Child and Adolescent Psychopathology [3 ed.] 111916995X, 9781119169956

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Child and Adolescent Psychopathology

Child and Adolescent Psychopathology Third Edition

Edited by

Theodore P. Beauchaine Stephen P. Hinshaw

Copyright © 2017 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, or on the Web at www.copyright.com. Requests to the publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, 201-748-6011, fax 201-748-6008, or online at www.wiley.com/go/permissions. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Readers should be aware that Internet Web sites offered as citations and/or sources for further information may have changed or disappeared between the time this was written and when it is read. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering professional services. If legal, accounting, medical, psychological or any other expert assistance is required, the services of a competent professional should be sought. For general information on our other products and services, please contact our Customer Care Department within the U.S. at 800-956-7739, outside the U.S. at 317-572-3986, or fax 317-572-4002. Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com. Library of Congress Cataloging-in-Publication Data Names: Beauchaine, Theodore P., editor. | Hinshaw, Stephen P., editor. Title: Child and adolescent psychopathology / edited By Theodore P. Beauchaine, Stephen P. Hinshaw. Description: Third edition. | Hoboken, N.J. : John Wiley & Sons Inc., [2017] | Includes bibliographical references and index. Identifiers: LCCN 2016026246 | ISBN 9781119169956 (cloth) | ISBN 9781119169963 (epdf) | ISBN 9781119169970 (epub) Subjects: LCSH: Child psychopathology. | Adolescent psychopathology. Classification: LCC RJ499 .C48237 2016 | DDC 618.92/89—dc23 LC record available at https://lccn.loc.gov/2016026246

Printed in the United States of America third edition HB Printing 10 9 8 7 6 5 4 3 2 1

Contents

Foreword

ix

Preface

xiii

List of Contributors

xvii

Part I THE DEVELOPMENTAL PSYCHOPATHOLOGY APPROACH TO UNDERSTANDING MENTAL ILLNESS 1

2

3

Developmental Psychopathology as a Scientific Discipline: A 21st-Century Perspective Stephen P. Hinshaw

3

Classifying Psychopathology: The DSM, Empirically Based Taxonomies, and the Research Domain Criteria Theodore P. Beauchaine and Daniel N. Klein

33

Genetic, Environmental, and Epigenetic Influences on Behavior Theodore P. Beauchaine, Lisa Gatzke-Kopp, and Ian R. Gizer

68

Part II VULNERABILITIES AND RISK FACTORS FOR PSYCHOPATHOLOGY 4

Risk and Resilience in Child and Adolescent Psychopathology Bruce E. Compas, Meredith Gruhn, and Alexandra H. Bettis

113

5

Child Maltreatment and Risk for Psychopathology Sara R. Jaffee

144

6

Impulsivity and Vulnerability to Psychopathology Emily Neuhaus and Theodore P. Beauchaine

178

7

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability to Psychopathology Jerome Kagan

213

v

vi Contents 8

9

The Adaptive Calibration Model of Stress Responsivity: Concepts, Findings, and Implications for Developmental Psychopathology Bruce J. Ellis, Marco Del Giudice, and Elizabeth A. Shirtcliff

237

Exposure to Teratogens as a Risk Factor for Psychopathology Lauren R. Doyle, Nicole A. Crocker, Susanna L. Fryer, and Sarah N. Mattson

277

10

Brain Injury and Vulnerability to Psychopathology Peter Arnett, Jessica E. Meyer, Victoria C. Merritt, Lisa Gatzke-Kopp, and Katherine E. Shannon Bowen

316

11

Emotion Dysregulation as a Vulnerability to Psychopathology Pamela M. Cole, Sarah E. Hall, and Nastassia J. Hajal

346

12

Neighborhood Effects on the Development of Delinquency Wesley G. Jennings and Nicholas M. Perez

387

Part III

EXTERNALIZING DISORDERS

13

Attention-Deficit/Hyperactivity Disorder Joel Nigg

14

Oppositional Defiant Disorder, Conduct Disorder, and Juvenile Delinquency Benjamin B. Lahey and Irwin D. Waldman

15

Substance Use Disorders Sandra A. Brown, Kristin L. Tomlinson, and Jennifer Winward

Part IV

407

449 497

INTERNALIZING DISORDERS

16

Anxiety Disorders Carl F. Weems and Wendy K. Silverman

531

17

Obsessive-Compulsive and Related Disorders Emily Ricketts, Deepika Bose, and John Piacentini

560

18

Depressive Disorders Daniel N. Klein, Brandon L. Goldstein, and Megan Finsaas

610

19

The Development of Borderline Personality and Self-Inflicted Injury Erin A. Kaufman, Sheila E. Crowell, and Mark F. Lenzenweger

642

Part V 20

21

OTHER DISORDERS

Trauma- and Stressor-Related Disorders in Infants, Children, and Adolescents Bruce D. Perry Bipolar Disorder Joseph C. Blader, Donna J. Roybal, Colin L. Sauder, and Gabrielle A. Carlson

683 706

Contents

vii

22

Autism Spectrum Disorder Susan Faja and Geraldine Dawson

745

23

Childhood-Onset Schizophrenia Robert F. Asarnow and Jennifer K. Forsyth

783

24

Eating Disorders Eric Stice and Deanna Linville

818

About the Authors

839

Author Index

841

Subject Index

875

Foreword

T

he remarkable third edition of Child and Adolescent Psychopathology represents an academic tour de force presenting the science of development associated with progressions to mental disorder. These processes are typically multiple and interacting. Indeed, their importance is clear, as neurodevelopmental models of psychopathology are dominant today. Sadly, both stigmatization—primarily from profound misunderstanding of mental disorders— and low economic status remain barriers to research and treatment (Martinez & Hinshaw, 2016; Merikangas et al., 2011). The chapters show remarkable breadth, including the challenge of integrating genetics, brain imaging, brain trauma, and prenatal and physiological as well as environmental variables in a clinically meaningful way. Clinicians have already benefitted from studies detailing patterns of continuity and discontinuity. Indeed, such investigations can help to prevent premature prediction and labeling that in itself may be harmful. These models, as well as the transactional nature of many dysfunctional behaviors, preclude simplistic causal pathways. Brain imaging has yet to contribute to clinical diagnosis and care, even though longitudinal and large-sample cross-sectional studies are starting to indicate subpopulation developmental brain phenotypes that have integrative potential for developmental psychopathology (Giedd et al., 2015; Gur, 2016). For example, it is possible that different developmental trajectories in attention-deficit/hyperactivity disorder reflect alternate clinical forms, as delayed cortical developmental may well relate to greater improvement in adolescence (Shaw et al., 2013). In our sister science of developmental neurobiology, true “clinical breakthroughs” have emerged, such as the use of rapamycin for tuberous sclerosis (Franz et al., 2006), and magnesium infusion for prevention of cerebral palsy (Rouse et al., 2008). These are large-effect-size interventions of interest to child psychiatrists because of associated psychopathologies in these conditions. Both were serendipitous discoveries, which by definition cannot be planned. At the same time, it remains troubling how much risk remains embedded in political arenas of community infrastructure (e.g., support for schools, housing, and law enforcement). We must transcend psychobiology to incorporate multiple levels of analysis, as amply shown in the following chapters. ix

x Foreword The Research Domain Criteria (RDoC; Cuthbert, 2014), highlighted in a number of chapters, do not represent a truly new approach. Dimensional as well as categorical measures have been hallmarks of NIH-funded psychiatric research for decades (Weinberger, Glick, & Klein, 2015), and neurobiologically founded, multiple-levels-of analysis research has contributed to key advances in our understanding of etiology since at least the mid-20th century (Beauchaine & Thayer, 2015). Evidence is mounting for age- and category-related interactions with dimensional brain MRI measures (e.g., Wiggins et al., 2016). In all, the RDoC provides a useful and surprisingly interactive set of measures. Finally, I found inspiration in the several authors who reviewed the predictive and possible treatment implications of regulatory physiological measures for developmental psychopathology. Ultimately, these models will be judged on when and how these regulatory processes can be changed, given the complexity of initial measurements and the potential for highly individualized treatment plans. One might read this entire volume as a basis for future personalized therapies, paralleling the present movement in medicine. In all, the chapters herald considerable promise for the future. Judith L. Rapoport, MD Chief, Child Psychiatry Branch National Institute of Mental Health 10 Center Drive Building 10, Room 3 N202 Bethesda, MD 20892-1600

REFERENCES Beauchaine, T. P., & Thayer, J. F. (2015). Heart rate variability as a transdiagnostic biomarker of psychopathology. International Journal of Psychophysiology, 98, 338–350. Cuthbert, B. N. (2014). The RDoC framework: Facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry, 13, 28–35. Franz, D. N., Leonard, J., Tudor, C., Chuck, G., Care, M., Sethuraman, G., . . . Crone, K. R. (2006). Rapamycin causes regression of astrocytomas in tuberous sclerosis complex. Annals of Neurology, 59, 490–498. Giedd, J. N., Raznahan, A., Alexander-Bloch, A., Schmitt, E., Gogtay, N., & Rapoport, J. L. (2015). Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development. Neuropsychopharmacology, 40, 43–49. Gur, R. C. (2016). Prospective community studies linking cognitive deficits to subclinical symptoms and a step toward precision medicine. JAMA Psychiatry, 73, 109–110.

Foreword

xi

Martinez, A., & Hinshaw, S. P. (2016). Mental health stigma: Theory, developmental issues, and research priorities. In D. Cicchetti (Ed.), Developmental psychopathology: Vol. 4. Risk, resilience, and intervention (3rd ed., pp. 997–1039). Hoboken, NJ: Wiley. Merikangas, K. R., He, J. P., Burstein, M., Swendsen, J., Avenevoli, S., Case, B., . . . Olfson, M. (2011). Service utilization for lifetime mental disorders in U.S. adolescents: Results of the National Comorbidity Survey-Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry, 50, 32–45. Rouse, D. J., Hirtz, D. G., Thom, E., Varner, M. W., Spong, C. Y., Mercer, B. M., . . . Roberts, J. M. (2008). A randomized, controlled trial of magnesium sulfate for the prevention of cerebral palsy. New England Journal of Medicine, 359, 895–905. Shaw, P., Malek, M., Watson, B., Greenstein, D., de Rossi, P., & Sharp, W. (2013). Trajectories of cerebral cortical development in childhood and adolescence and adult attention-deficit/hyperactivity disorder. Biological Psychiatry, 74, 599–606. Weinberger, D. R., Glick, I. D., & Klein, D. F. (2015). Whither Research Domain Criteria (RDoC)?: The good, the bad, and the ugly. JAMA Psychiatry, 72, 1161–1162. Wiggins, J. L., Brotman, M. A., Adleman, N. E., Kim, P., Oakes, A. H., Reynolds, R. C., . . . Leibenluft, E. (2016). Neural correlates of irritability in disruptive mood dysregulation and bipolar disorders. American Journal of Psychiatry. Epub ahead of print.

Preface

A

s we noted in the preface of the second edition of Child and Adolescent Psychopathology (Beauchaine & Hinshaw, 2013), global costs of mental illness—in terms of morbidity, mortality, and other forms of human suffering—are staggering. In many developed countries including the United States, over one third of individuals suffer from a major psychiatric disorder at some point in their lives (Kessler et al., 2009). In low- and middle-income countries, mental disorders account for 25% and 34%, respectively, of total years lived with disability, yet most of those affected receive no treatment (WHO World Mental Health Survey Consortium, 2004). Although treatment rates are slightly higher in wealthy countries, mental disorders continue to carry significant stigma. As a result, many avoid seeking help, and a lack of treatment parity remains for mental disorders vs. other health-related conditions (Hinshaw, 2007; Martinez & Hinshaw, 2016). When the two of us met nearly 18 years ago, knowledge of the causes of mental illnesses was quite limited compared to today. Although behavioral genetics studies had shown that most psychiatric disorders are at least moderately heritable, little was known about molecular genetic, neural, or hormonal mechanisms of heritability. Moreover, neither epigenetic alterations in gene expression, nor rare structural variants, had been identified as possible mechanisms through which environment might confer vulnerability to psychopathology. Many prevailing models of mental illness still pitted nature and nurture against each other as competing causes of psychopathology. Transactional models, in which biological vulnerabilities are presumed to interact with environmental risk factors to eventuate in mental illness, were few in number and limited in specification of neurobiological mechanisms, as advanced neuroimaging was in still in its infancy. Given limitations in technology, most of what we learned about mental illness has traditionally been obtained through observation and classification of symptoms (see Chapter 2 [Beauchaine & Klein]). Although useful in early stages of identifying different forms of mental illness, symptom classification often tells us little if anything about underlying causal processes—be they biological or environmental—that lead to particular disorders. In editing this book, we therefore sought authors with expertise in the developmental psychopathology perspective, which emerged only about 35 years ago (see Chapter 1 [Hinshaw]). This perspective follows from xiii

xiv Preface the observation that human behavioral traits—including those that predispose to psychopathology—almost always arise from complex transactions between biological vulnerabilities and exposure to environmental risks across development. For example, heritable conditions such as attention-deficit/hyperactivity disorder, depression, schizophrenia, and substance dependence are shaped strongly by environmental influences, and effects of environmentally transmitted risks such as child maltreatment are moderated by genes and other biological predispositions (see e.g., Beauchaine & McNulty, 2013). Furthermore, through epigenetic mechanisms, the expression of several genes that are implicated in behavior regulation can be altered by experience, including exposure to stress and trauma—findings that defy anachronistic distinctions derived from reductionistic models. Thus, we asked all authors to identify both biological and environmental contributors to psychopathology and to discuss how these interact and transact across development to amplify risk. This dynamic view of mental disorders served as the impetus for both the first and second editions of this book, and continues as a driving force behind the current third edition, which includes substantially updated material. Before the first edition was published, most graduate-level psychopathology texts were organized around the symptom-based approach to classifying mental illness, with limited consideration of the genetic and neural underpinnings of behavior or the interplay between biological vulnerabilities and environmental risk factors across development. However, in the nine years since the first edition was published, appreciation for the complexity of such transactions in the development of psychopathology has increased, and many new and exciting findings have emerged (see e.g., Beauchaine & Goodman, 2015). Elucidating causes of mental illness is an international public health concern. The better we understand etiology across all relevant levels of analysis, including genetic, neural, familial, and cultural (to name a few), the better position we are in to devise more effective prevention and intervention programs (Beauchaine, Neuhaus, Brenner, & Gatzke-Kopp, 2008). Thus, even though this text does not address treatment, we hope readers will keep in mind while digesting each chapter how important it is to identify causes of mental illness in our efforts to reduce human suffering. This motivation played a central role in the National Institute of Mental Health (2015) establishing the Research Domain Criteria (RDoC) project. RDoC is a collaboration between NIMH and researchers around the world to develop a neuroscience-informed system of characterizing psychopathology that identifies genetic, neural, hormonal, and social determinants of major behavioral systems that contribute to human function, and at the extremes, mental illness (see Chapter 2 [Beauchaine & Klein]). Readers will likely note that some disorders that are often addressed in psychopathology texts are not included in this book. For example, we do not cover developmental disorders or intellectual disability. In omitting these disorders, we are not implying that they are unimportant. Rather, the vast literature on developmental disabilities makes it difficult to cover the topic adequately in a text that already includes 24 chapters. Thus, we were left with a difficult choice, and we

Preface xv decided not to limit coverage of the conditions contained herein. We refer interested readers to other sources (e.g., Burack, Hodapp, Iarocci, & Zigler, 2011) for excellent coverage of this domain. We now invite you to join us in the quest for a deeper understanding of the development of mental disorders, which almost always originate in childhood and adolescence. We hope that our emphases on genetic and other biological vulnerabilities, and how these interact with environmental risk factors and contexts will challenge any preconceived notions you may have about what is “biological” and what is “environmental” in relation to normal and atypical development. We hope as well that our coverage will prompt the next generation of investigators, clinicians, and policymakers to pursue the daunting but essential goal of explaining, treating, and preventing the devastation that so often accompanies psychopathology. Theodore P. Beauchaine Stephen P. Hinshaw

REFERENCES Beauchaine, T. P., & Goodman, S. H. (Eds.). (2015). Ontogenic process models of psychopathology [Special Section]. Journal of Abnormal Psychology, 124, 771–877. Beauchaine, T. P., & Hinshaw, S. P. (2013). Preface. In T. P. Beauchaine & S. P. Hinshaw (Eds.), Child and adolescent psychopathology (2nd ed., pp. xi–xiii). Hoboken, NJ: Wiley. Beauchaine, T. P., & McNulty, T. (2013). Comorbidities and continuities as ontogenic processes: Toward a developmental spectrum model of externalizing behavior. Development and Psychopathology, 25, 1505–1528. Beauchaine, T. P., Neuhaus, E., Brenner, S. L., & Gatzke-Kopp, L. (2008). Ten good reasons to consider biological processes in prevention and intervention research. Development and Psychopathology, 20, 745–774. Burack, J. A., Hodapp, R. M., Iarocci, G., & Zigler, E. (Eds.). (2011). The Oxford handbook of intellectual disability and development. New York, NY: Oxford University Press. Hinshaw, S. P. (2007). The mark of shame: Stigma of mental illness and an agenda for change. New York, NY: Oxford University Press. Kessler, R. C., Aguilar-Gaxiola, S., Alonso, J., Chatterji, S., Lee, S., Ormel, J., . . . Wang, P. S. (2009). The global burden of mental disorders: An update from the WHO World Mental Health (WMH) Surveys. Epidemiologia e Psichiatria Sociale, 18, 23–33. Martinez, A., & Hinshaw, S. P. (2016). Mental health stigma: Theory, developmental issues, and research priorities. In D. Cicchetti (Ed.), Developmental psychopathology. Vol. 4: Risk, resilience, and intervention (3rd ed., pp. 997–1039). Hoboken, NJ: Wiley. National Institute of Mental Health. (2015). NIMH strategic plan for research. Retrieved from http://www.nimh.nih.gov/about/strategic-planning-reports/index.shtml WHO World Mental Health Survey Consortium. (2004). Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. Journal of the American Medical Association, 291, 2581–2590.

List of Contributors

Peter Arnett Pennsylvania State University

Sheila E. Crowell University of Utah

Robert F. Asarnow UCLA School of Medicine

Nicole A. Crocker San Francisco VA Medical Center

Theodore P. Beauchaine The Ohio State University

Geraldine Dawson Duke University School of Medicine

Alexandra H. Bettis Vanderbilt University Joseph C. Blader University of Texas Health Science Center at San Antonio Deepika Bose University of California, Los Angeles Sandra A. Brown University of California, San Diego Gabrielle A. Carlson State University of New York at Stony Brook

Marco Del Giudice University of New Mexico Lauren R. Doyle San Diego State University Bruce J. Ellis University of Utah Susan Faja Harvard Medical School Megan Finsaas State University of New York at Stony Brook Jennifer K. Forsyth UCLA Department of Psychology

Pamela M. Cole Pennsylvania State University

Susanna L. Fryer University of California San Francisco

Bruce E. Compas Vanderbilt University

Lisa Gatzke-Kopp Pennsylvania State University xvii

xviii

List of Contributors

Brandon L. Goldstein State University of New York at Stony Brook Meredith Gruhn Vanderbilt University Sarah E. Hall Wheaton College Nastassia J. Hajal University of California, Los Angeles Stephen P. Hinshaw University of California, Berkeley Sara R. Jaffee University of Pennsylvania Wesley G. Jennings University of South Florida Jerome Kagan Harvard University Erin A. Kaufman University of Utah Daniel N. Klein State University of New York at Stony Brook Benjamin B. Lahey University of Chicago Mark F. Lenzenweger State University of New York at Binghamton and Weill Cornell Medical College

Victoria C. Merritt Pennsylvania State University Jessica E. Meyer Pennsylvania State University Emily Neuhaus Seattle Children’s Research Institute Joel Nigg Oregon Health and Science University Nicholas M. Perez University of South Florida John Piacentini University of California, Los Angeles Bruce D. Perry Child Trauma Academy Houston, TX Emily Ricketts University of California, Los Angeles Donna J. Roybal University of Texas Health Science Center at San Antonio Colin L. Sauder University of Texas Health Science Center at San Antonio Katherine E. Shannon Bowen University of Washington Elizabeth A. Shirtcliff Iowa State University

Deanna Linville University of Oregon

Wendy K. Silverman Yale University School of Medicine

Sarah N. Mattson San Diego State University

Eric Stice Oregon Research Institute

List of Contributors Kristin L. Tomlinson University of California, San Diego

Carl F. Weems Iowa State University

Ian R. Gizer University of Missouri

Jennifer Winward University of California, San Diego

Irwin D. Waldman Emory University

xix

Child and Adolescent Psychopathology

PART I

THE DEVELOPMENTAL PSYCHOPATHOLOGY APPROACH TO UNDERSTANDING MENTAL ILLNESS

CHAPTER 1

Developmental Psychopathology as a Scientific Discipline A 21st-Century Perspective STEPHEN P. HINSHAW

I

nformation continues to accumulate, at an increasingly rapid pace, about the complex processes and mechanisms underlying the genesis and maintenance of child and adolescent forms of mental disorder. Our major goal for this, the third edition of Child and Adolescent Psychopathology—in chapters written by international experts on the topics of interest—is to present current information, particularly surrounding core vulnerabilities and risk factors for major dimensions and categories of behavioral and emotional problems of youth. As in our prior editions (Beauchaine & Hinshaw, 2008, 2013), we emphasize psychobiological vulnerabilities in the active context of environmental forces that shape development. Framed somewhat differently, an important objective for each chapter is to delineate potential ontogenic processes in progressions to mental disorder, signifying mechanisms underlying individual development, with the realization that multiple vulnerabilities and risk factors interact and transact in case-specific yet ultimately predictable ways (Beauchaine & Hinshaw, 2016; Beauchaine & McNulty, 2013; Hinshaw, 2015). Parallel to the first two editions, we do not prioritize assessment or treatment-related information in this book, given that such coverage would necessitate a second or even third volume (e.g., Mash & Barkley, 2006, 2007). Although the book’s title focuses on children and adolescents, I note immediately that psychopathology, in many (if not most) cases, unfolds across the entire lifespan. Most so-called adult manifestations of mental disorder have origins, if not outright symptom presentations, prior to age 18. Moreover, even the earliest-appearing forms of behavioral and emotional disturbance typically portend escalating symptoms and impairments that can persist for decades (e.g., Kessler, Berglund, Demler, Jin, & Walters, 2005). Because resilience is also a possibility (Luthar, 2006), lifespan 3

4 The Developmental Psychopathology Approach approaches to the topics of interest in this book are increasingly mandated for thorough understanding, carrying profound clinical as well as scientific implications. The child is the father of the man—and the mother of the woman—given that adults emerge from a cascading set of processes set in motion years before. Before delving further, I immediately acknowledge the major debt that Ted Beauchaine and I owe to all of our contributors, as each is a major force in the scientific literature. We asked them to integrate state-of-the-art knowledge into the chapters that follow. Indeed, given the fast-escalating sophistication of mechanistic accounts of the development of psychopathology—which are now integrating genetic vulnerability and brain architecture in the presence of contextual forces across development, providing unprecedented levels of synthesis (Hinshaw, 2015)— no current compendium can afford to rest on the laurels of previous editions. The field’s work is emerging at ever-more-detailed levels of analysis, with the promise of accounts that should, in the future, better inform evidence-based practice in the context of validated knowledge structures that can be applied to the clinical phenomena under consideration. In this initial chapter, I delineate the clinical and policy-related importance of the subject matter at hand, explicate core principles of developmental psychopathology (DP), and provide a general overview of the sequence of the chapters and their contents. In so doing I aim to set the stage for the cutting-edge advances and wisdom provided in the remainder of the volume.

RELEVANCE AND IMPORTANCE The subject matter under consideration in this volume is at once clinically compelling and conceptually fascinating. Mental disorders yield substantial impairment, pain, and suffering for individuals, families, communities, and even cultures. The levels of personal and family tragedy involved are often devastating (Hinshaw, 2008a). At the same time, multifactorial vulnerabilities and risk factors— along with the complex, transactional developmental progressions that produce symptoms and impairments—challenge investigators from disciplines as diverse as neuroscience, genomics, public health, psychology, psychiatry, and public policy to emerge with new insights and syntheses. Overall, the clinical need is urgent and the scientific motivation compelling. I begin with the concept of impairment. As elaborated in nearly every working guide to psychopathology (e.g., American Psychiatric Association, 2013; Wakefield, 1992), a designation of mental illness mandates, beyond behavior patterns or symptoms, that the individual in question display impairment or “harm” before a diagnosis is made. Clinically, then, attention must be paid to the often-excruciating pain and suffering attending to conditions as diverse as autism-spectrum disorders, various sequelae of maltreatment, severe attention deficits and impulsivity, interpersonal aggression, significant anxiety and mood disorders, thought disorders (including schizophrenia), eating-related conditions, self-destructive behavior patterns and personality configurations, and substance use disorders. Each is

Developmental Psychopathology as a Scientific Discipline

5

linked to setback and suffering, societal reverberations, and significant costs, the latter measurable in terms of huge expenditures borne by society, not related just to treatment per se but to the long-range outcomes of interpersonal, educational, and vocational failure that often attend to mental disorders (for an example of the huge costs linked to attention-deficit/hyperactivity disorder [ADHD], see Hinshaw & Scheffler, 2014). Of course, impairment and harm—whether personal or experienced by others— are not sufficient for designating individuals as suffering from a mental disorder. In the view of Wakefield (1992), both harm (which involves a value-laden component) and dysfunction (a scientific construct) are required before mental illness should be diagnosed. Per Wakefield, dysfunction is “the failure of a mental mechanism to perform a natural function for which it was designed by evolution” (p. 373). Although mental health fields lack the objective markers and pathognomonic signs1 as those found in medicine and neurology (see Chapter 2 [Beauchaine & Klein]), our aim for the accumulated work in the present volume is to propel knowledge of dysfunctional mechanisms related to child and adolescent psychopathology. At the same time, findings from each chapter remind us that the origins of mental health conditions are reciprocal, dynamic, multilevel, and fully linked with processes linked to environmental context. Not every aspect of psychopathology is necessarily impairing. At the level of evolution, it cannot be the case that mental disorder is inevitably or inexorably linked to personal failure or reduced fecundity; otherwise, how would conditions such as severe thought and mood disorders have perpetuated across human history (for evolutionary psychological explanations of mental disorder, see Neese, 2005)? Partial genetic loadings or vulnerabilities in biological relatives may well carry adaptive advantage; at least some aspects of symptoms could yield inspiration or thriving. Still, clinical and population-level facts regarding impairment linked to mental illness are stark. Emotional and behavioral problems among children and adolescents are distressingly prevalent and often lead to serious impairments in such crucial life domains as academic achievement, interpersonal competencies, and independent living skills (for thorough accounts, see Mash & Barkley, 2014). These conditions incur intensive pain for individuals, families, and communities at large, delimiting life opportunities and triggering major burdens for caregivers, school districts, and health care systems. In short, far too many young lives are compromised by mental illness. Moreover, child and adolescent conditions and mental-health-related issues are growing in impact. As just one harrowing example, recent data from the World Health Organization reveal that, worldwide, the number-one cause of death for girls aged 15–19 years is now suicide (World Health Organization, 2014). 1. A pathognomonic sign is an indicator, usually biological, that at once (1) proves that a person suffers from a disease of known etiology, and (2) eliminates all other disease processes as potential causes. For a detailed discussion of the role of pathognomonic signs in medicine vs. psychiatry/psychology, see Beauchaine and Thayer (2015).

6 The Developmental Psychopathology Approach Rates of self-injury have escalated rapidly over the past decades, and conditions like autism and ADHD are undergoing huge increases in diagnosed prevalence (e.g., Visser et al., 2014). The age of onset of serious mood disorders appears to be dropping, signaling the importance of contextual “push” in unearthing vulnerability (Hinshaw, 2009). In both the developing and developed world, serious mental disorder in youth portends major life consequences and even tragedy (see, for example, Sawyer et al., 2002). Moving beyond childhood and adolescence per se, each year the Global Burden of Disease findings convey that a number of mental health conditions (along with neurological and substance use disorders) are among the world’s most impairing illnesses (Whiteford, Ferrari, Degenhardt, Feigin, & Vos, 2015). Indeed, the variable called “years lived with disability” is dominated by individuals with mental disorders in our current era, on par with and often surpassing so-called physical diseases. By the time of adulthood, economic costs related to mental illness escalate with respect to employment-related impairments, yielding huge public-entitlement expenditures and lack of productivity. In short, from a number of important lenses, mental disorders are tragically impairing, robbing individuals of opportunities to thrive and be productive, often in the prime of their lives. If readers sense a call to action in these words, they have read my intentions precisely. Crucially, mental health and physical health are inexplicably intertwined. It is now well known that serious mental disorder is associated with reductions in life expectancy averaging from 10 to 25 years (e.g., Chang et al., 2011). The reasons here are plentiful: high-risk lifestyles, lack of access to medical care, suicide, homicide, co-occurring chronic (e.g., cardiovascular disease; diabetes), and infectious (e.g., HIV) illnesses, and related unhealthy practices such as smoking and substance abuse. Even nonpsychotic disorders (e.g., ADHD; many forms of depression) are linked to long-term health risks (e.g., Barkley, Murphy, & Fischer, 2008). Recent findings reveal links between a range of mental disorders and a startling list of chronic physical illnesses (Scott et al., 2016). Given this set of enormously costly, persistent, and deeply human consequences and needs, why not rely on traditional clinical efforts in psychology and psychiatry for solutions, given their long, venerable histories? As detailed in earlier accounts, however, these efforts have led to static views of psychopathology, with priority given to categorical diagnoses that inevitably lump together individuals with substantially different etiologic pathways into the same “condition” (e.g., Cicchetti, 1984, 1990). Moreover, the reciprocally deterministic nature of development, both typical and atypical, is not well captured by such static diagnostic systems (or nosologies, see Chapter 2 [Beauchaine & Klein]). Because of the huge expansion of knowledge in a host of related fields and subfields, the complex yet compelling perspectives offered by DP have taken hold with increasing rapidity, providing a call to investigators from a host of seemingly disparate disciplines regarding the promise of uncovering relevant mechanisms. Absent the multifaceted nature of DP models and paradigms, traditional perspectives are too often sterile

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and impoverished, carrying huge potential for treatments and prevention efforts to be directed at the wrong targets. Despite scientific and clinical urgency surrounding this entire topic, barriers stand in the way of increased scientific understanding and access to evidence-based treatment. Perhaps the primary issue is that mental disturbance, at any age, remains highly stigmatized (e.g., Hinshaw, 2007; Hinshaw & Stier, 2008; Martinez & Hinshaw, 2016). Intensive stigma and shame—related to the unpredictability of the behavior patterns in question, the threat they convey to perceivers’ well-being, and their media-propelled linkages to violence and incompetence—too often preclude help seeking, prevent empathic responses, and serve to render mental health a lower priority than physical health, despite inextricable linkages between the two. Depressingly, although public knowledge of mental illness has grown considerably since the 1950s, the U.S. public is far more likely to link mental illness with dangerousness than in the past (see Phelan, Link, Stueve, & Pescosolido, 2000). Moreover, rates of stigma and social distance related to mental illness have not changed appreciably in recent decades (Pescosolido et al., 2010). Reasons are complex but may relate to (a) increased numbers of seriously impaired individuals on the streets, without needed community services and resources; (b) enhanced public awareness that “dangerousness” is one of the few mandates for involuntary commitment to hospitals—along with frequent media attention linking mental illness to mass shootings, oftentimes inaccurately; and (c) the tenuousness of evidence that biogenetic ascriptions to mental illness (i.e., that it is a “brain disease” or a “disease like any other”) can eliminate stigmatization (see Haslam & Kvaale, 2015; Martinez, Piff, Mendoza-Denton, & Hinshaw, 2011; Pescosolido et al., 2010). Indeed, although biological perspectives are a necessary antidote to the “blaming the family” and “castigating the individual” perspectives that dominated psychology and psychiatry for much of the 20th century, their reductionistic promotion is neither accurate nor aiding the cause of stigma reduction, in part because they appear to promote pessimism and dehumanization. Instead, DP perspectives offer complex as opposed to simplistic or reductionistic conceptions of mental disorder, potentially leading to appreciation of the multidetermined biological and contextual factors related to psychopathology instead of personal or family weakness or blame, or notions of genetic flaw (e.g., Haslam & Kvaale, 2015; Martinez & Hinshaw, 2016). In all, despite major advances in both basic science and clinical applications in recent years, as highlighted in the following chapters, the field’s knowledge of developing brains and minds in multiple, interacting contexts is still rudimentary. It is hard to imagine otherwise, given the sheer complexity of the subject matter under consideration. As noted in introductory chapters to the earlier editions of this volume (Hinshaw, 2008b, 2013), the trajectory of human prenatal neural development is nothing short of staggering, with literally thousands of new neurons proliferating during each second of development after the first few weeks following conception, as well as massive pruning and synaptogenesis in the first several years of life. Still, for those who enjoy a challenge and are excited by questions that will take both many

8 The Developmental Psychopathology Approach decades and many great minds and scientific teams to answer—with the potential payoff of bettering the human condition—the hope is that this volume will serve as a call to join the major scientific and clinical efforts so urgently needed. Indeed, if the field is to continue to make headway toward understanding, treating, and preventing the serious clinical conditions that emerge during childhood and adolescence, the best minds of the current and forthcoming generations of scholars and clinicians need to join the effort. At this point, I provide a review of core axioms and principles of DP. These points reflect the multidisciplinarity and transactional nature of the field, signifying that static models and unidimensional conceptions are simply not able to explain the fascinating and troubling development of maladaptive behavior patterns comprising the domain of psychopathology.

