turquoise. Analogical stimuli presented in colour, for example, turquoise white (sample), turquoise purple (sameness comparison), red blue (difference comparison)

S

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Fig. 8.4  Training stimuli: example directly presented compound elements for directly presented analogical responding in Kirsten et al. (2022) Note. Relational networks presented in colour, for example (from left to right), purple S red, brown S green, black S orange, pink S blue, white S green, yellow S black, grey S pink, red S turquoise. Analogical stimuli presented in colour, for example, yellow black (sample), white pink (difference comparison), purple red (sameness comparison)

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Fig. 8.5  Two probe types for CE analogy and CE + D analogy Note. Top panel: CE analogy without a distractor. Relational networks presented in colour, for example (from left to right), purple S red, brown S green, black S orange, pink S blue, white S

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Experiment 2 was a replication of Experiment 1, but participants were children with autism spectrum disorder (ASD). Characterised by impairments in social interaction and social communication (American Psychiatric Association, 2013), ASD currently affects one in 54 children in the United States (Maenner et  al., 2020). It has been argued that children with ASD face significant language comprehension challenges due in part to their difficulty in understanding figurative language (Kalandadze et al., 2018; Persicke et al., 2012). Considering the prevalence of figurative language in our socio-verbal environment, children with ASD and other language delays face considerable comprehension challenges due to their difficulty with understanding non-literal language. However, the acquisition of analogical language in children struggling with ASD has received little attention. Considering that analogy seems centrally important for language and cognition, training analogy in children struggling with language development could result in significant language generativity. In the only extant behavioural study in this area, Persicke et al. (2012) used RFT as the theoretical background to successfully teach naturalistic metaphorical language to three participants with ASD using multiple exemplar training. In addition, Persicke et al. found that participant responses generalised to untrained, novel metaphors. However, two notable experimental limitations were observed: participant history with the metaphors could not be controlled, and the relative difficulty of the metaphors was not quantified, and thus, difficulty across metaphors could not be established. In contrast, in Kirsten et  al. (2022), all relations were established among arbitrary stimuli within the experimental task, thus obviating the need to control for task variance and participant history with language. Two children with ASD were assessed and trained in relating relations. Following training, both participants successfully showed analogical responding during CE Probe sets, including the original CE Probe Set 1 used during baseline testing, a novel CE Probe Set 2, and the generalisation probe, CE + D Probe. These results suggest that this format can be used to successfully train children with ASD to respond to analogical relations as defined by RFT. Future researchers could investigate whether training the core component processes of analogical responding in this way might facilitate training and understanding of more complex figurative language and whether analogical training results in the generative understanding of analogy and other figurative language in everyday language. One notable feature of the Kirsten et al. (2021, 2022) studies was that analogical responding was tested and trained using a novel RFT-based protocol, and more specifically, an adaptation of the RFT-based protocol used in Kirsten and Stewart (2021). The utilisation of shapes across all trials obviated the need to control for participants’ previous experience and knowledge as well as controlled for stimulus consistency across trials. The results of these studies suggest the applied and experimental potential of this format. For example, by using monochromatic circles and single-lettered contextual cues, the REP format makes it easy to produce multiple training and testing sets suitable for young children and pre-readers, making it possible to directly train children on complex relations with many exemplars. Moreover, this format did not require any relational pre-training but instead allowed for faster

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testing (with multiple versions of tests) than is possible with the tricky methodological issues in MTS procedures. Finally, a participant’s previous experience and knowledge is not an experimental confound. These favourable variables of the REP format permitted controlled studies in which we could target analogy testing and training directly while maintaining experimental control. That is, the REP format afforded in Kirsten et al. with quick and effective stimulus control allowing them to implement a multiple baseline design to examine the efficacy of multiple exemplar training to establish the core repertoire. For example, once participants were trained on the format of the REP in the pre-assessments, they were able to immediately implement analogical baseline testing across all participants and then implement controlled training and testing conditions with novel sets of stimuli. In addition, the REP format provided design flexibility for different generalisation probe types.

The Future of Analogical Relations Considering the ubiquity of analogical responding in everyday life, and the potential for improving language and cognition, further research into analogy assessment and training, in general, is undoubtedly warranted. Up until recently, most empirical work on verbal behaviour has primarily been influenced by Skinner’s (1957) analysis of verbal behaviour (Dymond et al., 2010; Dixon et al., 2017a). Consequently, commonly used language assessments, such as the Assessment of Basic Language and Learning Skills  – Revised (ABLLS-R; Partington, 2008) and the Verbal Behaviour Milestones and Placement Program (VB-MAPP; Sundberg, 2008), are based on Skinner’s analysis of verbal behaviour; thus, training focuses on the basic verbal operants (i.e. echoics, mands, tacts, intraverbals), with little attention to more complex verbal behaviour. More recently, Dixon et al. (2014, 2018) and Dixon et al. (2017b) provided experimental work assessing and training more complex language. The Kirsten and Stewart (2021) and the Kirsten et al. (2021, 2022) studies further contribute to the work on relational language assessment and training. The REP format used in these studies lends itself to the easy replication and modification required for an individualised relational curriculum. Future RFT work on analogy could also extend the REP format to test and train analogical relations beyond coordination and distinction. Previously, Lipkens and Hayes (2009) successfully looked at multiple relations (i.e. sameness, difference, comparison and opposition) in analogy in adult participants. Lipkens and Hayes tested across selection-based and topography-based tasks, including selecting the correct relata, selecting the correct relational cue and producing the correct relata. However, the Lipkens and Hayes procedure required extensive pre-training as well as reading and writing skills. For young children, it might be possible to test and train multiple relations and topography-based responses using variations of the REP format used in the present study. For example, in Lipkens and Hayes’ selecting relata task, the participant was given the sample, a relational cue and two comparisons; participants had to select the correct comparison based on the relational cue;

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in selecting the correct relation task, the participant had to select the correct relational cue given the sample and the comparison stimulus; and in producing the relata task, the participant had to produce the correct relata given the sample stimulus and relational cue. The REP format would support these various tasks and make them accessible to young children. For example, in producing the relata tasks, the response could include shading in a blank circle with the correct colour, and in selecting the relation tasks, the same label format (i.e. S or D) used in the current study could be applied and extended to other relations. A closely related possibility for further research would be to examine the effects of training sameness relations on the emergence of other relations. For example, once participants have been trained in coordinate analogical responding, performance with analogies involving other types of relations (e.g. comparative–comparative) could be tested to see if generalisation across relations could occur. Kirsten and Stewart (2021) found that coordinate analogical responding was acquired before comparative, opposite, temporal and hierarchical analogical responding. Future research could examine whether relating these other relations might be prompted by training analogy of coordination. Alternatively, despite the empirical findings of Kirsten and Stewart, it might also be investigated whether, under particular circumstances, training analogy involving non-coordinate relations might be able to support the emergence of analogy of coordination. MET (i.e., multiple exemplar training) of analogy might also be tested by examining whether training just one variety of analogy (e.g. coordination) alone facilitates generalisation in novel relational varieties of analogy, or whether training additional relational varieties of analogy might be required to promote generalisation. RFT allows for a functional analysis of an individual’s existing analogical abilities. The RFT research literature shows that methods for effective testing and training analogical relations in children as young as 5, as well as children with ASD and other forms of developmental delay, have begun to be developed and might be effectively deployed in the applied arena. Considering the correlation between intelligence and analogical responding, the benefits of including analogical relations in a child’s curriculum seem apparent and thus the continued investigation and deployment of RFT-based methods for assessing and training analogy should be of interest to researchers and practitioners alike.

References Alexander, P.  A., Willson, V.  L., White, C.  S., Fuqua, J.  D., Clark, G.  D., Wilson, A.  F., & Kulikowich, J. M. (1989). Development of analogical reasoning in 4- and 5-year-old children. Cognitive Development, 4(1), 65–88. https://doi.org/10.1016/0885-­2014(89)90005-­1 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). American Psychiatric Association. Barnes, D., Hegarty, N., & Smeets, P. M. (1997). Relating equivalence relations to equivalence relations: A relational framing model of complex human functioning. The Analysis of Verbal Behavior, 14(1), 57–83. https://doi.org/10.1007/BF03392916