PRINCIPLES OF DP Many of the conceptual bases for integrating developmental principles and models into the study of child and adolescent psychopathology have been present for several centuries, spanning diverse fields and disciplines (e.g., Cicchetti, 1990). Yet it is only in the past 40 years that DP has taken formal shape as a perspective on behavioral and emotional disturbance throughout the lifespan, and as a major conceptual guidepost for the study of both normal and atypical development. During this period, DP has exerted a major force on clinical child psychology, child psychiatry, developmental psychology, developmental neuroscience, and a number of other disciplines in both behavioral and neurological sciences. Not only have new courses been formed at major universities, but journals have been created and new paradigms of conceptualizing mental disorder have gained traction (Insel et al., 2010; see Chapter 2 [Beauchaine & Klein]). It is remarkable how pervasive the DP perspective has become, galvanizing a host of clinical and scientific efforts and in the process becoming mainstream. DP simultaneously comprises a theoretical model regarding the origins of mental disorders, a multidisciplinary approach linking principles of normative development to the genesis and maintenance of psychopathology, and a scientific discipline closely tied to clinical child and adolescent psychology and psychiatry but transcending the usual diagnosis-based emphases of these fields (Cicchetti, 2016; Lewis & Randolph, 2014). Through its focus on the dynamic interplay of biology and context, genes and environments, and transactional processes linking multilevel influences to the development of healthy and atypical functioning, DP has come to dominate current conceptual models of psychopathology. Many of its core ideas emerge from disciplines such as philosophy, systems theory, and embryology (see Gottlieb & Willoughby, 2006, for elaboration). The syntheses represented in this volume, reflecting DP’s continuing growth into the first two decades of the 21st century, are cutting-edge, given the major knowledge explosion in recent years, related largely to greater understanding of psychobiological influences as they transact with contextual forces.

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What characterizes a truly developmental view of psychopathology, versus descriptive, symptom-focused presentations dominating most classification systems? DP’s originators contended with this core question (e.g., Achenbach, 1974; Cicchetti, 1990; Rutter & Sroufe, 1984; Sroufe & Rutter, 2000), and current syntheses still grapple with the fundamental issues involved (Cicchetti, 2016; Lewis & Rudolph, 2014). From my perspective the key issues constitute multidisciplinarity; acknowledgment of dynamic, multilevel processes; and appreciation of systems-level change in producing developmental transitions (whether the systems are biological or social). Despite the many gains that have been made, it is important to realize at the same time how far we must still travel to comprehend the development and maintenance of psychopathology via the tools and models of DP. The trail ahead is long and steep. I list several core points that are commonly viewed as central to the DP perspective. These include the necessity of (a) interweaving studies of normal development and pathological functioning into a true synthesis; (b) examining developmental continuities and discontinuities of traits, behavior patterns, emotional responses, and disorders; (c) exploring both risk and protective factors and their interplay, so that competence, strength, and resilience as well as pathology and impairment can be understood; (d) involving reciprocal, transactional models of influence in the field’s causal models through which linear patterns of association and causation are replaced by probabilistic, dynamic, nonlinear, and complex conceptual models; and (e) capturing the importance of both psychobiological vulnerabilities and social/cultural context in understanding the function of behavioral and emotional patterns. Three related principles bear emphasis: 1. Multiple pathways to pathology exist. Indeed, disparate routes may lead to behaviorally indistinguishable conditions or outcomes, exemplifying the construct of equifinality. For example, aggressive behavior can result from physical abuse, from a heritable tendency toward disinhibition, from injury to the frontal lobes, from coercive parenting interchanges with the developing child, from prenatal and perinatal risk factors acting in concert with early experiences of insecure attachment or parental rejection, or—as is probably most often the case—from different combinations of these vulnerabilities and risk factors. A key problem with static nosologies is their assumption that everyone receiving a similar psychiatric diagnosis has the “same” underlying patterns and processes of psychopathology. Similarly, multifinality pertains when a given vulnerability, risk factor, or initial state fans out into disparate outcomes across different individuals (Cicchetti & Rogosch, 1996). Maltreatment may or may not lead to severe maladaptation, depending on a host of intervening factors. As another example, extremes of inhibited temperament may induce intense shyness and social withdrawal; but other, healthier outcomes are also possible, depending on the presence or absence of additional risk or protective factors.

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The Developmental Psychopathology Approach 2. DP models often place emphasis on person-centered research designs, in which the typical practice of examining global effects of one or more risk/protective variables across an entire sample or population is supplemented by consideration of unique subgroups—whether defined by genotypes, personality variables, socialization practices, neighborhoods, or other key factors—and their unique developmental journeys across the lifespan (see Bergman, von Eye, & Magnusson, 2006). From a slightly different perspective, developmental continuities and discontinuities may well differ across homogeneous subgroups of participants. Even in variable-centered research, key moderator variables and mediator processes must always be considered (e.g., Hinshaw, 2002; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001), to ensure that (a) results are applicable to subsets of participants grouped on moderator variable of interest (males versus females, those from different ethnic groups, or those with different patterns of comorbidity) and (b) underlying mechanisms of change, gleaned from mediator variables, are taken into account. 3. Given the rapid growth in recent years of genomic models as well as brain imaging methods, DP researchers in the 21st century must pay increasing attention to the role of the brain, and neuroscientific principles in general, toward accounting for the wide range of extant pathologies and their devastating effects. The field has come a long way from the middle of the 20th century, when biological and temperamental factors were virtually ignored in accounts of child development and psychopathology. Again, however, progress will be stalled if the psychosocial reductionism of prior generations is replaced by biological and genetic reductionism in the current era. A key antidote is for students and investigators to embrace a multiple-levels-of-analysis approach, integrating across genes and gene products, neural systems, and temperamental traits and core behavioral patterns, in contexts of families, schools, and neighborhoods, including the general culture (Cicchetti, 2008; Insel et al., 2010). Isolated, single-factor or single-level models and paradigms are inadequate to the task.

In other words, the greatest potential for progress in the DP field is made when investigators travel back and forth between “micro” and “macro” levels—including intermediate steps or pathways—to understand mechanisms that underlie development of adjustment and maladjustment. The essential task is to link events at the level of genes (e.g., genetic polymorphisms; transcription and translation), neurotransmitters, and neuroanatomical development, into individual differences in temperament, social cognition, and emotional response patterns. At the same time, such bottom-up conceptions must be supplemented by top-down understanding of ways in which family interaction patterns, peer relations, school factors, and neighborhood/community variables influence the developing, plastic brain, even at the level of gene expression (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Overall, progress toward understanding pathological behavior will require

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multidisciplinary efforts in which investigators ranging from geneticists and biochemists, scientists focusing on basic psychological processes and individual psychopathology, experts on family and neighborhood processes, examiners of clinical service systems, and public health officials as well as policy experts must work collaboratively and in increasingly diversified ways. The phenomena under consideration are too complex, too dynamic, and too multifaceted to be understood by an exclusive focus on psychobiological processes, family factors, peer processes, or cultural factors in isolation. Performing the necessary kinds of investigations often mandates large-scale, complex, and interdisciplinary work, necessitating collaborations across traditional disciplinary boundaries. Note that key concepts and principles of DP have been stated and restated across a large number of articles, chapters, and books. Indeed, detailed discussion could easily fill a volume unto itself. The challenge for the current chapter is to encapsulate several core tenets, in the service of foreshadowing and illuminating content on specific processes and specific mental dimensions and disorders.

Normal and Atypical Development Are Mutually Informative As opposed to the study of discrete, mutually exclusive categories of disorder, DP models emphasize that nearly all relevant phenomena represent aberrations in continua of normal developmental pathways and processes—and, accordingly, that without understanding typical development, the study of pathology will remain incomplete and decontextualized. As just one example, related to a research area within my own expertise, illuminating the nature of ADHD requires thorough understanding of normative development of attention, impulse control, and self-regulation (e.g., Barkley, 2015; Hinshaw & Scheffler, 2014; Nigg, Hinshaw, & Huang-Pollack, 2006; Sonuga-Barke, Bitsakou, & Thompson, 2010; see also Chapter 13 [Nigg]). Similarly, investigations of autism must account for the development of interpersonal awareness and empathy, as well as social motivation—which typically takes place over the first several years of life—to gain understanding of the devastating consequences of failure to attain such development (Dawson & Toth, 2006; see also Chapter 22 [Faja & Dawson]). Additional examples exist across all forms of disordered emotion and behavior. Although considered set breaking at the outset of modern DP conceptions, this point is now taken for granted: Few would doubt the wisdom of understanding developmental sequences and processes associated with healthy outcomes as extremely relevant to elucidation of pathology. Intriguingly, however, the process is conceptualized as bidirectional, as investigations of pathological conditions—sometimes referred to as adaptational failures in the language of DP (Sroufe, 1997)—can and should provide a unique perspective on normative development. Thus, the study of disrupted developmental progressions can and should facilitate our understanding of what is normative. This core tenet of DP, of mutual interplay between normality and pathology, is now

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espoused widely. Examples abound in neurology, where the study of disrupted neural systems enhances understanding of healthy brain functioning (Gazzaniga, Ivry, & Mangun, 2014). But just how appropriate is this perspective for DP? Outside of neurological formulations, where single lesions or single genes are investigated quite specifically, can studies of psychopathology inform normal development? It is commonly accepted that greater knowledge of basic emotion, cognition, attention, memory, social awareness, self-regulation, and so forth feeds into understanding of pathology. Indeed, almost no forms of mental disorder constitute clearly demarcated, qualitatively distinct categories or taxa, so processes applying to individuals near the peak of the bell curve are likely to apply to those further out on the continuum. Yet regarding the other direction—the informing of normal-range processes from study of the abnormal—we can legitimately ask what has been learned from far more complex developmental processes linked to mental disorder as regards application to normative development. In other words, in the absence of surgical lesions in certain brain tracts or single-gene forms of pathology such as phenylketonuria, can the far messier domain of psychopathology cycle back to inform developmental science? Examples are becoming more apparent. The horrific experiments of nature that occurred when infants and toddlers in Eastern Europe were subjected to harsh, sterile institutionalization in large orphanages several decades ago, which included a bare minimum of human contact, provide important data (see O’Connor, 2006, for review). From accumulated research evidence, it is now clear that the more months—during infancy, toddlerhood, and the preschool years—a child is exposed to such conditions, the worse his or her developmental outcomes, both cognitively and socially. In short, the longer the periods of deprivation, the lower the chances for recovery. Intriguingly, the most common behavioral outcomes related to such early deprivation include inattention and overactivity, rather than conduct problems per se—a clear example of equifinality, given that heritable risk is the strongest contributor to such problems in more normative samples (see Kennedy et al., 2016; Kreppner et al., 2001). Moreover, assignment to foster care can mitigate such developmental risk, if performed during the second or third year of life (Nelson et al., 2008). Indeed, for previously institutionalized girls, random assignment to foster care, compared to continued institutionalization, led to improvements in internalizing behavior patterns, mediated by the gaining of attachment security via change from institutional care to family placements (McLaughlin, Zeanah, Fox, & Nelson, 2012). Thus, even in a harshly abandoned and deprived sample, attachment processes were implicated in reductions of anxiety and depression. Whereas mediators of competence in more normative samples are still open to exploration, the extent of social and cognitive “catch-up” following removal from harsh institutional care is potentially informative about normal-range development of secure relationships and cognitive performance.

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As reviewed in introductory chapters of previous editions of this volume (Hinshaw, 2008b, 2013), further examples exist from the domains of ADHD and autism-spectrum disorders. For the former, information about disruptions to inhibitory control and reward-related mechanisms from individuals with clinical levels of the relevant symptoms informs developmental science about normative development of self-regulation and intrinsic motivation. Regarding autism, intensive investigation of social deficits has relevance to understanding normative development of “theory of mind” during the toddler and preschool years. Other examples abound outside the realm of neurodevelopmental disorders, in the areas of depression, anxiety, and response to trauma. Certainly, symptoms and systems at play in all such domains are more complex than in classic cases from neurology, but two-way communication between the atypical and typical is possible. If our text had a “post-chapter quiz”—or suggestions for extra credit for readers and students—I would suggest there be mandated exploration, when examining relevant literature and pertinent clinical cases, of specific ways in which knowledge of pathological patterns can inform normative development. My guess is that this task could be an eye-opener for everyone involved.

Developmental Continuities and Discontinuities With this principle, it is commonly asserted that DP models must emphasize both continuous and discontinuous processes at work in the development of pathology. Taking the specific example of externalizing and antisocial behavior, it is well known from a number of longitudinal investigations that antisocial behaviors show strong stability across time, meaning that correlations are substantial between early measures of aggressive and antisocial tendencies and those made at later times. In other words, rank order remains relatively preserved, such that the most aggressive individuals at early points in development remain highly aggressive, compared to others, across development. But does this well-replicated finding mean that the precise forms of externalizing, antisocial behavior remain constant? Clearly not, given that children who exhibit extreme temper tantrums and defiance during toddlerhood and preschool years are not especially likely to exhibit high rates of tantrums during adolescence. Rather, they have a strong likelihood of displaying early verbal aggression and then beyond-normative physical aggression in grade school, excessive covert antisocial behaviors in preadolescence, and high rates of delinquency by their teen years, followed by adult manifestations of antisocial behavior after adolescence, including partner abuse (e.g., Moffitt, 2006). In short, continuities exist, but these are heterotypic in nature, as the actual form of the underlying antisocial trait changes form with development. The implications are profound. That is, investigators of continuity of psychopathology must take into account developmental progressions. Continuity may not be linear or static: During development, new life opportunities and brain maturation portend ascension of new

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forms of pathological behavior. Predictability may well exist, but in complex and nonlinear fashion (see Hinshaw et al., 2012; Meza, Owens, & Hinshaw, 2016; and Swanson, Owens, & Hinshaw, 2014, for the example of emerging self-harm as girls with ADHD grow into their adult years). Another important consideration is that patterns of continuity may differ considerably across separable subgroups with different developmental patterns or trajectories. Not all highly aggressive or antisocial children remain so, as some are prone to desist with the transition to adolescence. Others, however—the so-called early starter or life-course-persistent subgroup—maintain high rates through at least early adulthood, although, as noted in the paragraph above, the specific forms of the antisocial actions change across development. Yet not all early starters persist. In addition, a large subset of youth do not display major externalizing problems in childhood but instead shows a sharp increase with adolescence (Moffitt, 2006). Understanding such continuities and discontinuities via relatively homogeneous subgroups is likely to yield greater understanding than plots of overall curves or “growth.” Sophisticated statistical strategies (for example, growth mixture modeling) are increasingly used to aid and abet this search for separable trajectories or classes defined on patterns of change of the relevant dependent variable (Muthén et al., 2002). In all, continuities abound across the course of development, but developmental associations of interest are not often simple or simplistic. The kinds of developmental perspectives emphasized in DP, and in this text, mandate examination of life trajectories, interactive and transactional processes, and multiple-levels-of-analysis perspectives. Without their consideration, relevant models are once again destined to oversimplification and a loss of relevant clinical information.

Risk and Protective Factors A key focus of a discipline such as DP—with the term psychopathology embedded in its title—is to discover the nature of behavioral and emotional problems, syndromes, and disorders. Many different definitional schemes have been invoked to define and explain psychopathological functioning, with none able to provide a complete picture. Indeed, it is clear that biological vulnerabilities, psychological processes, environmental potentiators, and cultural-level norms and expectations all play major roles in defining and understanding behavioral manifestations that are considered abnormal and pathological in a particular social context. Both biological vulnerabilities and environmental risk factors are antecedent variables that predict such dysfunction, and the ultimate goal is to discover which variables are both malleable and potentially causal of the disorder in question (Kraemer et al., 1997; see also Kraemer et al., 2001). Yet disordered behavior is not uniform, so vulnerabilities and risk factors are not inevitable predictors. Indeed, for most individuals with diagnosable forms of psychopathology, symptoms

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and impairments wax and wane over time. It is often difficult to know when dysfunction precisely begins; it is also quite normative for periods of serious problems to be followed by healthier adjustment. In fact, the myth that mental disturbance is uniformly debilitating, handicapping, and permanent is a key reason for the continuing stigmatization of mental illness (Hinshaw, 2007; Hinshaw & Cicchetti, 2000). Crucially, not all individuals who experience vulnerabilities and risk factors for disorder develop subsequent pathology. Resilience is the term used to define unexpectedly good outcomes, or competence, despite the presence of adversity or risk (Luthar, 2006; Masten & Cicchetti, 2016). Indeed, the concept of multifinality, noted previously, directly implies that, depending on a host of biological, environmental, and contextual factors, variegated outcomes may well emanate from common risk factors, with the distinct possibility of resilience and positive adaptation in some cases. DP is therefore involved centrally in the search for what have been called protective factors: variables and processes that mitigate vulnerability/risk and promote more successful outcomes than would be expected in their presence. Controversy surrounds the construct of resilience, the nature of protective factors, and the definitions of competent functioning (see Burt, Coatsworth, & Masten, 2016). Some have claimed that there is no need to invoke a set of special, mysterious processes that are involved in resilience, given that a certain percentage of any sample exposed to a risk factor will show better-than-expected outcomes and that protective factors are all too often simply the opposite poles of what we typically think of as risk variables or vulnerabilities (e.g., higher rather than lower IQ; easier rather than more difficult temperament; warm and structured rather than cold and lax parenting). Still, it is crucial to examine processes that may be involved in promoting competence and strength rather than disability and despair, given that such processes may be harnessed for prevention efforts and may provide key conceptual leads toward the understanding of both pathology and competence. In short, gaining understanding of why some children who are born into poverty fare well in adolescence and adulthood (see, for example, Wadsworth, Evans, Grant, Carter, & Duffy, 2016), why some individuals with alleles that tend to confer risk for pathological outcomes do not evidence psychopathology, why some youth with difficult temperamental features develop into highly competent adults, and why some people who lack secure attachments or enriching environments during their early years nonetheless show academic and social competence is essential for knowledge of both health and maladjustment. It is not just a luxury but a necessity to investigate positive developmental outcomes, given the inseparability of health and pathology. Competence can shed light on the pathways that deflect from pathology and, in so doing, may provide otherwise hidden insights into necessary developmental components of adjustment versus maladjustment (Luthar, 2006; Masten & Cicchetti, 2016).

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Reciprocal, Transactional, Ontogenic Process Models Linear models of causation, for which static psychological or psychobiological variables are assumed to respond in invariant ways to the influence of vulnerabilities and risk factors, are not adequate to the task of explaining psychopathology and its development. Richters (1997) provided detailed explication, highlighting that unique explanatory systems are needed to deal with “open systems” such as human beings. Pathways to adolescent and adult functioning are marked by reciprocal patterns or chains, in which children influence parents, teachers, and peers, who in turn shape the further development of the child (for an early, influential model, see Bell, 1968). Such mutually interactive processes propel themselves over time, leading to what are termed transactional models. Some developmental processes appear to operate via cascading, escalating chains (Masten et al., 2006) or even “symphonic” effects (Boyce, 2006). Indeed, nonlinear, dynamic systems models are needed to explicate core developmental phenomena (Granic & Hollenstein, 2006). Sensitive data-analytic strategies and innovative research designs are crucial tools for fostering greater understanding of such phenomena. These kinds of models can be used to elucidate equifinal and multifinal processes, as described above. They also exemplify, once again, problems inherent in static, categorical models of pathology (e.g., American Psychiatric Association, 2013; see Chapter 2 [Beauchaine & Klein]). Recognition of such problems led the leadership of the National Institute of Mental Health to develop, several years ago, an alternative to categorical diagnosis, via an endeavor called the Research Domain Criteria (RDoC; see Insel et al., 2010). This dimensional means of accounting for psychopathology specifically embodies a multiple-levels-of-analysis approach by positing a number of core, dimensional behavioral systems, with clear biological substrates, shaped by context. At the same time, ontogenic process models of psychopathology have witnessed a resurgence (see Beauchaine & Hinshaw, 2016; Beauchaine & McNulty, 2013), whereby heritable vulnerabilities transact with toxic contextual forces (e.g., coercive family interactions; violent neighborhoods) to yield psychopathology, particularly of the externalizing variety. Self-injury appears to fall in the same domain of relevant processes (see Chapter 19 [Crowell]). In all instances, static and/or linear models of influence must give way to reciprocal and transactional chains of influence.

Psychobiological Discoveries Intersect and Interact With Context The genomic era has been upon us for some time, and advances in brain imaging research—despite criticisms of its methods and false-positive rates (Vul, Harris, Winkielman, & Pashler, 2009)—have made the developing brain far more accessible to scientific view than ever before. Although it is mistaken, as emphasized throughout, to give primacy to any single level of analysis (brain, context, or other), we have asked contributors to pay particular attention to psychobiological

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factors and processes. Part of the reason is historical: Family systemic and environmental views dominated the field for much of the 20th century. Also, we now know that without understanding potential effects of genes, physiological processes, and biological vulnerabilities to psychopathology, there is little hope of understanding the most severe forms of disorder. Yet the brain is remarkably plastic and contexts influence biological unfolding. Thus, Ted Beauchaine and I have asked authors to emphasize contextualization of the psychobiological perspectives they present. In fact, reductionistic accounts of (a) the primacy of single genes, (b) the inevitable predictability of later functioning from early temperament, or (c) the placement of psychopathology completely inside brightly colored brain images are as short-sighted as the exclusively environmental accounts of psychopathology that dominated much of the 20th century. Indeed, a key tenet of DP is that family, school-related, neighborhood, and wider cultural contexts are central for the unfolding of aberrant as well as adaptive behavior. This point cannot be overemphasized. What may have been adaptive, genetically mediated benefits at one point in human evolutionary history may be maladaptive in current times, given major environmental and cultural changes that render certain traits far less advantageous than previously (e.g., storage of fat in times of uncertain meals and sudden need for survival-related activity; presence of undue anxiety in relation to certain feared stimuli when conditions have markedly changed with respect to sedentary lifestyles). There are few absolutes in terms of behavior patterns that are inherently maladaptive or risk factors that inevitably yield dysfunction; cultural setting and context are all-important for understanding and creating healthy versus unhealthy adaptation. Similarly, key environmental factors (such as parenting styles) are not always uniformly positive or uniformly negative in terms of their developmental effects. Deater-Deckard and Dodge (1997) showed that authoritarian parenting predicts antisocial behavior among White, middle-class children but not necessarily among African-American families. At the same time, many forms of mental disorder are present at roughly equivalent rates across multiple cultures, revealing key evidence for universality. Yet effects of risk or protective factors often differ markedly depending on developmental timing, family and social contexts, and niches that exist in given cultures for their expression and resolution (Serafica & Vargas, 2006). In short, the DP perspective tells us clearly that setting and context are all-important (see also Rutter et al., 1997). The area of gene × environment interactions in DP provides an important, if contentious, case example. The underlying idea is that genotypes moderate the effects of environmental context on the development of psychopathology, and vice versa (i.e., environmental factors moderate genetic effects on mental disorder). With profound implications for DP, this subfield erupted, 15 years ago, with core publications by Caspi and colleagues (Caspi et al., 2002, 2003). However, such widely cited findings have been subject to meta-analyses, which initially challenged the robustness of such results regarding interactions of the

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serotonin transporter gene with maltreatment or stressful life events (e.g., Risch et al. 2009) and then subsequently upheld the initial results when all relevant investigations were included (Karg, Burmeister, Shedden, & Sen, 2011). Both statistical power and selection biases are major factors in all such investigations. In a commentary, Caspi, Hariri, Holmes, Uher, and Moffitt (2010) made the point that interactive effects are accentuated in smaller-sample investigations that feature viable measures of environmental stress—highlighting the importance of precise measures of both the genetic (Dick et al., 2015) and the contextual side of the equation. Similar but greatly expanded perspectives have been provided by Dick et al. (2015), who outline essential recipes for avoiding the major issue of false positive findings in research on gene × environment interactions; and by Keller (2014), who adds to the cautionary note that many gene × environment researchers will overestimate such interactive power lest they explicitly take into account potentially confounding effects of passive gene-environment correlation. Furthermore, Bakermans-Kranenburg and van IJzendoorn (2015), Belsky and Pluess (2009), and Ellis, Boyce, Belsky, Bakermans-Kranenburg, and van IJzendoorn (2011) argue that some “vulnerability” genes are actually “susceptibility” genes, exquisitely responsive to either extremely good or poor environments—with the latter contentions also challenged by a range of artifacts that can produce false-positive findings. In fact, the potential confounding of genetic and environmental contributions to behavior through gene-environment correlation is unquestioned, which is why contributions such as Harold et al. (2013)—who demonstrated reciprocal and transactional effects of child ADHD symptoms and negative parenting with respect to continuations of child behavior in adoptive samples, in which parents and children are biologically unrelated—are essential from a DP perspective. The bottom line is that increasingly sophisticated investigations, with careful attention paid to selection of genes, selection of environments, and careful consideration of a host of design and statistical issues, are needed to elucidate and validate specific ways in which genetic variation may be accentuated or unleashed in particular environmental contexts. In cutting-edge research on DP, the Journal of Abnormal Psychology recently published a special section of articles on ontogenic process models in the field, with special emphasis on investigations focused on the integration of (a) geneenvironment interplay, (b) neuroimaging correlates, and (c) contextual factors that may elicit pathological outcomes across development. I was asked to provide a commentary on these articles, and in doing so I noted that in many ways they represent the cutting edge of the field, largely related to such integration (Hinshaw, 2015). Commenting on only a subset (see also Hankin et al., 2015; LeMoult et al., 2015; Little et al., 2015; and Vrshek-Schallhorn et al., 2015), I first highlight that Carey et al. (2015) revealed an endocannibanoid polymorphism that interacted with childhood sexual abuse to predict development of cannabis dependence in adolescence. Upping the level of complexity and biological relevance, in one of their samples they also studied basolateral amygdala habituation.

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This investigation added a dynamic neural measure to the usual Gene × Environment interaction paradigm, with findings suggestive of a plausible biological pathway leading to cannabis dependence symptoms. Moreover, Pagliaccio et al. (2015) examined early life stress and genetic risk— indexed by a composite score of 10 polymorphisms in hypothalamic-pituitaryadrenal axis genes (see Nikolova, Ferrell, Manuck, & Hariri, 2011, for information on the amalgamation of “risky” alleles in polygenic risk indices), in relation to both (a) amygdala-related connectivity with other brain regions and (b) downstream anxiety symptoms and emotion regulation skills. Evidence was found for both moderation (of early stress by genetic vulnerability) related to low connectivity, and mediation (whereby such reduced connectivity was linked to poor emotion regulation). In addition, Chhangur et al. (2015) examined interactions of two dopamine receptor alleles with core aspects of parenting (high control, low support) to predict adolescent delinquency, using five waves of adolescent data. One genetic variant (DRD2), in interaction with low parental support, showed the expected interaction. Intriguingly, the shape of the interaction was curvilinear, such that the combination of the DRD2 allele in question (A2A2) with low parental support was associated with quick increases in delinquency across early to mid-adolescence, followed by sharp decreases by late adolescence. It may be the case that different configurations of genes and family environments are needed to explain the pernicious group of youth with persistent antisocial behavior patterns (see Gizer, Otto, & Ellingson, 2016). Finally, as highlighted above with respect to gene × environment research in general, most such investigations are seriously underpowered, so only replication can reveal strong evidence for interactive effects (Dick et al., 2015). Throughout this special section of articles, it was openly admitted by authors that interactive effects are typically of small size regarding typical effect-size metrics. It is noteworthy that Chhangur et al. (2015) were diligent in following the strong advice of Keller (2014) to adjust for potential gene-environment correlations before claiming significant effects of Gene × Environment interactions. In all, the possibility that genetically induced variation in vulnerability to psychopathology is moderated by stressful or downright harmful environmental factors—and conversely, that contextual influences on key outcomes are moderated by genotype—remains a tantalizing and theoretically fascinating possibility, with considerable supportive research evidence amidst a sea of controversy about the entire endeavor (e.g., Bakermans-Kranenburg & van IJzendoorn, 2015; Dick et al., 2015; Keller, 2014). This example of the intersection of biology and context is emblematic of the promise—and problems—of the field in the second decade of the 21st century. In sum, recent investigations in the field are explicitly tying in gene-environment interplay with (a) sensitive measures of brain function and (b) randomized clinical trials (Bakermans-Kranenburg & van Ijzendoorn, 2015), in the attempt to elucidate developmental pathways to psychopathology of various forms. The progenitors of

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DP would probably not, a generation and more ago, have envisioned the extent to which technological advances and conceptual sophistication have propelled the gene-environment field along the lines of core DP axioms and principles, nor the wholesale questioning of the endeavor.

SUMMARY Each of the previous points converges on the core theme that the development of psychopathological functioning is multidetermined, complex, interactive, transactional, and in many instances nonlinear. For those who like problems and solutions wrapped in neat packages, the study of DP will undoubtedly be a frustrating if not unfathomable endeavor. On the other hand, for those who are intrigued by the diverse clinical presentations of various pathological conditions in childhood and adolescence; for those who are fascinated with how much remains to be learned about antecedent conditions and maintaining factors; for those who are possessed by an intense “need to know” about underlying mechanisms of child and adolescent forms of mental illness; and for those who realize the need to consider healthy outcomes and competence as well as maladaptation, the DP perspective is a necessary guide to and framework for the rapidly growing scientific enterprise linking normal and atypical development. Longitudinal, multilevel investigations are typically mandated to gain the types of knowledge needed to understand psychopathology (and competence) from a developmental perspective, with potentially high yield for basic developmental science; for elucidation of highly impairing behavioral, emotional, and developmental conditions; and for informing prevention and intervention efforts. The study of DP is ever expanding, engaging scientists from multiple disciplines and perspectives. Progress is emerging quickly, but the territory to explore remains vast.

CHAPTER CONTENTS In our instructions to the volume’s contributors, we asked for up-to-date material that is simultaneously developmentally based, clinically relevant, and directly inclusive of the types of psychobiological formulations gaining ascendancy in the mental-health enterprise. In other words, our aim for each chapter was presentation of state-of-the-art, DP-laden information, full of complexity but presented in a manner facilitating comprehension and integration. Specifically, for chapters dealing with particular disorders and dimensions of psychopathology, we requested coverage of historical context, epidemiology, diagnostic issues, sex differences, etiology (including psychobiological and contextual factors, as well as RDoC considerations when possible), developmental processes, cultural variables, and synthetic comments to illuminate the pathology under discussion. We clarified that emphasis on neural and neurophysiological processes must not be reductionistic. Indeed, psychosocial and family factors—which served

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as the predominant modality throughout much of the past century—interact and transact with biological vulnerabilities to produce both maladaptation and healthy adaptation throughout development (Beauchaine & Hinshaw, 2016; Beauchaine & McNulty, 2013). There is no escaping the need for integrative and integrated models as the field moves forward. Thus, we asked contributors to consider multilevel models and transactional processes. Indeed, as noted above, modern views of behavioral and molecular genetics have placed into sharp relief the unique and interactive roles that environmental and cultural forces exert on development (e.g., Belsky & Pluess, 2009; Dodge & Rutter, 2011; Hyde, 2015). Given page limitations and our desire for focused rather than exhaustive coverage, each chapter is relatively brief. Our goal is that readers can use these contributions as a springboard for additional exploration of conceptual frameworks, empirical research on mechanisms of interest, and building blocks for a new generation of evidence-based prevention and treatment efforts. As can be seen, the early chapters pertain to core conceptual and developmental issues and factors, and later chapters cover specific dimensions and disorders of interest. Immediately following this introductory chapter, Theodore Beauchaine and Daniel Klein (Chapter 2) provide crucial material spanning categorical (i.e., DSM) empirically based (e.g., the Child Behavior Checklist; Achenbach, 2009), and continuous (i.e., RDoC) methods and models for conceptualizing psychopathology. Certainly, dimensional/continuous accounts are gaining traction, yet at the same time clinical needs call for categorical diagnoses. Integrating these overarching frameworks is therefore necessary. The material in this chapter provides needed context for each of the remaining entries. Next, in Chapter 3 Beauchaine, Lisa Gatzke-Kopp, and Ian Gizer discuss crucial concepts related to gene-environment interplay in the genesis of psychopathology. This chapter exemplifies what is now a truism: genes and environments must not be viewed as separable, independent factors influencing mental disorders, as their effects are tightly intertwined in reciprocal and transactional fashion. In keeping with current trends in DP, this chapter conveys core material from both behavioral genetic and molecular genetic perspectives and discusses rapidly evolving research on epigenetic processes through which environmental experiences alter DNA expression, with possible implications for psychological adjustment. It does not shy away from either promise or controversy regarding this endeavor. Bruce Compas, Meredith Gruhn, and Alexandra Bettis (Chapter 4) present essential material on risk and resilience, providing a needed set of concepts and principles related to the potential for better-than-expected outcomes for subsets of vulnerable and high-risk youth. We must remember that not all children who express biological vulnerabilities and/or grow up with exposure to environmental risk develop pathological outcomes; indeed, one of the core DP principles noted above pertains to multifinal outcomes resulting from adverse early experiences. This chapter challenges conceptions of inevitable pathology from early vulnerability and risk.

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In Chapter 5, Sara Jaffee covers the crucial area of child maltreatment, providing needed integration of psychosocial and psychobiological mechanisms through which maltreatment confers risk for a wide range of pathological outcomes. This chapter is a paragon of integrated and integrative perspectives on this prevalent and potentially devastating set of risk factors; compared to earlier formulations on maltreatment, her coverage of biological processes shows an explosion of growth in this arena. Chapter 6, written by Emily Neuhaus and Theodore Beauchaine, covers impulsivity and vulnerability to psychopathology, viewing impulse-control problems as an underlying dimension that confers vulnerability to a range of mental disorders. Such risk is “expressed,” however, in the context of often-toxic environments, whether in the form of maladaptive parenting, less-than-responsive schools, or violent neighborhoods. In other words, transactional models, spanning biological vulnerability and environmental risk, are necessary for considerations of the development of psychopathology, particularly for the next generation of ontogenic process models in the DP field. Chapter 7, written by Jerome Kagan, deals with the temperamental construct of behavioral inhibition, emphasizing its predictive power for pathological outcomes in some but not all cases. Written with flair, it provides both historical and current perspectives on links between temperament and environment. In Chapter 8, Bruce Ellis, Marco Del Giudice, and Elizabeth Shirtcliff cover the highly relevant constructs of allostasis and biological sensitivity to context, topics that are receiving increasing coverage in the research literature each year. Notable here are both the complexity of the relevant biological mechanisms involved and the inherent interplay between genes, biological substrates, and environmental inputs intricately involved in these phenomena. They contrast their adaptive calibration model to the earlier construct of allostatic load per se, arguing for the greater predictive and explanatory power of adaptive calibration. Chapter 9, written by Lauren Doyle, Nicole Crocker, Susanna Fryer, and Sarah Mattson, covers the important area of exposure to teratogens (chemicals ingested by pregnant mothers) that confer risk for physical malformations as well as behavioral and emotional sequelae for the child, once born. As all students of pharmacology know, the placenta provides a completely permeable border for any and all drugs ingested by the mother, and the fetus’s organs for metabolizing foreign substances are slow to develop—potentially providing for a host of teratogenic exposures. Consequences for developmental psychopathology are profound. Next, in Chapter 10, Peter Arnett, Jessica Meyer, Victoria Merritt, Lisa Gatzke-Kopp, and Katherine Shannon Bowen write about brain injury as a risk factor for psychopathology. The multiple ways in which the developing brain can receive insults—and the complex pathways through which such injury affects development—are staggering. This chapter provides information about which many readers will have relative unfamiliarity; we are glad to have included these essential perspectives in our third edition.

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Immediately following is Chapter 11 by Pamela Cole, Sarah Hall, and Nastassia Hajal on the still-growing topic of emotion regulation and dysregulation. Clearly, this chapter moves “up” a level from Chapters 9 and 10 in terms of levels of analysis, as the former chapters are heavily biological. Indeed, the ways in which intraindividual vulnerability and contextual risk shape individuals’ abilities to recognize, process, and act on emotions (their own and those of others) are fascinating and of real importance to psychopathology. Finally, rounding out the early “conceptual” chapters, in Chapter 12 Wesley Jennings and Nicholas Perez move up another level again, considering effects of neighborhoods on psychopathology, particularly externalizing behaviors. As in each of the other chapters, transactional processes are highly salient, as this analysis clarifies ways in which systems-level influences represented by neighborhood-level effects interact with individual vulnerabilities and risk factors to shape the most pronounced cases of antisocial behavior. Beginning the section of chapters on disorders and dimensions of salience to psychopathology, Joel Nigg (Chapter 13) presents an elegant, integrative view on the development of attention-related and impulse-control problems (categorized as ADHD). Despite the strongly heritable nature of such symptoms, other biological-level influences as well as contextual processes are central to their developmental unfolding, as portrayed in this state-of-the-art chapter. Then, in Chapter 14, Benjamin Lahey and Irwin Waldman present, in a parallel framework, interconnected processes related to development of aggression and antisocial behavior—which are tremendously costly to property, lives, and the economy as a whole. Once again, multiple levels of analysis and transactional processes are on center stage in this synthetic chapter, which features intensive discussion of important subfacets of externalizing behavior patterns. In Chapter 15, Sandra Brown, Kristin Tomlinson, and Jennifer Winward discuss the topic of substance use disorders in adolescence and beyond. Because the major impairments—physical, emotional, economic—linked to substance abuse are legion, this chapter will be of interest to readers from multiple disciplines and perspectives. In addition to elucidating developmental pathways and mechanisms, the chapter authors also feature biological effects of substances on the developing brain, a vital issue not often sufficiently emphasized. Next, Carl Weems and Wendy Silverman use Chapter 16 to convey essential, developmentally relevant information on anxiety disorders, which are prevalent and frequently devastating in the impairments they “carry.” As the field moves from a multiple-categories conception of anxiety conditions, embodied by the DSM approach, to more current formulations informed by developmental psychopathology and transactional models, this chapter provides essential reading. Chapter 17, by Emily Ricketts, Deepika Bose, and John Piacentini, covers obsessive-compulsive conditions and disorders, including OCD, body dysmorphic disorder, hair-pulling disorder, hoarding disorder, and skin-picking disorder. As noted by their placement in a separate chapter, these conditions reveal different

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developmental processes and pathways from other anxiety-related disorders. Biological and environmental mechanisms underlying symptom display are emphasized. In Chapter 18, authored by Daniel Klein, Brandon Goldstein, and Megan Finsaas, the subject matter is the highly prevalent and severely impairing spectrum of depressive disorders. The evolving picture of biological vulnerability and psychosocial risk related to depression in youth—operating transactionally and in equifinal fashion—provides fertile testing ground for many core tenets of DP. Indeed, the chapter features the heterotypically continuous manifestations of depressive disorders across the lifespan, shaped by biological vulnerability and contextual risk. Erin Kaufman, Sheila Crowell, and Mark Lenzenweger (Chapter 19) write about the related but partially independent topics of borderline personality configurations and self-injury. In intriguing ways, these areas signify the confluence of internalizing and externalizing tendencies in the same youth; massive increases in rates of self-harm, along with its undoubted psychobiological and psychosocial roots, make this chapter another fulcrum point for a large number of DP principles and processes. Chapter 20 features the contentious and clinically important topic of traumarelated disorders, authored by Bruce Perry. Here again is an area in which genetic vulnerabilities are accentuated in the face of traumatic life events—and in which long-term consequences of trauma are experienced in both biological systems and a range of psychological and emotional symptoms. Then, in Chapter 21, Joseph Blader, Donna Roybal, Colin Sauder, and Gabrielle Carlson take on the controversial topic of bipolar-spectrum disorders, which continue to be a source of contention in the field (i.e., does bipolar illness exist in children—and if so, what forms does it take)? Issues of heritability along with psychosocial stressors, and of “kindling” across the lifespan—such that episodes potentially become more self-generating and frequent over time—are salient in this chapter. Chapter 22 authored by Susan Faja and Geraldine Dawson, features the crucial topic of autism spectrum disorders. The fast rise in diagnosed prevalence, the serious impairments accruing from the symptoms, the early age of onset in most cases, and the controversies over effective intervention strategies render many issues in this area contentious—and of major clinical and scientific importance. The biological explosion of knowledge about this area is featured in this chapter. Robert Asarnow and Jennifer Forsyth, in Chapter 23, deal with the low-prevalence but clinically and scientifically fascinating area of schizophrenia spectrum disorders in children and adolescents, long a source of diagnostic controversy. Their formulations, steeped in psychobiological vulnerability in transaction with stressful family environments, provide an authoritative account, revealing the importance of this topic for modern conceptions of early-onset schizophrenia. Finally, Chapter 24, authored by Eric Stice and Deanna Linville, takes on the area of eating disorders. In writing about an area associated with intensive pain

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for individuals and family members alike, the authors add binge eating disorder to the traditional syndromes of anorexia nervosa and bulimia nervosa for this current synthesis. In sum, each chapter features complex, interactive processes spanning psychobiological vulnerabilities and psychosocial risk factors, while providing strong emphasis on a developmental neuroscience perspective. Overall, the study of atypical development is fascinating, complex, and clinically as well as scientifically essential. It carries major potential for elucidating processes through which normal development occurs, at the same time that it highlights both expected and unexpected pathways to potentially devastating behavioral and emotional outcomes. As the 21st century continues its lightning-fast progressions into multilevel, integrative models of risk and resilience (and of health and pathology), it is heuristic to consider, simultaneously, the major progress made each year in the field along with the fundamental ignorance the field still possesses of the relevant variables, principles, and pathways linked to impairing mental disorders. We hope that you, the readers, are enticed by the clinical and scholarly puzzles that remain to be solved as well as humbled by the huge clinical need that remains in place for every single child, adolescent, family, and community experiencing the isolation, pain, and impairment related to mental disorder. The best minds of the next generations of scientists, clinicians, and policy makers need to become deeply engaged in the long journey that remains in front of us.

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adolescence: Influence of gender, development, genetic susceptibility, and peer stress. Journal of Abnormal Psychology, 124, 803–816. Harold, G. T., Leve, L. D., Barrett, D., Elam, K., Neiderhiser, J. M., Natsuaki, N. M, . . . Thapar, A. (2013). Biological and rearing mother influences on child ADHD symptoms: Revisiting the developmental interface between nature and nurture. Journal of Child Psychology and Psychiatry, 54(10), 1038–1046. Haslam, N., & Kvaale, E. P. (2015). Biogenetic explanations of mental disorder: The mixed- blessings model. Current Directions in Psychological Science, 24(5), 399–404. Hinshaw, S. P. (2002). Intervention research, theoretical mechanisms, and causal processes related to externalizing behavior patterns. Development and Psychopathology, 14, 789–818. Hinshaw, S. P. (2007). The mark of shame: Stigma of mental illness and an agenda for change. New York, NY: Oxford University Press. Hinshaw, S. P. (Ed.) (2008a). Breaking the silence: Mental health professionals disclose their personal and family experiences of mental illness. New York, NY: Oxford University Press. Hinshaw, S. P. (2008b). Developmental psychopathology as a scientific discipline: Relevance to behavioral and emotional disorders of childhood and adolescence. In T. P. Beauchaine & S. P. Hinshaw (Eds.), Child and adolescent psychopathology (pp. 3–26). Hoboken, NJ: Wiley. Hinshaw, S. P., & Kranz, R. (2009). The triple bind: Saving our teenage girls from today’s pressures. New York, NY: Ballantine. Hinshaw, S. P. (2013). Developmental psychopathology as a scientific discipline: Rationale, principles, and recent advances. In T. P. Beauchaine & S. P. Hinshaw (Eds.), Child and adolescent psychopathology (2nd ed., pp. 1–18). Hoboken, NJ: Wiley. Hinshaw, S. P. (2015). Developmental psychopathology, ontogenic process models, gene-environment interplay, and brain development: An emerging synthesis. Journal of Abnormal Psychology, 124, 771–775. Hinshaw, S. P., & Cicchetti, D. (2000). Stigma and mental disorder: Conceptions of illness, public attitudes, personal disclosure, and social policy. Development and Psychopathology, 12, 555–598. Hinshaw, S. P., Owens, E. B., Zalecki, C., Huggins, S. P., Montenegro-Nevado, A., Schrodek, E., & Swanson, E. N. (2012). Prospective follow-up of girls with attention-deficit hyperactivity disorder into young adulthood: Continuing impairment includes elevated risk for suicide attempts and self-injury. Journal of Consulting and Clinical Psychology, 80, 1041–1051. Hinshaw, S. P., & Scheffler, R. M. (2014). The ADHD explosion: Myths, medication, money, and today’s push for performance. New York, NY: Oxford University Press. Hinshaw, S. P., & Stier, A. (2008). Stigma as related to mental disorders. Annual Review of Clinical Psychology, 4, 269–293. Hyde, L. W. (2015). Developmental psychopathology in an era of molecular genetics and neuroimaging: A developmental neurogenetics approach. Development and Psychopathology, 27, 587–613.

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Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., . . . Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167(7), 748–751. Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation. Archives of General Psychiatry, 68(5), 444–454. Keller, M. C. (2014). Gene × environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry, 75(1), 18–24. Kennedy, M., Kreppner, J., Knights, N., Kumsta, R., Maughan, B., Golm, D., . . . Sonuga-Barke, E. J. S. (2016). Early severe institutional deprivation is associated with a persistent variant of adult attention-deficit/hyperactivity disorder: Clinical presentation, developmental continuities and life circumstances in the English and Romanian Adoptees study. Journal of Child Psychology and Psychiatry. Online ahead of print. doi: 10.1111/jcpp.12576 Kessler, R. C., Berglund, P., Demler, O., Jin, R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey replication. Archives of General Psychiatry, 62, 593–602. Kraemer, H. C., Kazdin, A. E., Offord, D. R., Kessler, R. C., Jensen, P. S., & Kupfer, D. J. (1997). Coming to terms with the terms of risk. Archives of General Psychiatry, 54, 337–343. Kraemer, H. C., Stice, E., Kazdin, A., Offord, D., & Kupfer, D. (2001). How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. American Journal of Psychiatry, 158, 848–856. Kreppner, J. M., O’Connor, T. G., Rutter, M., & the English and Romanian Adoptees Study Team. (2001). Can inattention/overactivity be a deprivation disorder? Journal of Abnormal Child Psychology, 29, 513–528. LeMoult, J., Ordaz, S. J., Kircanski, K., Singh, M. K., & Gotlib, I. (2015). Predicting first onset of depression in young girls: Interaction of diurnal cortisol and negative life events. Journal of Abnormal Psychology, 124, 850–859. Lewis, M., & Rudolph, K. D. (Eds.). (2014). Handbook of developmental psychopathology (3rd ed.). New York, NY: Springer. Little, K., Olsson, C. A., Youssef, G. J., Whittle, S., Simmons, J. G., Yucel, M., . . . Allen, N. B. (2015). Linking the serotonin transporter gene, family environments, hippocampal volume, and depression onset: A prospective imaging gene × environment analysis. Journal of Abnormal Psychology, 124, 834–849. Luthar, S. S. (2006). Resilience in development: A synthesis of research across five decades. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 739–795). Hoboken, NJ: Wiley. Martinez, A., & Hinshaw, S. P. (2016). Mental health stigma: Theory, developmental issues, and research priorities. In D. Cicchetti (Ed.), Developmental psychopathology: Vol. 4. Risk resilience, and intervention (3rd ed., pp. 997–1039). Hoboken, NJ: Wiley.

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Martinez, A., Piff, P. K., Mendoza-Denton, R., & Hinshaw, S. P. (2011). The power of a label: Mental illness diagnoses, ascribed humanity, and social rejection. Journal of Social and Clinical Psychology, 30, 1–23. Mash, E. J., & Barkley, R. A. (Eds.). (2006). Treatment of child disorders (3rd ed.). New York, NY: Guilford Press. Mash, E. J., & Barkley, R. A. (Eds.). (2007). Assessment of child disorders (4th ed.). New York, NY: Guilford Press. Mash, E. J., & Barkley, R. A. (Eds.). (2014). Child psychopathology (3rd ed.). New York, NY: Guilford Press. Masten, A. S, & Cicchetti, D. (2016). Resilience in development: Progress and transformation. In D. Cicchetti (Ed.), Developmental psychopathology: Vol. 4. Risk, resilience, and intervention (3rd ed., pp. 271–333). Hoboken, NJ: Wiley. McLaughlin, K. A., Zeanah, C. H., Fox, N. A., & Nelson, C. A. (2012). Attachment security as a mechanism linking foster care placement to improved mental health outcomes in previously institutionalized children. Journal of Child Psychology and Psychiatry, 53, 46–55. Meza, J., Owens, E. B., & Hinshaw, S. P. (2016). Response inhibition, peer preference and victimization, and self-harm: Longitudinal associations in young adult women with and without ADHD. Journal of Abnormal Child Psychology, 44(2), 323–334. Moffitt, T. E. (2006). Life course persistent versus adolescence limited antisocial behavior. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 570–598). New York, NY: Wiley. Muthén, B. O., Brown, C. H., Masyn, K., Jo, B., Khoo, S. T., Yang, C. C., . . . Liao, J. (2002). General growth mixture modeling for randomized prevention trials. Biostatistics, 3, 459–475. Nelson, C. A., Zeanah, C. H., Fox, N. A., Marshall, P. J., Smyke, A. T., & Guthrie, D. (2007). Cognitive recovery in socially deprived young children: The Bucharest Early Intervention Project. Science, 318, 1937–1940. Neese, R. M. (2005). Evolutionary psychology and mental health. In D. Buss (Ed.), Handbook of evolutionary psychology (pp. 903–927). Hoboken, NJ: Wiley. Nigg, J. T., Hinshaw, S. P., & Huang-Pollack, C. (2006). Disorders of attention and impulse regulation. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 358–403). Hoboken, NJ: Wiley. Nikolova, Y. S., Ferrell, R. E., Manuck, S. B., & Hariri, A. R. (2011). Multilocus genetic profile for dopamine signaling predicts ventral striatum reactivity. Neuropsychopharmacology, 36(9), 1940–1947. O’Connor, T. G. (2006). The persisting effects of early experiences on psychological development. In D. Cicchetti & D. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 202–234). Hoboken, NJ: Wiley. Pagliaccio, D., Luby, J. L., Bogdan, R., Agrawal, A., Gaffrey, M. S., Belden, A. C., . . . Barch, D. M. (2015). Amygdala functional connectivity, HPA axis genetic

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variation, and life stress in children and relations to anxiety and emotion regulation. Journal of Abnormal Psychology, 124, 817–833. Pescosolido, B. A., Martin, J. K., Long, J. S., Medina, T. R., Phelan, J. C., & Link, B. G. (2010). “A disease like any other”? A decade of change in public reactions to schizophrenia, depression, and alcohol dependence. American Journal of Psychiatry, 167, 1321–1330. Phelan, J. C., Link, B. G., Stueve, A., & Pescosolido, B. A. (2000). Public conceptions of mental illness in 1950 and 1996: What is mental illness and is it to be feared? Journal of Health and Social Behavior, 41, 188–207. Richters, J. E. (1997). The Hubble Hypothesis and the developmentalist’s dilemma. Development and Psychopathology, 9, 193–229. Risch, N., Herrell, R., Lehner, T., Liang, K. Y., Eaves, L., Hoh, J., . . . Merikangas, K. R. (2009). Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: A meta-analysis. Journal of the American Medical Association, 301(23), 2462–2471. Rutter, M., Dunn, J., Plomin, R., Simonoff, E., Pickles, A., Maughan, B., . . . Eaves, L. (1997). Integrating nature and nurture: Implications of person-environment correlations and interactions for developmental psychopathology. Development and Psychopathology, 9(2), 335–364. Rutter, M., & Sroufe, L. A. (2000). Developmental psychopathology: Concepts and challenges. Development and Psychopathology, 12, 265–296. Sawyer, M. G., Whaites, L., Rey, J. M., Hazell, P. L., Graetz, B. W., & Baghurst, P. (2002). Health-related quality of life of children and adolescents with mental disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 41(5), 540–537. Scott, K. M., Lim, C., Al-Hamzawi, A., Alonso, J., Bruffaerts, R., Caldas-de-Almeida, J. M., . . . Kessler, R. C. (2016). Association of mental disorders with subsequent chronic physical conditions: World mental health surveys from 17 countries. JAMA Psychiatry, 73(2), 150–158. Serafica, F. C., & Vargas, L. A. (2006). Cultural diversity in the development of child psychopathology. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 1. Theory and method (2nd ed., pp. 588–626). Hoboken, NJ: Wiley. Sonuga-Barke, E., Bitsakou, P., & Thompson, M. (2010). Beyond the dual pathway model: Evidence for the dissociation of timing, inhibitory, and delay-related impairments in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 49, 345–355. Sroufe, L. A. (1997). Psychopathology as an outcome of development. Development and Psychopathology, 9, 261–268. Sroufe, L. A., & Rutter, M. (1984). The domain of developmental psychopathology. Child Development, 55, 17–29. Swanson, E. N., Owens, E. B., & Hinshaw, S. P. (2014). Pathways to self-harmful behaviors in young women with and without ADHD: A longitudinal investigation of mediating factors. Journal of Child Psychology and Psychiatry, 44, 505–515.

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Visser, S. N., Danielson, M. L., Bitsko, R. H., Holbrook, J. R., Kogan, M. D., Ghandour, R. M., . . . Blumberg, S. J. (2014). Trends in the parent-report of health care provider-diagnosed and medicated attention-deficit/hyperactivity disorder: United States, 2003–2011. Journal of the American Academy of Child and Adolescent Psychiatry, 53, 34–46. Vrshek-Schallhorn, S., Stoud, C. B., Mineka, S., Zinborg, R. E., Adam, E. K., Redei, E. E., . . . Craske, M. G. (2015). Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression. Journal of Abnormal Psychology, 124, 776–790. Vul, E., Harris, C., Winkielman, P., & Pashler, H. (2009). Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science, 4(3), 274–290. Wadsworth, M. E., Evans, G. W., Grant, K., Carter, J. S., & Duffy, S. (2016). Poverty and the development of psychopathology. In D. Cicchetti (Ed.), Developmental psychopathology: Vol. 4. Risk, resilience, and intervention (3rd ed., pp. 136–179). New York, NY: Wiley. Wakefield, J. C. (1992). Disorder as harmful dysfunction: A conceptual critique of DSM-III-R’s definition of mental disorder. Psychological Review, 99(2), 232–247. Whiteford, H. A., Ferrari, A. J., Degenhardt, L., Feigin V., & Vos, T. (2015). The global burden of mental, neurological, and substance use disorders: An analysis from the Global Burden of Disease Study 2010. PLoS One, 10(2), e0116820. World Health Organization. (2014). Health for the world’s adolescents: A second chance in the second decade. Geneva, Switzerland: Author.

CHAPTER 2

Classifying Psychopathology The DSM, Empirically Based Taxonomies, and the Research Domain Criteria THEODORE P. BEAUCHAINE AND DANIEL N. KLEIN

A

ll scientific disciplines have rules for classifying phenomena and events that fall within their purview. Chemistry, for example, among the more advanced physical sciences, has fundamental laws that describe what constitutes an element (i.e., the number of protons in an atomic nucleus), what gives rise to similarities among elements (e.g., common bonding properties), how elements differ from one another (e.g., solubility vs. inertness), and how elements interact across levels of analysis to create what might otherwise be inexplicable phenomena (e.g., the high boiling point of water conferred by hydrogen bonds). For chemistry, these and other properties are summarized in the periodic table, which represents a taxonomy of elements. Although issues of taxonomy in chemistry are far more complex than this brief description implies, the example illustrates how important precise classification is in any discipline. Accurate classification ultimately leads to better prediction and control of external events, which are primary objectives of science (Braithwaite, 1953; see also Beauchaine, Gatzke-Kopp, & Mead, 2007). In chemistry, control of chemical reactions and molecular compounds has led to astounding advances in processes such as water purification, improving quality of life for millions. As outlined in Chapter 1 [Hinshaw], a major goal of developmental psychopathology is to improve prediction and control of mental illness, which should ultimately lead to more effective prevention and intervention programs, alleviating considerable human suffering (see also Beauchaine, Neuhaus, Brenner, & Gatzke-Kopp, 2008). Taxonomies of diseases, including psychopathology, are often referred to as nosologies. In this chapter we describe the predominant classification system of psychopathology in the United States—the Diagnostic and Statistical Manual of 33

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Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013). In doing so we (a) outline the history of the DSM; (b) highlight important issues and difficulties that emerge when diagnosing psychopathology; and (c) juxtapose the DSM-5 and its limitations with alternative perspectives and theoretical orientations, including empirically derived taxonomies and the Research Domain Criteria (RDoC). The latter is a fairly new approach to characterizing psychopathology that is currently being developed by the National Institute of Mental Health (2015a).

HISTORICAL CONTEXT Unlike the physical sciences, such as physics, chemistry, and geology, clinical psychology and psychiatry are relatively new. In fact, the first well-organized attempt in the United States at devising a classification system of psychopathology occurred only 64 years ago with publication of the first edition of the DSM (APA, 1952). As a result, psychology and psychiatry still struggle with unresolved taxonomic issues,1 some of which are specific to children and adolescents (see e.g., Achenbach & Rescorla, 2006; Beauchaine, Klein, Crowell, Derbidge, & Gatzke-Kopp, 2009; Eaton, Krueger, South, Simms, & Clark, 2011; Jensen, Knapp, & Mrazek, 2006; Krueger et al., 2011; World Health Organization, 1996). These issues are described in sections to follow.

Early Versions of the DSM The current version of the DSM is the DSM-5 (APA, 2013), which is actually the eighth in a series of DSMs, including both major and minor revisions, dating to 1952 (DSM-I, 1952; DSM-II, 1968; DSM-II, seventh printing, 1974; DSM-III, 1980; DSM-III-R, 1987; DSM-IV, 1994; DSM-IV-TR, 2000; DSM-5, 2013). Below we provide brief descriptions of each DSM, list the primary objectives of the American Psychiatric Association in undertaking each revision, and outline major changes in each new edition. DSM-I. The DSM-I (APA, 1952) was an effort by the APA to produce a single nomenclature for psychopathology. Prior to the DSM-I, there were several alternative classification systems, none of which was used consistently across the United States (see Blashfield, 1998). The DSM-I was influenced strongly by Adolph Meyer’s psychobiology, which characterized psychopathology as a reaction 1. We are not suggesting that taxonomic questions have been resolved in other sciences. In fact, issues of classification continue to be debated in many other fields, including evolutionary biology (see e.g., Laurin, 2010) and paleontology (see Beauchaine, 2003).

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to stress (e.g., Meyer, 1934). Hence, all disorders included “reaction” in their titles (e.g., depressive reaction). In formulating the DSM-I, the APA relied on the collective opinion of its membership. To do so, it sent detailed questionnaires to 10% of members, from which proposed categories of psychopathology were derived. Three broad classes of psychopathology emerged, including organic brain syndromes, functional disorders, and mental deficiency. Within these broad classes, 108 specific diagnoses were created (depending on the method of counting), only one of which could be applied specifically to children (adjustment reaction of childhood/adolescence). Final approval of psychiatric classes and specific diagnoses was obtained through a vote of the full APA membership. As this description implies, the DSM-I had little if any basis in empirical research. DSM-II. The DSM-II (APA, 1968), which contained about 182 diagnoses (again, depending on the method of counting), was published with few changes in process or philosophy. A major goal in formulating the DSM-II was to improve communication among mental health professionals—especially psychiatrists (e.g., Scotti & Morris, 2000). The DSM-II had strong psychoanalytic overtones, reflecting the training of most psychiatrists at the time. Major diagnostic classes of psychopathology were expanded from 3 to 11, and a number of childhood and adolescent disorders were added, including group delinquent reaction, hyperkinetic reaction, overanxious reaction, runaway reaction, unsocialized aggressive reaction, and withdrawing reaction. Since publication of the DSM-II, international treaty has dictated that the DSM and the International Classification of Diseases (ICD) be compatible. The ICD, published by the World Health Organization (WHO), is the classification system used in most other countries to diagnose mental illness. Some changes made to the DSM-II were needed to render it more similar to the ICD-8 (WHO, 1966). Currently, the ICD is in its 10th edition—revised (ICD-10; WHO, 2008). The ICD-11 is expected in 2018 (WHO, 2015). DSM-II, Seventh Printing. In the seventh printing of the DSM-II (APA, 1974), homosexuality was removed as a mental disorder, following protests by gay rights activists at the 1970 Annual Convention of the APA in San Francisco and a subsequent vote of the membership. This landmark event illustrates several important and interrelated points about diagnosis of mental illness. First, diagnostic systems such as the DSM, which are constructed by social institutions, always reflect social values (see e.g., McCarthy & Gerring, 1994). Second, psychiatry and related disciplines at times reinforce prevailing social value systems, which can lead to stigmatization of certain members of society, with considerable potential for negative effects on mental health (see e.g., Prilleltensky, 1989). Finally, as a social institution, the APA is not indifferent to sociopolitical influence.

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Removing homosexuality from the DSM-II also foreshadowed struggles to deal with validity of psychiatric diagnosis more broadly, a major issue confronted in later revisions of the DSM, as described below.

Reliability, Validity, and Subsequent Versions of the DSM In contrast to the DSM-I (APA, 1952) and the DSM-II (APA, 1968), the DSM-III (APA, 1980) was designed to be descriptive and largely atheoretical, so it would appeal and be useful to professionals from disciplines and conceptual orientations beyond psychiatry. Research on clinical features and etiologies of major forms of psychopathology were also weighted heavily in formulating the DSM-III—a major shift from the consensus opinion approach to constructing its earlier versions (see above). Thus, introduction of the DSM-III in 1980 was a watershed event in modern classification of psychopathology. Prior to 1970, most mental health professionals in the United States were not especially concerned with psychiatric diagnosis. The dominant paradigm was psychoanalysis, which did not place much stock in diagnosis. However, in the 1960s a new paradigm, often referred to as biological psychiatry, challenged and ultimately supplanted psychoanalysis as the dominant perspective in the United States. One agenda of biological psychiatry proponents was to make the discipline more scientific by increasing its emphasis on empirical research, particularly on the biological bases and treatment of psychopathology, thereby bringing psychiatry into mainstream modern medicine. Diagnosis played a central role in this agenda, as a reliable and valid classification system was necessary for the enterprise. Indeed, how successful could research on biological causes/correlates of psychopathology be if the major independent variable—diagnosis—was unreliable or invalid? Because diagnosis was a cornerstone of well-developed specialties in medicine (e.g., Engel, 1977), emphasis on reliable diagnosis was paramount. However, there was a major obstacle: limited evidence of interrater reliability of psychiatric diagnosis (e.g., Spitzer & Fleiss, 1974). Problems with reliability were hard to ignore. First, rates of various diagnoses differed dramatically between the United States and most European countries. For example, the rate of schizophrenia was many times higher in the United States than in the United Kingdom. In order to address this issue, a team of researchers in the United States and United Kingdom launched the Cross-National Diagnostic Project (for a description see Gurland, 1976). Using the same diagnostic criteria and assessment procedures, they found that differences in clinical diagnoses between hospitals in New York and London were attributable entirely to different diagnostic practice; patients’ symptoms were virtually identical in both cities. Furthermore, clinical diagnoses by British psychiatrists corresponded more closely to patients’ actual clinical presentations than those by American psychiatrists, who greatly overdiagnosed schizophrenia and underdiagnosed mood disorders. Second, almost all studies that addressed diagnostic reliability during that era indicated very low interrater agreement. Spitzer and Fleiss (1974) aggregated

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data from these studies, and calculated interrater reliability using the kappa (κ) statistic, which measures the degree of association between categorical constructs such as presence vs. absence of a diagnosis, correcting for chance agreement. In general, κs ranging from 0 to .20 indicate slight agreement, .21 to .40 fair agreement, .41 to .60 moderate agreement, .61 to .80 substantial agreement, and .81 to 1.0 excellent agreement (Landis & Koch, 1977). Spitzer and Fleiss reported that κs from previous interrater reliability studies were .41 for depression, .33 for mania, .45 for anxiety neurosis, .57 for schizophrenia, and .71 for alcoholism. Only the latter could be considered adequate. Spitzer and Fleiss (1974) attributed low interrater reliability to two sources: criterion variance and information variance. Criterion variance refers to diagnosticians’ reliance on different criteria when making a diagnosis, whereas information variance refers to collection of different data (see below). With respect to criterion variance, if one clinician diagnoses schizophrenia on the basis of even mild indications of cognitive slippage (a form of thought disorder), whereas another reserves the diagnosis only for patients who exhibit severe delusions or hallucinations, agreement will be low. In this regard, the DSM-I (APA, 1952) and DSM-II (APA, 1968) were not helpful because their diagnostic criteria were vague. Each diagnosis was described in several sentences listing characteristic signs and symptoms, yet there was no specification of how many symptoms were required, how long a symptom had to be present, or whether other symptoms might rule out a diagnosis (e.g., in a patient with visual hallucinations, could schizophrenia be diagnosed in the context of acute alcohol withdrawal?).

Operationalizing Diagnostic Criteria: Reducing Criterion Variance The criterion variance problem was addressed initially by Mandel Cohen, who was interested in developing a more empirical approach to studying psychopathology. Cohen conducted several pioneering studies of mood, anxiety, and somatoform disorders. These involved formulating very careful criteria for diagnosis, applying them to what at the time were large samples of patients, and examining patients’ clinical presentations, family histories, and clinical course (see Healy, 2002). Psychiatric journals were not particularly interested in this work, so most of Cohen’s papers were published in medical journals (e.g., Cohen, Cassidy, Flanagan, & Spellman, 1937; Cohen, Robins, & Purtell, 1952), with very little effect on psychiatry or psychology. One of Cohen’s students was Eli Robins, who became chair of the Psychiatry Department at Washington University in St. Louis. Throughout the 1960s, Robins and several colleagues, including Samuel Guze and George Winokur, applied Cohen’s approach in a series of landmark studies of psychopathology (e.g., Arkonac & Guze, 1963; Reich, Clayton, & Winokur, 1969). One of the hallmarks of the Washington University approach was development of systematic operational (i.e., explicit) diagnostic criteria for a selected group of diagnoses.

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This approach was explicated by E. Robins and Guze (1970), who published a brief yet highly influential paper in which they advanced a five-step process toward ensuring that psychiatric classes were specific, objective, and nonarbitrary. Using the example of schizophrenia, Robins and Guze suggested that diagnostic validity can be established only when a clinical syndrome is characterized by (1) a cluster of covarying symptoms and etiological precursors (obtained from clinical description); (2) reliable physiological, biological, and/or psychological markers (obtained from laboratory studies); (3) readily definable exclusionary criteria; (4) a predictable course (assessed through follow-up studies); and (5) increased rates of the same disorder among first-degree relatives (assessed through family studies). The Robins and Guze method was soon used by Feighner et al. (1972) to develop the first set of psychiatric disorders that were validated systematically. Associated symptom lists are now referred to as the Feighner Criteria. Although the primary motivation in formulating the Feighner Criteria was to validate psychiatric disorders (see Kendler, Munoz, & Murphy, 2009), doing so required specification of explicit operational criteria, as noted above. Soon after the Feighner Criteria (1972) were published, the NIMH sponsored the Collaborative Study of the Psychobiology of Depression, a multisite investigation of the clinical features, family history, biological correlates, and course of depression (see Katz, Secunda, Hirschfeld, & Koslow, 1979). As part of this study, the NIMH contracted with Spitzer and Endicott to develop a revised version of the Feighner criteria, which came to be known as the Research Diagnostic Criteria (RDC; Spitzer, Endicott, & Robins, 1978). Thus, by the late 1970s, the importance of specifying operational criteria for psychiatric disorders was widely recognized among the psychopathology research community, which strongly influenced development of the DSM-III (APA, 1980) and all subsequent versions of the DSM (see e.g., Cloninger, 1989; Kendler et al., 2009), including the DSM-5 (APA, 2013).

Structured Interviews: Reducing Information Variance With the goal of reducing information variance, a major task of the US-UK Cross-National Project was to standardize collection of data on symptoms, assessed by British and American clinicians. Accordingly, Wing, Cooper, and Sartorius (1974) developed a standardized clinical interview that provided (a) specific questions to be asked by the interviewer, (b) specific rating scales for each symptom, (c) conventions for making ratings, and (d) a detailed glossary defining each symptom. This instrument was called the Present State Examination (PSE), which was designed to allow experienced clinicians to obtain a systematic assessment of patients’ current symptoms. It did not collect information on previous course or history and therefore could not be used to make diagnoses. However, it was an important advance in standardizing collection of information across clinicians and sites.