References

193

Barnes-Holmes, D., Regan, D., Barnes-Holmes, Y., Commins, S., Walsh, D., Stewart, I., Smeets, P. M., Whelan, R., & Dymond, S. (2005). Relating derived relations as a model of analogical reasoning: Reaction times and event-related potentials. Journal of the Experimental Analysis of Behavior, 84, 435–451. https://doi.org/10.1901/jeab.2005.79-­04 Carpentier, F., Smeets, P.  M., & Barnes-Holmes, D. (2002). Matching functionally same relations: Implications for equivalence-equivalence as a model for analogical reasoning. The Psychological Record, 52, 351–370. https://doi.org/10.1007/BF03395435 Carpentier, F., Smeets, P. M., & Barnes-Holmes, D. (2003). Equivalence-equivalence as a model of analogy: Further analyses. The Psychological Record, 53, 349–371. Carpentier, F., Smeets, P.  M., Barnes-Holmes, D., & Stewart, I. (2004). Matching derived functionally-same stimulus relations: Equivalence-equivalence and classical analogies. The Psychological Record, 54, 255–273. https://doi.org/10.1007/BF03395473 Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61(2), 173–198. https://doi. org/10.1007/BF03395755 Cassidy, S., Roche, B., Colbert, D., Stewart, I., & Grey, I. M. (2016). A relational frame skills training intervention to increase general intelligence and scholastic aptitude. Learning and Individual Differences, 47, 222–235. https://doi.org/10.1016/j.lindif.2016.03.001 Chiesa, M. (1994) Radical Behaviorism: The Philosophy and the Science. Boston, MA: Authors’ Cooperative. Christie, S., & Gentner, D. (2014). Language helps children succeed on a classic analogy task. Cognitive Science, 38(2), 383–397. https://doi.org/10.1111/cogs.12099 Dancygier, B., & Sweetser, E. (2014). Cambridge textbooks in linguistics: Figurative language. Cambridge University Press. https://doi.org/10.1007/s10864-­018-­9302-­2 Dixon, M.  R., Belisle, J., Whiting, S.  W., & Rowsey, K.  E. (2014). Normative sample of the PEAK relational training system: Direct training module and subsequent comparisons to individuals with autism. Research in Autism Spectrum Disorders, 8(11), 1597–1606. https://doi. org/10.1016/j.rasd.2014.07.020 Dixon, M. R., Belisle, J., McKeel, A., Whiting, S., Speelman, R., Daar, J. H., & Rowsey, K. (2017a). An internal and critical review of the PEAK relational training system for children with autism and related intellectual disabilities: 2014-2017. The Behavior Analyst, 40(2), 493–521. https:// doi.org/10.1007/s40614-­017-­0119-­4 Dixon, M. R., Rowsey, K. E., Gunnarsson, K. F., Belisle, J., Stanley, C. R., & Daar, J. H. (2017b). Normative sample of the PEAK relational training system: Generalization module with comparison to individuals with autism. Journal of Behavioral Education, 26(1), 101–122. https:// doi.org/10.1007/s10864-­016-­9261-­4 Dixon, M. R., Belisle, J., & Stanley, C. R. (2018). Derived relational responding and intelligence: Assessing the relationship between the PEAK-E pre-assessment and IQ with individuals with autism and related disabilities. The Psychological Record, 68(4), 419–430. https://doi. org/10.1007/s40732-­018-­0284-­1 Dymond, S., May, R. J., Munnelly, A., & Hoon, A. E. (2010). Evaluating the evidence base for relational frame theory: A citation analysis. The Behavior Analyst, 33(1), 97–117. https://doi. org/10.1007/bf03392206 Fagot, J., & Maugard, A. (2013). Analogical reasoning in baboons (papio papio): Flexible reencoding of the source relation depending on the target relation. Learning and Behavior, 41, 229–237. https://doi.org/10.3758/s13420-­012-­0101-­7 Gentner, D. (1983). Structure mapping: A theoretical framework for analogy. Cognitive Science, 7(2), 155–170. https://doi.org/10.1016/S0364-­0213(83)80009-­3 Gentner, D., & Forbus, K. D. (2011). Computational models of analogy. Wiley Interdisciplinary Reviews: Cognitive Science, 2(3), 266–276. Gentner, D., & Holyoak, K. J. (1997). Reasoning and learning by analogy. American Psychologist, 52, 32–34.

194

8  Analogy: Relating Relations

Gentner, D., Holyoak, K. J., & Kokinov, B. (Eds.). (2001). The analogical mind: Perspectives from cognitive science. MIT Press. Gillan, D. J., Preman, D., & Woodruff, G. (1981). Reasoning in the chimpanzee: I. Analogical reasoning. Journal of Experimental Psychology: Animal Behavior Processes, 7(1), 1–17. https:// doi.org/10.1037/0097-­7403.7.1.1 Goswami, U. (1996). Analogical reasoning and cognitive development. In H.  W. Reese (Ed.), Advances in child development and behavior (pp. 91–138). Elsevier Science. Goswami, U., & Brown, A.  L. (1989). Melting chocolate and melting snowmen: Analogical reasoning and causal relations. Cognition, 35(1), 69–95. https://doi. org/10.1016/0010-­0277(90)90037-­K Hayes, J., & Stewart, I. (2016). Comparing the effects of derived relational training and computer coding on intellectual potential in school-age children. British Journal of Educational Psychology, 86(3), 397–411. https://doi.org/10.1111/bjep.12114 Hesse, M. (1965). Aristotle’s logic of analogy. The Philosophical Quarterly, 15(61), 328–340. https://doi.org/10.2307/2218258 Hesse, M. (1996). Models and analogies in science. Notre Dame University Press. Hofstadter, D. R. (2001). Epilogue: Analogy as the core of cognition. In D. Gentner, K. J. Holyoak, & B.  N. Kokinov (Eds.), The analogical mind: Perspectives from cognitive science (pp. 499–537). MIT Press. Hofstadter, D., & Sander, E. (2013). Surfaces and essences: Analogy as the fuel and fire of thinking. Basic Books. Holyoak, K. J. (2005). Analogy. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 117–142). Cambridge University Press. Holyoak, K. J., & Thagard, P. (1995). Mental leaps: Analogy in creative thought. MIT Press. Holyoak, K. J., Gentner, D., & Kokinov, B. N. (2001). Introduction: The place of analogy in cognition. In D. Gentner, K. J. Holyoak, & B. N. Kokinov (Eds.), The analogical mind: Perspectives from cognitive science (pp. 1–19). MIT Press. Kalandadze, T., Norbury, C., Naerland, T., & Naess, K. A. B. (2018). Figurative language comprehension in individuals with autism spectrum disorder: A meta-analytic review. Autism, 22(2), 99–117. https://doi.org/10.1177/1362361316668652 Kirsten, E.  B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record. https://doi.org/10.1007/s40732-­021-­00457-­y Kirsten, E. B., Stewart, I., & McElwee, J. (2021). Testing and training analogical responding in young children using relational evaluation procedure. The Psychological Record. https://doi. org/10.1007/s40732-­021-­00468-­9 Kirsten, E.  B., Stewart, I., & McElwee, J. (2022). Testing and training analogical responding in children with and without autism. The Psychological Record. https://doi.org/10.1007/ s40732-­021-­00493-­8 Lapiàna, W. P. (2004). Merit and diversity: The origins of the law school admissions test. Saint Louis University Law Journal, 48, 955–990. Lipkens, R., & Hayes, S. C. (2009). Producing and recognizing analogical relations. Journal of the Experimental Analysis of Behavior, 91, 105–126. https://doi.org/10.1901/jeab.2009.91-­105 Maenner, M. J., Shaw, K. A., Baio, J., Washington, A., Patrick, M., DiRienzo, M., Christensen, D.  L., Wiggins, L.  D., Pettygrove, S., Andrews, J.  G., Lopez, M., Hudson, A., Baroud, T., Schwenk, Y., White, T., Rosenberg, C.  R., Lee, L.  C., Harrington, R.  A., Huston, M, et  al. (2020). Prevalence of autism spectrum disorder among children aged 8 years. Autism and Developmental Disabilities Monitoring Network, 69(SS-4), 1–12. https://doi.org/10.15585/ mmwr.ss6904a Matos, M. A., & Passos, M. L. P. (2010). Emergent verbal behavior and analogy: Skinnerian and linguistic approaches. The Behavior Analyst, 33, 65–81. https://doi.org/10.1007/BF03392204 Morsanyi, K., & Holyoak, K.  J. (2010). Analogical reasoning ability in autistic and typically developing children. Developmental Science, 13(4), 578–587. https://doi. org/10.1111/j.1467-­7687.2009.00915.x

References

195

Oppenheimer, J. R. (1956). Analogy in science. American Psychologist, 11, 127–135. Partington, J.  W. (2008). The assessment of basic language and learning skills-revised (the ABLLS-R). Behavior Analysts. Persicke, A., Tarbox, J., Ranick, J., & St. Clair, M. (2012). Establishing metaphorical reasoning in children with autism. Research in Autism Spectrum Disorders, 6, 913–920. https://doi. org/10.1016/j.rasd.2011.12.007 Polya, G. (2004). How to solve it: A new aspect of mathematical method. Princeton University Press. (Original work published 1945). Richland, L., & Simms, N. (2015). Analogy, higher order thinking, and education. Wiley Interdisciplinary Reviews: Cognitive Science, 6, 177–192. https://doi.org/10.1002/wcs.1336 Ruiz, F. J., & Luciano, C. (2011). Cross-domain analogies as relating derived relations among two separate relational networks. Journal of the Experimental Analysis of Behavior, 95, 369–385. Ruiz, F. J., & Luciano, C. (2015). Common physical properties among relational networks improve analogy aptness. Journal of the Experimental Analysis of Behavior, 103, 498–510. https://doi. org/10.1002/jeab.147 Skinner, B. F. (1957). Verbal behavior. Copley Publishing Group. Smirnova, A., Zorina, Z., Obozova, T., & Wasserman, E. (2015). Crows spontaneously exhibit analogical reasoning. Current Biology, 25, 256–260. https://doi.org/10.1016/j.cub.2014.11.063 Spellman, B.  A., & Schauer, F. (2005). Legal reasoning. In K.  J. Holyoak & R.  G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp.  719–735). Cambridge University Press. Sternberg, R.  J. (1977). Component processes in analogical reasoning. Psychological Review, 84(4), 353–378. Stewart, I., & Barnes-Holmes, D. (2001). Relations among relations: Analogies, metaphors, and stories. In S.  C. Hayes, D.  Barnes-Holmes, & B.  Roche (Eds.), Relational frame theory: A post-Skinnerian account of human language and cognition (pp.  73–86). Kluwer Academic/ Plenum Publishers. Stewart, I., Barnes-Holmes, D., Roche, B., & Smeets, P. M. (2001). Generating derived relational networks via the abstraction of common physical properties: A possible model of analogical reasoning. The Psychological Record, 51, 381–408. Stewart, I., Barnes-Holmes, D., Roche, B., & Smeets, P. M. (2002). A functional analytic model of analogy: A relational frame analysis. Journal of the Experimental Analysis of Behavior, 78, 375–396. Stewart, I., Barnes-Holmes, D., & Roche, B. (2004). A functional-analytic model of analogy using the relational evaluation procedure. The Psychological Record, 54(4), 531–552. https://doi. org/10.1007/BF03395491 Stewart, I., Barnes-Holmes, D., & Weil, T. (2009). Training analogical reasoning as relational responding. In R.  A. Rehfeldt & Y.  Barnes-Holmes (Eds.), Derived relational responding: Applications for learners with autism and other developmental disabilities (pp. 257–279). New Harbinger Publications. Stewart, I., McLoughlin, S., Mulhern, T., Ming, S., & Kirsten, E. B. (2020). Assessing and teaching complex relational operants: Analogy and hierarchy. In M. Fryling, R. A. Rehfeldt, J. Tarbox, M. Fryling, & L. J. Hayes (Eds.), Applied behavior analysis of language and cognition: Core concepts & principles for practitioners. Context Press/New Harbinger Publications. Sundberg, M.  L. (2008). VB-MAPP: Verbal behaviour milestones assessment and placement program: A language and social skills assessment program for children with autism or other developmental disabilities. AVB Press. Vosniadou, S., & Ortony, A. (Eds.). (1989). Similarity and analogical reasoning. Cambridge University Press.

Chapter 9

Relational Frame Theory and Language

Language is a complex repertoire that appears to be unique to humans and despite our attempts to Dr. Dolittle with varying species, it remains a distinctly human behavioural and cognitive repertoire (for an overview, see Hughes & Barnes-­ Holmes, 2014; Lionello-DeNolf, 2009; Zentall et al., 2014; Urcuioli et al., 2014). However, what exactly is it that allows us to speak with meaning and listen with understanding? (Hayes, 1996). The question of the generativity of language is one that has plagued behaviour analysis since Chomsky’s (1959) initial critique of the field. Hopefully, the preceding chapters have hinted the role that Relational Frame Theory (RFT) may play in answering this question to at least some degree (of course, additional research is required in this field to further explore this domain). Afterall, the capacity to arbitrarily relate stimuli along any number of dimensions (e.g. sameness, difference, hierarchy, comparison), or relationally frame, is the very repertoire that underpins generativity of behaviours – including that of language. Indeed, the phenomenon of transformation of stimulus function outlined within RFT is one which is theorised to be the basis of novel language production in the absence of direct reinforcement (Stewart et  al., 2013). For example, published research in the area of applied behaviour analysis on the repertoire of derived manding has indicated that transformation of stimulus function appears to play a pivotal role in generative language (e.g. Belisle et  al., 2020; Halvey & Rehfeldt, 2005; Murphy & Barnes-Holmes, 2009, 2010a, b; Raaymakers et al., 2019; Rehfeldt & Root, 2005; Rosales & Rehfeldt, 2007).

Generative and Derived Manding in Research Murphy and Barnes-Holmes (2009) developed a protocol to facilitate derived manding for specific amounts with three young children aged 4–10. Two of the participants (aged 9 and 10) had no known diagnoses, although mild learning difficulties had been reported for one child (i.e. Jasmine). The final participant (aged 4) had a © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_9

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reported severe speech delay. The protocol aimed to facilitate arbitrarily applicable relational responding (AARR) in accordance with comparison and coordination and employed nonsense syllables as arbitrary stimuli within the mand training phase. A board-game format was developed to contrive situations in which the children would mand for specific amounts because the format required the children to retain a set of six tokens in the centre panel to win the game, thereby requiring the children to request the addition or even the removal of tokens. As such, the game was designed to include trials in which (1) the experimenter placed fewer than six tokens on the centre panel, requiring the child to request additional tokens; (2) the experimenter filled the centre panel with six tokens and also included additional tokens in the space outside the panel, requiring the child to request the removal of tokens; and (3) the experimenter placed six tokens on the centre panel, which meant that the child did not have to make any requests for either the removal or addition of tokens. Within these trials, the children were provided with an array of mand stimulus cards (designated as A stimuli: A1, A2, A3, A4 and A5), which they were informed could be used to add or subtract tokens by the instructor. Manding the appropriate amount was met with verbal praise and the delivery of one point (a point system was in place such that children could exchange these points for backup reinforcers such as games, activities, etc.). However, if the child manded an incorrect amount, the instructor presented or removed the number of tokens manded (even though it was incorrect – such an action provided visual feedback of their selection), then delivered a correction (e.g. “you should have given me card A1, because you needed to get rid of two tokens”) and a new (and different) trial commenced. Participants were sequentially introduced to each of the A stimuli for manding – beginning with stimuli A1 and A2, and concluding with stimuli A3, A4 and A5. Positional prompts were used to facilitate the selection of the appropriate arbitrary stimulus for each trial; however, this level of prompting was faded across trials until independent responding emerged. Participants were then introduced to conditional discrimination training using a matching-to-sample (MTS) procedure in which participants matched the A stimuli that they had employed within mand training to corresponding B stimuli (i.e. A1– B1; A2–B2) and also matched B stimuli to C stimuli (i.e. B1–C1; B2–C2). Correct selections included positive reinforcement as delivered in the mand training phase. If a participant made an incorrect selection, the investigator gave a correction, indicating the B or C stimulus to select. As in mand training, this section of training initially focused on the stimuli A1 and A2 (and their corresponding B equivalents) before moving to the stimuli A3, A4 and A5. Following the successful acquisition of A–B relations, the children then entered training for B–C relations. Upon the completion of B–C conditional discrimination training, participants were then tested for derived transfer of manding. This phase of assessment was similar to mand training; however, the A stimuli were replaced with C stimuli (i.e. C1 = remove 2 tokens; C2  =  remove 1 token; C3  =  neither remove or add tokens; C4  =  add 1 token; C5 = add 2 tokens) and the participants’ parents were also involved in this stage of testing. The children were asked to attend to the board, count the tokens and select the appropriate card from the C stimuli presented and give that to their parents.

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Within this phase, the experimenters did not remove or add tokens and no feedback on performance was provided during assessment. Participants were then provided with further conditional discrimination training that functioned as an ABA reversal design (see Chap. 5 for further information on this experimental design), in which new functions and relations were trained for the B stimuli (i.e. B1–C2, B2–C1, B3–C5, B4–C3 and B5–C4). As the relations between stimuli had been changed, the derivation of function was expected to also transfer to the C stimuli (i.e. C2 = −2 tokens, C1 = −1 token, C5 = 0 token, C3 = +1 token and C4 = +2 tokens), with all three children being assessed for derivation of mands using the C stimuli. Consistent with a withdrawal or reversal design, the participants were retrained on the original relationship between stimuli using the B stimuli (i.e. B1 = C1, B2 = C2, B3 = C3, B4 = C4 and B5 = C5) and assessed for derivation of mand function with C stimuli in the original pattern observed (i.e. C1  =  −2, C2  =  −1, C3  =  0, C4  =  +1 and C5 = +2). All three participants demonstrated derived manding in accordance with the newly trained relations across the reversal procedures, although some additional training and retraining on conditional discrimination was needed for each participant (to varying levels) across the ABA phases. A similar procedure was conducted by Murphy and Barnes-Holmes (2010b) with three autistic teenagers, each with an established verbal repertoire, to assess the efficacy of this procedure for derived manding. This study was more condensed than their previous 2009 study and excluded the reversal component of the experimental design, meaning that participants were provided with mand training, conditional discrimination training and then assessed for derivation of mands (as per the early phases of Murphy & Barnes-­ Holmes, 2009). The experimenters observed a replication of experimental effects, with each participant demonstrating derived mands, with only one participant requiring further multiple exemplar training (i.e., MET). The success of this protocol indicates the utility of an RFT-­based approach to language and also provides a useful template for practitioners to approach generative language. While it is tempting to think that language is vocal, we must also remember that language (and communication) can be diverse and non-vocal and that such repertoires are also amenable to training to facilitate generative manding repertoires. For example, Still et al. (2015) taught derived manding repertoires, with mands being produced on a touchscreen tablet, to 11 autistic children across two studies. Within Study 1, eight autistic children who communicated via a picture exchange communication system (PECS) were assessed for their receptive and expressive language abilities using the British Picture Vocabulary Scale  – Third Edition (BPVS-III; Dunn et al., 2009) and the Expressive Vocabulary Test – Second Edition (EVT-II; Williams, 2007) and preferred items using a preference assessment. This was followed by probes for (1) mands, (2) derived requesting and (3) derived relations using the relational completion procedure (RCP; for more information on this procedure, see Chap. 3). Manding probes were contrived to assess the extent to which the children would request items that were missing and were necessary to engage in play (e.g. the pen for the etch-a-sketch). In this context, the selection of a picture (e.g. a picture of the pen from the etch-a-sketch) and its exchange with a communication partner for the missing item in question was scored as a mand by the

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experimental team. The derived requesting probes were identical to the previously outlined manding probe; however, it assessed whether children could request missing items by exchanging the text corresponding to the item (i.e. the word “pen” would be exchanged for the pen component of the etch-a-sketch). Derived relations probes using the RCP assessed the children’s ability to match spoken words to pictures (i.e. A–B relations), matching pictures to text (i.e. B–C relations), text to pictures (i.e. C–B relations) and spoken word to text (i.e. A–C relations). The participants were then provided with mand training that involved teaching the children how to ask for the missing part of the toy needed to play by selecting the corresponding picture on the tablet. A combination of prompting, prompt fading, verbal praise, reinforcement in the form of the manded item and differential reinforcement (e.g. independent responses were reinforced with edibles) was used to teach this manding repertoire. The children were then provided with conditional discrimination training in which they were taught A–B (i.e. spoken word to picture) and B–C (i.e. picture to text) training. All participants successfully completed training and indicated derivation of relations. All participants had indicated performance below their chronological age on the EVT-II and BPVS-III prior to testing; unfortunately, however, the researchers failed to examine whether there were any corresponding changes in these scores following training. Study 2 demonstrated greater experimental control by employing a multiple probe design (rather than the pre-test/post-test design employed in Study 1) to further assess the efficacy of the training protocol. Three autistic children whose methods of communication included a combination of eye gaze, gestures and words to request items, with one child also leading a communication partner to the desired item, participated in Study 2, which was identical in procedure to the earlier study. However, following conditional discrimination training phases, children were then assessed on B–A (i.e. the tacting of pictures) and C–A relations (i.e. tact/reading of text). All three participants successfully completed the manding phase and the conditional discrimination phases of training. Interestingly, for the measures of derived manding and derived relations, two participants demonstrated 100% correct text requesting (i.e. derived manding) on all post-A–C training probes; however, this was not observed in the third participant until he was exposed to a mixture of A–C and A–B trials. Furthermore, all children demonstrated the emergence of an A–C repertoire post-training. Such a study indicates the utility of an RFT approach to communication and language outside of the realm of vocal–verbal language.