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At the same time, psychiatrists at Washington University developed a semistructured diagnostic interview for use in various research projects being conducted in their department. Like the PSE, it included standardized questions and rating scales. However, it also provided a systematic assessment of the development and course of psychopathology, rather than focusing only on the patient’s current state (Woodruff, Goodwin, & Guze, 1974). Thus, it included all information necessary to make diagnoses according criteria established at the time (see above). Soon afterward, as part of their role in the NIMH Collaborative Study of the Psychobiology of Depression Study, Endicott and Spitzer (1978) developed a semistructured diagnostic interview called the Schedule for Affective Disorders and Schizophrenia (SADS). This interview allowed trained clinicians to collect systematic and reliable data on both current symptoms and history of most major psychiatric disorders. Thus, use of the SADS also allowed clinicians to make specific diagnoses. By the time the DSM-III was published in 1980, structured diagnostic interviews were accepted as state-of-the-art in psychiatric assessment. However, both the PSE and SADS were quite time consuming, and neither matched the DSM-III. Hence, Spitzer and Williams (1983) developed a new instrument, the Structured Clinical Interview for DSM-III (SCID), which eventually assessed all major disorders in the DSM-III and later the DSM-III-R (e.g., Spitzer, Williams, Gibbon, & First, 1990), DSM-IV (e.g., First, Spitzer, Gibbon, & Williams, 2002), and DSM-5 (First, Williams, Karg, & Spitzer, 2015). One objective was that the SCID be sufficiently user-friendly to be adopted in routine clinical practice in addition to research, although such adoption is extremely limited. Another major development in structured interviewing was construction of the Diagnostic Interview Schedule (DIS; Robins, Helzer, Croughan, & Ratcliff, 1981), by Lee Robins (not to be confused with E. Robins, her spouse), a sociologist at Washington University who pioneered research on antisocial personality disorder (see, e.g., Dishion & Hiatt Racer, 2013). The impetus for development of the DIS was a report by the Carter Administration’s Presidential Commission on Mental Health, which stressed the need to collect better data on the prevalence of mental disorders in the United States. This report led to the NIMH Epidemiological Catchment Area (ECA) survey, the largest epidemiological study of mental disorders ever conducted at that time (see Regier et al., 1984). When designing this study, it was clear that hiring trained clinicians to conduct diagnostic interviews with over 18,000 participants would be prohibitively expensive. L. Robins and colleagues therefore developed the DIS so it could be used by lay interviewers with no previous training in psychopathology. Because it was designed for use by nonclinicians, it is much more structured than other diagnostic interviews, and, unlike the PSE, SADS, and SCID, it leaves no room for interviewer judgment in formulating questions and rating symptoms. With these latter instruments, the interviewer is expected to probe

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respondents’ answers until confident they understand the question and are reporting a clinically significant experience that is relevant to the construct being assessed. In contrast, with the DIS, interviewers take the respondents’ report at face value. Thus, it is a respondent-based, as opposed to an interviewer-based interview (Angold & Fisher, 1999). Diagnoses are derived by computer using DSM criteria. In order to assess rates of psychopathology in large epidemiological samples of children and adolescents, the NIMH later developed the Diagnostic Interview Schedule for Children (DISC; Costello, Edelbrock, Dulcan, Kalas, & Klaric, 1984). The current version of the DISC assesses 30 DSM-IV-TR (APA, 2000) psychiatric disorders. It is designed for use with parents of children, ages 6–17, and with both children and adolescents, ages 9–17. There is currently no DISC for the DSM-5, although one is being constructed. This tardiness may be of limited consequence for most childhood disorders, as changes to the DSM-5 were minimal (see below). Two exceptions are disruptive mood dysregulation disorder and intermittent explosive disorder—new diagnoses that are not represented in previous instantiations of the DSM (see e.g., Beauchaine & McNulty, 2013; Leibenluft & Stoddard, 2013). Like the DIS, the DISC is respondent-based, and can be administered by lay interviewers (Shaffer, Fischer, Lucas, Dulcan, & Schwab-Stone, 2000). Both the DIS and DISC have been controversial, with some questioning the validity of diagnoses so completely based on self-report—especially among youth (see e.g., Renou, Hergueta, Flament, Mouren-Simeoni, & Lecrubier, 2004). Indeed, adolescents who suffer from externalizing behavior disorders such as ADHD and conduct disorder often underreport their symptoms (e.g., Sibley et al., 2010). It is therefore routinely recommended that adult informants (parents) also provide data for such conditions. Nevertheless, considerable evidence points toward reliability of the DISC (see Shaffer et al., 2000), and its use in research settings is now commonplace. Finally, semistructured, interviewer-based diagnostic interviews have also been developed to assess psychopathology among children and adolescents (Dougherty, Klein, Olino, & Laptook, 2008). The most widely used of these is a downward extension of the SADS—the Kiddie SADS (Kaufman et al., 1997).

The DSM-III, DSM-III-R, DSM-IV, and DSM-5 DSM-III. Following from his extensive work on psychiatric diagnosis outlined above, Spitzer was chosen to lead on revisions to the DSM-III. Rather than continuing with tradition, he looked toward the Feighner et al. (1972) criteria and the RDC (Spitzer, Endicott, & Robins, 1978) as a means of solving the problem of criterion variance. The DSM-III therefore became the first official classification system in psychopathology that used specific symptoms, including inclusion, exclusion, and duration criteria for each diagnosis. This effort required a major expansion of the

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Feighner criteria and the RDC, which at the time covered no more than about 15 disorders. The DSM-III (APA, 1980) also introduced multiaxial classification. Thus, in addition to classifying major psychiatric syndromes (Axis I), separate axes were created for personality disorders (Axis II); physical conditions that are relevant to understanding a person’s presenting problem (Axis III); psychosocial and environmental stressors and problems (Axis IV); and overall severity, or global assessment of functioning (GAF; Axis V). Use of multiple axes was a means of addressing patients’ uniqueness in making a diagnosis: not every patient with the same diagnosis is the same in all respects. This is a particularly important consideration in developmental psychopathology research (see Chapter 1 [Hinshaw]), which emphasizes equifinality and contextual influences on the development of mental illness (see Chapters 1 [Hinshaw] and 4 [Compas, Gruhn, & Bettas]). DSM-III-R. A revised version of the DSM-III (APA, 1987) was published only seven years later. In large part because so little new research was available, changes were minimal, and the revision was not extensive enough to warrant being called a fourth edition. The rationale for the revision was that some diagnostic criteria were inconsistent, unclear, or contradicted by subsequent research (APA, 1987). Despite almost no alterations to diagnostic criteria, one set of changes had major consequences. Following publication of the DSM-III (APA, 1980), several studies were published questioning widespread use of exclusion criteria. Exclusion criteria are a means of implementing diagnostic hierarchies, which serve to simplify diagnosis. Patients typically present with a wide array of symptoms. Traditionally, a major task of diagnosing has been differential diagnosis—deciding what the most appropriate diagnosis is among many possibilities suggested by the patient’s clinical presentation. Diagnostic hierarchies are useful in differential diagnosis because they indicate which symptoms should receive priority. Prior to the DSM-III-R, organic mental disorders (syndromes attributable to central nervous system disease, brain trauma, or significant substance abuse) were at the top of the diagnostic hierarchy. Next came schizophrenia. Then came major mood disorders, with neurotic and personality disorders at the bottom. Thus, in the absence of organic factors, schizophrenia symptoms were accorded priority in diagnosis, regardless of the presence of major mood, neurotic, and/or personality disorder features. In the absence of both organic factors and schizophrenia symptoms, mood disorder symptoms took precedence regardless of neurotic and personality disorder features. Finally, neurotic and personality disorder diagnoses were only considered if organic, schizophrenia, and mood disorder features were absent. Several studies in the early 1980s demonstrated that exclusion criteria in the DSM-III (APA, 1980) were often arbitrary and caused a loss of significant information. For example, family histories of patients with major depression and panic

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disorder differed from those of patients with major depression alone (Leckman, Weissman, Merikangas, Pauls, & Prusoff, 1983). Hence, comorbid panic disorder appeared to be important, and excluding the panic disorder diagnosis among patients with major depression represented a loss of potentially important information. In light of these considerations, exclusion criteria were largely abandoned from the DSM-III-R (APA, 1987) onward, except those used to rule out organic (general medical or substance-induced) causes of disorder. As might be expected, eliminating exclusion criteria led to a significant increase in rates of comorbidity—the co-occurrence of two or more disorders (see Klein & Riso, 1993). As a consequence, understanding comorbidity has been a top agenda item in psychopathology research ever since (see e.g., Angold, Costello, & Erkanli, 1999; Beauchaine & Cicchetti, 2016a, 2016b; Beauchaine, Hinshaw, & Pang, 2010; Klein & Riso, 1993). At the same time, reduction of hierarchical exclusion criteria has resulted in a diminished role for differential diagnosis in diagnostic practice. DSM-IV. In 1994 the DSM-IV (APA, 1994) was published. One motivation for publishing a new version so soon was the international treaty requirement that the DSM be consistent with the ICD (see above), which was undergoing revision. Although content changes were again relatively minor, the process through which DSM-IV revisions were derived witnessed a marked change. Revisions were driven much more by data than before, and the process was more systematic and better documented. As outlined in the DSM-IV itself: (a) review papers were commissioned by the APA addressing relevant literature for almost all existing and proposed categories; (b) the NIMH funded 12 multisite field trials to collect data to inform decisions about revisions to criteria; (c) the MacArthur Foundation provided funding for several investigators to reanalyze existing data sets, thereby providing additional data relevant to proposed revisions, and; (d) the literature reviews, results from field trials, reanalyses, and rationales for all revisions were published in a multivolume DSM-IV Sourcebook (e.g., APA, 1996). A similar process was carried forward to the DSM-5, as described below. DSM-IV-TR. In the text revision to the DSM-IV, published in 2000 (APA, 2000), diagnostic categories and their criteria were left almost completely unchanged. Instead, factual errors were corrected; sections of text describing each diagnostic category, associated features, advances in laboratory and clinical research, and so on were revised based on new research; and diagnostic codes that had changed in the latest edition of the ICD were updated. DSM-5. The revision process for the DSM-5 (APA, 2000) began in 1999 with an informal discussion about the need to improve validity of psychiatric diagnosis between Steven Hyman, director of the NIMH; Steven Mirin, medical director of

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the APA; and David Kupfer, chair of the APA Committee on Psychiatric Diagnosis and Assessment at the NIMH (APA, 2012a). This discussion spawned the initial DSM-5 Research Planning Conference in 1999, sponsored by both the APA and the NIMH. Participants invited to this conference included experts in behavioral genetics, molecular genetics, neuroscience, life-span development, cognition, and behavior. Notably, many of those involved in the DSM-IV revision were not invited, with the explicit purpose of encouraging new thinking. The Committee commissioned a series of white papers to identify (a) areas of needed research, (b) cross-cutting unresolved issues in psychiatric diagnosis, (c) ways in which the burgeoning research base in neuroscience could inform psychiatric diagnosis, and (d) issues of culture in psychopathology, among others. Soon after the conference, Darrel Regier was recruited to coordinate development of the DSM-5. Regier became vice chair of the DSM-5 Task Force, which was chaired by David Kupfer. A first set of white papers appeared in 2002 (Kupfer, First, & Regier, 2002), and a second set appeared in 2007 (Narrow, First, Sirovatka, & Regier, 2007). These edited volumes identified specific areas in which new research was needed. Between 2004 and 2008, 13 conferences were held among experts at the NIMH, the APA, the WHO, the American Psychiatric Institute for Research and Education, the National Institute on Drug Abuse, and the National Institute on Alcoholism and Alcohol Abuse. Participants from both the United States and other nations wrote a series of review papers, from which more specific research agendas were developed (APA, 2012b). In 2006, Kupfer and Regier nominated chairs of the diagnostic work groups for the DSM-5 Task Force, who were approved by the APA Board of Trustees in 2007. These chairs then recruited leading experts in their fields to populate individual work groups, which were approved by the APA in 2008, after they had begun meeting. Thirteen work groups were formed, representing major diagnostic categories in the DSM-IV-TR (APA, 2000). As with previous revisions (see above), the DSM-5 Task Force implemented a series of field trials, this time to ascertain the validity, reliability, feasibility, and clinical utility of proposed criteria, including new dimensional indices—an approach never used in previous versions of the DSM. A goal of the field trials was to develop diagnostic criteria that are useful in both research and clinical settings. However, the design and implementation of the field trials were controversial, and the reliability of a number of criterion sets proved to be disappointing (Frances & Widiger, 2012; Regier et al., 2013), although they led to some revisions of criteria (APA, 2012c). The personality disorders (PD) section was one of the most controversial parts of DSM-IV, and significant changes to PDs were anticipated in DSM-5. Indeed, the PD Work Group proposed a hybrid categorical/dimensional approach to diagnosis that required meeting overarching criteria for PD including impairment in self and interpersonal functioning. It also added five higher-order pathological trait dimensions

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(negative affectivity, detachment, antagonism, disinhibition, psychoticism) and 25 lower-order facets on which all individuals would be rated. In addition, they recommended retaining only six of the 10 specific PD diagnoses: obsessive-compulsive, narcissistic, schizotypal, avoidant, antisocial, and borderline, with revisions of specific criteria for these diagnoses to reflect the pathological traits noted above (see Klein, Bufferd, Dyson, & Danzig, 2014 for a discussion of the application of these criteria in youth). The four PDs with the smallest databases—paranoid, schizoid, histrionic, and dependent—were to be dropped. These changes would have been a marked departure from the DSM-IV-TR, which used a categorical system in which PDs were grouped into three clusters (Cluster A, paranoid, schizoid, schizotypal; Cluster B, antisocial, borderline, histrionic, narcissistic; Cluster C, avoidant, dependent, obsessive-compulsive) and did not include overarching criteria for PD or trait dimensions. Despite recommendations of the PDs Work Group, these changes were not implemented, and the PDs section of the DSM-5 was left unchanged from DSM-IV-TR. Proposed changes offered by the DSM-5 PDs Work Group appear in Section III of the manual (emerging measures and models) and are being used by researchers, but it is unlikely that this system will be used in clinical practice. In contrast, changes were made to a number of other sections. Here we focus on the most notable of these changes. Interested readers are referred to Beauchaine and Hayden (2016), and to specific chapters in this volume, for more detailed accounts. A major change was elimination of the DSM-IV multiaxial system of diagnosis (see above). The rationale for this change stemmed from the conceptual overlap between the major Axis I clinical syndromes and the Axis II personality disorders, as many Axis I disorders share the hallmarks of personality disorders—early-onset, persistence, and pervasive impact on functioning (Klein et al., 2014). In addition, Axes III, IV, and V were often if not usually ignored in applied settings. Several changes, albeit minor, were made to ADHD. The DSM-IV-TR included three ADHD subtypes, including primarily hyperactive-impulsive, primarily inattentive, and combined. This subtyping scheme was dropped from the DSM-5 in favor of presentations, which specify whether criteria have been met for hyperactivity/impulsivity, inattention, or both (i.e., combined)—specifically in the past 6 months. This change follows from recognition that many children move in and out of subtypes over time (e.g., Todd et al., 2008). In addition, the DSM-5 no longer includes ADHD among the disruptive behavior disorders, but instead moves it to the neurodevelopmental disorders section, which includes intellectual disabilities, communication disorders, autism spectrum disorder, specific learning disorder, and motor disorders. This decision was based on (a) evidence for aberrant neural responding and functional connectivity across several brain regions/networks among children, adolescents, and adults with ADHD (see e.g., Chapter 13 [Nigg]; Diamond, 2005; Fair et al., 2013; Plichta & Scheres, 2014; Rubia, 2011), and (b) hope that classifying ADHD as a neurodevelopmental disorder will lead to early

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diagnosis, more thorough assessment, easier access to intervention, and more research on effects of comorbid inattention and learning disabilities on academic achievement (see Tannock, 2013). In addition, the age of onset criterion for impairing symptoms was increased from under 7 to under 12 years of age, and symptom thresholds were reduced somewhat for adult diagnoses. More radical changes, such as expanding the number of impulsivity-related symptoms, were not adopted. Changes were also made to the mood disorders section. In contrast to the DSM-IV-TR, which had one mood disorders section, the DSM-5 differentiates between unipolar and bipolar disorders by parsing the categories into two sections, in order to acknowledge the link between bipolar disorder and schizophrenia spectrum disorders. In addition, the exclusionary criterion for bereavement is removed for major depressive disorder (MDD), given little evidence for meaningful differences between depressive episodes following loss compared with those that occur in other contexts (e.g., Kendler, Myers, & Zisook, 2008; although see Wakefield, 2013 for an opposing view). A new category of mood disorder, persistent depressive disorder, subsumes DSM-IV-TR chronic MDD and dysthymic disorder, given limited evidence of meaningful differences between the two syndromes (e.g., Klein, 2010; Klein, Shankman, Lewinsohn, Rohde, & Seeley, 2004). More fundamental changes were made to the anxiety disorders section. Panic disorder and agoraphobia are now separate disorders, and posttraumatic stress disorder is moved from the anxiety disorders chapter into a new section, trauma and stressor-related disorders, given evidence of partially distinct etiologies (e.g., Stein, Craske, Friedman, & Phillips, 2011). Perhaps the largest change is elimination of OCD from the anxiety disorders section, which follows from emerging evidence that anxiety disorders and OCDs exhibit different patterns of comorbidity and arise from partially independent neural substrates (e.g., Stein et al., 2010; although see Abramowitz & Jacoby [2015] for a dissenting view). Finally, the DSM-5 no longer distinguishes between anxiety disorders of childhood vs. adulthood, given limited evidence validity of such distinctions (e.g., Bögels, Knappe, & Clark, 2013). Thus, separation anxiety can be diagnosed at any age. In addition to changes made to existing disorders, several new disorders were added to the DSM-5, a few of which are especially relevant for children and adolescents (although most also apply to adults). Disruptive mood dysregulation disorder (DMDD), which is characterized by severe tantrums accompanied by persistent dysphoric mood, was added to the depressive disorders section in DSM-5. This diagnosis was created, in large part, to reduce rampant overdiagnosis of pediatric bipolar disorder (see e.g., Batstra et al., 2012), given evidence that most children with severe mood dysregulation are not on the bipolar spectrum (see Chapter 21 [Blader, Roybal, Sauder, & Carlson]; Carlson & Klein, 2014). However, studies of the course and validity of DMDD are only beginning to appear (e.g., Dougherty et al., 2014). Another new diagnosis is intermittent explosive disorder (IED), which is characterized by severe emotional lability (particularly anger and aggression). IED differs

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from DMDD in that it does not require persistent dysphoria between outbursts, or a childhood onset. IEE has a lifetime prevalence rate of almost 8% among adolescents (McLaughlin et al., 2012). A third addition to the DSM-5 is nonsuicidal self-injury (NSSI), which is listed as a condition for further study. Adding NSSI follows from recognition that (a) its prevalence rate has increased in recent years (Nock 2010); (b) it is exhibited by a large proportion of depressed adolescents, especially girls (e.g., Wilkinson, Kelvin, Roberts, Dubicka, & Goodyer, 2011); (c) it is often a developmental precursor to borderline personality disorder (e.g., Crowell, Beauchaine, & Linehan, 2009); (d) it is associated with altered patterns of central nervous system activity (e.g., Sauder, Derbidge, & Beauchaine, 2015), peripheral nervous system activity (e.g., Crowell et al., 2005), neuroendocrine responding (Beauchaine, Crowell, & Hsiao, 2015), and serotonergic function (e.g., Crowell et al., 2008); and (e) it marks considerable functional impairment, both concurrently and prospectively, and predicts future suicide attempts better than any other independent variable (e.g., Klonsky, May, & Glenn, 2012; Nock 2010).

THE DSM AND DEVELOPMENTAL PSYCHOPATHOLOGY Although it is important for any student of psychopathology to understand the history behind, rationale for, and use of the predominant classification system of mental disorders in the United States, it is equally important to understand limitations of that system. Indeed, several departures in philosophy between the DSM approach and the developmental psychopathology approach to characterizing mental health are apparent. Historically, criticisms of the DSM have come from both within and outside psychiatry (see e.g., McCarthy & Gerring, 1994; van Praag, 2010), with developmental psychopathologists providing some of the most incisive critiques (e.g., Richters & Cicchetti, 1993). We and others have summarized these critiques, and provided a few of our own elsewhere (e.g., Beauchaine, 2003; Beauchaine et al., 2009; Cummings, Davies, & Campbell 2000; Hinshaw & Park, 1999; Hudziak, Achenbach, Altoff, & Pine, 2007). Here we provide an overview of such criticisms, some of which are specific to the DSM-5, but most of which apply to the overall philosophy that undergirds—oftentimes implicitly—categorical diagnostic systems.

Problems With Changes to the DSM-5 Even though most changes to the DSM-5 were minor, it will take years of research to determine how effective this newest revision will be in increasing the validity of psychiatric diagnosis—a major objective of the DSM-5 Task Force, the APA, and other interested parties (see e.g., Kraemer, Kupfer, Narrow, Clarke, & Regier, 2010). It is

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likely, however, that several decisions made by the DSM-5 Task Force will interfere with this objective. Although the Task Force explicitly charged DSM-5 workgroups with proposing changes that were founded in empirical research, the Task Force ultimately ignored several of these recommendations. For example, despite strong evidence that several PDs can be diagnosed reliably in adolescence and that developmental precursors to these PDs exist (see e.g., Chapter 19 [Kaufman, Crowell, & Lenzenweger]; Beauchaine et al., 2009; Crowell, Kaufman, & Beauchaine, 2014; Klein et al., 2014), the DSM-5 proscribes PD diagnoses among those who are under age 18 years. Second, the DSM-5 retains all DSM-IV-TR PDs, despite little evidence for the validity of several and almost no evidence for validity of the A, B, and C clustering structure outlined above (see Beauchaine et al., 2009). The decision to move ADHD into the neurodevelopmental disorders section and out of the disruptive behavior disorders section is also problematic in some ways. As noted earlier, this decision was based largely on practical grounds, such as hopes for earlier diagnosis, more thorough assessment, easier access to intervention, and more research on effects of comorbid inattention and learning disabilities on academic achievement (Tannock, 2013). Notably, such considerations were not applied to other disorders. If they had been, one could argue convincingly that conduct disorder (CD) should have also been moved, since ADHD and CD share common neurodevelopmental substrates and psychopathological endpoints (see Chapter 13 [Nigg]; Beauchaine & McNulty, 2013; Diamond, 2005; Fair et al., 2013; Gatzke-Kopp, 2011; Gatzke-Kopp et al., 2009; Kopp & Beauchaine, 2007; Rubia, 2011). Thus, moving ADHD to a different section of the DSM obscures its etiological connections with CD and other disruptive behavior disorders (see Beauchaine & Hayden, 2016; Beauchaine & Hinshaw, 2016; Beauchaine, Zisner, & Sauder, 2017). Of course, there is not complete correspondence between (a) ADHD and (b) CD and other antisocial-spectrum conditions (for a historical overview, see Hinshaw, 1987; see also Ahmad & Hinshaw, 2016), but placing ADHD in the neurodevelopmental disorders section may not be conceptually clarifying in all respects. From a developmental psychopathology perspective, the decision to drop the multiaxial structure that characterized the DSM-III, DSM-III-R, DSM-IV, and DSM-IV-TR, particularly Axis IV (psychosocial and environmental stressors), is also unfortunate. De-emphasizing psychosocial and contextual factors downplays the important role that environment plays in shaping almost all forms of mental illness—even those with strong genetic underpinnings (see Chapters 1 [Hinshaw] and 3 [Beauchaine, Gatzke-Kopp, & Gizer] Beauchaine et al., 2017).

Additional Criticisms of the DSM Approach Problems With Construct Validity. Although application of the Feighner Criteria and the RDC to some (though not nearly all) disorders represents an attempt to ensure

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diagnostic validity (see above), reliability has been of far greater concern from the DSM-III onward (APA, 1980; see e.g., Kraemer, Kupfer, Narrow, Clarke, & Regier, 2010). It is important to note that reliability is necessary for validity but does not ensure validity. To use a somewhat hyperbolic example, separate raters can agree with very high precision that a person is over 6′ 5′′ (reliability), but such agreement says nothing about height being a symptom of mental illness (validity). Indeed, any such assertion would be fully arbitrary—a situation that applied to sexual orientation before the seventh printing of the DSM-II, when homosexuality was considered a mental disorder (see above). In developmental psychopathology research, construct validity refers to the extent to which symptoms of a diagnosis mark an objective, nonarbitrary entity that relates to mental health outcomes. Construct validity should be considered whenever the cause of a trait cannot be observed directly (Cronbach & Meehl, 1955), which is usually the case for psychopathology. To borrow an example we have used elsewhere (Beauchaine & Marsh, 2006), consider the difference between a medical syndrome such as pancreatic cancer and a common psychiatric condition such as MDD. In the former case, a patient presents at his/her physician’s office with a collection of symptoms, which might include weight loss, dark urine, nausea, and abdominal pain. This collection of symptoms, or manifest indicators, leads to a hypothesis on the part of the physician regarding its unobserved, or latent cause. Importantly, for a medical condition such as pancreatic cancer, the hypothesis is confirmed or disconfirmed by a biopsy or other diagnostic test. If the biopsy is positive, the cause of the disorder becomes known. If the biopsy is negative, a new hypothesis is generated and tested. Compare this with a depressed individual, who also presents with a collection of symptoms, including depressed mood, anhedonia, fatigue, weight loss, and insomnia. In contrast to the case of pancreatic cancer, there are no diagnostic tests that can identify most causes of depression (although certain medical conditions such as hypothyroidism can be identified and should therefore be ruled out). Thus, we are left with a somewhat tautological definition of depression: The patient is depressed because s/he presents with a collection of symptoms, and the patient presents with a collection of symptoms because s/he is depressed. We are therefore forced to infer psychopathology with no gold standard or pathognomonic sign of disease state (see Beauchaine & Thayer, 2015). Under such conditions, difficulties posed for construct validation of psychiatric disorders are often formidable. Prior to publication of the DSM-III (APA, 1980), almost no evidence existed for the construct validity of any diagnostic category (Kendell, 1989), because all were derived clinically rather than through systematic research (see above). At present, even after decades of relevant research, unanswered questions about the construct validity of many psychiatric disorders abound. For example, in research on pediatric bipolar disorder, issues regarding proper diagnostic cutoffs and delimitation from other disorders including

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ADHD have not been addressed fully (see Chapter 21 [Blader, Roybal, Sauder, & Carlson] Carlson & Klein, 2014). Heterogeneity Within Diagnostic Classes. A related issue follows from the observation that diverse etiologies often result in what appears to be a single disorder, a phenomenon known as equifinality (see Chapter 1 [Hinshaw]). For example, impulsivity may arise from one of several sources, each of which may be expressed behaviorally as ADHD (see Chapters 6 [Neuhaus & Beauchaine], 13 [Nigg], & 10 [Arnett et al.]; Castellanos-Ryan & Séquin, 2015; Zisner & Beauchaine, 2015). However, since DSM diagnoses are all derived syndromally (i.e., from symptoms with little if any regard to etiology or pathophysiology), different underlying causes of a disorder may never be ascertained, even when it is possible to do so. Both treatment and prevention are improved when pathophysiological and etiological diagnosis are used rather than syndromal diagnosis (see Beauchaine et al., 2008; Preskorn & Baker, 2002). For example, if hypothyroidism is identified in the pathophysiology of depression, treatment follows a very different course (synthetic thyroxine treatment) than antidepressant use and/or psychotherapy. Although this example may seem extreme, potentially meaningful distinctions among depression subtypes are underemphasized in the DSM-5. For example, melancholia—a subtype of depression that appears to arise from different etiological mechanisms than nonmelancholic depression (see Leventhal & Rehm, 2005)—may confer increased risk of adverse long-term functional outcomes including suicide (e.g., Carroll, Greden, & Feinberg, 1980; Coryell & Schlesser, 2001), yet it is not classified as a separate mood disorder, even though some argued ardently for doing so in the DSM-5 (e.g., Parker et al., 2010). Categorical Versus Dimensional Measurement. One of the most persistent criticisms of the DSM is that all disorders are diagnosed categorically (i.e., present vs. absent), even though overwhelming research evidence indicates that most forms of psychopathology (a) reflect extreme expressions of continuously distributed traits (see e.g., Haslam, Holland, & Kuppens, 2012; Hudziak et al., 2007; Krueger & Tackett, 2015; Krueger, Watson, & Barlow, 2005; Trull & Durrett, 2005), and (b) are rooted in interactions among neural systems that subserve overlapping behavioral and emotional functions (see e.g., Beauchaine, 2015; Beauchaine & Thayer, 2015). Even in rare exceptions when psychiatric vulnerability may be distributed categorically (e.g., schizotypy; see Lenzenweger, McLachlan, & Rubin, 2007), individual differences in symptom expression are nevertheless observed and meaningful functionally (Beauchaine, Lenzenweger, & Waller, 2008). They also provide key information about current functioning and long-term prognosis. Other adverse consequences of categorizing dimensions include difficulty ascertaining optimal diagnostic cutoffs (e.g., 95th percentile? 98th percentile?

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see Meehl, 1995), and loss of statistical information (see MacCallum, Zhang, Preacher, & Rucker, 2002). Individuals in need of intervention may also be turned away because they fail to meet diagnostic criteria even though they suffer considerable impairment. To address such problems, hybrid classification systems have been proposed in which both presence vs. absence and severity of psychopathology are assessed (e.g., Hudziak et al., 2007). As outlined above, such an approach was recommended by the PDs Work Group for the DSM-5, but was ultimately rejected. Notably, dimensional assessment has long been used in child psychopathology research, even when applying DSM criterion sets (e.g., Achenbach & Edelbrock, 1991; Conners, Sitarenios, Parker, & Epstein, 1998; Gadow & Sprafkin, 1997; Robinson, Eyberg, & Ross, 1980). Such is not the case in adult psychopathology research. Failure to Consider Development. Developmental psychopathologists have been especially critical of the DSM because it fails to consider issues of development in diagnosis (e.g., Beauchaine et al., 2017; Richters & Cicchetti, 1993; Sroufe, 1997). With few exceptions (e.g., early-onset conduct disorder; see Chapter 14 [Lahey & Waldman]), child and adolescent psychopathology are assessed and diagnosed without consideration of normative developmental trends in behavior, and without acknowledgement that single behavioral traits—including those that confer vulnerability to psychopathology—may be expressed differently at different ages. Heterotypic continuity refers to such changes in the behavioral expression of psychopathology across development (see Chapter 1 [Hinshaw]). As an example, we have known for over 50 years that delinquent adult males almost invariably traverse a developmental pathway that begins with severe hyperactivity/impulsivity as early as toddlerhood, followed in rough temporal sequence by oppositional defiant disorder (ODD; Chapter 14 [Lahey & Waldman]) in preschool, early-onset conduct disorder (CD; Chapter 14 [Lahey & Waldman]) in elementary school, substance use disorders (SUDs; Chapter 15 [Brown, Tomlinson, & Winward]) in adolescence, and antisocial personality disorder (ASPD) in adulthood (see e.g., Beauchaine & Hinshaw, 2016; Beauchaine & McNulty, 2013; Beauchaine et al., 2017; Loeber & Hay, 1997; Lynam, 1998; Robins, 1966). Thus, even though continuity in externalizing conduct is common among those on this trajectory, specific behaviors vary considerably across development (Ahmad & Hinshaw, 2016; Beauchaine, Shader & Hinshaw, 2015; Hinshaw, Lahey, & Hart, 1993). Among other consequences, failure to consider heterotypic continuity results in (a) a research literature that is fractionated based on topographies of behavior (e.g., tantrums in toddlerhood, truancy in elementary school, substance use in adulthood) rather than etiology, (b) alternative treatment strategies for conditions such as CD and SUDs that are not informed by one another when they would benefit from being so (see Beauchaine et al., 2008), and (c) faulty conclusions about etiology and comorbidity of externalizing disorders (see Beauchaine et al., 2010). Finally, there is growing evidence that many

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preschool-aged children meet DSM criteria for psychiatric disorders (Bufferd, Dougherty, Carlson, Rose, & Klein, 2012). However, it is often unclear where to draw the line between developmentally normative and pathological behavior in early childhood, and whether diagnostic criteria developed for older children, adolescents, and adults are appropriate for preschoolers (Bufferd, Dyson, Hernandez, & Wakschlag, 2016). Failure to Consider Culture and Other Contextual Issues. In general, the DSM is indifferent to both (a) culturally induced individual differences in behavior that might be mistaken for psychopathology (see e.g., Marsella & Yamada, 2010), and (b) cultural, socioeconomic, and other contextually driven individual differences in the expression of psychopathology (see e.g., Lewis-Fernández et al., 2010; Gone & Kirmayer, 2010). As a result, strict adherence to DSM criterion sets without consideration of race, ethnicity, and class can lead to both false positive and false negative conclusions regarding the presence versus absence of psychopathology. One objective of the developmental psychopathology approach is to construct a discipline that acknowledges the role of context in shaping behavior, and that does not assume—even implicitly—that group differences in behavior between members of the dominant social class and other cultural subgroups always imply deficits in functioning among the latter (e.g., Garcia-Coll, Akerman, & Cicchetti, 2000; Cicchetti & Toth, 2009; see also Chapter 1 [Hinshaw]).

EMPIRICALLY DERIVED CLASSIFICATION SYSTEMS Early on, the DSM was, and in many ways remains, a top-down, deductive approach to classifying psychopathology. Opinions of experts are still weighed heavily in the revision process, and empirical findings are sometimes eschewed, despite explicit calls for, both within and outside DSM workgroups, a research-based taxonomy of mental illness (see above). In stark contrast to this approach, developmental psychopathologists have a long history of constructing and using, in both research and clinical settings, bottom-up, inductive systems of classification and assessment that derive almost fully from empirical interrelations among symptoms of psychopathology. The earliest and most renowned of these is the parent-report Child Behavior Checklist (CBCL; Achenbach & Edelbrock, 1983), which was later expanded to include both teacher (Teacher Report Form [TRF]; Achenbach & Edelbrock, 1986) and self-report versions (Youth Self-Report [YSR]; Achenbach & Edelbrock, 1987). Collectively, these instruments, along with more newly developed adult versions, comprise the Achenbach System of Empirically Based Assessment (ASEBA; Achenbach, 2009). The CBCL and its successors were derived from factor analyses of large sets of symptoms of psychopathology. These studies, and subsequent factor-analytic evaluations of adult psychopathology (e.g., Krueger, 1999), demonstrated a remarkably consistent hierarchical latent structure of mental illness in which two higher-order,

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internalizing

internalizing spectrum disorder 1

internalizing spectrum disorder 3

internalizing spectrum disorder 2

externalizing

externalizing spectrum disorder 1

externalizing spectrum disorder 3

externalizing spectrum disorder 2

Figure 2.1 A simplified depiction of the hierarchical latent structure of psychopathology. Adapted from Beauchaine and Thayer (2015).

latent factors, internalizing and externalizing, account for much of the covariation among first-order factors (i.e., behavioral syndromes).2 This hierarchical latent structure of psychopathology is depicted in Figure 2.1. First-order internalizing factors include constructs such as anxious/depressed, withdrawn/depressed, and somatic complaints, whereas first-order externalizing factors include constructs such as impulsivity, rule-breaking behavior, and aggression. When using the CBCL and related empirically based assessment instruments, children and adolescents (and/or parent and teachers) rate each symptom, and these ratings are summed to provide scores on individual first-order syndromes. Syndrome scores are then added to compute broad-band (i.e., higher-order) internalizing and externalizing scores. There are several advantages of empirically based assessment, compared with the approach to diagnosis represented in the DSM. First, raters are not forced to render dichotomous diagnostic decisions. Rather, each individual receives a set of scale scores, the severity of which can be evaluated vis-à-vis national norms. Oftentimes, children who score at or above the 95th percentile are considered to be clinically impaired. Lower but elevated scores, such of those above 85th percentile, may also be flagged for concern. Second, empirically based assessment does not 2. Factor analysis is a mathematical approach to reducing large numbers of items (in this case, symptoms), into a smaller number of factors, each of which consists of items that share common variance. Although most factor analyses of psychopathology allow for correlated factors, correlations of items within factors exceed correlations of items across factors. Interested readers are referred elsewhere for detailed accounts of factor analysis (e.g., Thompson, 2004).