Language Deficits and AARR The relationship between language and the ability to derive relations is further supported by research, which indicates that individuals who experience language deficits also demonstrate a reduced ability to derive relations between stimuli on an arbitrary level (Barnes et al., 1990). More importantly, a host of research has indicated that teaching AARR repertoires positively impacts the development of

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linguistic ability, with improvements on AARR also being associated with improvements in the comprehension and production of language (e.g. Murphy & Barnes-­ Holmes 2010a, b; Persicke et al., 2012; Walsh et al., 2014). For example, Persicke et al. (2012) identified three autistic children (interestingly, with the pseudonyms of Sheldon, Howard and Raj – a Big Bang Theory reference presumably), who required metaphorical language interventions and designed an RFT-based protocol to facilitate metaphorical language production and comprehension within the context of a multiple baseline design across participants. Prior to training, participants had established behavioural repertoires, which were considered necessary for interacting with the training programme, these included: (1) the capacity to listen to and answer questions about short stories, (2) the ability to describe objects by listing a minimum of three of their features and (3) the ability to discriminate between same and different. During baseline, all participants were assessed for metaphorical language by listening to a short story read aloud by the experimenter (composed by the experimenters, with each story outlining three features). The three features of the stimuli discussed within the story were then incorporated into questions containing metaphors. For example, when presented with the following story: I walked to school once during the winter, and forgot to wear gloves. There was snow everywhere. I didn’t see the big area of ice underneath all the snow and when I stepped on it, I slipped and fell. (Persicke et al., p. 916).

The child was then required to recount the story (to ensure an attending/observing response) and was then presented with three questions including metaphors, such as “If I say the snow was a blanket, what do I mean?”, “If I say my hands were icicles, what do I mean?” and “If I say the ice was a wet bar of soap, what do I mean?”. Each of these questions included shared features, for instance the shared feature of the first question was covering (i.e. both blankets and the snow covers), the shared feature of the second question was frozen (i.e. both icicles and the hands were frozen) and the shared feature of the final question was slippery (i.e. both the ice and a wet bar of soap are slippery), which were used to assess metaphorical comprehension. Following baseline, each participant entered the first phase of training (i.e. MET). The first session involved the introduction of two stories (similar to those employed in baseline), while the subsequent sessions included two mastered stories and two novel stories. As in baseline, participants were read a short story and asked to provide a summation to indicate an attending response and were then presented with a metaphor question. Reinforcement in the form of specific praise was provided for correct responses. If, however, the child produced an incorrect response, the experimenter used leading questions to discuss the hierarchical relationship between the target and its features, the vehicle and its features and the relations of distinction and the relations of coordination between them (although there is no script provided by the experimenter as to how exactly this was achieved). If the child was still unable to ascertain the shared feature, the experimenter then used an echoic prompt stating the shared feature. Following MET, the participants entered an additional phase of training that added a visual aid to the existing MET procedure. Using this visual aid (a laminated

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white piece of paper), the participants were asked to write the target (e.g. snow, hands, ice) at the top of one column, and the vehicle (e.g. blanket, icicle, wet bar of soap) at the top of the other column. The children were then asked to write a list of the features of the target and vehicle item in their respective columns and then draw a connecting line between the matching features. Verbal and gestural prompts were initially used to facilitate the participants’ use of the visual aid and individualisations of the procedure were made where necessary (e.g. Howard demonstrated difficulty reading and writing the items on the list, so pictures were employed instead). The visual aid component of training was only introduced if the participants provided an incorrect response during training, such that all trials began without a visual aid and without prompts to facilitate independent responding. Once participants had reached mastery criterion, they were then assessed for generalisation of responding using two completely novel stories, which had not been included in either baseline or training assessments before and after post-training (with two new stories and six new questions being employed for the latter test). Post-training assessment was conducted after the initial generalisation assessment and included the stories and questions from baseline assessment. All participants demonstrated some improvement in responding when they entered MET; however, a more stable and consistent increase in the responding of two participants (i.e. Sheldon and Howard) occurred once MET was combined with a visual aid, with the third participant (i.e. Raj) demonstrating acquisition of metaphorical questions in the MET phase alone. All participants demonstrated generalization of responding in the first probe, but indicated variable responding in post-training sessions (67–100% for Sheldon, 33–100% for Howard and 50–100% for Raj) before again demonstrating strong generalised responding in the final generalisation probe.

Language Emergence and RFT The ability to derive relations, both arbitrarily and non-arbitrarily, emerges throughout the course of development, increasing in complexity potentially as a result of increased exposure to contextual cues within the natural environment (Kirsten & Stewart, 2021; Mulhern et al., 2017). Additionally, the emergence of derived relational responding coincides with the period of development in which language itself begins to emerge rapidly (Lipkens et al., 1993; Luciano et al., 2007). For instance, in an early longitudinal study by Lipkens et al. (1993) data indicated that symmetry (as proposed by stimulus equivalence) or mutually entailed coordination emerges at 17  months. These relations (and many others) are then combined indicating the emergence of transitivity (as proposed by stimulus equivalence) or combinatorial entailment in accordance with coordination at 23 months. This period of development also coincides with the emergence of vocal language. Luciano et  al. (2007) extended on these findings by examining the impact of MET in derived equivalence responding across three experiments with a 15-month-­ old child. The first experiment employed MET in receptive symmetry (i.e. listener

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behaviour) to determine whether this training would facilitate the naming of new objects and the emergence of derived mutual entailment of novel stimuli. Within this study, the child was given a new object (i.e. stimulus A) and the mother gave its name (i.e. stimulus B), thereby providing the infant with an A–B relationship. This relationship was then assessed bidirectionally (i.e. in the B–A direction) in two ways: (1) by asking the infant to select the previously named object (i.e. the name of the object is Stimulus B in this instance) from an array of objects, including the target object (i.e. the physical object is Stimulus A in this context) and (2) by presenting the physical object to the infant and asking them to name it or provide an approximation of the name. This was conducted across ten different objects and was trained across immediate and delayed presentations of the reverse sound–object relation combined with specific praise and positive reinforcement for correct selections of objects; however, no approximations of naming occurred. The results indicated the emergence of receptive symmetry (i.e. a bidirectional listener repertoire) but no change was observed in the infants’ naming repertoire. Experiments 2 and 3 aimed to establish visual–visual equivalence relations with the infant, with Experiment 2 commencing when Gloria was 17 months. Experiment 2 aimed to establish two three-member equivalence networks (i.e. A1-B1-C1 and A2-B2-C2) of visual stimuli when presented in an MTS format with two comparison stimuli. The first phase of training involved A–B training in which Gloria matched A1 to B1 and A2 to B2, which was followed by B–A testing, B–C training, C–B testing and mixed training trials (i.e. A–B, B–A, B–C and C–B trials were presented until Gloria met mastery criterion). The derivation of combinatorially entailed relations (i.e. A–C and C–A) was then assessed across three consecutive blocks of four trials each. Gloria met criterion on training when she was 19 months old but still did not demonstrate any evidence of naming the included stimuli upon request. Experiment 3 was almost identical to that of Experiment 2 but was conducted when Gloria was 22 months old and used three stimuli as comparison stimuli rather than the two included in Experiment 2. Gloria demonstrated equivalence responding as in Experiment 2; however, upon the completion of Experiment 3, a naming repertoire also emerged. The results of this longitudinal study indicate that AARR and the derivation of relationships have some relationship with the onset and emergence of language.

The Brain, Language and AARR Early research by Dickins et al. (2001) examined the neural activity of 12 participants engaging in stimulus equivalence (which can be conceptualised as AARR of coordination) using fMRI. Participants also underwent a test of verbal fluency and their brain activity was observed during this phase of assessment. This study was one of the first to indicate the areas of neural activity involved in AARR and rather interestingly it found that when engaged in AARR coordination, the neural activity observed during this task was similar to that observed during the verbal fluency task.

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Both tasks indicated neural activation in the dorsolateral prefrontal cortex and the posterior parietal cortex bilaterally; however, only the verbal fluency task indicated activity in Broca’s area. In 2005, there was a further flurry of research that examined neural activity when performing AARR (e.g. Barnes-Holmes et  al., 2005a, b; Whelan et  al., 2005). Barnes-Holmes et  al. (2005a), for instance, examined neurological activity when trained and tested on two four-member arbitrary equivalence relations using nonsense syllables and also recorded brain activity when engaged in a single- or two-­ word lexical decision task. The results indicated that event-related potentials (ERPs) and reaction times were observed within (but not across) equivalence relations and were similar to those observed within the lexical decision task, indicating that AARR coordination may serve as an appropriate model for semantic relations. BarnesHolmes et al. (2005b) also examined the ERPs of AARR analogy with same:same analogy and different:different analogy. Analogical responding is considered a linguistic ability and is even included in the verbal IQ section (i.e. Level 5) of the Stanford-Binet Intelligence Scales, fifth Edition (SB5; Roid, 2003). Their findings indicated distinct patterns for these analogical repertoires within the left-­hemispheric pre-frontal region, indicating that these are functionally different AARR repertoires. This is an important point for programmes considering the assessment and training of analogy – it is not appropriate to assume that the acquisition of same:same analogy will necessarily equate to generalisation and acquisition of different:different analogy. Such a finding provides further information regarding the complexities and nuances of language itself – not all analogical relations are equal! Research conducted by Schlund et al. (2008), which examined derived relational responding in accordance with stimulus equivalence, found that the activity observed in the hippocampus during AARR appeared to be involved in maintaining the relational structure of sameness and also in the flexible memory expression among stimuli within a class. Furthermore, the neural imaging produced within this study also indicated that magnitude differences existed when a participant recognised an incorrect stimulus relation relative to their recognition of correct derived stimulus relations. The role of the hippocampus in the production, storage and expression of language has been considered within other realms of psychology (e.g. Duff & Brown-Schmidt, 2012), indicating that the neural activity during AARR of coordination observed by Schlund et al. (2008) may bear some similarity to the neural activity observed during linguistic activities.

Relational Flexibility and Language In previous chapters we have discussed the importance of relational flexibility as part of a fully developed and complex relational repertoire. Adding to the importance of relational flexibility, research has also indicated that this aspect of relational framing is also associated with performance on linguistic tasks (O’Hora et al., 2008; O’Toole & Barnes-Holmes, 2009; Whelan et al., 2005). For example, Whelan

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et al. (2005) employed non-arbitrary training to establish arbitrary stimuli as contextual cues for “same” and “opposite” before entering participants into an arbitrary MTS training phase (the stimuli were non-words that were structured to resemble words and were presented to the participants as “foreign” words) using these newly established contextual cues. Participants were then presented with a lexical decision task in which they were presented with a pair of textual stimuli that included the previously seen “foreign” words in addition to non-word words and were asked to respond to indicate whether the word pairs that were displayed on screen were both “foreign” words or not. The researchers examined the participants’ reaction times and found that their response times to pairs of foreign words were faster when these “foreign” words were related than when they were unrelated. The findings of this study indicate that this ability to relate stimuli with speed and accuracy is a crucial component to language more generally. Previous research has also indicated a positive correlation between AARR across several relational frames and language. For example, in Chap. 6, we outlined the work of O’Hora et al. (2008), which indicated that temporal relational responding was positively related to verbal comprehension as measured by the Wechsler Adult Intelligence Scale – Third Edition (WAIS-III), while O’Toole and Barnes-Holmes (2009) also found that relational responding in accordance with temporality, distinction and coordination was positively related to IQ measurement using the Kaufman Brief Intelligence Test (KBIT), which includes the assessment of expressive language. These findings are further bolstered by the findings of Hayes et al. (2016; which are explored in greater detail in Chap. 3), who employed an REP to assess AARR in accordance with coordination and distinction with children aged 2–5. Participants were assessed using the abbreviated battery of the SB5 and the Preschool Language Scale to assess language skills. Their findings indicated a correlation between performance on the REP (i.e. AARR coordination and distinction) and abbreviated IQ scores and linguistic abilities as measured by the Preschool Language Scale. Additionally, Mulhern et al. (2017) conducted research on AARR hierarchy and containment (see Chap. 7 for further information), which found a positive relation between AARR of hierarchy and containment and non-arbitrarily applicable relational responding (NAARR) of containment with verbal IQ as measured by the SB5 and linguistic ability measured via the Peabody Picture Vocabulary Test, fourth Edition (PPVT-4; Dunn & Dunn, 2007). These findings were then extended by Kirsten and Stewart (2021), who assessed AARR and NAARR in accordance with coordination, comparison, opposition, hierarchy temporality and analogy and also found a significant relationship with performance on these relational repertoires and the verbal components of the SB5. Early RFT research has also indicated the potential efficacy of AARR training with a focus on relational flexibility to facilitate improvements on linguistic ability (e.g. Cassidy et al., 2011). For instance, within their first study, Cassidy et al. (2011) used a computerised MET to teach AARR in accordance with coordination, opposition and comparison with eight children (aged 8–12 with no known diagnoses). All children were assessed using the Wechsler Intelligence Scale for Children (WISCIII; Wechsler, 1992) before and after training (18 months after the initial test) and

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full-scale IQ, verbal IQ and performance IQ scores were calculated based on these assessments. It was found that following training, all participants demonstrated an increase in full-scale IQ, performance IQ and verbal IQ. In their second study, eight children (aged 11–12) who had been identified as demonstrating educational difficulties were also assessed for IQ using the WISC-IV (Wechsler, 2004), which produced composite scores on verbal comprehension, perceptual reasoning, working memory and processing speed before and after AARR training (participants were assessed using the WISC-IV 9  months following their initial assessment). As in Study 1, a computerised MET aimed to increase AARR of coordination, opposition and comparison using arbitrary stimuli and had a timed component (i.e. participants had to respond quickly and accurately within a time limit). Following the completion of training, a significant improvement in full scale IQ was observed, in addition to an improvement on the WISC-IV subscales of verbal comprehension, perceptual reasoning and processing speed. The results of this early research indicated the potential efficacy of an RFT-based teaching protocol to enhance linguistic ability, and indeed cognitive ability more broadly. Hayes and Stewart (2016) advanced upon the previous work of Cassidy et al. by including an active control condition within their work and comparing this to the experimental condition of SMART (i.e. Strengthening Mental Abilities with Relational Training). Twenty-eight children (aged 10–11) served as participants and were randomly assigned to either the Scratch computer coding (i.e. active control condition) or the SMART condition. Prior to training, all participants were assessed using the Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999), which included four subtests (i.e. vocabulary, similarities, block design and matrices matching) to provide a full-scale IQ score, verbal IQ score and performance IQ score. The participants were then tested with three subtests of the Wechsler Individual Achievement Test (WIAT-II; Wechsler, 2005) including reading, spelling and numerical operations, in addition to two subtests of the WISC-IV (Wechsler, 2004) of digit span and letter and number sequencing. Participants were also administered the Relational Abilities Index, which was a computerised task assessing AARR in accordance with coordination, opposition and comparison (more than and less than). Additionally, as part of the Irish educational system, all children in primary schools are required to complete the Drumcondra test (i.e. Drumcondra Primary Mathematics Test and Drumcondra Primary Reading Test; Educational Research Centre, 2006, 2007) on an annual basis. These tests are group-­administered and are standardised tests of reading (assessing reading vocabulary and reading comprehension) and mathematics administered by their primary school teacher. The researchers were provided with the participants’ Drumcondra scores for English and Mathematics from the previous year to include within their analysis. An analysis of the measures at pre-intervention indicated that scores on the Relational Abilities Index were positively correlated with WASI full-scale IQ and block design, WIAT spelling, reading and numerical operations, WISC letter and number sequencing and Drumcondra scores for both English reading and Mathematics. Following these assessments, participants began either SMART or Scratch training with each group completing exactly 29  hours of training. SMART training

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aimed to increase AARR of coordination, opposition and comparison, while Scratch training aimed to teach computer coding skills. The results indicated that participants who received SMART training showed improvements in several domains that were not observed in the control condition. These included improvements in full-­ scale WASI IQ scores, block design scores measured by the WASI, all three subtests of the WIAT (i.e. spelling, reading and numerical operations), both subtests of the WISC (i.e. digit span and letter and number sequencing), Drumcondra Mathematics and relational ability scores (measured by the Relational Abilities Index). McLoughlin et al. (2020) extended on this research by recruiting a slightly larger sample size of 49 children (aged 6–10), who were assigned to either SMART or a chess condition. As in Hayes and Stewart (2016), all students were enrolled in a primary school in Ireland, and as such had participated in the annual Drumcondra tests for both English and Mathematics. The participants were also assessed using the Kaufman Brief Intelligence Test (KBIT-2; Kaufman & Kaufman, 2004) and for their personality traits using the Big Five Scale for Children (Gaio, 2012). The results indicated that the number of stages of SMART completed by participants was negatively associated with negative emotion (as measured by the Big Five Scale for Children), with higher scores of negative emotion correlated with a lower number of SMART stage completion. Further analyses indicated that the children who participated in SMART demonstrated an improvement on several domains that were not evidenced by the chess control group. Specifically, children within the SMART group demonstrated significant gains in non-verbal IQ, and the Drumcondra English subtests of vocabulary, comprehension and raw scores; however, children within the chess condition demonstrated improvement in mathematical implementation (as measured by the Drumcondra) that was not observed in the children exposed to SMART. This study will be explored further within Chap. 10 by the primary author of the paper (lucky you!). The findings of the studies outlined above each indicate the potential role of AARR in the expression, production and comprehension of language. Furthermore, these studies indicate that teaching protocols employing RFT have also successfully improved the linguistic ability of students as measured by several different standardised assessments. Although several studies have considered the utility of an RFT-based teaching strategy with children without any diagnoses, there is a dearth of peer-reviewed research examining the efficacy of these training protocols among more diverse populations and determining their efficacy on overall language ability and verbal repertoires. However, a recent study by Murphy et al. (2019) aimed to address this rather large gap in the research. The researchers compared a traditional tabletop teaching format to the Teacher IRAP (T-IRAP; see Chap. 3 for further information on the IRAP), which is an interactive computerised program, to teach AARR and NAARR coordination and distinction to five autistic children aged 7–12. All participants were assessed using the PPVT-4 and KBIT (Kaufman & Kaufman, 1990) pre- and post-training. Of the five participants, only one successfully completed the NAARR phase of training and was exposed to AARR training and this participant was also the only student who experienced a change in raw scores on the measures of the PPVT (a measure of receptive language) and the KBIT (a measurement of

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verbal and non-verbal intelligence). The results of this study not only demonstrate the role of AARR in language but also indicate the potential struggles and difficulties of establishing these repertoires in populations who demonstrate deficits and difficulties in this area while also considering the ethical question of “when is it appropriate to stop teaching a goal?” The science within this area is still somewhat new and there is further need for growth and expansion on the existing concepts; however, RFT offers a promising framework for the study of language across diverse populations, and it is hoped that this chapter (and indeed, this book overall) has provided an aid in your applied work, study and/or research! TLDR Cheat Sheet Event-related These are recordings of the voltage fluctuations or electrical activity (measured potential: through the scalp) within the brain that are linked to a specific event, such as being engaged in a cognitive task.