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force diagnosticians, even implicitly, to choose one disorder over others. Rather, elevated scores both within and across internalizing and externalizing domains are observed and expected, which “carves nature at its joints” more effectively than assigning a single disorder. For example, adolescents with conduct disorder (CD), although likely to experience symptoms of ADHD, are often diagnosed only with the former disorder, which may interfere with treatment and obscure etiological relations between the two conditions (e.g., Beauchaine et al., 2010; 2017). Third, such systems are more sensitive to capturing heterotypic comorbidity, whereby an individual with a primary externalizing disorder, for example, also displays—often subclinically—symptoms of an internalizing disorder (see, e.g., Zisner & Beauchaine, in press). Based on these considerations and others, empirically based assessment is used in almost all research contexts among developmental psychopathologists, even when DSM-derived diagnoses are also evaluated.

THE RESEARCH DOMAIN CRITERIA In 2009, the NIMH, as part of its Strategic Plan (NIMH, 2015a), launched a new initiative, the Research Domain Criteria (RDoC; e.g., Cuthbert & Insel, 2013; NIMH, 2015b; Sanislow et al., 2010), to provide an alternative framework, particularly for research purposes, of studying and ultimately classifying psychopathology. RDoC was developed out of frustration with the slow pace in understanding the etiopathogenesis of, and development of effective treatments for, mental disorders, and a sense that the DSM has not adequately facilitated and may have hindered such progress (Insel et al., 2010). RDoC acknowledges that nearly all current DSM-defined clinical phenotypes are etiologically heterogeneous and lack neurobiological validity, and that information about core etiological mechanisms is needed to identify more homogeneous, biologically valid phenotypes (see also Beauchaine & Thayer, 2015)—a precondition for specifying molecular genetic substrates of psychopathology (see Chapter 6 [Neuhaus & Beauchaine]). Furthermore, RDoC assumes that key etiological influences, and ultimately clinical phenotypes, take the form of dimensions rather than discrete classes, an observation that has proven almost axiomatic in psychopathology research (see e.g., Forbes, Tackett, Markon, & Krueger, in press; Krueger & Tackett, 2015; Krueger et al., 2002). RDoC descends from biobehavioral motivational systems perspectives, which were advanced initially in the mid- to late 20th century by distinguished investigators including Jeffrey Gray (see e.g., Gray, 1987) and Peter Lang (e.g., Lang, Bradley, & Cuthbert, 1992). These investigators identified broad, neurally mediated activation/approach and inhibition/withdrawal systems, which predispose to individual differences in dispositional responding to specific classes of stimuli (e.g., Beauchaine & Thayer, 2015; Fowles, 1988). RDoC, which is intended to be an evolving project that integrates research across human and infrahuman species, posits the existence of five major domains of behavior, which should be studied across multiple units of analysis, ranging from genes to molecules to cells to neural

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circuits (e.g., emotion-modulated startle) to physiology (e.g., heart rate) to behavior (naturalistic observation or in particular tasks) to self-reports (interviews, questionnaires). These five domains, each of which includes a number of subdomains, were selected for their potential relevance to psychopathology, and because aspects of their neural circuitry are already understood. The domains include negative valence systems (acute threat [or fear], potential threat [or anxiety], sustained threat, loss, and frustrative nonreward); positive valence systems (e.g., initial responsiveness to reward, sustained responsiveness to reward, reward learning); cognitive systems (e.g., attention, perception, cognitive control, working memory), systems for social processes (e.g., affiliation and attachment, social communication, perception and understanding of the self, perception and understanding of others), and arousal and regulatory systems (arousal, circadian rhythms, sleep and wakefulness) (NIMH, 2015b). These five domains and their subdomains are presented in a series of rows, and units of analysis head a series of columns, which together comprise the RDoC matrix (Morris & Cuthbert, 2012). Ultimately, cells in the matrix will be filled with measures of constructs in each domain, at each unit of analysis (e.g., fear-potentiated startle is a measure of the acute fear subdomain at the unit of circuits). Following from Cronbach and Meehl’s (1955) classic construct validation framework, the goal is to develop and test a “nomological network” of hypotheses about interrelations among measures at various levels of analysis for each construct represented in the domains and subdomains. The RDoC matrix also includes a column for paradigms, referring to tasks that are particularly useful in assessing the domain construct (National Advisory Mental Health Council Workgroup on Tasks and Measures for Research Domain Criteria, 2016). Finally, two important dimensions that are recognized as being critically important but are not formally included in the matrix are environmental influences and development (Casey, Oliveri, & Insel, 2014). Despite its significant effect on funding priorities in the United States, RDoC is still very much under development and faces a number of questions and challenges. First, it is not clear how thoroughly and systematically development, the course of psychopathology, and environmental influences (including culture) will be incorporated, given that these are not formally represented in the matrix. Second, the construct validity of the domains and subdomains is only partially established. For example, it must be determined whether RDoC should include all of the most crucial domains and subdomains, and whether the convergent and discriminant validity of the domains and subdomains are consistent with the structure posited in the matrix. Third, even if phenotypes are defined on the basis of underlying processes rather than clinical presentation, it is likely that complex behaviors reflect interactions among multiple domains and subdomains (multifinality), and that particular domains and subdomains contribute to many different patterns of behavior (equifinality) (Beauchaine & Thayer, 2015). Fourth, measures for many of the cells in the matrix have yet to be identified, and the construct validity of many (if not most) of the candidate measures is only partially established. Moreover, related

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to the previous point, it is likely that most of the endophenotypes/intermediate phenotypes that populate the cells are themselves highly complex (Iacono, Vaidyanathan, Vrieze, & Malone, 2014; see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]), and may reflect effects of multiple domains and subdomains. Fifth, magnitudes of associations between measures at different levels of analysis are often very modest, making it difficult to demonstrate construct validity (Patrick et al., 2013). Sixth, there are significant conceptual challenges to understanding relationships between and across units of analysis (Cicchetti, 2008; Meehl, 1977; Miller, 2010). Seventh, despite efforts not to privilege lower units of analysis, there are concerns that it may be susceptible to biological reductionism (e.g., Beauchaine et al., 2017; Berenbaum, 2010). Finally, and perhaps most importantly, the RDoC matrix does not include clinical phenotypes to classify patients and provide targets for clinical research and treatment. Although this omission raises questions about clinical relevance, it is central to the entire endeavor. RDoC assumes that biologically valid phenotypes are likely to be narrower than, or cut across, diagnostic constructs in the DSM. Thus, a major goal of the RDoC initiative is to identify phenotypes that are related to impairment in core domains of biobehavioral functioning. Just as 35 years ago the field assumed that introduction of operational diagnostic criteria in DSM-III (APA, 1980) would increase reliability, thereby leading to more valid phenotypes, enhanced understanding of etiopathogenesis, and the development of more effective treatments (see above), proponents of RDoC are wagering that research elucidating core biobehavioral systems across multiple units of analysis will yield more valid phenotypes and better understanding of the causes and treatment of mental disorders.

CONCLUSIONS In this chapter, we reviewed historical developments in psychiatric diagnosis and identified core issues confronted by those who seek to classify psychopathology. As our review indicates, the history of the DSM, RDoC, and the complexities behind their development are far more intricate than might be surmised at first glance. Although considerable efforts of many talented scientists have contributed to revising the DSM, longstanding issues of validity (and to a lesser extent reliability) remain to be addressed fully. Among the most important limitations of the DSM framework are its failures to (a) capture developmental processes underlying current and future risk for psychopathology, (b) specify pathophysiological and etiological mechanisms of psychopathology, (c) map broad biobehavioral traits that predispose to psychopathology across traditional diagnostic boundaries, and (d) account fully for contextual influences such as ethnicity and culture on the development of psychopathology. Although the RDoC initiative addresses some of these limitations, it ignores others—particularly those related to development, environment, and culture. These and other issues, which are central to the developmental psychopathology perspective (Chapter 1 [Hinshaw]), are addressed in chapters to follow.

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Kopp, L., & Beauchaine, T. P. (2007). Patterns of psychopathology in the families of children with conduct problems, depression, and both psychiatric conditions. Journal of Abnormal Child Psychology, 35, 301–312. Kraemer, H. C., Kupfer, D. J., Narrow, W. E., Clarke, D. E., & Regier, D. A. (2010). Moving toward DSM-5: The field trials. American Journal of Psychiatry, 167, 1158–1160. Krueger, R. F. (1999). The structure of common mental disorders. Archives of General Psychiatry, 56, 921–926. Krueger, R. F., Eaton, N. R., Clark, L. A., Watson, D., Markon, K. E., Derringer, J., . . . Livesley, W. J. (2011). Deriving an empirical structure of personality pathology for DSM-5. Journal of Personality Disorders, 25, 170–191. Krueger, R. F., Hicks, B. M., Patrick, C. J., Carlson, S. R., Iacono, W. G., & McGue, M. (2002). Etiologic connections among substance dependence, antisocial behavior, and personality: Modeling the externalizing spectrum. Journal of Abnormal Psychology, 111, 411–424. Krueger R. F., & Tackett, J. L. (2015). The externalizing spectrum of personality and psychopathology: An empirical and quantitative alternative to discrete disorder approaches. In T. P. Beauchaine & S. P. Hinshaw (Eds.), Oxford handbook of externalizing spectrum disorders (pp. 79–89). New York, NY: Oxford University Press. Krueger, R. F., Watson, D., & Barlow, D. H. (2005). Toward a dimensionally based taxonomy of psychopathology [Special section]. Journal of Abnormal Psychology, 114, 491–569. Kupfer, D. J., First, M. B., & Regier, D. A. (2002). A research agenda for DSM-V. Washington, DC: American Psychiatric Association. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1992). A motivational analysis of emotion: Reflex-cortex connections. Psychological Science, 3, 44–49. Laurin, M. (2010). The subjective nature of Linnaean categories and its impact in evolutionary biology and biodiversity studies. Contributions to Zoology, 79, 131−146. Leckman, J. F., Weissman, M. M., Merikangas, K. R., Pauls, D. L., & Prusoff, B. A. (1983). Panic disorder and major depression: Increased risk of depression, alcoholism, panic, and phobic disorders in families of depressed probands with panic disorder. Archives of General Psychiatry, 40, 1055–1060. Leibenluft, E., & Stoddard, J. (2013). The developmental psychopathology of irritability. Development and Psychopathology, 25, 1473–1487. Lenzenweger, M. F., McLachlan, G., & Rubin, D. B. (2007). Resolving the latent structure of schizophrenia endophenotypes using expectation-maximization-based finite mixture modeling. Journal of Abnormal Psychology, 116, 16–29. Leventhal, A. M., & Rehm, L. P. (2005). The empirical status of melancholia: Implications for psychology. Clinical Psychology Review, 25, 25–44. Lewis-Fernández, R., Hinton, D. E., Laria, A. J., Patterson, E. H., Hofmann, S. G., Craske, M. G., . . . Liao, B. (2010). Culture and the anxiety disorders: Recommendations for DSM-V. Depression and Anxiety, 27, 212–229.

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Rubia, K. (2011). “Cool” inferior frontostriatal dysfunction in ADHD versus “hot” ventromedial orbitofrontal-limbic dysfunction in conduct disorder: A review. Biological Psychiatry, 69, e69–e87. Sanislow, C. A., Pine, D. S., Quinn, K. J., Kozak, M. J., Garvey, M. A., Heinssen, R. K., . . . Cuthbert, B. N. (2010). Developing constructs for psychopathology research: Research Domain Criteria. Journal of Abnormal Psychology, 119, 631–639. Sauder, C. L., Derbidge, C. M., & Beauchaine, T. P. (2015). Neural responses to monetary incentives among self-injuring adolescent girls. Development and Psychopathology. Epublished ahead of print. Scotti, J. R., & Morris, T. L. (2000). Diagnosis and classification. In M. Hersen & R. T. Ammerman (Eds.), Advanced abnormal child psychology (pp. 15–32). Mahwah, NJ: Erlbaum. Shaffer, D., Fischer, P., Lucas, C. P., Dulcan, M. K., & Schwab-Stone, M. E. (2000). NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 28–38. Sibley, M. H., Pelham, W. E., Molina, B. S. G., Waschbusch, D. A., Gnagy, E. M., Babinski, D. E., & Biswas, A. (2010). Inconsistent self-report of delinquency by adolescents and young adults with ADHD. Journal of Abnormal Child Psychology, 38, 645–656. Spitzer, R. L., Endicott, J., & Robins, E. (1978). Research Diagnostic Criteria. Archives of General Psychiatry, 35, 773–782. Spitzer R. L., & Fleiss, J. L. (1974). A re-analysis of the reliability of psychiatric diagnosis. British Journal of Psychiatry, 125, 341–347. Spitzer, R. L., & Williams, J. B. W. (1983). The DSM-III classification of affective disorders. Acta Psychiatrica Scandinavica, S310, 106–116. Spitzer, R. L., Williams, J. B. W., Gibbon, M., & First, M. B. (1990). Structured Clinical Interview for DSM-III-R, Patient Edition/Non-patient Edition (SCID-P/SCID-NP). Washington, DC: American Psychiatric Press. Sroufe, L. A. (1997). Psychopathology as an outcome of development. Development and Psychopathology, 9, 17–29. Stein, D. J., Craske, M. G., Friedman, M. J., & Phillips, K. A. (2011). Meta-structure issues for DSM-5: How do anxiety disorders, obsessive compulsive and related disorders, post-traumatic stress disorders, and dissociative disorders fit together? Current Psychiatry Reports, 13, 248–250. Stein, D. J., Fineberg, N. A., Bienvenu, O. J., Denys, D., Lochner, C., Nestadt, G., . . . Phillips, K. A. (2010). Should OCD be classified as an anxiety disorder in DSM-5? Depression and Anxiety, 27, 495–506. Tannock, R. (2013). Rethinking ADHD and LD in DSM-5: Proposed changes in diagnostic criteria. Journal of Learning Disabilities, 46, 5–25. Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. Washington, DC: American Psychological Association.

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Todd, R. D., Huang, H., Todorov, A. A., Neuman, R. J., Reiersen, A. M., Henderson, C. A., . . . Reich, W. C. (2008). Predictors of stability of ADHD subtypes from childhood to young adulthood. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 76–85. Trull, T. J., & Durrett, C. A. (2005). Categorical and dimensional models of personality disorder. Annual Review of Clinical Psychology, 1, 355–380. van Praag, H. M. (2010). No functional psychopharmacology without functional psychopathology. Acta Psychiatrica Scandinavica, 122, 438–439. Wakefield, J. C. (2013). The DSM-5 debate over the bereavement exclusion: Psychiatric diagnosis and the future of empirically supported treatment. Clinical Psychology Review, 33, 825–845. Wilkinson, P., Kelvin, R., Roberts, C., Dubicka, B., & Goodyer, I. (2011). Clinical and psychosocial predictors of suicide attempts and nonsuicidal self-injury in the adolescent depression antidepressants and psychotherapy trial (ADAPT). American Journal of Psychiatry, 168, 495–501. Wing, J. K., Cooper, J. F., & Sartorius, N. (1974). The measurement and classification of psychiatric symptoms. London, UK: Cambridge University Press. Woodruff, R. A., Goodwin, D. W., & Guze, S. B. (1974). Psychiatric diagnosis. New York, NY: Oxford University Press. World Health Organization. (1966). ICD-8: International statistical classification of diseases and related health problems (10th rev. ed.). Geneva, Switzerland: Author. World Health Organization. (1996). Multiaxial classification of child and adolescent psychiatric disorders. Cambridge: Cambridge University Press. World Health Organization. (2008). ICD-10: International statistical classification of diseases and related health problems (10th ed., rev.). Geneva, Switzerland: Author. World Health Organization. (2015). Classifications: International statistical classification of diseases. Retrieved from http://www.who.int/classifications/icd/en/ Zisner, A., & Beauchaine, T. P. (2016). Midbrain neural mechanisms of trait impulsivity. In T. P. Beauchaine and S. P. Hinshaw (Eds.), Oxford handbook of externalizing spectrum disorders (pp. 184–200). New York, NY: Oxford University Press. Zisner, A., & Beauchaine, T. P. (in press). Common neural circuitry for trait impulsivity, irritability, and anhedonia: A mechanism of heterotypic comorbidity among externalizing disorders and unipolar depression. Development and Psychopathology.

CHAPTER 3

Genetic, Environmental, and Epigenetic Influences on Behavior THEODORE P. BEAUCHAINE, LISA GATZKE-KOPP, AND IAN R. GIZER

HISTORICAL CONTEXT

T

heories regarding causes of psychopathology span much of written history. In the 2nd century A.D., Galen—extending the writings of Hippocrates—attributed temperamental characteristics to individual differences in four bodily humors. According to his account of human behavior, melancholia—or depression—resulted from excess black bile, whereas emotional volatility resulted from excess yellow bile. Although Galen’s theory placed the locus of mental illness within the individual, other historically influential accounts of psychopathology emphasized the role of environment in shaping behavior. Perhaps the most famous of these is Freud’s psychoanalytic theory, which attributed causes of mental illness to intrapsychic conflicts among the id, ego, and superego. According to Freud, both the ego and superego derived their relative strength or weakness almost exclusively from early experience. Although extracted from very different historical epochs, these examples reflect a clear difference in beliefs about the importance of nature versus nurture in the development of mental illness. Until the 20th century, such differences in opinion were irresolvable because formal scientific methods had not been applied to the study of psychopathology, and because appropriate technological and methodological tools had not been developed to effectively parse the relative contributions of heritable and environmental influences on behavior. Toward the end of the century, however, advances in molecular genetics, along with refinements in both behavioral genetics and statistical modeling, provided means for resolving longstanding questions about the etiology of psychopathology (see e.g., Rende & Waldman, 2006). Yet despite these breakthroughs, disagreements over the relative contributions of genes and environment in explaining psychopathology lingered 68

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(see e.g., Albee & Joffe, 2004; Beauchaine, Neuhaus, Brenner, & Gatzke-Kopp, 2008; Rutter, 2014). Indeed, preferred explanations for individual differences in behavior have waxed and waned between genes and environment several times during the past 50 years, often influenced as much by political considerations as by scientific discovery and innovation (see Rutter, Moffitt, & Caspi, 2006). In the past 20 or so years, a far more balanced perspective has emerged. Theoretical advances, the capacity to conduct genome-wide scans, and widespread use of the advanced methods mentioned above have confirmed that both genetic and environmental influences play significant roles in the expression of almost all behavioral traits—including those linked to psychopathology—and that the nature versus nurture question is misleading because it forces us to choose between influences that are almost always interdependent. In fact, environment can affect development by altering gene expression through epigenetic processes, which we describe in later sections. Epigenetic effects blur traditional boundaries between genes and environments in shaping behavior. Furthermore, although genetic and environmental influences on behavior have often been treated as separate, a growing body of research indicates that Gene × Environment interactions are often more important in determining behavior then either factor alone (see Moffitt, Caspi, & Rutter, 2006; Rutter, 2014). It has long been known, for example, that impulsivity is a highly heritable trait (e.g., Hinshaw, 2002, 2003; see also Beauchaine & Gatzke-Kopp, 2012; Beauchaine, Hinshaw, & Pang, 2010; Gizer, Otto, & Ellingson, 2015; Chapter 6 [Neuhaus & Beauchaine]), which confers vulnerability to a host of behavioral disorders including delinquency, antisocial behavior, and both alcohol and substance dependencies (see, e.g., Beauchaine & Cicchetti, 2016a; Beauchaine & McNulty, 2013; Krueger et al., 2002). However, impulsive boys and girls are more likely to develop these conditions in neighborhoods with high rates of drug use, violence, and criminality (Lynam et al., 2000; Meier, Slutske, Arndt, & Cadoret, 2008), and/or when maltreated by caretakers ( Jaffee et al., 2005; Chapter 5 [Jaffee]). Furthermore, genetically vulnerable individuals may evoke reactions from others that exacerbate their inherited susceptibilities to psychopathology, exemplifying evocative gene-environment correlation (e.g., Burt, 2008; O’Connor, Deater-Deckard, Fulker, Rutter, & Plomin, 1998). Thus, combinations of genetically conferred vulnerabilities and environmentally mediated risk factors result in worse outcomes than either influence alone (Beauchaine, Zisner, & Sauder, 2017). When vulnerability and risk interact in such a way, studying either in isolation causes us to underestimate their combined importance (see Beauchaine, Neuhaus et al., 2008). Our primary objective in writing this chapter is to provide an integrated account of the interplay of heritable and environmental influences on psychopathology across the lifespan. We focus primarily on broad conceptual issues given that findings specific to particular forms of psychopathology are presented in later chapters. Our approach is informed considerably by the work of Rutter and others, who have written extensively about the mutual interplay of genes and environment in shaping human development and behavior (see e.g., Moffitt, 2005; Rutter, 2010, 2014; Rutter, Moffitt et al., 2006).

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THE DEVELOPMENTAL PSYCHOPATHOLOGY PERSPECTIVE As outlined in Chapter 1 [Hinshaw], contents of this book are organized around the developmental psychopathology perspective, an approach to studying mental illness that emerged in the past 35 years. The developmental psychopathology framework is advantageous for studying the emergence of behavior disorders because it integrates strengths of numerous other disciplines, including psychiatric genetics, child clinical psychology, child psychiatry, developmental psychology, epidemiology, and clinical neuroscience, among others (see e.g., Beauchaine & McNulty, 2013). Developmental psychopathologists seek to characterize the course of mental illness as precisely as possible, across all relevant levels of analysis. Levels of analysis refer to different systems through which a psychopathological trait is expressed, spanning genes to behavior to broad cultural factors (see Beauchaine & Gatzke-Kopp, 2012; Cicchetti, 2008; Gottlieb, 2007; Hinshaw & Beauchaine, 2015). The advantage of a multiple-levels-of analysis approach to understanding psychopathology is exemplified in research on schizophrenia, an oftentimes progressively degenerative disorder in which afflicted individuals experience delusions, exhibit odd behaviors, and become isolated and avolitional (see Chapter 23 [Asarnow & Forsyth]). Although vulnerability to schizophrenia is highly heritable, most likely through combinations of both vulnerability genes (see Gottesman & Gould, 2003), and rare structural genetic variants (Costrain et al., 2015; Walsh et al., 2008), the exact genetic mechanisms have only begun to be identified. However, it is important to note that identifying all such genes will not result in a full understanding of the disorder, because genes do not affect behaviors—including those related to psychopathology—directly (see Rutter, Moffitt et al., 2006). Rather, they code for variations in protein expression that lead to structural and functional variations in the central nervous system and other organ systems. In isolation, these structural and functional variations are typically not necessary or sufficient to cause psychopathology. For example, traits associated with genetic vulnerability to schizophrenia, including neuromotor abnormalities, eye tracking dysfunction, and abnormal activity in the prefrontal cortex during working memory tasks, can be present in vulnerable individuals whether or not they manifest the disorder (Callicott et al., 2003; Erlenmeyer-Kimling, Golden, & Cornblatt, 1989; Glahn et al., 2003; Lenzenweger, McLachlan, & Rubin, 2007; Ross, 2003). As is the case with many psychiatric conditions, progression from genetic predisposition to manifestation of schizophrenia is affected profoundly by environmental influences (Cannon et al., 2002). Conversely, protective familial environments can both improve the course of the disorder, and in some cases prevent onset of illness (e.g., Cornblatt, 2001; see also Chapter 23 [Asarnow & Forsyth]). This example illustrates the importance of incorporating information from genetic, neurological, behavioral, and environmental levels of analysis toward understanding

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the complexity of debilitating conditions such as schizophrenia. Specifying determinants of psychopathology across all relevant levels of analysis and understanding interactions and longitudinal transactions across levels is therefore a primary objective of developmental psychopathology research (see Beauchaine & Cicchetti, 2016a; Beauchaine & Gatzke-Kopp, 2012; Beauchaine & McNulty, 2013; Cicchetti, 2008).

TERMINOLOGICAL AND CONCEPTUAL ISSUES Our main goals in writing this chapter are to (a) describe the interactive roles of heritability and environment in shaping behavior, particularly psychopathology, and (b) present important principles for interpreting more specific findings presented in later chapters and in the literature more broadly. Toward addressing these objectives, we first consider distinctions between genotypes, phenotypes, and endophenotypes, important constructs in behavioral and molecular genetics research. Although our descriptions are necessarily brief, they provide a foundation for understanding contents presented later in this volume.

Genotypes, Phenotypes, and Endophenotypes Genotype. The word genotype refers to structural composition of DNA as it exists within an individual. The human genome is largely fixed in the population, but approximately 0.2% of the genome varies across individuals. The term genotype is sometimes used to refer to an individual’s entire genetic sequence, and at other times in reference to a single gene, or more frequently, to describe an individual’s genetic sequence at a single point of variation. Of most interest to psychiatric geneticists is variation in DNA that influences functions or regulation of genes. Genes are composed of DNA, which guides synthesis of messenger RNA through a process called transcription. In turn, messenger RNA guides production of polypeptides through a process called translation. These polypeptides are the building blocks of proteins, or gene products. Differences in genetic sequence, referred to as allelic variants, give rise to individual differences in the volume or functionality of gene products. Some of these individual differences influence behavior. For example, some genetic variants give rise to individual differences in synthesis, reuptake, and catalysis of neurotransmitters that subserve mood, self-regulation, and motivation. When compromised, these neurotransmitter systems, including serotonin, dopamine, and norepinephrine, among others, may confer vulnerability to mood disorders, impulse control problems, and asociality (see Beauchaine, Neuhaus, Zalewski, Crowell, & Potapova, 2011). Traditionally, all genetic variation was assumed to be inherited fully and fixed across the lifespan. It was also believed that heritable genetic variation encoded

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psychiatric disorders directly, through either single or multiple loci—assumptions referred to as monogenic and polygenic determinism, respectively. These assumptions imply (at least for serious mental disorders) that particular genes or patterns of genes always result in psychopathology, regardless of environmental input (see Rutter, Moffitt et al., 2006). However, it is now recognized that a number of intervening influences—many of which fall under environmental control—affect gene transcription, translation, and promotion, thereby altering gene expression. Although we discuss some of these intervening influences in later sections, for now it is sufficient to state that (a) both genes and environments are implicated in the expression of almost all forms of psychopathology, (b) there are no genes “for” particular behaviors or disorders (although rare, single-gene neurological disorders do exist), (c) environments can alter gene expression, and (d) many people who are genetically vulnerable never develop mental illness (see Kendler, 2005; Plomin, 1989)—a phenomenon known as incomplete penetrance. Phenotype. The term phenotype refers to observable characteristics—both physical and behavioral—that result from the interplay between an organism’s genes and the environment. The phenotype concept stems from early work in Mendelian genetics, whereby physical characteristics of an organism are reliable, outwardly measurable indicators of underlying genotypes. In Mendel’s experiments on flower color and pea pod shape, phenotypes were dictated almost exclusively by inherited pairs of dominant and recessive genes, with very limited environmental influence except in cases of severe deprivation (Hartl & Jones, 2002). Such is the case when a phenotype is determined monogenically. In contrast, polygenic traits are influenced by many genes, so correspondences between genotypes and phenotypes are far from 1:1. Furthermore, with multiple genetic influences, there are many opportunities for both gene-gene interactions and environmental regulation of gene expression (see below). This far-from-complete correspondence between genotypes and behavioral phenotypes presents formidable obstacles for psychiatric genetics (see Gatzke-Kopp, 2011), another topic we return to below. Endophenotype. As defined by Gottesman and Gould (2003), endophenotypes are “measurable components unseen by the unaided eye along the pathway between disease and distal genotype” (Gottesman & Gould, 2003, p. 636). In this sense, endophenotypes are a special case of phenotypes, as they are also measurable physical, physiological, or behavioral traits. However, they are presumed to be closer to the functional output of gene(s) in question (see Beauchaine, 2009; Gould & Gottesman, 2006; Lenzenweger, 2014). This closer proximity to genes makes carefully chosen endophenotypes valuable to psychiatric geneticists in their attempts to identify (a) specific alleles associated with psychopathology and (b) genetically vulnerable individuals who have not yet developed psychopathology (see Castellanos & Tannock, 2002; Gizer et al., 2015; Skuse, 2001).

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In psychiatric genetics, it is important to distinguish between endophenotypes and other types of biomarkers (see Beauchaine, 2009; Lenzenweger, 2014). At the broadest level, biomarkers are measureable characteristics that indicate either vulnerability to, or direct manifestation of, mental illness. For example, preliminary evidence suggests that choline concentrations in the anterior cingulate cortex correlate with depression severity among patients with bipolar disorder, as indicated by positron emission tomography (Moore et al., 2000). Choline concentrations may therefore serve as an objective biomarker of both clinical state and treatment response. Although such information may be quite useful in understanding the neural bases of mood and mood state among affected individuals, to qualify as an endophenotype a biomarker must be state independent. In other words, an endophenotype must mark genetic vulnerability, whether or not an individual is currently symptomatic, in order to be maximally useful to geneticists in the search for genes that contribute vulnerability to mental disorders. To qualify as an endophenotype, a biomarker must (a) segregate with illness in the general population, (b) be heritable, (c) be state independent, (d) cosegregate with disorder within families, (e) be present at higher rates in affected families than in the general population, and (f) be measured reliably and specifically (Gould & Gottesman, 2006). Thus, although the terms biomarker and endophenotype are often used interchangeably, the latter are a subset of the former, with much greater specificity and utility in genetics research (Beauchaine, 2009). To date, a limited number of reliable endophenotypes have been identified in the psychopathology literature. A particularly good example comes from research on schizophrenia. As noted above, patients with schizophrenia experience irregularities in smooth-pursuit eye tracking of moving stimuli, as measured by sophisticated eye-tracking devices (see e.g., Gooding & Basso, 2008). Although the pathophysiology of such deficiencies is not fully understood, about 80% of patients with schizophrenia exhibit the trait, as do about 45% of their first-degree relatives, compared with only 10% of those in the general population (Gottesman & Gould, 2003; see also Kathmann, Hochrein, Uwer, & Bondy, 2003). Importantly, this 10% figure matches the population prevalence rate of schizophrenia liability.1 Thus, eye tracking dysfunction segregates with illness in the general population, is heritable, is state independent, cosegregates within families, is observed at higher rates in affected families than in the population, and is specific to schizophrenia liability. It is therefore quite useful in identifying those with a genetic predisposition to the disorder, even if they have not developed outwardly expressed symptoms. Detecting premorbid vulnerability among such individuals may have important implications for prevention, particularly when early identification improves long-term prognosis (see McGorry et al., 2002). 1. As most readers are likely aware, the prevalence of schizophrenia is about 1% in the population. However, about 10% carry genetic vulnerability. This is an example of incomplete penetrance, described above.

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PSYCHIATRIC GENETICS Broadly speaking, there are two overarching objectives of psychiatric genetics. The first is to parse variability in behavioral traits (e.g., impulsivity, aggression, anxiety) within populations into portions accounted for by (a) heritable influences, (b) environmental influences, and sometimes (c) Gene × Environment (G × E) interactions. This goal is accomplished through behavioral genetics research. The second is to identify specific alleles or other gene variants that confer vulnerability to psychopathology. This is accomplished though molecular genetics research. Thus, behavioral genetics and molecular genetics research provide information about psychopathology at different levels of analysis.