References Barnes, D., McCullagh, P. D., & Keenan, M. (1990). Equivalence class formation in non-hearing impaired children and hearing impaired children. The Analysis of Verbal Behavior, 8(1), 19–30. https://doi.org/10.1007/BF03392844 Barnes-Holmes, D., Regan, D., Barnes-Holmes, Y., Commins, S., Walsh, D., Stewart, I., Smeets, P. M., Whelan, R., & Dymond, S. (2005a). Relating derived relations as a model of analogical reasoning: Reaction times and event-related potentials. Journal of the Experimental Analysis of Behavior, 84(3), 435–451. https://doi.org/10.1901/jeab.2005/79-­04 Barnes-Holmes, D., Stauntan, C., Whelan, R., Barnes-Holmes, Y., Commins, S., Walsh, D., Stewart, I., Smeets, P. M., & Dymond, S. (2005b). Derived stimulus relations, semantic priming, and event-related potentials: Testing a behavioural theory of semantic networks. Journal of the Experimental Analysis of Behavior, 84(3), 417–433. https://doi.org/10.1901/jeab.2005.78-­04 Belisle, J., Paliliunas, D., Lauer, T., Giamanco, A., Lee, B., & Sickman, E. (2020). Derived relational responding and transformations of function in children: A review of applied behavior-­ analytic journals. The Analysis of Verbal Behavior, 36(1), 115–145. https://doi.org/10.1007/ s40616-­019-­00123-­z Cassidy, S., Roche, B., & Hayes, S. C. (2011). A relational frame training intervention to raise intelligence quotients: A pilot study. The Psychological Record, 61, 173–198. https://doi. org/10.1007/BF03395755 Chomsky, N. (1959). Review: Verbal behaviour by B. F. Skinner. Language, 35(1), 26–58. Dickins, D.  W., Singh, K.  D., Roberts, N., Burns, P., Downes, J.  J., Jimmieson, P., & Bentall, R. P. (2001). An fMRI study of stimulus equivalence. Neuroreport, 12(2), 405–411. https://doi. org/10.1097/00001756-­200102120-­00043 Duff, M. C., & Brown-Schmidt, S. (2012). The hippocampus and the flexible use and processing of language. Frontiers in Human Neuroscience, 6, 69. https://doi.org/10.3389/fnhum.2012.00069 Dunn, L. M., & Dunn, D. M. (2007). Peabody picture vocabulary test, fourth edition (PPVT-4). Pearson. Dunn, L. M., Dunn, D. M., Styles, B., & Sewell, J. (2009). The British picture vocabulary scale (3rd ed.). G L Assessment.

References

209

Educational Research Centre. (2006). Drumcondra primary mathematics test – Revised: Levels 3 – 6 administration manual and technical manual. Educational Research Centre. Educational Research Centre. (2007). Drumcondra primary reading test – Revised: Levels 3 – 6 administration manual and technical manual. Educational Research Centre. Gaio, V. (2012). Psychometric properties of the big five questionnaire-children (BFQ-C) in American adolescents. Arizona State University. Halvey, C., & Rehfeldt, R.  A. (2005). Expanding vocal requesting repertoires via relational responding in adults with severe developmental disabilities. Analysis of Verbal Behavior, 21(1), 13–25. https://doi.org/10.1007/BF03393007 Hayes, L.  J. (1996). Listening with understanding and speaking with meaning. Journal of the Experimental Analysis of Behavior, 65(1), 282–283. https://doi.org/10.1901/jeab.1996.65-­282 Hayes, J., & Stewart, I. (2016). Comparing the effects of derived relational training and computer coding on intellectual potential in school-age children. British Journal of Educational Psychology, 86(3), 397–411. https://doi.org/10.1111/bjep.12114 Hayes, J., Stewart, I., & McElwee, J. (2016). Assessing and training young children in same and different relations using the relational evaluation procedure (REP). The Psychological Record, 66(4), 547–561. https://doi.org/10.1007/s40732-­016-­0191-­2 Hughes, S., & Barnes-Holmes, D. (2014). Associative concept learning, stimulus equivalence, and relational frame theory: Working out the similarities and differences between human and non-­ human behavior. Journal of the Experimental Analysis of Behavior, 101(1), 156–160. https:// doi.org/10.1002/jeab.60 Kaufman, A.  S., & Kaufman, N.  L. (1990). The Kaufman brief intelligence test. American Guidance Service. Kaufman, A. S., & Kaufman, N. L. (2004). Kaufman brief intelligence test (2nd ed.). Wiley Online Library. Kirsten, E. B., & Stewart, I. (2021). Assessing the development of relational framing in young children. The Psychological Record. https://doi.org/10.1007/s40732-021-00457-y Lionello-DeNolf, K.  M. (2009). The search for symmetry: 25 years in review. Learning and Behavior, 37(2), 188–203. https://doi.org/10.3758/LB.37.2.188 Lipkens, R., Hayes, S. C., & Hayes, L. J. (1993). Longitudinal study of the development of derived relations in an infant. Journal of Experimental Child Psychology, 56(2), 201–239. https://doi. org/10.1006/jecp.1993.1032 Luciano, C., Becarra, I. G., & Valverde, M. R. (2007). The role of multiple-exemplar training and naming in establishing derived equivalence in an infant. Journal of the Experimental Analysis of Behavior, 87(3), 349–365. https://doi.org/10.1901/jeab.2007.08-­06 McLoughlin, S., Tyndall, I., Pereira, A., & Mulhern, T. (2020). Non-verbal IQ gains from relational operant training explain variance in educational attainment: An active-controlled feasibility study. Journal of Cognitive Enhancement, 5(1), 35–50. https://doi.org/10.1007/ s41465-­020-­00187-­z Mulhern, T., Stewart, I., & McElwee, J. (2017). Investigating relational framing of categorization in young children. The Psychological Record, 67(4), 519–536. https://doi.org/10.1007/ s40732-­017-­0255-­y Murphy, C., & Barnes-Holmes, D. (2009). Establishing derived manding for specific amounts with three children: An attempt at synthesizing Skinner’s verbal behavior with relational frame theory. The Psychological Record, 59(1), 75–91. https://doi.org/10.1007/BF03395650 Murphy, C., & Barnes-Holmes, D. (2010a). Establishing five derived mands in three adolescent boys with autism. Journal of Applied Behavior Analysis, 43(3), 537–541. https://doi. org/10.1901/jaba.2010.43-­537 Murphy, C., & Barnes-Holmes, D. (2010b). Establishing complex derived manding with children with and without a diagnosis of autism. The Psychological Record, 60(3), 489–503. https://doi. org/10.1007/BF03395723 Murphy, C., Lyons, K., Kelly, M., Barnes-Holmes, Y., & Barnes-Holmes, D. (2019). Using the teacher IRAP (T-IRAP) interactive computerized programme to teach complex flexible relational responding with children with diagnosed autism spectrum disorder. Behavior Analysis in Practice, 12(1), 52–65. https://doi.org/10.1007/s40617-­018-­00302-­9

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9  Relational Frame Theory and Language

O’Hora, D., Peláez, M., Barnes-Holmes, D., Rae, G., Robinson, K., & Chaudhary, T. (2008). Temporal relations and intelligence: Correlating relational performance with performance on the WAIS-III. The Psychological Record, 58(4), 569–584. https://doi.org/10.1007/BF03395638 O’Toole, C., & Barnes-Holmes, D. (2009). Three chronometric indices of relational responding as predictors of performance on a brief intelligence test: The importance of relational flexibility. The Psychological Record, 59, 119–132. https://doi.org/10.1007/BF03395652 Persicke, A., Tarbox, J., Ranick, J., & St Clair, M. (2012). Establishing metaphorical reasoning in children with autism. Research in Autism Spectrum Disorders, 6(2), 913–920. https://doi. org/10.1016/j.rasd.2011.12.007 Raaymakers, C., Garcia, Y., Cunningham, K., Krank, L., & Nemer-Kalser, L. (2019). A systematic review of derived verbal behavior research. Journal of Contextual Behavioral Science, 12, 128–148. https://doi.org/10.1016/j.jcbs.2019.02.006 Rehfeldt, R. A., & Root, S. L. (2005). Establishing derived requesting skills in adults with severe developmental disabilities. Journal of Applied Behavior Analysis, 38(1), 101–105. https://doi. org/10.1901/jaba.2005/106-­03 Roid, G. H. (2003). Stanford-Binet intelligence scales (5th ed.). Riverside Publishing. Rosales, R., & Rehfeldt, R. A. (2007). Contriving transitive conditioned establishing operations to establish derived manding skills in adults with severe developmental disabilities. Journal of Applied Behavior Analysis, 40(1), 105–121. https://doi.org/10.1901/jaba.2007.117-­05 Schlund, M. W., Cataldo, M. F., & Hoehn-Saric, R. (2008). Neural correlates of derived relational responding n tests of stimulus equivalence. Behavioral and Brain Functions, 4(6), 1–8. https:// doi.org/10.1186/1744-­9081-­4-­6 Stewart, I., McElwee, J., & Ming, S. (2013). Language generativity, response generalization, and derived relational responding. The Analysis of Verbal Behavior, 29, 137–155. https://doi. org/10.1007/BF03393131 Still, K., May, R.  J., Rehfeldt, R.  A., Whelan, R., & Dymond, S. (2015). Facilitating derived requesting skills with a touchscreen tablet computer for children with autism spectrum disorder. Research in Autism Spectrum Disorders, 19, 44–58. https://doi.org/10.1016/j.rasd.2015.04.006 Urcuioli, P. J., Wasserman, E. A., & Zentall, T. R. (2014). Associative concept learning in animals: Issues and opportunities. Journal of the Experimental Analysis of Behavior, 101(1), 165–170. https://doi.org/10.1002/jeab.62 Walsh, S., Horgan, J., May, R.  J., Dymond, S., & Whelan, R. (2014). Facilitating relational framing in children and individuals with developmental delay using the relational completion procedure. Journal of the Experimental Analysis of Behavior, 101(1), 51–60. https://doi. org/10.1002/jeab.66 Wechsler, D. (1992). Wechsler intelligence scale for children (3rd ed.). Psychological Corp. Wechsler, D. (1999). Wechsler abbreviated scale of intelligence (WASI). The Psychological Corp. Wechsler, D. (2004). Wechsler intelligence scale for children (4th ed.). Harcourt Assessment. Wechsler, D. (2005). Wechsler individual achievement test (2nd ed.). The Psychological Corp. Whelan, R., Cullinan, C., O’Donovan, A., & Valverde, M. R. (2005). Derived same and opposite relations procedure association and mediated priming. International Journal of Psychology and Psychological Therapy, 5(3), 247–264. Williams, K. T. (2007). Expressive vocabulary test (2nd ed.). Pearson. Zentall, T. R., Wasserman, E. A., & Urcuioli, P. J. (2014). Associative concept learning in animals. Journal of the Experimental Analysis of Behavior, 101(1), 130–151. https://doi. org/10.1002/jeab.55

Chapter 10

RFT and Intelligence Shane McLoughlin

This chapter aims to consider a relational frame theory (RFT) approach to human intelligence. Why should we care about it? Is relational framing part of intelligence or does relational framing underlie it? Can we use RFT to raise intelligence? The latter has been described as the “Holy Grail” of psychological research, so it seems worth discussing. This chapter is written by one RFT researcher amongst several in this space. With this in mind, I have attempted to make it clear that this is a personal account rather than consensus within the field. I do not think there is any such consensus amongst RFT researchers on this topic. As you may or may not be aware, intelligence research is quite sociologically controversial. This has led to this topic being greatly misunderstood, and so I hope to clarify what is and is not a mainstream idea here. Afterwards, I will discuss the RFT conception of intelligence and two popular RFT-inspired approaches to “brain training”. The findings from these studies, if I might borrow a statistical term, only “weakly correlate” with the public discourse around these studies. This chapter ends with a note of caution around current research on RFT and intelligence, calls for much more caution about how this research is discussed publicly and sets out ten research questions that have yet to be fully answered by RFT.

What Is Intelligence? Contrary to what many an undergraduate comes away from their degree believing, intelligence does appear to exist. For those who would prefer that it did not exist, the explanation for “what intelligence is” is maddeningly simple. But for you, dear reader who wants to know what is, in fact, correct, this is a good thing. Take a S. McLoughlin University of Birmingham, Birmingham, UK [email protected] © Springer Nature Switzerland AG 2022 T. Mulhern, Relational Frame Theory, https://doi.org/10.1007/978-3-031-19421-4_10

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random group of 100 questions that require abstract (i.e., responding that is based on symbolic rather than formal properties) reasoning ability to answer correctly. For example, consider the following questions: • “Spell onomatopoeia.” • “Which of the following four options is the correct definition of the pathetic fallacy?” • “What is eight times -94?” • “Circle, triangle, square, pentagon – what comes next?” • “11, 27, 38, 3, 92, 826, 203, 17, 91, 324  – repeat this number sequence backwards.” Then ask 1000 people to answer them, you can produce a score on this test for each person. If you then take an entirely different set of 100 questions that require abstract reasoning and do the same, (i) the people who score highly (relative to others) on one set of questions will also score highly (relative to others) on the other set of questions, (ii) the people who score in the middle on one set of questions will tend to score in the middle on the other set of questions, and (iii) those who score low on the first set of questions will score low on the second set of questions. The underlying factor that makes people score well, or not, across all cognitive tests is what Charles Spearman called “g” – general intelligence. So, what is IQ? To answer that, we should probably revise the above statement where I said: the people who score highly (relative to others) on one set of questions will also score highly (relative to others) on the other set of questions

And change this to: the people who score highly (relative to others their age) on one set of questions will also score highly (relative to others their age) on the other set of questions

When we produce an estimate of g and correct that score for age, we have IQ. But, how exactly would we do this? Here is one simple way: 1. We give a list of questions of varying difficulty to a group of people of the same age, with each person getting a total score. 2. We rank people’s scores by changing their total scores into a z-score. 3. We multiply people’s z-scores by what we want the standard deviation for the spread of data to be (usually 15, for IQ). 4. We add 100 to each. This leaves us with a total number of answers correct for each person at a particular age, such that the average score is 100, with most people scoring between 85 and 115 (i.e. plus or minus 1SD), and that any deviation from 100 represents how far above or below average intelligence you are compared with others your age. Now, imagine that life is one big intelligence test (see Gottfredson, 1997); a third set of questions, if you will. You guessed it... People’s IQ reliably predicts performance on things that require cognitive ability in real life: academic achievement (Zaboski et  al., 2018), job performance (Schmidt & Hunter, 2004), earnings (Gensowski,

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2018), social mobility (Forrest et  al., 2011), mate selection (van Leeuwen et  al., 2008), humour (Greengross & Miller, 2011), and many more variables besides. I am sure you have also heard that there are lots of different kinds of abilities (e.g. Gardner’s Multiple Intelligences, Sternberg’s Triarchic Theory): kinaesthetic intelligence, emotional intelligence, practical intelligence, and so on. This is false. If we break down the 100 questions from our hypothetical IQ test into sub-groups of questions that, in theory, require spatial rotation abilities to score well in, versus practical intelligence (or “street smarts”), or vocabulary, or mathematical intelligence, you will find that people who score highly (relative to others their age) in one kind of intelligence will also tend to score highly (relative to others their age) on all the other kinds of intelligence. Functionally speaking, therefore, they are not different kinds of intelligence. In fact, this general and well-replicated finding (see Warne & Burningham, 2019), called the positive manifold, outright falsifies the multiple intelligences idea as being something that is generally true. The academic consensus on this by experts in the area is that there is one main kind of intelligence, g, and critiques of this idea have been poorly formulated and extensively debunked (e.g., see Warne et al., 2019). Glad to have gotten that out of the way, once and for all. A brief corollary on the multiple intelligences idea, if I may. There can be specific deficits in what appear to be different kinds of intelligences. For example, if Wernicke’s area of the brain is damaged, this can affect speech comprehension without affecting, say, performance on a reaction speed test. Cases like this are the exception rather than the rule. Saying so is not any kind of slight against the affected individuals, it is merely distinguishing between what is generally the case for most people and those who are exceptions to what is generally the case. Men are generally taller than women. Alas, five foot six inches.

RFT and Intelligence In the last section, we had an example of different questions that might require symbolic reasoning to answer correctly. But what if we amend this slightly, adding in one additional bullet point? • “Spell onomatopoeia” • “Which of the following four options is the correct definition of the pathetic fallacy?” • “What is eight times -94?” • “Circle, triangle, square, pentagon – what comes next?” • “11, 27, 38, 3, 92, 826, 203, 17, 91, 324  – repeat this number sequence backwards.” • “WUG comes before YED, ZID comes after KIG.  Is WUG to YED like KIG to ZID?” In this example, we can see that the last “question” is a relational reasoning task of the sort we commonly encounter in RFT.  Specifically, this appears to be an

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analogy task. In RFT terms, this is the identification of a frame of coordination between two relations. Or as we might more commonly say, “A is to B as C is to D”. In RFT terms, if we are to break that down, what we are really saying is “the relationship that holds between A and B is the same kind of relationship that holds between C and D”. Curiously, analogy tasks are common components of IQ tests. Moreover, they tend to be more highly correlated with estimates of g than other components of IQ (Haier, 2016). A correlation of r = 1.0 means that two things are one and the same, while a correlation of r = 0.0 means that two things vary completely independently of one another. Could it be that relational reasoning is not just another component of g, but that relational reasoning abilities are sufficiently highly related that they and g can be considered to be the same thing? Cassidy et al. (2010) argue that they may be, and my colleagues and I have argued elsewhere that this is certainly plausible, and in line with findings from other fields (McLoughlin et al., 2020a). One way of testing Cassidy et al.’s (2010) thesis is to train relational reasoning skills and find out whether the real-world outcomes predicted by IQ change as a result. This is harder than it sounds. There are two main research programmes on this at present. The first is the SMART programme (Strengthening Mental Abilities with Relational Training; Cassidy et  al., 2016) and the second is the PEAK programme (Promoting the Emergence of Advanced Knowledge; see Dixon et al., 2014).

The SMART Programme The SMART programme can be found at www.raiseyouriq.com. It is based on the doctoral work of Dr. Sarah Cassidy, who was supervised by one of the RFT OGs, Dr. Bryan Roche (and we discussed this training protocol earlier in Chap. 3). Dr. Cassidy’s research culminated in a study in which 12 participants across two studies were trained in relational framing tasks and this coincided with large increases in IQ, greater than one standard deviation (equivalent to >15 IQ points). This needs to be put in perspective before we move on. Just how big is 15 points in IQ terms? I will try to give you a sense of this in the following few paragraphs. Let’s try to answer this by looking at the most popular form of cognitive training: working memory training. The idea here would be that if we train people to hold more pieces of information in their mind at a time, this will transfer to affect IQ. The most optimistic estimates of the effects of working memory training on IQ would suggest about a 2–3 point rise, on average, across about 20 different studies (Au et al., 2015). Most people believe this to be an overestimate though (see Simons et al., 2016). Similarly, other forms of cognitive training have been, given how well funded some of these research programmes have been, spectacularly unsuccessful (Sala et al., 2019). Some of the first IQ tests were developed during the aftermath of World War I by Terman and others and, to this day, IQ tests are used as one of the US army’s selection criteria. Tests such as the Armed Services Vocational Aptitude Battery (2022; just like the SAT, GRE, and other general knowledge tests) are IQ tests. It is illegal