Behavioral Genetics Despite its name, behavioral genetics research does not involve direct measurement of genes, and in fact emerged as a discipline well before technological advances that allow for mapping of the human genome. Traditionally, behavioral genetics studies have applied statistical modeling techniques to parse sources of variance in observed behavior (phenotypes) into three broad classes, including additive genetic effects, shared environmental effects, and nonshared environmental effects. Additive genetic effects encompass all sources of variance in a behavioral trait that are accounted for by heritable mechanisms within a population. Although potentially confusing to explain, these “genetic effects” can arise from both genetic and nongenetic (although heritable) sources. For example, some genes are activated (“turned on”) among offspring only when their mothers are exposed to particular environments, oftentimes prenatally (see Rutter, Moffitt et al., 2006). Such maternal programming effects may increase vulnerability to, or protect against, the emergence of psychopathology through epigenetic mechanisms, described in more detail below. These effects are not purely genetic, yet they are often subsumed within the additive genetic component in behavioral genetics studies. Accordingly, to avoid confusion in this chapter we refer to heritable effects on behavior when the source of heritability cannot be attributed unambiguously to main effects of genes. In the shorthand of behavioral genetics, heritable effects are denoted A, shared environmental effects are denoted C, and nonshared environmental effects are denoted E (hence the term ACE model). When squared, each term signifies a proportion of variance in behavior accounted for. In theory, these sources sum to 1.0, accounting for all variance within a population for a behavioral (or other phenotypic) trait (a2 + c2 + e2 = 1.0). Parsing a behavioral trait into heritable, shared environmental, and nonshared environmental components is accomplished through twin, family, and adoption studies, by comparing correspondences between behavioral traits among

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individuals who are and are not related genetically. For example, in a basic twin design, the following assumptions are made in estimating A, C, and E: 1. Monozygotic (MZ) twins who are raised in the same family share 100% of their genes (A) and 100% of their common environment (C). Thus, the squared correlation (r2 ) between phenotypes of MZ twins provides an estimate of a2 + c2 (r2 MZ = a2 + c2 ). 2. Dizygotic (DZ) twins who are raised in the same family share 50% of their genes (A), and 100% common environment (C). Thus, the squared correlation between phenotypes of DZ twins provides an estimate of 1/2 a2 + c2 . Rearranging algebraically, a2 = 2(r2 MZ − r2 DZ ), and c2 = r2 MZ − a2 . 3. Residual error variance provides an estimate of e2 via the formula e2 = 1 − (a2 + c2 ). Note, however, that such nonshared environmental variance includes both environmental effects unique to siblings, and measurement error. Behavior genetics can also be conducted using nontwin designs, following the assumptions that (a) sibling-sibling pairs share 50% of their genes, but twin sibling pairs share more common environment than nontwin sibling pairs; (b) parents share 50% of their genes with each of their children; and (c) relatives such as aunts, uncles, and grandparents share 25% of their genes. It is important to note that these genetic relatedness percentages are true at the aggregate (population) level. Thus, any given individual may share slightly more or less than 50% of his or her genes with a sibling due to random allocation of each parent’s genes during embryogenesis. Accordingly, accuracy of ACE models depends, in part, on sample size. Accurate estimates of A, C, and E also rest on two additional assumptions. The first is that parents mate randomly. Assortive mating refers to situations in which reproduction does not occur randomly. Rather, heritable traits of individuals attract them to similar individuals, and these similar traits are passed on to offspring (e.g., shy individuals may be attracted one another). When this occurs, estimates of C are spuriously increased, and estimates of A are spuriously decreased (see Dhamija, Tuvblad, & Baker, 2015). Assortive mating has been demonstrated for several psychiatric disorders, including ADHD (e.g., Boomsma et al., 2010). The second assumption is that environmental similarity does not differ for MZ vs. DZ twin pairs—termed the equal-environments assumption. One method used to test this assumption is to compare two sets of MZ twin pairs: one set raised by parents who correctly believed they were MZ twins, and one set raised by parents who incorrectly believed they were DZ twins during childhood. If these sets of twins are equally similar behaviorally, parents are probably not engaging in behavior that makes MZ twins more similar than DZ twins, which supports the equal environments assumptions (e.g., Scarr & Carter-Saltzman, 1979). Alternative approaches used to test the equal environments assumption also support it. Even so, greater

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genetic differences between DZ twins can lead these twin pairs to experience more divergent environments relative to MZ twins, but since this results from genetic differences, it is not considered a violation of the equal environments assumption. This point is discussed in more detail in subsequent sections on gene-environment interplay. Although variations in behavioral genetics designs are sometimes used, most are built around these assumptions.2 Interested readers are referred to Plomin, DeFries, Knopik, and Neiderhiser (2013) for a more comprehensive account of behavioral genetics research. Behavioral genetics studies have evaluated heritabilities of a wide range of psychiatric disorders. For example, symptoms of hyperactivity/impulsivity among children with ADHD consistently yield heritability coefficients in the .70–.75 range (see Dhamija et al., 2015), and are therefore attributable largely to heritable effects (A). Most of the remaining variance is attributable to nonshared environmental effects (E), with negligible if any contribution from shared environments (C) (Burt, 2009). Heritability coefficients this large are rarely observed so early in life. By adulthood, however, many psychiatric disorders yield similarly high heritabilities, a point we turn to next. Complexities and Limitations of Behavioral Genetics. Several complexities and caveats should be considered in any discussion of the behavioral genetics of psychopathology. Perhaps most important, heritable vulnerabilities and environmental risk factors often interact to affect both age of onset and severity of psychopathology. For example, in many cases genetic liability is insufficient to result in schizophrenia (see above). Rather, vulnerability is translated into illness only when coupled with significant environmental risk (Gottesman & Gould, 2003). When heritable vulnerabilities (G) and environmental risk factors (E) mutually influence the course of psychopathology, a Heritability × Environment (G × E) interaction is observed (see below). Crucially, G × E interactions cannot be disentangled from pure heritability effects in behavioral genetics studies unless the specific environmental variable that interacts with genetic vulnerability is quantified precisely. In most behavioral genetics studies, effects of environment are inferred from residual variance, not measured variance (see above). Under such conditions, unmeasured G × E interactions are subsumed within the heritability coefficient (see Rutter, 2014). Thus, developmental increases in the heritability of almost all forms of psychopathology (Bergen, Gardner, & Kendler, 2007; see below) in part reflect accumulating effects of environmental risk exposure interacting with genetic vulnerability across the lifespan.

2. An alternative to the ACE model is the ADE model, in which D represents nonadditive, or dominant genetic effects. Dominance is indicated when MZ correlations are more than double those obtained for DZ/full sibling pairs. ACE and ADE models can be compared statistically to see which provides a better fit. In a recent meta-analysis, Nikolas and Burt (2010) found that the ADE model provides a better fit for symptoms of inattention, whereas the ACE model provides a better fit for symptoms of hyperactivity.

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As a result, behavioral genetics studies in which specific environmental influences are not measured overestimate main effects of heritability on emerging mental illness. The likely end result may be a literature-wide overestimation of main effects of heritability in the pathogenesis of psychopathology. This is by no means a trivial point because the uniformly high heritability coefficients of adult psychiatric disorders (e.g., Shih, Belmonte, & Zandi, 2004) are sometimes interpreted as evidence that environment contributes little to the expression of psychopathology. In recognition of this limitation, increasingly sophisticated efforts to quantify G × E interactions have appeared in recent years. These studies, some of which are described below, suggest that G × E interactions may be more common than thought previously (e.g., Caspi et al., 2002; Caspi et al., 2003; Caspi et al., 2010; Dodge & Rutter, 2011; Moffitt, 2005). However, most G × E interactions have been tested in molecular genetics research (see below), not behavioral genetics research. Moreover, many such findings need to be replicated to confirm their validity (see Duncan & Keller, 2011). As just noted, it has become apparent in recent years that heritability coefficients of almost all behavioral traits—including those associated with psychopathology— increase substantially from childhood to adulthood (see Beauchaine, Neuhaus et al., 2008; Bergen et al., 2007). This general pattern applies to almost all forms of psychopathology that have been assessed at different points in development, including antisocial behavior, anxiety, depression, eating disorders, and substance dependences (Bergen et al., 2007; Hicks et al., 2007; Klump, McGue, & Iacono, 2000; Lyons et al., 1995). Moreover, although environmental effects such as peer influences affect age of onset of smoking and drinking behaviors, both smoking maintenance and heavy drinking are accounted for almost exclusively by heritable effects (e.g., Boomsma, Koopsman, Van Doormen, & Orlebeke, 1994; Koopsman, Slutske, Heath, Neale, & Boomsma, 1999; Koopsman, van Doornen, & Boomsma, 1997; McGue, Iacono, Legrand, & Elkins, 2001; Viken, Kaprio, Koskenvuo, & Rose, 1999). Psychopathology researchers have offered a number of potential explanations for increasing heritability coefficients. These include suggestions that the nature of psychopathology may be different among children than among adults (e.g., Klein, Torpey, Bufferd, & Dyson, 2008), that different genetic factors operate in childhood versus adolescence (e.g., Kendler, Gardner, & Lichtenstein, 2008), and that differences in heritability may indicate diverse equifinal pathways to psychopathology (e.g., Silberg, Rutter, & Eaves, 2001). Notably, evocative and active gene-environment correlations (rGE), discussed below, also contribute to increases in heritabilities of behavioral traits across the lifespan. This occurs because small initial behavioral differences between DZ twins become magnified over time as genetic differences cause twin pairs to provoke and seek out different environments, which then amplify phenotypes, increasing behavioral differences. In contrast, MZ twin pairs remain relatively similar over time, and, when compared to the declining similarity of DZ twin pairs, cause heritability estimates to increase (Beam & Turkheimer, 2013).

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Although some or all of these mechanisms are likely to be operative, important artifactual influences should also be considered. For example, developmental increases in heritability are a mathematical necessity in twin and adoption studies whenever there are individual differences in age of onset, even when underlying causal processes of psychiatric disturbance are similar (see Beauchaine, Neuhaus et al., 2008). Heritability is estimated from concordance of psychopathology among twin pairs. Differences in age of onset—which could be caused by environmental insults or stochastic (chance, random) effects—necessarily produce increasing concordance over time, thereby increasing heritability. Importantly, even when they are reared in very similar environments, phenotypic variation among MZ twins is observed, highlighting the importance of nonshared environment (Wong, Gottesman, & Petronis, 2005). Regardless of the causes, moderate to high heritabilities are observed for almost all adult psychiatric disorders, with smaller but significant nonshared environmental effects and negligible if any shared environmental effects. This fact led Turkheimer (2000) to coin the three laws of the behavior genetics: (1) all human behavioral traits are heritable, (2) effects of being raised in the same family are smaller than effects of genes, and (3) a substantial portion of variation in complex human behavioral traits is not accounted by effects of genes or families. It is also important to note that behavioral genetics studies are usually conducted with large samples recruited through twin registries. Ideally, these samples are representative of the population from which they are drawn. As a result, behavioral genetics analyses parse mostly normal variation in individual differences. This variation is analyzed by constructing structural models to evaluate linear associations between heritable influences and behavior and between environmental influences and behavior. However, linear associations do not always represent processes that operate at the extremes of a distribution—the very region where psychopathology is represented (see e.g., Beauchaine, 2003). According to most definitions, psychopathology is limited to the upper (or lower) extremes of a normal distribution, usually defined as the 95th or 98th percentile (or the 2nd or 5th percentile). Mechanisms of behavior can be quite different at the extremes of a distribution than near the mean of a distribution (see Beauchaine, Lenzenweger, & Waller, 2008; Plichta & Scheres, 2014). Thus, gene-behavior and environment-behavior relations among individuals with psychopathology can be swamped in behavioral genetics analyses by mostly normative variation in individual differences, thereby going undetected. Finally, behavioral genetics studies are nonspecific, providing broad information about heritable versus environmental risk but yielding no information about particular genes that contribute to phenotypes. As a result, these studies cannot be used to identify disease processes or mechanisms of psychiatric disturbance. Behavioral genetics models contribute most effectively to informing theoretical frameworks from which hypotheses can be derived for specific genetics testing, a topic discussed more thoroughly below.

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Molecular Genetics Linkage Studies. In contrast to behavioral genetics, molecular genetics studies identify specific genetic polymorphisms (i.e., allelic variants) that confer vulnerability to psychopathology. There are two broad types of molecular genetics approaches: linkage and association studies. Linkage studies scan broad sections of the genome, and require large samples of families with two or more children affected by psychopathology. Genetic data are collected from family members, and searches are conducted for genetic markers with known chromosomal locations. Notably, linkage studies are ideally suited for identifying rare genetic variants (described below) of moderate to large effect sizes. They are therefore quite effective at identifying risk loci for monogenic or oligogenic traits (i.e., traits determined by one gene or a small number of genes). For example, the gene responsible for cystic fibrosis was found by “linking” the disease to a genetic variant on the long arm of Chromosome 7 within affected families. This discovery was followed by several subsequent linkage analyses that identified the specific chromosomal location (see Bolsover, Hyams, Jones, Shepard, & White, 1997). In contrast, successful application of linkage analysis to complex and highly polygenic traits has proved to be far more difficult. In child psychopathology research, linkage analyses have been applied to families of sibling pairs with autism to identify susceptibility loci for the disorder (see Chapter 22 [Faja & Dawson]). These studies specify Chromosomes 7, 8, and 9 as likely locations of autism susceptibility genes, with additional markers on Chromosomes 4 and 11 for females and males, respectively (see Lowe, Werling, Constantino, Cantor, & Geschwind, 2015; Schellenberg et al., 2006). Specification of multiple susceptibility loci indicates that autism is a multifactorial disorder. Although these investigations provide insights into the pathogenesis of autism, specific genes or combinations of genes necessary for developing the disorder have yet to be identified conclusively. Nevertheless, information obtained from linkage studies can narrow the list of candidate genes considerably. Linkage studies have also been used to identify susceptibility loci for externalizing behavior disorders (see e.g., Gizer et al., 2016; Jain et al., 2007). To date, linkage studies of psychiatric disorders have produced more failures to replicate than replications, with surprisingly few exceptions (see Craddock & Forty, 2006; Duncan & Keller, 2011; Stein & Gelernter, 2010; Zhou et al., 2008). A likely explanation is that most psychiatric traits are polygenic and multifactorial. Effect sizes attributable to identified variants are therefore small. For example, early linkage studies of autism spectrum disorder (ASD) were conducted under the assumption that 10–20 genes might contribute to vulnerability. However, current studies suggest that as many as 1,000 different genes may be involved (Sanders et al., 2012). If true, this highly polygenic architecture may explain why linkage studies fail to replicate. If rare variants in each of these genes contribute to ASD vulnerability, many will apply to just a handful of families, making it difficult to replicate linkage to a given locus. Thus, linkage studies of complex traits require large collections of families in order for signals to be detected. Importantly,

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advances in genetic sequencing make it more feasible to measure rare genetic variation, which has led to renewed interest in linkage analysis. Studies of ASD provide one example of how aggregating samples can increase statistical power and lead to identification of vulnerability loci. As noted above, early linkage studies of ASD identified a susceptibility locus on the long arm of Chromosome 7 (e.g., Ashley-Koch et al., 1999). Subsequent meta-analyses confirmed this result (Badner & Gershon, 2002; Trikalinos et al., 2006), and fine mapping studies implicate variation in the contacting-associated protein-like 2 (CNTNAP2) gene as one source of this linkage signal (Alarcón et al., 2008; Arking et al., 2008). Notably, this conclusion is supported by a recent sequencing study that identified a rare, functional variant in CNTNAP2 as a susceptibility locus for ASD (O’Roak et al., 2011). It is important to note, however, that this is one of only a few early success stories. Much linkage work remains toward identifying genes that confer susceptibility to psychopathology. Association Studies. In contrast to linkage studies, which attempt to identify allelic variants that cosegregate with the trait of interest within families, genetic association studies attempt to identify allelic variants that segregate with the trait of interest in the general population. Early association studies took the form of candidate gene studies in which specific genes that were hypothesized to be involved in neurobiological vulnerability to psychiatric disorders were examined for evidence of relations with those disorders. In such studies, allelic frequencies of one or more variants of the candidate gene are compared among individuals with and without the disorder, using classic case-control designs. Genetic associations for dichotomous traits (disordered vs. not disordered) are expressed as odds ratios, which compare the likelihood that a person with a candidate polymorphism has a target disorder with the likelihood that a person without a candidate polymorphism has a target disorder. Odds ratios > 1 indicate higher likelihood of illness among those with versus without the candidate allele. Results for continuous traits can be expressed using effect size statistics that indicate the proportion of variance explained, such as R2 . As genotyping technologies evolved, it became feasible to cost-effectively genotype hundreds of thousands of genetic variants. This was a necessary development for genome-wide association studies (GWAS), in which genetic markers that are spread across the entire genome are tested individually for association with the trait of interest, with no assumptions about which biological systems or genes might contribute to susceptibility (see Pearson & Manolio, 2008). Notably, very large samples (beginning at >30,000 cases and controls) are required to achieve adequate power given the severe correction required for multiple testing. When these sample sizes are achieved, GWAS can lead to significant advances in our understanding of genetic influences on psychopathology. Such is the case for schizophrenia, for which more than 100 susceptibility loci have been identified (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014).

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Although there are multiple methods for conducting either type of association study (see Cordell & Clayton, 2005), two are most common. In case-control designs, allelic frequencies of candidate genes are compared among those with and without psychopathology in a population. Although case-control studies can provide large numbers of participants and are therefore powerful statistically, they are vulnerable to population stratification, which refers to differences in allelic frequencies across ethnicities and geographical locals. These can introduce confounds into case-control designs, producing false positive results. Current case-control association studies, and GWAS in particular, rely on large sets of randomly selected genetic variants that are used to determine an individual’s ancestry. Population stratification can also be avoided with family-based designs in which parents serve as controls. The most commonly used of these designs is the transmission disequilibrium test (TDT; Spielman, McGinnis, & Ewens, 1993), which quantifies transmission of genetic alleles from parents to offspring. Affected offspring, along with both biological parents, are genotyped. If a parent is heterozygous for the variant of interest (i.e., “Aa” rather than “AA” or “aa” genotype, to use a simple example), offspring will have a 50–50 chance of inheriting either allele. If a candidate polymorphism confers risk for psychopathology, however, the risk allele should be transmitted from parent to offspring at a rate that exceeds 50%. An important drawback of this approach is that only heterozygous parents are informative for the analysis, and thus, the final sample size is substantially reduced because only a fraction of parents possess this genotype. As noted above, association studies, particularly case-control designs, can detect genetic effects that account for far less variance in behavior than linkage studies. However, well-articulated theories are required to identify candidate genes for analysis, and large samples are required to detect variants given the small effect sizes typically associated with them (odd ratios < 1.1 or R2 < 0.01). As described in Chapter 6 (Neuhaus & Beauchaine), for example, contemporary neural theories of impulsivity implicate the mesolimbic and mesocortical dopamine (DA) systems (see Beauchaine & Gatzke-Kopp, 2012; Gatzke-Kopp, 2011; Gatzke-Kopp et al., 2009). Given that impulsivity is a highly heritable trait that confers vulnerability to almost all externalizing disorders (Beauchaine & McNulty, 2013; Beauchaine et al., 2010, 2016), genes involved in synthesis, reuptake, and metabolism of DA should be associated with at least some of these conditions. Consistent with this supposition, association studies have identified several candidate alleles involved in DA neurotransmission, including variations in the DRD4 gene (Chromosome 11p15.5) and the DAT1 gene (Chromosome 5p15.3), among others (see Castellanos & Tannock, 2002; Gizer, Ficks, & Waldman, 2009; Gizer et al., 2016). Rare Structural Variants. A somewhat recent development in psychiatric genetics is the use of genome-wide scans to identify rare structure variants, or copy-number variants (CNVs), including both microduplications and microdeletions. As these terms imply, such variants result from either more than or fewer

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than the normal number of genes being inserted on certain chromosomes. In addition, CNVs can be caused by inversion and translocation of genes. Rare structural variants can be either inherited or arise de novo via mutation, and are implicated in the pathogenesis of autism (Sebat et al., 2007; Chapter 22 [Faja & Dawson]), schizophrenia (e.g., Rees et al., 2014; Walsh et al., 2008; Chapter 23 [Asarnow & Forsyth]), and ADHD (Lesch et al., 2011). In fact, Walsh et al. (2008) demonstrated duplications and deletions of genes among 20% of individuals with early-onset schizophrenia versus 5% of controls. Moreover, for both autism and schizophrenia, implicated genes disproportionately affect neurodevelopment (see Grayton, Fernandesa, Rujescub, & Collier, 2012). In addition to their direct effects, structural variants may interact with other susceptibility genes to “push” certain individuals over the threshold for developing psychopathology. Complexities and Limitations of Molecular Genetics. Even though molecular genetics studies are far more specific than behavioral genetics studies, they are not without limitations. Perhaps the biggest is the small amount of variance in behavior for which most identified variants account. For example, although behavioral genetics studies routinely yield heritability coefficients that explain close to 80% of the variance in impulsivity (see e.g., Dhamija et al., 2015; Nikolas & Burt, 2010), specific variants identified in molecular genetics studies account for a very small fraction of this effect, a situation that applies to all psychiatric disorders. This is often referred to as the missing heritability problem (see Slatkin, 2009). Furthermore, nonreplications across studies are common (Gizer et al., 2009, 2016). A key reason is assumed to be the multifactorial nature of most psychiatric disorders, including ADHD (see e.g., Swanson & Castellanos, 2002). Nevertheless, considerable work remains toward mapping genetic substrates of almost all behavioral traits that confer vulnerability to psychopathology—and how they interact with both one another and the environment.

Heterogeneity of Phenotypes The search for candidate genotypes through selection of homogenous phenotypes presents significant challenges to psychiatric genetics research. Success of this approach is maximized when the association between genotype and phenotype is 1:1, which is almost never the case for psychopathology or any complex trait (see above). Indeed, most disorders are multifactorially determined, and most diagnostic criteria are specified solely at the behavioral level of analysis, and are therefore affected by nongenetic influences. Thus, in addition to the small effect sizes described above, phenotypic heterogeneity presents a second obstacle to identifying genetic substrates of psychopathology (see Rende & Waldman, 2006; Skuse, 2001). Such heterogeneity can arise from three sources. First, criteria used for symptom assessment and participant selection often differ across studies. Fore example, some labs prefer broader

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definitions that include both aggressive and nonaggressive antisocial activities, whereas others confine their definitions to overtly aggressive and violent offenses. In general, narrower definitions yield higher heritability coefficients in behavioral genetics studies and more replicable evidence for linkage and/or association in molecular genetics studies (e.g., Eley, Lichtenstein, & Moffitt, 2003; Waldman et al., 1998)—presumably because narrow phenotypes identify individuals with similar genetic vulnerabilities. Second, the same or similar symptoms can develop through different etiological pathways, a phenomenon known as equifinality (Cicchetti & Rogosch, 1996; see also Chapter 1 [Hinshaw]). For example, some cases of depression are influenced more by biological vulnerability and less by environmental risk, whereas others are influenced less by biological vulnerability and more by environmental risk (see e.g., Beauchaine, Crowell, & Hsiao, 2015; Cicchetti & Rogosch, 2002; Harrington, Rutter, & Fombonne, 1996). Thus, different combinations of liability and risk can give rise to very similar behavioral syndromes. Third, diagnostic syndromes are highly complex and are often defined by constellations of symptoms. Most diagnostic criteria require only a subset of these symptoms to meet threshold, allowing for a single diagnostic label to apply to a multitude of symptom profiles. Within a given syndrome, a certain set of symptoms may derive from greater genetic influence than another set. For example, evidence suggests that melancholia—a more severe form of depression with a particularly insidious course—is more heritable and results from different genetic vulnerabilities than other forms of mood disorder (Eaves et al., 2005; Willeit et al., 2003). Despite such indications that melancholia is distinct from other forms of depression, until quite recently most genetic studies of depression—both behavioral and molecular—lumped all participants who met DSM criteria into a single group for analysis, with no effort to stratify by subtype. One consequence is to water down and obscure genetic effects on specific depression subtypes, resulting in small effect sizes and failures to replicate (see Castellanos & Tannock, 2002; Skuse, 2001). This pattern has led to numerous calls for the use of carefully chosen endophenotypes to differentiate between subgroups with distinct heritable vulnerabilities (e.g., Gottesman & Gould, 2003; Hasler, Drevets, Manji, & Charney, 2004). In the case of melancholia, abnormal hypothalamic-pituitary-adrenal axis reactivity, which is associated with a polymorphism in the promoter of the serotonin transporter gene, has emerged as a potential endophenotype (see e.g., Coryell, & Schlesser, 2001), although additional research is needed. This example illustrates why tightened definitions of psychopathology are required to specify genetic vulnerabilities more precisely.

GENE-ENVIRONMENT INTERDEPENDENCE Gene-environment interdependence occurs when heritable and environmental influences either correlate or interact with one another to explain more variance in behavior than their combined main effects (Rutter, 2014). There are several forms of

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gene-environment interdependence, each of which is outlined briefly below. More comprehensive accounts can be found in Duncan and Keller (2011), Moffitt et al. (2006), Rutter (2006, 2010), and Rutter, Moffitt et al. (2006).

Gene-Environment Interaction As mentioned above, gene-environment interaction (G × E) refers to situations in which environments moderate effects of genes on behavior or (equivalently) genes moderate effects of environments on behavior.3 Among the most renowned examples of a G × E interaction, demonstrated by Caspi et al. (2003), is the finding that polymorphisms in the promoter region of the serotonin transporter gene (5-HTTLPR) moderate effects of stressful life events—including maltreatment between ages 3 and 11—on adult depression. Individuals with two copies of the short allele (s/s homozygous) are more likely to experience adult depression following child adversity than individuals with two copies of the long allele (l/l homozygous). Those who are heterozygous (s/l) are intermediately vulnerable. Similar findings for the 5-HTTLPR gene have since been reported by others (Eley et al., 2004; Kaufman et al., 2004; see also Chapter 18 [Klein, Goldstein, & Finsaas]). Polymorphisms in the 5-HTTLPR gene (s/s) also moderate effects of stressful life events on development of drinking and drug use (Covault et al., 2007). Although findings of 5-HTTLPR × Stress interactions have been disputed by some (e.g., Risch et al., 2009), this moderating effect remains the most studied example of a G × E interaction in the psychiatric genetics literature, with many well controlled studies continuing to suggest that the s allele indeed confers susceptibility to depression following adversity, particularly when environmental influences are measured with precision (Caspi et al., 2010; Starr, Hammen, Conway, Raposa, & Brennan, 2014). Importantly, although the main effect of maltreatment in predicting depression in the Caspi et al. (2003) study was significant, the main effect of 5-HTTLPR variation was not. Thus, had the G × E interaction not been assessed, variation in the 5-HTTLPR allele would have appeared to be unrelated to adult depression. This example argues strongly for careful consideration of environment in psychiatric genetics research, and illustrates how failure to assess interaction effects can lead to incorrect inferences about the importance of heritability in the expression of psychopathology (see Beauchaine, Neuhaus, et al., 2008; Crowell et al., 2008). 3. Deciding whether genes moderate effects of environment on behavior or whether environments moderate effects of genes on behavior is dictated by theoretical considerations. For example, Caspi et al. (2002) demonstrated that maltreated children become violent later in life only if they carry a specific variable number tandem repeat in the promoter region of the monoamine oxidase A gene. This could be viewed as a case of genetic variation moderating effects of maltreatment or as a case of maltreatment moderating effects of genetic variation. Analytically, the decision is arbitrary, as the mathematics are identical. In both cases, the effect of one variable differs as a function of the other—the statistical definition of interaction. Our preference is to consider genetic variation the predictor and environment the moderator because genetic variation precedes maltreatment.

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Gene-Environment Correlation Gene-environment correlation (rGE) refers to situations in which (a) heritable traits of parents affect their child’s exposure to adverse environments (also known as an indirect genetic effect), or (b) heritable traits of children affect their own exposure to adverse environments. Such correlations come in three forms, including active, evocative, and passive (see Plomin, DeFries, & Loehlin, 1977). Active rGE. Active rGE occurs when a child’s heritable vulnerabilities influence his or her selection of environments. For example, a primary neural substrate of impulsivity is deficient mesolimbic DA activity (see Beauchaine & McNulty, 2013; Beauchaine et al., 2016; Gatzke-Kopp, 2011; Gatzke-Kopp et al., 2009). This DA dysregulation predisposes to sensation-seeking behaviors, including early initiation and sustained use of substances, association with delinquent peers, and other high-risk activities (see Chapter 6 [Neuhaus & Beauchaine]). Thus, genetically vulnerable children and adolescents are predisposed to seek risky environments and experiences, some of which may compound vulnerability. For instance, vulnerable individuals are more likely to engage in high-risk behaviors such as substance use. Such experiences can canalize trajectories toward psychopathology directly through pharmacological effects of drugs on developing mesocortical and mesolimbic brain systems (e.g., Catlow & Kirstein, 2007; see Chapter 15 [Brown, Tomlinson, & Winward]), and/or indirectly through exposure to antisocial peer influences and subsequent restriction of access to prosocial peer groups (e.g., Dishion, Kim, & Tein, 2015). In this manner, active rGE associated with externalizing behavior can feed back to exacerbate preexisting heritable compromises in avolition and self-control (Beauchaine & McNulty, 2013; Beauchaine et al., 2017). Similar active rGE has been described for other traits including anxiety (Fox, Hane, & Pine, 2007). Evocative rGE. Evocative rGE occurs when genetically influenced behaviors elicit reactions from others that interact with and exacerbate existing vulnerabilities. As outlined immediately above, one behavioral trait that can evoke environmental risk is impulsivity. Impulsive children present with challenging behaviors that elicit and reinforce ineffective parenting, which in turn amplifies risk for progression of ADHD to more serious externalizing behaviors (e.g., Patterson, DeGarmo, & Knutson, 2000). O’Connor, Deater-Deckard et al. (1998) reported an evocative rGE in a sample of children at high genetic vulnerability for externalizing behaviors who were adopted at birth. Despite being raised by adoptive parents, these children received more negative parenting than those in a matched control group. Because the adoptive parents’ behaviors could not be explained by shared genetic risk with the child, these data provide strong evidence for evocative rGE. Similar findings have since been reported by Neiderhiser et al. (2004) and Harold et al. (2013). Evoked negative responses from others can then amplify a child’s ineffective self-control, thereby increasing his or her externalizing behaviors and eliciting

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further negative parental responses. Over time, evoked cycles of negativity may affect developing neural systems through mechanisms of neural plasticity, with potential long-term consequences for adjustment (see Beauchaine, Neuhaus et al., 2008; Beauchaine et al., 2011; Pollak, 2005). In this manner, evocative rGE may amplify and solidify behavior patterns that were once malleable (see Fishbein, 2000). As noted previously, this type of reciprocal feedback, as well as that described for active rGE, provides a potential explanation for the increasing heritability of behavioral traits typically observed across the lifespan (Beam & Turkheimer, 2013). Passive rGE. Passive rGE occurs when genetic factors that are common to both a parent and child influence parenting behaviors or home environments more generally. This process can be associated with either positive or negative outcomes. For example, an intelligent parent may purchase more books for her child and read to her more often than most mothers read to their children. In this case, a genetic advantage is correlated with environmental opportunity. Parents can also confer both genetic vulnerability to their offspring and provide risky rearing environments. For instance, twin studies indicate that genes play a significant role in the intergenerational transmission of depression (e.g., Rice, Harold, & Thapar, 2005; Rice, Lewis, Harold, & Thapar, 2013), yet overwhelming evidence also demonstrates that maternal depression adversely affects parenting (Lovejoy, Graczyk, O’Hare, & Neuman, 2000; Rice et al., 2013). Given such findings, it may be tempting to infer passive rGE as a mechanism of intergenerational transmission of depression. However, passive rGE cannot be disentangled from shared environmental effects in ordinary behavioral genetics designs (for a discussion of the difference between rGE and shared environmental effects, see Rutter, Moffitt et al., 2006). Rather, sophisticated analyses of data collected from pairs of twin parents are required. No such studies have been conducted to demonstrate passive rGE for maternal depression. However, Neiderhiser et al. (2004) used a twin parent design to identify passive rGE for positive but not negative aspects of maternal parenting behavior in a normative sample. Because these are the only conclusive data demonstrating passive rGE for parenting behavior, further research is needed. Notably however, recently developed statistical models may provide for parsing passive rGE and G × E without twin parent designs (Price & Jaffee, 2008).

EPIGENESIS As alluded to above, a range of exogenous influences—including trauma, adverse rearing conditions, prenatal exposure to stress hormones, diet, and even cultural factors experienced early in life—can alter gene expression, with effects on neural development, neurotransmitter function, and behavior (see, e.g., Masterpasqua,

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2009; Roth, 2013; Tremblay & Côté, 2009). The term epigenesis refers to changes in gene expression that are environmentally mediated (i.e., “regulated,” “activated,” “turned on,” “silenced,” etc.). These occur through structural changes to DNA molecules that do not affect DNA sequence (Hartl & Jones, 2002). Notably, our understanding of the many epigenetic mechanisms that underlie this process is limited. Methylation processes (conversion of cytosine to 5-methylcytosine), which alter accessibility of DNA to mRNA in modulating gene expression, represent a well-studied mechanism, although our understanding of this phenomenon is rapidly evolving. More advanced knowledge is critically important as recent studies demonstrate that epigenetically induced changes to DNA structure are far more dynamic than imagined even a decade ago. In a now famous paper, Fraga et al. (2005) reported increasingly divergent patterns of DNA methylation over the lifespans of monozygotic twins, which indicates that epigenetic marks derived from nonshared environmental exposures accumulate over our lifetimes. Epigenetic effects on behavior were first reported in the animal literature. For example, Weaver et al. (2004) discovered epigenetically induced genetic variation in hippocampal glucocorticoid receptors among rat pups that experienced high levels of maternal caretaking, including licking, grooming, and arched-back nursing compared with pups that experienced low levels of such behaviors. This epigenetic effect transmits adaptive variations in stress responding to offspring (see Meany, 2007). Rat pups reared in high-risk environments, where such maternal caretaking behaviors are altered, have more reactive hypothalamic-pituitaryadrenocortical responses and are consequently more fearful, leaving them better prepared for the high-risk environment they are likely to face as they mature. Although epigenetic changes in gene expression clearly occur in humans, demonstrating their effects on behavior is more difficult than among animals because it requires random assignment of groups to different rearing environments (e.g., impoverished vs. enriched; see Rutter, 2014), an ethically indefensible practice. However, indirect evidence of epigenesis can be gleaned by (a) measuring methylation of genes within target tissues and (b) correlating methylation with adversity. Such studies have become common in recent years following articulation of rich theoretical models invoking epigenetic processes in the emergence of several forms of psychopathology. In fact, epigenetic mechanisms are implicated in an ever-broadening list of psychiatric syndromes, including antisocial behavior (e.g., Tremblay, 2005), schizophrenia (e.g., Roth, Lubin, Sodhi, & Kleinman, 2009), bipolar disorder (e.g., Petronis, 2003), autism (e.g., Shulha et al., 2011), addiction (e.g., Renthal & Nestler, 2008), ADHD (e.g., Mill & Petronis, 2008), PTSD (Smith et al., 2011), suicide (Poulter et al., 2008), and depression (e.g., Schroeder, Krebs, Bleich, & Frieling, 2010). Interestingly, administration of antidepressants to rodents induces epigenetic changes in the P11 promoter, which modulates serotonin receptor (5-HT1B ) function (Svenningsson et al., 2006) and is implicated in the pathophysiology of depression

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in humans (Melas et al., 2011). Other studies link childhood adversity to epigenetically induced changes in glucocorticoid receptor genes (e.g., Tyrka, Price, Marsit, Walters, & Carpenter, 2012), which modulate stress responding. The epigenome appears to be especially vulnerable to environmental insults that occur prenatally or very early in postnatal life (Roth, 2013). Diet, teratogen exposure, and in utero stress exposure are among the most common triggers of epigenesis during these developmental periods. From an evolutionary perspective, some degree of flexibility in responding to a range of environments has clear survival advantages. However, behaviors that are advantageous in some contexts may be disadvantageous in others, conferring vulnerability to psychopathology (e.g., Mead, Beauchaine, & Shannon, 2010). Thus, activation and deactivation of genes via epigenetic processes may play important roles in both vulnerability and resilience to psychopathology (see Kramer, 2005; Rutter, 2005; Rutter, Moffitt et al., 2006). Our ability to evaluate epigenetic changes in brain tissue among live humans is quite limited. For example, although animal models suggest that epigenetic alterations in hippocampal glucocorticoid receptors should be found among humans who incur adversity early in life, measuring methylation in such specific brain tissues is not possible (Davies et al., 2012). Nevertheless, postmortem studies indicate increased cytosine methylation of the glucocorticoid receptor (NR3C1) promoter in the hippocampi of those who were exposed to child abuse (McGowan et al., 2009). Furthermore, some theorize that for certain disorders, the most relevant epigenetic changes may be systemic in nature and might therefor be observed across tissue types. As evidence, some recent studies indicate substantial correlations between epigenetic marks in multiple tissues (Davies et al., 2012; Tylee, Kawaguchi, & Glatt, 2013). Thus, use of peripheral tissues such as blood as proxies for brain tissue does have some support.

GENETICS OF COMORBIDITY The term comorbidity refers to the co-occurrence of more than one psychiatric disorder within an individual. Although many subtypes and causes of comorbidity have been described (see Beauchaine & Cicchetti, 2016a, b; Caron & Rutter, 1991; Klein & Riso, 1993), two broad forms are important for this discussion. Homotypic comorbidity refers to co-occurrence of multiple externalizing disorders or internalizing disorders within an individual. For example, externalizing disorders including ADHD, oppositional defiant disorder (ODD), conduct disorder (CD), antisocial personality disorder (ASPD), and substance use disorders (SUDs) often co-occur, particularly as development proceeds from childhood through adulthood (see Beauchaine & McNulty, 2013; Beauchaine et al., 2010, 2016; Lewinsohn, Shankman, Gau, & Klein, 2004). Comorbidity of internalizing disorders, including depression, dysthymia, and anxiety disorders is also high (Angold & Costello, 1993; Brady & Kendall, 1992; Ferdinand, Dieleman, Ormel, & Verhulst, 2007).

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In contrast to homotypic comorbidity, heterotypic comorbidity refers to the co-occurrence of at least one externalizing disorder and at least one internalizing disorder within an individual (e.g., CD and depression). This form of comorbidity is more perplexing because many (though not all) symptoms appear to overlap minimally (see Sauder, Beauchaine, Gatzke-Kopp, Shannon, & Aylward, 2012; Kopp & Beauchaine, 2007; Zisner & Beauchaine, 2016). For example, depression includes symptoms of sadness, anhedonia, and feelings of guilt and/or worthlessness, whereas CD is characterized by sensation seeking, lying, property destruction, and aggression. Despite these apparently distinct presentations, rates of comorbidity of CD and depression are much higher than expected by chance (Angold & Costello, 1993; Essau, 2003; Zisner & Beauchaine, 2016).

Behavioral Genetics of Comorbidity Comorbid disorders have often been treated as distinct yet co-occurring conditions with different etiologies (see Beauchaine, 2003; Kopp & Beauchaine, 2007), yet behavioral genetics studies suggest common heritable substrates for both homotypic and heterotypic comorbidity. Biometric modeling of latent associations between supposedly distinct syndromes has advanced our understanding of comorbidity, as described next. Homotypic Comorbidity. Behavioral genetics analyses indicated that most disorders within the externalizing spectrum share a common heritable vulnerability, with similar findings reported for disorders within the internalizing spectrum (Baker, Jacobson, Raine, Lozano, & Bezdjian, 2007; Kendler, Prescott, Myers, & Neale, 2003; Krueger et al., 2002; Lahey, Van Hulle, Singh, Waldman, & Rathouz, 2011; Tambs et al., 2009). For example, about 80% of shared variance in disinhibition, conduct problems, antisocial personality, alcohol dependence, and drug dependence is accounted for by a single latent impulsivity trait (Krueger et al., 2002). Yet each specific category of externalizing conduct is influenced strongly by environment. Thus, trait impulsivity arising primarily from heritable predispositions manifests differently depending on environmental opportunities (see Beauchaine & Cicchetti, 2016a; Beauchaine & McNulty, 2013; Beauchaine et al., 2017; Lynam et al., 2000, Chapter 6 [Neuhaus & Beauchaine]). Following from these models, molecular genetic and neurobiological research targeting the common heritable vulnerability of trait impulsivity—as opposed to specific psychiatric syndromes—may provide advances in our understanding of etiology (see, e.g., Forbes, Tackett, Markon, & Krueger, in press), whereas research on environmental risk mechanisms may be more beneficial if focused on factors that differentially contribute to specific syndromes. Heterotypic Comorbidity. Behavioral genetics studies also suggest common heritability across the internalizing and externalizing spectra (see e.g., Lahey

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et al., 2011). For example, O’Connor, McGuire, Reiss, Hetherington, and Plomin (1998) reported that 45% of the covariation between depressive and antisocial symptoms was accounted for by common genetic liability among 10- to 18-year-old twins. Similar findings have since been reported by others in both adolescent and adult samples (e.g., Burcusa, Iacono, & McGue, 2003; Caspi et al., 2014; Kendler et al., 2003). Such findings offer an explanation of comorbidity not as diagnostic co-occurrence of supposedly independent conditions, but rather as covariation of related syndromes stemming from common heritable vulnerabilities. The general latent structure of psychopathology, as determined from twin and family studies, is depicted in Figure 3.1. Recently, Caspi et al. (2014) reported that a general, higher-order psychopathology factor, which they labelled p, accounted in part for observed comorbidity among internalizing and externalizing disorders, both concurrently and across 20 years spanning adolescence to midlife, in the Dunedin Multidisciplinary Health and Development Study. High p scores were heritable, and associated with greater life impairment and poor executive function. Thus, p appears to confer general vulnerability to psychopathology via deficiencies in top-down, prefrontal control over behavior, which interacts with bottom-up, subcortical vulnerabilities to eventuate in specific manifestations of psychopathology (see Beauchaine, 2015; Beauchaine & Thayer, 2015). This “bifactor” model of psychopathology, which has been replicated in several independent samples of children, adolescents, and adults

internalizing

anxiousmisery

major depression

fear

simple phobia

dysthymia

generalized anxiety

externalizing

social phobia

panic disorder

agoraphobia

alcohol dependence

drug dependence

antisocial personality

Figure 3.1 The general latent structure of psychopathology, as determined by twin, adoption, and population-based studies. Adapted from Krueger (1999)

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general vulnerability factor (prefrontal function)

Level of Analysis

behavioral genetic vulnerability trait/ cortical neural substrate

behavioral genetic vulnerability trait

behavioral syndrome

internalizing vulnerability (trait anxiety)

internalizing spectrum disorder 1

internalizing spectrum disorder 3

externalizing vulnerability (trait impulsivity)

externalizing spectrum disorder 1

internalizing spectrum disorder 2

subcortical neural substrate

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septo-hippocampal function (BIS) (5HT, NE)

externalizing spectrum disorder 3

externalizing spectrum disorder 2

psychotic disorder 1

psychotic disorder 3

psychotic disorder 2

septo-hippocampal function (BIS) (5HT, NE)

mesolimbic function (BAS) (DA)

Figure 3.2 The bifactor structure of psychopathology, including a superordinate general vulnerability factor (see Caspi et al., 2014; Lahey et al., 2011; Lahey et al., 2012).

(e.g., Lahey et al., 2011; Lahey, Van Hulle, Singh, Waldman, & Rathouz, 2012), appears in Figure 3.2.

Molecular Genetics of Comorbidity Homotypic Comorbidity. Recall that molecular genetics studies benefit from and in some cases require sound theory to guide the search for candidate genes. As noted above, modern accounts of impulsivity implicate mesolimbic DA dysfunction (Beauchaine & Gatzke-Kopp, 2012; Beauchaine et al., 2017; Gatzke-Kopp et al., 2009; Chapter 6 [Neuhaus & Beauchaine]). In fact, aberrant neural responding in the mesolimbic DA system, including the ventral tegmental area and its projections to the nucleus accumbens, the caudate, and the putamen, is a core neural substrate of vulnerability to all or most externalizing behaviors (Beauchaine & McNulty, 2013; Gatzke-Kopp et al., 2009). Furthermore, studies using both positron

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emission tomography and functional magnetic resonance imaging indicate that low levels of neural activity in the DA-mediated primary reward centers of the brain predispose to sensation seeking, irritability, negative affectivity, and low motivation—core symptoms of externalizing psychopathology (Durston, 2003; Laakso et al., 2003; Leyton et al., 2002; Scheres, Milham, Knutson, & Castellanos, 2007; Zisner et al., 2016). These findings suggest that genes involved in synthesis, catalysis, and reuptake of DA should be candidates in molecular genetics studies of externalizing behavior patterns. Chapter 6 [Neuhaus & Beauchaine] summarizes studies implicating numerous genes involved in DA neurotransmission (e.g., DAT1, DrD4, dopamine-𝛽-hydroxylase, monamine oxydase, catechol-O-methyl transferase) in expression of impulsivity and related externalizing psychopathology. In sum, central DA dysfunction may account for much of the shared vulnerability for externalizing disorders. In contrast, vulnerability to anxiety disorders is conferred largely through behavioral inhibition, which has been linked closely with serotonergic and noradrenergic neurotransmission and (see e.g., Gray & McNaughton, 2000; Chapter 7 [Kagan]). Heterotypic Comorbidity. Studies of overlapping vulnerabilities for conduct problems and depression provide potential insights into why heterotypic comorbidity is so common. At the symptom level, both internalizing and externalizing disorders are characterized by negative affectivity, irritability, and anhedonia (see Zisner & Beauchaine, 2016). Neurally, these symptoms are subserved by the same DA deficiencies just described and detailed in Chapter 6 [Neuhaus & Beauchaine] for externalizing disorders (Forbes et al., 2006; Nestler & Carlezon, 2006; Shankman, Klein, Tenke, & Bruder, 2007). In fact, neuroimaging studies reveal blunted activation within DA-mediated brain regions during reward tasks among externalizing children/adolescents and among those with depression (see Durston, 2003; Epstein et al., 2006; Forbes et al., 2006; Sauder, Derbidge, & Beauchaine, 2016; Scheres et al., 2007). Thus, externalizing and internalizing disorders appear to share a common neural deficiency that accounts, at least in part, for overlap in symptoms. This conclusion is consistent with results outlined above from behavioral genetics studies indicating a common heritable vulnerability for depression and antisocial behavior (Burcusa et al., 2003; Kendler et al., 2003; Lahey et al., 2011; O’Connor, Neiderhiser, Reiss, Hetherington, & Plomin, 1998). Importantly, deficiencies in DA-mediated reward circuitry are moderated by other biologically influenced traits to affect behavior (Corr & McNaughton, 2016). One such trait is behavioral inhibition (see Figure 3.1), which differentiates between those who present principally with CD and those who present principally with depression (see e.g., Beauchaine, 2001; Chapter 7 [Kagan]). Thus, high trait anxiety predisposes to depression among those with blunted reward systems, whereas low trait anxiety predisposes to delinquency. Trait anxiety is modulated by an entirely different (primarily serotonergic) neural network, often referred to as the septo-hippocampal

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system (Gray & McNaughton, 2000). This is an example of two heritable traits interacting to affect behavior (i.e., a Trait × Trait interaction; see Derryberry, Reed, & Pilkenton-Taylor, 2003).

GENETICS OF CONTINUITY Whereas homotypic continuity describes the unfolding of a single class of behavioral/emotional disturbance over time (e.g., aggression), heterotypic continuity refers to the sequential development of different (but related) internalizing or different externalizing behaviors or disorders across the lifespan (see Beauchaine & McNulty, 2013; Beauchaine et al., 2010, 2016; Ferdinand et al., 2007; Rutter, Kim-Cohen, & Maughan, 2006). For example, delinquent adult males are likely to have traversed a developmental pathway that began with tantrums and hyperactive/impulsive behaviors in toddlerhood, followed by ODD in preschool, early-onset CD in elementary school, SUDs in adolescence, and ASPD in adulthood (see Beauchaine et al., 2010; Loeber & Hay, 1997; Lynam, 1996).4 Developmental trajectories of internalizing disorders in which infant reactivity and early shyness mark liability for later anxiety and depression have also been described (Kagan, Snidman, Kahn, & Towsley, 2007; see also Rutter, Kim-Cohen, & Maughan, 2006; Chapter 7 [Kagan]). Few studies have addressed either the behavioral genetics or the molecular genetics of heterotypic continuity. Although some inferences can be offered from cross-sectional studies outlined above addressing homotypic comorbidity, longitudinal studies are required to make strong statements about the stability of behavior disorders over time or about heritable versus environmental bases of behavioral stability (see Rutter, Kim-Cohen et al., 2006). In one such behavioral genetics analysis, heritable factors accounted for much of the stability in antisocial behavior, depressive symptoms, and their co-occurrence over a 3-year interval among 10to 18-year-olds (O’Connor, Neiderhiser et al, 1998). Although molecular genetics studies addressing heterotypic continuity have not appeared in the literature to date, several genes that predispose to ADHD also predispose to conduct problems and SUDs (see Gizer et al., 2016), consistent with findings from behavioral genetics research implicating common genes for different externalizing disorders (see above). Genes associated with ADHD are also associated with ASPD (Martin, Hamshere, Stergiakouli, O’Donovan, & Thapar, 2015). Recently, we articulated an ontogenic process model of externalizing psychopathology in which the well-characterized developmental progression from early life ADHD to increasingly serious forms of problem behavior across development— including oppositional defiant disorder, conduct disorder, antisocial personality disorder, and substance abuse and dependence—are explained by passive 4. This does not mean that all or even most children with ADHD eventually develop antisocial behavior. Although children with ADHD are vulnerable to more serious externalizing conduct across development, many desist. Nevertheless, most antisocial adult males began as hyperactive-impulsive preschoolers.

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and evocative G × E (Ahmad & Hinshaw, 2016; Beauchaine & McNulty, 2013; Beauchaine et al., 2010, 2016, 2017). Individuals who inherit trait impulsivity and are exposed to coercive parenting are likely to generalize maladaptive social behaviors to extrafamilial settings and develop conduct problems. Once these emerge, deviant peer group affiliations are likely. In such peer groups, exposure to substances of abuse and opportunities to engage in crime are common. Consistent with the developmental perspective of this chapter and this entire volume, this a decidedly transactional model in which individual-level vulnerabilities eventuate in recalcitrant externalizing conduct only among those who are exposed to high-risk environments. Even though much progress has been made toward specifying behavioral and molecular genetic bases of psychopathology, considerable work remains on questions of comorbidity and continuity (for extended discussions, see Beauchaine & Cicchetti, 2016a, b; Rutter, Kim-Cohen et al., 2006). Nevertheless, investigations conducted to date suggest that mechanisms of both comorbidity and continuity are likely to result from broad vulnerability traits such as impulsivity and anxiety. This supposition is consistent with recent behavioral genetics approaches that have identified general internalizing and externalizing heritable vulnerabilities that account for more variance in psychopathology than do clusters of symptoms specific to any single disorder (e.g., Kendler et al., 2003; Krueger et al., 2002; Skuse, 2001).

SUMMARY AND CONCLUSIONS Despite expanded acknowledgment of the importance of both genes and environments in the development of psychopathology, much work remains toward uncovering specific mechanisms through which “nature” and “nurture” interact to affect behavior. Although behavioral genetics studies parse phenotypic variance into heritable versus environmental influences, genes are not measured in such studies. Rather, phenotypic similarities between related individuals are used to model heritable effects, which have both genetic and nongenetic origins. The considerable distance between genotypes and phenotypes, along with various interdependencies among genotypes, phenotypes, and environments, can lead to inflated and misleading estimates of heritability. Furthermore, molecular genetics studies aimed at identifying specific allelic variants that are associated with psychological dysfunction often fail to account for environmental moderators of vulnerability. More mechanistic studies, including experiments with animals, can uncover complex patterns of environmentally mediated gene expression and function. Such epigenetic processes, which have drawn considerable attention in recent years, are likely to be implicated in expression of numerous psychiatric disorders and may explain some of the large gap in variance (i.e., missing heritability) explained by molecular genetics versus behavioral genetics studies. Although epigenetic processes are difficult to study in humans, they should nevertheless be included in emerging models of developmental psychopathology.

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Most researchers now reject dichotomizing genetic and environmental influences on behavior (nature versus nurture). Indeed, boundaries between nature and nurture continue to dissolve as we increase our understanding of the interplay between heritable and experiential factors affecting psychopathology. Given the mutual interdependence of genes and environments in affecting behavior, it is no longer tenable to study psychopathology from strictly biological or environmental perspectives (see e.g., Beauchaine et al., 2017). The next generation of mental health professionals must reject false reductionism and be facile in their thinking about psychopathology across all relevant levels of analysis including genes, neural systems, family environments, neighborhoods, and even broader social systems (see Cicchetti, 2008). Breakthroughs in the understanding of and treatment of psychopathology are unlikely to occur by considering any single level of analysis in isolation.

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P A R T II

VULNERABILITIES AND RISK FACTORS FOR PSYCHOPATHOLOGY

CHAPTER 4

Risk and Resilience in Child and Adolescent Psychopathology BRUCE E. COMPAS, MEREDITH GRUHN, AND ALEXANDRA H. BETTIS

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he concepts of risk and resilience are cornerstones of the field of developmental psychopathology, with research on these constructs playing a central role in understanding the etiologies of various psychological symptoms and disorders. Risk research is concerned with factors and processes that are associated with increased probability of the development of psychopathology, whereas resilience research focuses on factors and processes that are associated with decreased probability of psychopathology among individuals who have been exposed to known vulnerabilities or risk factors. In this chapter, we provide an overview of these constructs in developmental psychopathology by first reflecting on the history of risk and resilience research, next reviewing contemporary issues in their definitions and conceptualization, and then presenting evidence for stress as a pervasive source of risk—and processes of coping and emotion regulation as important of processes of resilience. Finally, we provide a salient example of current research on processes of risk and resilience among children of depressed parents.

HISTORICAL CONTEXT Research and theory on processes of risk and resilience have long and rich histories, with the first large-scale programs of research on the interplay of these processes emerging in the behavioral sciences in the early 1970s. However, because the concept of resilience is dependent on identification of sources of risk, it is not surprising that studies examining sources of risk for psychopathology among children and adolescents preceded research on resilience. Work in this area stemmed from the traditions of risk research established in public health and focused on three general questions: (1) Who gets sick, and who doesn’t get sick? (2) What are risk factors 113

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for illness? and (3) What can be done to make illness less common? (Gruenberg, 1981; Masten, 2013; Masten et al., 1990). Early studies were largely correlational, linking various risk factors to poor outcomes in a variety of populations, including children of parents with psychopathology, children living in poverty, and children exposed to trauma or disaster (e.g., Anthony & Koupernik, 1974; Garmezy, 1974; Rutter, 1979). Although cross-sectional studies were valuable in providing the first indication of possible risk factors in these populations, a vital approach to identification of risk is found in large-cohort longitudinal studies. Several studies exemplify this approach, including (among many others) the Isle of Wight Study (e.g., Rutter, Tizard, Yule, Graham, & Whitmore, 1976), the Dunedin Longitudinal Study (e.g., Poulton, Moffitt, & Silva, 2015), and more recently the Bucharest Early Intervention Project (e.g., Nelson, Fox, & Zeanah, 2014; Zeanah et al., 2003). However, the origin of risk research in psychopathology is best reflected in early studies of children at high risk due to parental schizophrenia. Historically, any influence—whether exogenous or endogenous—that increased the likelihood of psychopathology, was considered to be a risk factor (Kraemer, Kazdin, Offord, Kessler, Jensen, & Kupfer, 1997). More recently, a distinction has been made in developmental psychopathology research between risk factors as external influences on an individual’s adjustment and vulnerabilities as biological predispositions that interact with external risk factors to eventuate in adverse mental health outcomes (see e.g., Shannon, Beauchaine, Brenner, Neuhaus, & Gatzke-Kopp, 2007). In this chapter, we maintain this distinction between vulnerabilities and risk factors, as doing so facilitates discussion of complex Biology × Environmental interactions in the emergence of psychopathology. Such interactions are far more common than once supposed (Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Four pioneering programs of research on risk shared a number of common features, and shaped research in this area for decades to come—-the Mauritius/Danish High Risk Project directed by Salvador Mednick and F. Schulsinger (Mednick & Schulsinger, 1968); Project Competence at the University of Minnesota headed by Norman Garmezy and colleagues (Garmezy, 1972, 1974; Garmezy & Streitman, 1974); the UCLA Family High Risk Project directed by Michael Goldstein and Eliot Rodnick (e.g., Jones, Rodnick, Goldstein, McPherson, & West, 1977; Rodnick & Goldstein, 1974); and the Rochester Longitudinal Study directed by Arnold Sameroff, Ronald Seifer, and Melvin Zax (e.g., Sameroff, Seifer, & Zax, 1982; Siefer, Sameroff, & Jones, 1981). All of these studies were concerned with children at extraordinarily high vulnerability/risk for psychopathology as conferred by parental schizophrenia. These studies investigated to varying degrees the role of genetic, psychological, and interpersonal/familial mechanisms of vulnerability and risk that distinguished these children from those of parents without psychopathology. One of the most striking findings of this work was the unexpected observation that in spite of exposure to significant risks associated with parental schizophrenia, a surprising number of children did not evidence psychopathology and, in fact, their

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development was characterized by high levels of competence. The observation that parental schizophrenia, which confers both genetic vulnerability and environmental risk, did not result in uniformly poor outcomes across individuals was an important impetus for research on the concept of resilience. Garmezy, Rutter, Werner, and others argued for the equal importance of understanding pathways to positive as well as to negative adjustment (e.g., Garmezy & Rutter, 1983; Rutter, 1987; Werner & Smith, 1982). As a result, a parallel set of questions was added to those put forth by Gruenberg (1981), including the following: (a) Who becomes healthy, stays healthy, recovers well, and develops well? (b) Why do some individuals display patterns of healthy development in spite of exposure to risk? (c) What can we do to promote and protect health or positive development and facilitate recovery? (Masten, 2013). Since the initial investigation of these questions in the 1970s, resilience research has moved through several waves. Investigators first worked toward defining, operationalizing, and measuring the concepts of risk and resilience with the goal of identifying factors within an individual that promote positive adjustment in the face of adversity (see Masten & Garmezy, 1985). Early work focused on dramatic individual cases of resilience, with an emphasis on observing differences in psychosocial outcomes among individuals in high vulnerability/risk groups (e.g., Anthony & Koupernik, 1974; Garmezy, 1985; Garmezy & Nuechterlein, 1972; Garmezy & Rutter, 1983; Rutter, 1979, 1985; Werner & Smith, 1982). As noted above, investigations of children of mothers suffering from schizophrenia played a crucial role in the emergence of research on resilience in childhood and adolescence (e.g., Garmezy, 1974; Garmezy & Streitman, 1974; Masten et al., 1990). Evidence that many of these children thrived despite high genetic vulnerability and environmental risk led to increasing empirical efforts to understand individual variations in response to adversity, such as differences in social competence (Garmezy, 1974). Garmezy’s seminal work also led to studies investigating factors of resilience in other domains, such as children affected by war, famine, poverty, and other disasters (Masten & Cicchetti, 2012). A second wave of resilience research was marked by an increasing recognition of the contribution of external factors in promoting positive adjustment in the face of risk. In the 1980s and early 1990s, research evolved to incorporate factors thought to be central in the development of resilience, including individual factors, familial factors, and extrafamilial support factors (Masten & Garmezy, 1985; Werner & Smith, 1982, 1992). Individual factors included qualities related to temperament, reflectiveness in meeting new situations, responsiveness to others, and cognitive skills. Family factors were marked by caregiver warmth, family cohesion, parents’ concern for their child’s well-being, and the presence of a caring adult in the absence of responsive parents. Finally, extrafamilial factors included a person who provides support and guidance to the child, such as a teacher or social worker (see also Luthar & Brown, 2007). More recently, risk and resilience research has shifted from identifying internal and external protective factors to understanding underlying protective processes that might account for resilient outcomes in children and adolescents (e.g.,

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Cicchetti, 2013; Cicchetti & Rogosch, 2012; Masten, 2014; Rutter, 2012). This shift in focus has led to a deeper exploration of how the three factors cited above (individual, familial, and support) may contribute to positive outcomes over time. Drawing on this increased focus on processes, we now examine some contemporary issues and challenges in the study of vulnerability, risk, and resilience.

CONTEMPORARY TERMINOLOGICAL AND CONCEPTUAL ISSUES As outlined above, processes of vulnerability, risk, and resilience as they relate to psychopathology in childhood and adolescence have been central to the study of developmental psychology for many years. However, there has been considerable debate regarding definitions of these constructs. Vulnerability and Risk. As alluded to above, the terms vulnerability and risk refer to increased probabilities of a negative developmental outcome in a specified population (Kraemer, 2003; Kraemer et al., 1997; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). Thus, they are quantitative concepts reflected as either odds ratios when outcomes are measured categorically or as some variant of a regression weight when outcomes are continuous or quantitative. A vulnerability is an endogenous characteristic of the individual (e.g., genetic, neural, hormonal) that increases the likelihood of psychopathology, particularly in contexts of environmental adversity. In parallel, a risk factor is an exogenous agent or characteristic of the environment related to the increased probability of a negative outcome. A landmark report by the National Research Council and the Institute of Medicine (NRC & IOM; 2009) further distinguished between risk factors that are specific to a particular outcome (e.g., depression) versus those that are nonspecific, or transdiagnostic and are related to a number of outcomes (e.g., depression, anxiety, eating disorders). In addition to distinguishing levels of vulnerability and risk, temporal precedence must be established between risks and outcomes; that is, the presence of or exposure to the risk factor must precede evidence of the development of the outcome. Kraemer et al. (2001) address the issue of temporal precedence within a typology of risk factors. If a risk factor is simply associated with an outcome at a single point in time, it is identified as a correlate. A correlate that precedes an outcome is a risk factor, and a risk factor that can be changed or changes with development is a variable risk factor. Finally, if manipulation of the risk factor changes an outcome, it is a causal risk factor. Rutter (2012) raised several cautions in interpretation of findings from risk research. According to his account, risk may be genetically rather than environmentally mediated (i.e., risk might represent reverse causation in which a disorder has led to the hypothesized risk factor, rather than the reverse). This point is one reason to distinguish between vulnerability and risk, as we do throughout this volume.

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Furthermore, risk processes might also reflect social selection or processes by which individuals select or shape their environments (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Cumulative Risk. Cumulative risk refers to the co-occurrence of more than one risk factor for a given individual or within a population (Sameroff, 2006). For example, poverty and economic hardship are associated with multiple additional risks factors, including neighborhood crime and violence, lack of access to quality schools, living in a single parent home, and heightened family conflict (e.g., Chen, 2007; Evans & Cassells, 2014; Evans, Li, & Whipple, 2013; Evans & Wachs, 2010; Miller, Chen, & Parker, 2011). Similarly, parental psychopathology, another important risk factor throughout childhood and adolescence, is linked with family conflict and marital discord as well as potential genetic vulnerability to psychopathology (e.g., Goodman et al., 2011; Karg, Burmeister, Shedden, & Sen, 2011). The probability of negative outcomes may increase additively or exponentially as the number of vulnerabilities and risk factors—or cumulative risk—increases. The effects of risk factors can also be nonlinear. Kraemer et al. (2001) spell out conditions in which one risk factor (A) moderates the effects of a second risk factor (B) on an outcome (O). For A to function as a moderator of B, A must precede B, A and B must not be correlated, and A cannot influence B directly. However, the strength of the effect of B on O must be affected by the level of A. For example, consider the interaction between sex and pubertal timing in predicting depression in adolescence, such that girls (but not boys) with early onset puberty have an increased likelihood of a major depressive episode (Negriff & Susman, 2011). Following the principles outlined by Kraemer et al. (2001), in this case sex (A) precedes pubertal timing (B), sex is uncorrelated with pubertal timing, and both are related to depression (O). However, the strength of the association between early onset puberty and depression is greater for girls than for boys; that is, pubertal timing moderates the relation between sex and depression (Copeland et al., 2010). Thus, pubertal timing is a source of increased vulnerability to depression among girls but not among boys. Greater precision of the relations among vulnerabilities and risk factors and their moderating effects will contribute to greater clarity in distinguishing between risk factors and sources of vulnerability and, ultimately, in devising strategies to promote resilience. Resilience. As noted above, the concept of resilience is linked closely to and has grown from research on risk. In the broadest sense, resilience refers to positive adaption despite significant experiences of adversity; however, there is considerable variation in how resilience is defined, conceptualized, and operationalized. Masten (2013) discussed four main controversies in resilience research. First, there is an ongoing debate as whether various definitions of resilience classify it as a process, capacity, trait, outcome, or adaptive pattern. Researchers initially defined

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and measured resilience as an outcome of interest (e.g., a given at-risk individual did not develop schizophrenia and achieved a lasting romantic relationship). However, it is argued that this approach fails to recognize individuals and their circumstances as constantly changing and interacting and that achieving a “positive outcome” involves a wide array of processes. Second, debate exists over whether there is a resiliency trait (Masten, 2012; Riley & Masten, 2005). Researchers have attempted to develop measures to assess resiliency as a trait; however, there is not yet convincing evidence of such an innate or stable characteristic (Masten, 2013), even though significant heritability has been observed for resilience processes (Kim-Cohen, Moffitt, Caspi, & Taylor, 2004). Third, investigators have asked whether the concept of resilience adds more to the field than simply being the positive reframing of risk and vulnerability—i.e., that protective factors are simply the polar opposites of risk factors (e.g., good vs. poor family functioning). Resilience investigators have defended this concept by pointing to the shift in focus of attention, research, and intervention incited by this concept (e.g., Luthar, 2006; Masten, 2011; Rutter, 2006). The fourth issue outlined by Masten (2013) involves criteria and standards of measurement. One main question of interest under this topic asks whether an individual needs to function positively in a specific domain, or across all possible areas of functioning, to meet criteria for being labeled “resilient.” A common criterion used is absence of psychopathology; however, there is growing recognition that individuals with serious psychopathology can function quite well given a well-established repertoire of coping strategies, indicating that resilience should not solely be defined by the absence of psychopathology. Luthar and colleagues (Luthar, 2006; Luthar & Cicchetti, 2000) assert that indicators used to represent resilience should parallel the adversity examined in terms of the domain assessed and the stringency of criteria used, yet other researchers suggest that defining “positive adaption” may be dependent on other factors, such as the sociocultural context in which an individual operates rather than solely the adversity faced (Clauss-Ehlers, 2008; Mahoney & Bergman, 2002; Waller, 2001). A final area of controversy in measuring this construct is a lack of consensus on the pattern of adaption that resiliency follows. Masten and Narayan (2012) propose an outline of patterns of adaptation in response to either acute trauma, or severe and chronic adversity, highlighting the importance of temporality. In this model, responses to acute trauma include (a) resistance or maintenance of function, (b) decline in functioning followed by recovery, and (c) functioning that improves over baseline as a result of the stressful experience. The question, then, is whether recovery after an initial drop in well-being meets criteria for resilience. Bonanno, Westphal, and Mancini (2005) argue that recovery after the initial decline is often incomplete. However, Luthar and Brown (2007) state that there is no

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good evidence to suggest that “resistance” and “recovery” groups of resilient individuals are qualitatively different or that these groups have distinct antecedents or consequences. Again, this distinction depends on the time frame used to characterize resilience. As the time frame increases, it is more likely that many individuals will recover, indicating again the necessity of longitudinal studies of resilience (Rutter, 2012). Despite the aforementioned debates in the field, researchers are united by the common goal of identifying mechanisms and processes that underlie positive adaption in the presence of vulnerability and risk. Current resilience research focuses on a process of positive adaptation in the presence of vulnerability and risk that may be the result of individual factors (e.g., how an individual copes with stress, genes), environmental factors (e.g., parental warmth, community support), or the interplay of the two (Cicchetti, 2013; Luthar, 2006; Luthar & Cicchetti, 2000; Rutter, 2012). Identification of processes that promote resilience in the face of risk is vital to creation of promising preventive interventions. Risk and Resilience. Although there is merit to understanding risk and resilience as distinct concepts, they may be better conceptualized as existing along a continuum. In many instances, high levels of a factor or process protect individuals from risk whereas low levels of the same factor or process amplify risk (Luthar, Sawyer, & Brown, 2006). For example, high IQ may serve as a protective factor in the face of socioeconomic adversity, whereas low IQ may increase the potency of the effects of poverty. Thus, IQ may both increase and decrease vulnerability associated with socioeconomic hardship. However, there are also instances where high levels of a factor are protective, but low levels are neutral or benign in relation to the source of risk. For example, temperamental characteristics of negative affectivity and positive affectivity, respectively, are vulnerability/risk and resilience factors for emotional problems (Compas, Connor-Smith, & Jaser, 2004). However, these traits are relatively independent, as low negative affectivity does not denote positive affectivity. Thus, low negative affectivity indicates the absence of this vulnerability factor but it does not necessarily serve as a protective factor. The situation is further complicated because some vulnerability/risk and protective factors are stable, whereas others change with development. For example, some temperamental characteristics emerge in infancy and remain stable throughout childhood and adolescence. Stable individual differences in temperament may function as either vulnerability or protective factors in adolescence, depending on the characteristic in question. Similarly, some features of the environment may be stable sources of risk or protection throughout childhood and adolescence (e.g., chronic poverty or a supportive and structured family environment), even though negative patterns of family interaction have been shown to be changeable with evidence-based intervention. Other factors

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may emerge during adolescence as sources of risk and protection and can be defined as developmental risk and protective factors. For example, some aspects of cognitive and brain development change dramatically during early adolescence and mark this as a period of heightened vulnerability for many adolescents (Albert, Chein, & Steinberg, 2013; Casey, Getz, & Galvan, 2008; Powers & Casey, 2015; Spear, 2011; Steinberg, 2008, 2015). Similarly, it appears that effects of certain types of stressful events are relatively benign during childhood but are much more likely to be associated with negative outcomes during adolescence (Hankin & Abramson, 2001). In human research, the final step in vulnerability/risk research is likely to involve preventive interventions designed to change established vulnerability and risk factors to determine their possible causal role and prevent the onset of psychopathology.

UNIFYING CONCEPTS FOR UNDERSTANDING RISK AND RESILIENCE: CURRENT PERSPECTIVES ON STRESS, COPING, AND EMOTION REGULATION Research on exposure to stressful events and circumstances and ways in which children and adolescents respond to and cope with stress are central to understanding processes of risk and resilience for psychopathology among young people. Specifically, exposure to stressful events and circumstances, including generation of stressors in neighborhood, school, peer, and family environments, are primary risk factors that exert effects on child and adolescent mental (and physical) health. Furthermore, individual differences in coping and related processes of stress reactivity and emotion regulation are crucial sources of resilience in the face of both distal and proximal sources of stress.