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to induct anyone into the army with an IQ of below 81 (i.e., the bottom 10%), and a maximum of 20% of the US army can have an IQ between 81 and 93 (10th-31st percentile). What we need to appreciate here is that the US army does not have any incentive to turn people away if they do not have to. Bigger armies deter, or if not, win wars. What does it say about what the army has learned about the real-life implications of IQ (in terms of either performance in life and death situations, or the opportunity cost of training people) if those who have every reason not to turn anyone away turn people away on the basis of low IQ? A useful anecdote to ponder. 15 points is approximately the difference between being average/normal and not being allowed into the army. Perhaps, unsurprisingly, different occupations have different mean, median, minimum, and maximum IQ levels. For example, Harrell and Harrell (1945) gathered IQ data from 18,782 white enlisted men and ranked their civilian occupations based on their average IQs. What they found was that cognitively complex jobs (e.g. accountants, lawyers, engineers, auditors, chemists) tended to have the highest average IQs, with most scoring above 120 or so. Less cognitively complex jobs that involved repetition of a smaller number of learned tasks (e.g. teamster, farmhand, lumberjack and labourer) had lower mean IQ scores, scoring 95 or lower. However, there is something troubling in these data. The lowest mean IQ of the 74 occupations sampled was 87.7. This means that if you scored 1SD below average in terms of IQ, you would not be above average for any occupation. Let that sink in for a moment. That’s a full 15% or so of the general population who will never be competitive at work in any job. And this was in 1945! Many of these jobs have been phased out now and are taken by machines, meaning that the lowest mean IQ job is likely higher than 87.7 now. So while we’re running around pretending that IQ does not exist, perhaps the sociological issue of our time is being studiously ignored. 15 points is the difference between being of average IQ and not being competitive at any job. Remember, IQ points are not actual points one accumulates. They are about where you rank relative to other people. So back to SMART. N = 12 in the first paper, across two studies. Promising initial findings, no doubt, but extraordinary claims require extraordinary evidence. And more specifically, if we want to make generalisable claims (e.g., “SMART raises IQ”), we need to have a representative sample that allows us to generalise those findings. So what has been done since? It is my belief that there has been a steady trajectory of improvement of methodological quality over the years. Cassidy et al. (2016) conducted two studies in which participants received training in the first formal version of SMART. These tasks initially involved simple mutual entailment tasks with easy symmetrical relations like this: HEF is the same as LOD. Is LOD the same as HEF? Over 55 stages, the difficulty gradually scaled up to have more relational premises and more complex asymmetrical relations like this: JUB is more than REB. FEG is more than VOG.

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REB is more than LEP. JUB is less than VOG. Is FEG less than LEP? In the first study, they found a 23-point mean IQ increase. There was no control condition, so we technically cannot say that this increase was not due to the passing of time, or factors such as expectancy effects (after all, every time they log in they see “www.raiseyouriq.com,” giving the game away, so to speak), or inadvertent coaching effects by teachers who were not blind to what the researchers expected to find. In their second study, the assessors were blind to the condition, mitigating against the latter. They also had a larger sample size (N = 30), improving generalisability of these findings, but this was still a relatively small sample. Moreover, there may have been issues with test administration and/or participant motivation as 18 students were omitted due to having too much variability in their scores. Again, the findings revealed large effects of SMART relational training on IQ, and on more direct indices of educational aptitude. However, the latter might inadvertently be misleading, as “educational aptitude” was measured using the Differential Aptitude Test – for all intents and purposes, another IQ test as previously outlined. Others have since included “inactive control” conditions (i.e., participants are tested from pre- to post-intervention only, with no task in between), both those with (Colbert et al., 2018) and without (Thirus et al., 2016) existing vested interests in SMART. Our own studies, later on, started to bring in “active control” conditions to test whether SMART was better at increasing IQ than people who were, at minimum, cognitively engaged in things like computer coding (McLoughlin et al., 2022) and chess (McLoughlin et al., 2020b), and had larger samples. None of these studies are what we might call “adequately powered” (i.e. the samples were still not large enough) as randomised controlled trials though, and even the active controls were not perfect. For example, while computer coding and chess might keep participants cognitively engaged, only the SMART condition has “raiseyouriq” in the URL. Other studies have focused on factors such as dosage (whether engaging in more SMART training leads to higher IQ gains; Amd & Roche, 2018), and we published a small pilot study on the effects of SMART on reaction times (McLoughlin et al., 2018), again, with several design limitations rendering the results tentative.

The PEAK Programme Promoting the Emergence of Advanced Knowledge (PEAK) is a similar approach to relational framing training to SMART, focusing more so on those with developmental disabilities. PEAK is widely lauded by RFT proponents as some of the most impactful of RFT research. Reed and Luiselli (2016) reviewed some of the earlier PEAK literature and concluded: With the evidence to date, we are strongly convinced that the PEAK Relational Training System and the PEAK-DTM [direct training module] are conceptually sound, psychometrically robust, and an innovative advancement of conventional ABA tactics for teaching children and youth who have autism and other developmental disabilities. (p. 210)

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These sorts of points are echoed by several others (discussed in Witts, 2018). Once again, extraordinary claims require extraordinary evidence, as we know – and we must be cautious in interpreting the existing data within the field. The big claim of RFT is that relational framing skills underlie intelligence. In other words, what we call “intelligence”, in lay terms, is really just an expression of relational skills. The contribution of PEAK in terms of corroborating RFT here is perhaps ambiguous, as I will argue here. For example, let us consider May and Treadwell’s (2021) article: “Convergent Validity and Internal Consistency of the PEAK Pre-assessments: Direct Correlations of Intelligence and Relational Ability”. What does that mean though? PEAK assessment scores correlated with IQ very highly (r2  =  0.77) and with unstandardised IQ test scores (r2  =  0.93). When two things correlate very highly, they might be the same thing, as mentioned previously. However, we don’t know if one (i.e. IQ or relational skills) underlies the other, or whether they both are caused by a third variable (e.g. socioeconomic status) based on a correlational study. Therefore, we cannot conclude anything about the causal relationship between g and relational framing from these studies aside from the fact that they are, well, related somehow. That is, both RFT and intelligence experts would predict this same outcome. So, how would we know if relational framing skills are something other than expressions of g? If RFT’s thesis is correct, we might expect those (i.e., people generally, in a large sample) who are good at solving one kind of relational framing task successfully to not necessarily solve another kind of relational framing task successfully; after all, these are thought to be skills that are learned, and thereby learning one skill does not necessarily entail learning of another. For example, those who are good at temporal framing (e.g., a before/after relation) might not necessarily be good at hierarchical framing (member/class). Alternatively, if g theory is correct, we should observe that relational skills all intercorrelate (in more technical terms, if we run a factor analysis, most of the variance will be explained by a single factor). At a glance, there seems to be some evidence of there being multiple components of the PEAK assessments, suggesting that they are measuring something other than g. For example, Rowsey et al. (2015) and Rowsey et al. (2017) both found four separate components of the PEAK assessments. As ever though, we need to look under the hood to see what is really going on. I asked myself whether there was much room for bias and/or error in this research. N = 98 and N = 84, respectively in those studies are too small a sample for a factor analysis that can be considered anything other than preliminary and tentative; factor analyses often have hundreds of participants, with some guides suggesting that 10–20 participants are required per question included (see Carpenter, 2018). Don’t get me wrong though; I have published studies in which the sample was technically too small, a priori. However, I hope I have taken pains to stress, in this chapter and elsewhere, how uncertain ours may actually be. After looking at the limited PEAK data on the putative multi-factorial structure of relational framing, I then went looking in the broader relational reasoning literature: I put “relational reasoning factor analysis” into Google Scholar. It turns out that Alexander et al. (2016) found that a multi-factor relational reasoning approach

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generally resembling RFT concepts best fit the data. However, again, the researchers have built their careers on the idea that relational reasoning is different from g and can be differentiated out into various components, and so it makes sense to look for sources of bias. There was a much bigger sample size, which is a strength here. However, they only conducted confirmatory analyses, which is what you do when you have a preconception about what you expect to find. I am curious, though, to find out what an atheoretically and, therefore, a theoretically unbiased exploratory analysis would show. Alexander et al.’s (2016) results look promising, but I will stay on the fence for now. After all, the core of good science entails objectivity and scepticism, and this is especially important to practice in a field like RFT in which so many empirical matters are yet to be settled. So instead, we might turn to PEAK intervention studies, just as we did previously with SMART: if we can raise relational framing skills, can we see long-term gains in PEAK assessment performance and far transfer towards other tasks that don’t “wash out” over time? Some studies have shown some evidence for near transfer of PEAK training effects. For example, Dixon et al. (2017) used PEAK-E (equivalence) curriculum to establish some derived categorical responding in three children with disabilities. As the authors point out in the paper, this was a test of 1 of 183 PEAK-E curricula, meaning that 182 were untested here. And again, N = 3 does not allow us to draw any conclusions about the general applicability of PEAK, nor whether generalised principles can be inferred (i.e. whether this corroborates RFT in general). There are several such small-N studies. However, in the interest of finding out what is generally the case, I will focus on experimental group designs. Dixon et al. (2018) administered their skills assessment before and after a year-­ long intervention with 34 children with autism. There were 19 children in the PEAK condition and 15 in the control group, so this study was very much underpowered. Looking at the statistical analyses of the results, they did a Mann–Whitney U test for significant differences in change scores from pre- to post-intervention across the two conditions. Ideally, for this design, there would be a mixed ANOVA in which there was a test for a Time*Condition effect and thereby determine whether the change in the intervention group is significantly greater (in statistical terms) than the change in the control group. This non-parametric test choice may have been because of the small sample. This anomaly notwithstanding, we might still qualitatively assess the change scores to see if there is a general pattern. Upon examining the plot of change scores illustrated in the second figure of their published paper, we can see that the main difference between the change scores in the PEAK vs control condition might have come down to a single outlier, rather than the PEAK participants generally having larger change scores than the control. This made me look for the p-value; I wanted to know whether the result was close to being non-significant. I found that the result was just reported as p