Stress and Emotions In spite of strong criticisms of the construct (e.g., Lazarus, 1993), stress remains a central factor in understanding risk for psychopathology. Prevailing definitions of stress include environmental circumstances or conditions that threaten, challenge, exceed, or harm the psychological or biological capacities of the individual. Grant, Compas, Stuhlmacher, Thurm, and McMahon (2003, p. 449) defined stressors during childhood and adolescence as “environmental events or chronic conditions that objectively threaten the physical and psychological health or well-being of individuals of a particular age in a particular society.” This definition is consistent with traditional objective measures and stimulus-based definitions of stress (e.g., Rudolph & Hammen, 2000). At the same time, events or chronic circumstances can threaten the well-being of an individual without leading to negative outcomes. Thus, stressful events and conditions are defined independently of their effects or outcomes. This definition allows for positive outcomes in the face of objectively threatening circumstances; that is, it allows for resilience.

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In a series of reviews, Grant and colleagues (Grant et al., 2003; Grant et al., 2004; Grant et al., 2006; McMahon, Grant, Compas, Thurm, & Ey, 2003) identified several overarching findings from research on stress and psychopathology among children and adolescents. First, as noted above, Grant et al. (2003) suggest that stress is best conceptualized in terms of the occurrence of acute events or chronic conditions or circumstances (referred to as stressors) that threaten the physical or mental health of the child or adolescent. The nature of events (e.g., parental divorce, family move) and chronic conditions (e.g., poverty, chronic parental conflict and discord) that constitute sources of stress vary as a function of children’s development and social context. Second, more than 50 prospective longitudinal studies have provided evidence that exposure to stressful events and chronic adversity predict increases in both internalizing and externalizing symptoms over time (Grant et al., 2004). Such longitudinal prediction suggests that stressors play a causal role in development of both types of symptoms. Thus, stressful events in the lives of children and adolescents meet criteria for risk factors (and even causal risk factors) as outlined by Kraemer et al. (2001). Third, consistent with a heuristic model of Nolen-Hoeksema and Watkins (2011), exposure to stressful life events functions as a distal risk factor for internalizing and externalizing symptoms, potentially mediated by more proximal family characteristics, including disrupted parenting and parent–child relationships (Grant et al., 2003; Grant et al., 2006). Evidence is particularly strong for poverty and economic disadvantage as distal risk factors that affect child/adolescent internalizing and externalizing symptoms through their effects on parenting (Grant et al., 2003). Finally, McMahon et al. (2003) concluded that exposure to stressful events and chronic sources of adversity plays a role in virtually all types of psychopathology including internalizing and externalizing problems, as well as more specific symptoms of depression, anxiety, eating disorders, aggressive behavior problems, conduct problems, substance use and abuse, and somatization. McMahon et al. (2003) note that across various stressors examined, the most consistent evidence for specificity is for the association of sexual abuse with internalizing symptoms, PTSD, and sexual acting-out symptoms. Subsequent research indicates specificity among a wider set of psychosocial risk factors that include but are not limited to stressful events (Shanahan, Copeland, Costello, & Angold, 2008). In contrast, evidence from the National Comorbidity Survey Replication (Green et al., 2010; McLaughlin et al., 2012) suggests that childhood adversities, including interpersonal loss (parental death, parental divorce, and other separation from parents or caregivers), parental maladjustment (mental illness, substance abuse, criminality, and violence), maltreatment (physical abuse, sexual abuse, and neglect), life-threatening childhood physical illness, and extreme childhood family economic adversity are associated with all types of psychopathology in adulthood. Thus, stressful life events and circumstances of adversity are broad, nonspecific risk factors for a wide range of co-occurring patterns of symptoms and disorders in childhood and adolescence—revealing clear evidence for multifinality (see Chapter 1 [Hinshaw]).

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The large body of research on the role of stressors in child and adolescent psychopathology could suggest that research in this area has reached its zenith and that there is little new to be learned. However, several new perspectives have emerged with strong potential to expand on the decades of research on stress and coping that inform understanding of processes of risk and resilience. Specifically, research in psychopathology has been reshaped by an emphasis on underlying processes as reflected in the Research Domain Criteria (RDoC) from the National Institute of Mental Health (Casey, Oliveri, & Insel, 2014; Insel & Cuthbert, 2015). A similar approach is needed to provide a better understanding of processes that reflect the foundations and substrates of stress and coping. Moreover, the construct of allostatic load highlights the importance of biological processes of stress. Allostatic load refers to the cost or wear and tear on biological and psychological systems as a result of chronic or repeated exposure to significant stress (McEwen & Stellar, 1993). Underlying biological systems can become dysregulated as a result of prolonged exposure to stressful events or conditions leading to behavioral, emotional, and biological dysfunction (Juster, McEwen, & Lupien, 2010). The concept of allostatic load has added value for understanding the role of stress in developmental psychopathology in part because unlike traditional research on stressful life events, it emphasizes the integration of multiple levels of analyses, including genetic and other neurobiological processes, developmental history, and current context and experience (Cicchetti, 2011). Drawing on studies of humans and animals, such multiple-levels-of-analysis research holds promise for delineating processes through which exposure to stressful events and circumstances contribute to development of psychopathology (see Chapter 1 [Hinshaw]). Research guided by the allostatic load framework has generated a number of findings that are potentially important to child and adolescent psychopathology. For example, initial conceptualizations of allostatic load emphasized the effects of chronic stress on activation and dysregulation of the hypothalamic-pituitary-adrenal axis and the production of cortisol. However, Beauchaine, Neuhaus, Zalewski, Crowell, and Potapova (2011) note the additional importance of dysregulation in monoamine neural systems including dopamine, norepinephrine, and serotonin. For example, repeated and prolonged exposure to stress often alters central serotonin expression through epigenetic mechanisms, conferring lifelong risk for anxiety, depression, and other adverse outcomes. Research on allostatic load highlights the important role of chronic exposure to stress as a major source of risk for other biological systems and behaviors as well. For example, repeated exposure to violence alters neurodevelopment in the hippocampus and prefrontal cortex, conferring risk for learning and memory difficulties, disrupted social affiliation, and substance use and abuse (Mead, Beauchaine, & Shannon, 2010). Research on the effects of stressful life events has typically focused on the occurrence of events within a specified and relatively recent period of time (e.g., the prior 6 months). In contrast, more recent research places greater emphasis on the developmental timing of exposure to stress, with evidence accumulating for the long-term significance of early exposure to stress and adversity. For example,

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work by Evans and colleagues documents long-term effects of growing up with the chronic stress of poverty on later psychological and physical health (e.g., Evans et al., 2010; Evans et al., 2013). Extensive research also indicates that exposure to abuse and neglect early in development is related to increased risk for subsequent psychopathology in childhood and adolescence (e.g., Heleniak, Jenness, Vander Stoep, McCauley, & McLaughin, 2016). Research on effects of stressful events and chronic stress has been enriched by a focus on the role of emotions that arise in response to sources of stress in the environment. Emotion is defined broadly as a person-environment interaction requiring attention that involves considerable personal significance and evokes complex, continuously evolving responses (Gross & Thompson, 2007). The environment may include external stimuli or internal representations involving thoughts and memories. Emotions have historically been divided into primary emotions (including anger, sadness, fear, happiness, disgust, surprise) and secondary emotions (e.g., shame, pride). Whereas primary emotions are direct responses to environmental stimuli and constitute a biological preparation for appraisal and response (Izard, 2002), secondary emotions occur as a result of primary emotions. Seminal work by Zajonc (1980) posited the primacy of emotions in human thought and behavior patterns. That is, personal beliefs about one’s likes and dislikes are based in automatic affective responses and do not require higher-order cognitive processes. The importance of emotions in the development of psychopathology is further reflected in the concept of emotion regulation, which we now consider along with the parallel construct of coping.

Coping and Emotion Regulation Given the significant role of stress in psychopathology during childhood and adolescence, coping with and regulating emotions in response to stress is a key feature of resilience. Skills needed to cope with stressful events and chronic adversity and to regulate emotions, including emotions that arise in response to stress, are fundamental aspects of development. The most widely cited definition of coping is that of Lazarus and Folkman (1984), which is derived from their appraisal-based model of stress and coping. They define coping as “constantly changing cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person” (Lazarus & Folkman, 1984, p. 141). Thus, coping is viewed as an ongoing dynamic process that changes in response to changing demands of a stressful encounter or event and includes purposeful responses. Definitions of coping following from the seminal work of Lazarus and Folkman have shifted toward a developmental emphasis (Compas, Connor-Smith, Saltzman, Thomsen, & Wadsworth, 2001; Eisenberg, Fabes, & Guthrie, 1997; Skinner, Edge, Altman, & Sherwood, 2003). For example, Skinner and Wellborn (1994) conceptualized coping as “action regulation under stress” and defined it as “how people mobilize, guide, manage, energize, and direct behavior, emotion, and orientation,

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or how they fail to do so” (p. 113). Compas et al. (2001) defined coping as “conscious volitional efforts to regulate emotion, cognition, behavior, physiology, and the environment in response to stressful events or circumstances” (p. 89). Building on work by Lazarus and Folkman, these definitions focus on effortful, purposeful responses to acute or chronic stressful events or circumstances. In other words, coping refers to processes that are enacted in response to stress, with an increasing emphasis on coping as a form of regulation in response to stress. Regulation of a wider range of functions, including emotion, behavior, cognitions, physiology, and the environment, is now included within the sphere of coping. There has been little consensus regarding the nature and dimensions or types of coping and emotion regulation in childhood and adolescence. Skinner, Edge, Altman, & Sherwood (2003) identified more than 400 categories or types of coping that have been represented in research on this construct. Previous categories include problem-versus emotion-focused coping, approach versus avoidance, and active versus passive coping. Although the problem-and emotion-focused distinction may be important historically, an alternative three-factor control-based model of coping has been validated successfully in several samples that are diverse with regard to ethnicity, nationality, and type of stress (Compas et al., 2001; Compas et al., 2014; Connor-Smith, Compas, Thomsen, Wadsworth, & Saltzman, 2000; Rudolph, Dennig, & Weisz, 1995). Within this model, responses to stress are first distinguished along the dimension of automatic versus controlled processes; coping responses are considered controlled, volitional efforts to regulate cognition, behavior, emotion, and physiological processes, as well as aspects of the environment in response to stress. Coping responses are further distinguished as primary control engagement (problem solving, emotional modulation, emotional expression), secondary control engagement (acceptance, cognitive reappraisal, positive thinking, distraction), or disengagement (cognitive and behavioral avoidance, denial, wishful thinking). This model is supported by at least seven confirmatory factor analytic studies with children, adolescents, and adults exposed to and coping with a wide range of stressors (e.g., peer stressors, war-related stressors, family stressors, economic stressors, chronic pain), from diverse socioeconomic and cultural backgrounds and international samples (e.g., Euro-American, Native American Indian, Spanish, Bosnian, Chinese), using multiple informants (Benson et al., 2011; Compas et al., 2006; Connor-Smith et al., 2000; Connor-Smith & Calvete, 2004; Wadsworth, Reickmann, Benson, & Compas, 2004; Yao et al., 2010). Research in emotion regulation has been carried out relatively separately from research on coping among children and adolescents. Emotion regulation research is organized around modulation of specific emotions (e.g., sadness, fear, anger), and includes any efforts to up or down regulate both positive and negative emotions (see Chapter 11 [Cole, Hall, & Hajal]). A widely accepted definition of emotion regulation has been offered by Thompson (1994): “The extrinsic and intrinsic processes responsible for monitoring, evaluating, and modifying emotional reactions, especially their intensive and temporal feature, to accomplish one’s goals”

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(pp. 27–28). This definition includes the set of processes that allows for the increase, decrease, or maintenance of an affective state (Davidson, Putnam, & Larson, 2000). According to Gross (1998) emotion regulation is a multistage process that includes generation and modulation of emotions, which can occur during several sequential steps (Gross, 1998). The phases during which specific emotions are regulated include both antecedent-focused strategies, which influence an emotion before it is formed fully, and response-focused strategies, which influence an emotion once it has been developed. In this process model, antecedent-focused strategies include situation selection, situation modification, attentional deployment, and cognitive change, and response-focused strategies include response modulation (e.g., Gross, 2001; Gross & Jazaieri, 2014; Gross, Sheppes, & Urry, 2011). Similar to the state of research on coping, a number of different emotion regulation strategies have been identified (e.g., cognitive reappraisal, emotional suppression) and there consensus has not been reached on the underlying structure of these strategies (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010). In spite of considerable overlap in conceptualization and measurement of coping and emotion regulation, the literatures on these two constructs have developed quite independently, with the former largely preceding the latter. We see this situation as problematic, as a richer understanding of adaptation to stress will result from integration of these lines of work. To that end, we now consider recent work on emotion regulation and coping. Coping and emotion regulation have both shared and nonshared features. Importantly, both constructs emphasize processes of regulation—whether regulation of emotions specifically (emotion regulation) or regulation of a broader set of responses to stress (coping). Furthermore, processes of regulation may be in response specifically to a stressor (coping) or occur across both positive and negative situations (emotion regulation). Several strategies appear common to both. For example, cognitive restructuring, as viewed in the context of coping as efforts to actively reinterpret stressful or negative events in more neutral or positive terms, overlaps heavily with the cognitive reappraisal form of emotion regulation. Implementation of this strategy is linked to reduced physiological and emotional arousal when an individual is presented with an emotional stimulus (e.g., Oschner, Bunge, Gross, & Gabrieli, 2002); it is used clinically as part of evidence-based cognitive behavioral therapy treatments for several disorders (e.g., Stark, Krumholz, Ridley, & Hamilton, 2009). Deficits in the use of adaptive strategies in response to stress and emotions have been tied to significant emotional and behavioral problems including symptoms of mood and anxiety disorders among children and adolescents (e.g., Bettis et al., 2016). Deficits in emotion regulation in the presence of stress have been tied to many DSM diagnoses among adults, including mood, anxiety, eating, and substance use disorders, as well as personality disorders (e.g., Campbell-Sills & Barlow, 2007; Gross & Levenson, 1997; Miller, Rathus, & Linehan, 2007). In addition, deficits in regulating negative emotions have been linked to internalizing and externalizing disorders among children and adolescents (Beauchaine, 2015). Therefore, strategies of

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coping and emotion regulation may be important sources of resilience for children and adolescents, particularly those at high risk for internalizing and externalizing psychopathology.

RISK AND RESILIENCE: CHILDREN OF DEPRESSED PARENTS To further exemplify stress and coping processes in child and adolescent vulnerability, risk, and resilience for psychopathology, we focus here on examples from research on development of depression during childhood and adolescence. Depression provides a useful example of these constructs because it increases dramatically in prevalence over the course of childhood and adolescence and because there is now a substantial body of work identifying stress as a significant source of risk, stress reactivity as a potential vulnerability, and coping as a source of resilience. Children and adolescents whose parents experience one or more episodes of depression are exposed to a significant source of vulnerability to and risk for depression and other mental health problems. Research on children of depressed parents builds on early vulnerability, risk, and resilience research on children of parents with schizophrenia, but depression has a far higher prevalence than schizophrenia. Indeed, the high prevalence of depression in the general population represents a significant mental health problem (Chapter 18 [Klein, Goldstein, & Finsaas]). As reported in the National Comorbidity Survey Replication, Kessler et al. (2003) found the lifetime prevalence of major depressive disorder to be 16.9%. It is expected that 32 to 35 million adults in the United States will experience an episode of depression over the course of their lifetime. Depression increases significantly from childhood to adolescence. Longitudinal studies suggest that middle adolescence (ages 15 to 16 years old) is a time of substantially increased risk for the onset of major depression (e.g., Hankin et al., 1998). Depression is also a highly recurrent disorder, as individuals who suffer from a first depressive episode have a 40% chance experiencing a subsequent episode, individuals with two episodes have an approximate 60% chance of a recurrence, and individuals with three episodes have 90% risk (e.g., Moffitt et al., 2010). Furthermore, an initial onset of depression during adolescence predicts a severe and recurrent course of disorder, with high levels of impairment (e.g., Hammen, Brennan, Kennan-Miller, & Herr, 2008). Rates of depression among women are highest in young adulthood, during childbearing years, and among women with children (Kessler et al., 2003). Among males, rates of depression are higher in those younger than age 45 than in those age 45 and older. The former age group of men is likely to have children (Kane & Garber, 2004). Thus, a significant number of children and adolescents are exposed repeatedly to symptoms of depression—both when their parents are in and out of episode. The large number of mothers who experience clinical depression during their children’s lifetimes is particularly problematic, as maternal depression is

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linked to significant negative developmental outcomes among children (Goodman, 2007; Goodman et al., 2011). Children of depressed parents are at high risk for both internalizing and externalizing psychopathology, including a two- to threefold increased risk of developing depressive disorders (NRC & IOM, 2009). As many as 50%–80% of offspring of depressed parents (7.5 to 12 million children) will meet criteria for a psychiatric disorder by young adulthood (NRC & IOM, 2009). Because adolescence marks a particularly important developmental period for increased depression risk, early to middle adolescent offspring (10 to 15 years old) of depressed parents are an ideal target for prevention, given their high risk for depression, anxiety, and externalizing behavior problems (NRC & IOM, 2009). Vulnerability, risk, and protective factors for children of depressed parents include biological, psychological, and interpersonal processes (Goodman & Gotlib, 1999). Indeed, because the heritability of major depression appears to be less than 50% (Sullivan, Neale, & Kendler, 2000), psychosocial risk factors are highly likely to be involved in intergenerational transmission. Having established that parental depression is a significant risk factor for depression and other forms of psychopathology among children and adolescents, it is important to understand mechanisms and processes through which vulnerability and risk affect offspring. In addition, since not all offspring of depressed parents develop psychopathology, understanding protective processes that lead to resilience is also important.

Vulnerability and Risk Processes Among Children of Depressed Parents Effects of parental depression on offspring are likely transmitted through multiple mechanisms, including heritable vulnerability in terms of dysfunctional neuroregulatory mechanisms; exposure to negative maternal cognitions, behaviors, and affect; and the stressful context of the adolescent’s life (Goodman & Gotlib, 1999). Of particular relevance to this chapter are disrupted interpersonal interactions that depressed individuals experience, which contribute to high levels of stress for children and adolescents in families of depressed parents. Specifically, parent–child interactions are critical mechanisms through which children are exposed to risk factors associated with parental depression, as parental depression affects parents’ behaviors and emotions in interactions within the family (Dix & Meunier, 2009; Lovejoy, Graczyk, O’Hare, & Neuman, 2000). Exposure to stressful parent–child interactions is a primary psychosocial mechanism through which parental depression exerts its effects on children (e.g., Gruhn et al., 2016; Jaser et al., 2005; Jaser et al., 2007; Jaser et al., 2008; Langrock, Compas, Keller, Merchant, & Copeland, 2002). Depression impairs parents’ abilities to effectively provide support, nurturance, and structure for their children, leading to disruptions in parenting. Most research on parenting in depressed families is concentrated on parenting difficulties associated with the physical,

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cognitive, and emotional symptoms of depression (e.g., sad mood, irritability, lack of interest, fatigue, or difficulty concentrating; Dix & Meunier, 2009). Parental withdrawal (e.g., avoidance or unresponsiveness to their children’s needs) and intrusiveness (e.g., irritability toward their children or excessive involvement in their children’s lives) are characteristic of depressed parents in their interactions with their children (e.g., Cummings, DeArth-Pendley, DuRocher-Schudlich, & Smith, 2001). Exposure to hostile, disengaged, and inconsistent parenting, as opposed to nurturing parenting, contributes to a chronically stressful and unpredictable environment for children and tends to result in increased symptoms among offspring of depressed parents. Recent studies show that children who are exposed to higher levels of parental intrusiveness/irritability and withdrawal have higher levels of internalizing and externalizing symptoms. For example, Langrock et al. (2002) found that both parental intrusiveness and withdrawal are correlated with higher levels of offspring anxiety/depression and aggression, according to parent reports. Jaser et al. (2005) extended those findings by demonstrating significant positive cross-informant correlations among adolescent reports of parental intrusive behaviors and parent reports of adolescent internalizing and externalizing symptoms. Using direct observations of parents’ behavior in a sample of parents with a history of depression, Gruhn et al. (2016) found that parental depressive symptoms were related to withdrawn parenting for parents of boys and girls and to intrusive parenting for parents of boys only. When covarying for intrusive parenting, parental depressive symptoms were related to withdrawn parenting for parents of boys. Moreover, when adjusting statistically for the other type of problem (i.e., internalizing or externalizing), withdrawn parenting specifically predicted externalizing problems but not internalizing problems among girls. No evidence of specificity was found for boys, suggesting that impaired parenting behaviors are diffusely related to both internalizing and externalizing symptoms for boys. Evidence suggests that behavioral effects of maternal depression are at least in part causal. For example, depressive symptoms among children of depressed mothers decrease when mothers’ depression is in remission, an effect that is partly accounted for by improvements in mothers’ parenting (Weissman et al., 2014). There may be long-lasting effects of disrupted parenting, as discord in mother-child relationships at age 15 predicts depressive symptoms in daughters of depressed mothers at age 20 (Katz, Hammen, & Brennan, 2013). Through several risk processes, offspring of depressed parents are at increased risk for depression and other forms of psychopathology. However, research suggests that even under the stressful circumstances of having a parent with depression, a substantial proportion of children are resilient and adapt successfully. Attempts to explain resilience have focused on potential moderators. Ways that adolescents react to and cope with the stress of living with a depressed parent may serve as both mediators and moderators of the effects of this stress.

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Sources of Resilience Among Children of Depressed Parents Styles of response to stress play critical roles in the effects that stress has on their emotional and psychological well-being (Compas et al., 2001; Compas et al., 2014). First, how do children cope with stress associated with parental depression? Second, how does depression in a parent constrain or alter ways that children cope with stress related to parents’ depression? Third, how do children’s coping responses moderate relations between stress and children’s adjustment in families of depressed parents? Our research group has studied coping and stress responses in three samples of adolescent offspring of depressed parents (Bettis et al., 2016; Dunbar et al., 2013; Fear et al., 2009; Jaser et al., 2005; Jaser et al., 2007; Jaser et al., 2008; Jaser, Champion, Dharamsi, Reising, & Compas, 2011; Langrock et al., 2002). First, we examined these processes in a sample of adolescents whose mother or father had a history of depression and who had experienced at least one episode of depression in the adolescent’s lifetime (Jaser et al., 2005; Jaser et al., 2007; Langrock et al., 2002). In this sample, adolescents’ use of secondary control coping (i.e., positive thinking, distraction, acceptance, and cognitive restructuring) was related to lower symptoms of anxiety and depression, both within and across adolescents’ and parents’ reports of adolescents’ coping and symptoms. Furthermore, higher levels of stress reactivity (emotional and physiological arousal, intrusive thoughts) were related to higher symptoms of anxiety/depression. A troubling pattern was identified in these adolescents. As levels of stress related to parental withdrawal and parental intrusiveness increased, adolescents reported using less secondary control coping and experiencing higher levels of stress reactivity (Jaser et al., 2005; Langrock et al., 2002). This finding is consistent with the notion that stress contributes to dysregulation (heightened stress reactivity) and interferes with controlled self-regulation and coping, both of which lead to increased risk for depressive symptoms (Compas, 2006). Second, we have examined coping and stress responses among adolescents whose mothers had a history of depression and compared them with a demographically matched sample of adolescents whose mothers had no history of depression (Jaser et al., 2008). As expected, the former group were higher in depressive symptoms and externalizing problems than adolescents whose mothers did not have a history of depression. Furthermore, the former group reported higher levels of stress reactivity (e.g., emotional and physiological arousal, intrusive thoughts) than the comparison group. Mothers’ reports of their current depressive symptoms and observations of maternal sadness during parent–child interactions in the laboratory were each related to higher levels of adolescents’ depressive symptoms and externalizing problems, higher stress reactivity, and lower levels of secondary control coping. Finally, adolescents’ use of secondary control coping and stress reactivity accounted for the relation between maternal history of depression and adolescents’ depressive symptoms. These findings replicate those found by Jaser et al. (2005) and Langrock et al. (2002) and extend them by using direct observations to assess parental depressive symptoms and parent-adolescent interactions.

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Third, we have examined stress and coping among adolescent offspring of mothers and fathers with a history of depression (Bettis et al., 2016; Dunbar et al., 2013; Fear et al., 2009). In this sample, our focus was on adolescents’ coping with interparental conflict. Once again, we found support for secondary control coping as a predictor of lower internalizing and externalizing symptoms, after accounting for method variance in adolescent and parent reports of coping and symptoms. Furthermore, secondary control coping partially or fully accounted for the association between interparental conflict and adolescent symptoms (Fear et al., 2009). In addition, Bettis et al. (2016) found that secondary control coping is a transdiagnostic correlate of lower levels of symptoms of anxiety and depression in youth. In contrast, primary control coping was related specifically to lower youth depressive symptoms but not anxiety symptoms. Disengagement coping was not a significant correlate of symptoms of anxiety or depression in youth (Bettis et al., 2016). Researchers have also examined emotion regulation (Compas et al., 2009; see earlier) among children of depressed parents, yet no such studies have been conducted to date among adolescents. The most extensive work has been conducted by Kovacs, Forbes, Silk, and colleagues and has used direct observation methods to assess young children’s (age 3 to 7 years old) emotion regulation in response to laboratory stress tasks, and examined the relation between children’s emotion regulation and depressive symptoms (Forbes, Fox, Cohn, Galles, & Kovacs, 2006; Forbes, Shaw et al., 2006; Silk, Shaw, Forbes, Lane, & Kovacs, 2006; Silk, Shaw, Skuban, Oland, & Kovacs, 2006). Because of the importance of understanding emotion regulation and depression in young people, we review these studies here. They are noteworthy for several reasons, including inclusion of a particularly high-risk sample—children whose mothers themselves first experienced depression during childhood—and use of both direct observations and physiological measures of emotion regulation. Silk, Shaw, Forbes, et al. (2006) observed children’s responses to a delay-ofgratification task as an example of an emotionally arousing (frustration) context for children and their mothers. Children of mothers with childhood-onset depression were more likely to focus on a delay object (a response that may be similar to rumination—as a form of passive engagement with the source of stress or emotional arousal) than children of mothers without a history of depression. Furthermore, use of positive reward anticipation (displays of joy and information gathering, a component of problem solving, a form of primary control engagement coping) was related to fewer internalizing symptoms among children of mothers with childhood-onset depression and current depressive symptoms, but not for children of mothers without a history of depression (Silk, Shaw, Skuban et al., 2006). These studies suggest that processes of coping and emotion regulation may develop during childhood and carry over into adolescence.

Preventing Psychopathology Among Children of Depressed Parents Drawing on evidence for the importance of stress and coping for positive child adjustment in families of depressed parents, Compas, Forehand, Keller

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and colleagues developed and tested the initial efficacy of a family group cognitive-behavioral (FGCB) preventive intervention for parents with a history of depression and their children (Compas, Forehand, & Keller, 2011; Compas, Keller, & Forehand, 2011; Compas, Langrock, Keller, Merchant, & Copeland, 2002). The preventive intervention is designed to reduce stressful parent–child interactions that are associated with parental withdrawal and irritability/intrusiveness and enhance children’s and parents’ use of secondary control engagement coping strategies to reduce the risk for symptoms and disorder in these children. The FGCB intervention is a manualized 12-session program (eight weekly and four monthly follow-up sessions) designed to teach coping skills in a small family group format to families with a parent who has a history of a depressive disorder. Each family group includes four families and is co-led by a mental health professional with extensive training in group facilitation and a doctoral student in clinical psychology. The program is designed for participation by both parents and children. Goals are to educate families about depressive disorders, increase family awareness of the impact of stress and depression on functioning, help families recognize and monitor stress, facilitate the development of children’s adaptive coping responses to stress, and improve parenting skills. Information is presented to group members during eight weekly sessions, practice and discussion of skills are facilitated during the sessions, and all members are given weekly at-home practice exercises. Four monthly follow-up booster sessions are included to provide additional practice and support in continued development and refinement of the skills learned in the initial weekly sessions. The intervention is designed to address hypothesized mediators of the effects of parental depression on children: parental depressive symptoms and negative affect, stressful parent–child interactions, and children’s coping with these stressors. The parenting component of the intervention includes building skills to increase parental warmth and involvement with their children, plus increasing structure and consequences for children’s problem behavior. Children are taught skills to cope with their parents’ depression, including the use of acceptance, distraction, and cognitive reappraisal. The coping skills that are taught and practiced as part of the program are designed to enhance development of secondary control coping strategies (cognitive restructuring, acceptance, distraction) among participants. The research summarized above shows that these strategies are effective in coping with stressful parent–child interactions associated with parental depression. The initial efficacy of the intervention has been tested in a clinical trial in which families were randomized to the FGCB intervention or to a written information (WI) comparison condition. Significant effects on children’s (ages 9 to 15 years) mental health favoring the FGCB intervention were found at 2-, 6-, and 12-month follow-ups (Compas et al., 2009), effects that were generally maintained at 18 months, although some effects dissipated at 24 months (Compas et al., 2011, 2015). The FGCB intervention led to significantly lower levels of Youth Self-Report (YSR) internalizing symptoms at 2, 6, 12, and 18 months and significantly lower externalizing symptoms at 12, 18, and 24 months. There was also an effect for the

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intervention on a specific youth self-report measure of depressive symptoms at 12 months and mixed anxiety-depression symptoms at 2, 6, 12, and 18 months. Effects on parents’ reports of their children’s symptoms were quite limited, with the only significant effect occurring for externalizing symptoms on the Child Behavior Checklist at 12 months. Finally, the FGCB intervention had a significant effect on children’s episodes of major depression as measured with diagnostic interviews with the parents and children. Over the 24 months from baseline, fewer children in the FGCB intervention experienced a major depressive episode (14.3%) than children in the WI comparison condition (32.7%). Mediational analyses examined whether changes in children’s coping and changes in parenting behaviors accounted for the effects of the FGCB on children’s mental health outcomes. Significant effects were found for changes in children’s coping as a mediator of the intervention, as changes in secondary control coping from baseline to 6 months mediated intervention effects on changes in children’s depression, mixed anxiety-depression, internalizing, and externalizing symptoms from baseline to 12-month follow-up. We also tested for possible effects of the intervention on children’s primary control coping, but there were no significant findings. The intervention was specific in its effects on secondary control coping, and strong evidence was found for secondary control coping as a protective factor for both internalizing and externalizing symptoms. These findings support the role of children’s coping and impaired parenting skills in parents suffering from depression as possible causal factors as outlined by Kraemer et al. (2001, 2002).

CONCLUSIONS Exposure to stress and adversity, and the ways that individuals cope with stress, are venerable and well-tested constructs that are central to understanding sources of vulnerability, risk, and resilience to psychopathology in children and adolescents. Stressful life events and chronic adversity, most notably poverty and chronic abuse during development, are powerful, nonspecific predictors of internalizing and externalizing symptoms and disorders. Among some individuals, vulnerability and risk are buffered by resilient qualities, including effective ways of coping with stress. Recent research supports a control-based model of coping among children and adolescents, with protective effects associated with use of primary and secondary control coping methods. The foundation of research on stress and coping is now being extended by research on new iterations on these themes, including the importance of processes of allostatic load, long-term effects of exposure to adversity early in development, and elucidation of specific emotion regulation processes as part of overall efforts to cope with stress. Advances in research on children and adolescents at high risk for depression provide salient examples of risk and resilience processes in this population. Perhaps most importantly, recent evidence suggests that these processes can inform the development of promising interventions to prevent depression in children at high risk. The field is now poised

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to extend research on stress, coping, and emotion regulation to other types of symptoms and disorders to inform the development of preventive interventions and treatments.

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CHAPTER 5

Child Maltreatment and Risk for Psychopathology SARA R. JAFFEE

EPIDEMIOLOGY OF ABUSE AND NEGLECT

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n 2013, the most recent year for which figures are available, approximately 3.9 million children in the United States were investigated as possible victims of abuse or neglect. Twenty percent of these investigations were substantiated (or indicated), representing 679,000 children nationally, or 9.1 per 1,000 children in the population (U.S. Department of Health and Human Services, Administration for Children and Families, Administration on Children, Youth, and Families, & Children’s Bureau, 2015). Of these children 1,520 died as a result of abuse or neglect. These figures represent a decline in maltreatment rates since the 1990s, although the extent of the decline may be more pronounced in official records as opposed to national surveys of youth or caregivers (Gilbert et al., 2012). As reviewed by Finkelhor and Jones (2006), the decline parallels a downward trend in crime rates overall and may reflect reductions in numbers of unwanted children, growing economic prosperity (with the exception of the Great Recession; Brooks-Gunn, Schneider, & Waldfogel, 2013), and increases in numbers of social workers, child protection workers, and child abuse prevention workers. Of those children who were substantiated victims of abuse or neglect, 79% were victims of neglect and 18% were victims of physical abuse. Neglect is defined as the failure to meet children’s basic physical needs with respect to clothing, hygiene, food, and safety, whereas physical abuse is defined as harm by a caregiver or someone who has responsibility for the child resulting in nonaccidental physical

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injury (from minor bruises to severe fractures or death) (Leeb, Paulozzi, Melanson, Simon, & Arias, 2008). Nine percent of children were victims of sexual abuse and 8.7% were victims of psychological maltreatment, the core feature of which is a pattern of behavior that impairs a child’s emotional development or sense of self-worth (Leeb et al., 2008). Finally, 10% were victims of “other” forms of abuse, which include, for example, “threatened abuse” or a parent’s drug or alcohol abuse (U.S. Department of Health & Human Services et al., 2015). These percentages add up to more than 100%, because of the presence of multiple forms of maltreatment in some youth. According to 2013 statistics, children under the age of 3 years were victimized at higher rates than older children, and children under the age of 1 year were victimized at the highest rates of all (23.1 per 1000 children) (U.S. Department of Health & Human Services et al., 2015). Boys and girls were equally likely to be victims of abuse or neglect, but 14.6 per 1,000 African-American children were victimized, compared with 8.1 per 1,000 White, and 8.5 per 1,000 Hispanic children (U.S. Department of Health & Human Services et al., 2015). Other sociodemographic predictors of maltreatment include family poverty, young motherhood (Mersky, Berger, Reynolds, & Gromoske, 2009; Sedlak & Broadhurst, 1996; Thornberry et al., 2014), parental history of antisocial behavior (Jaffee, Caspi, Moffitt, & Taylor, 2004; Thornberry et al., 2014), and a perpetrator’s history of maltreatment (Conger, Schofield, Neppl, & Merrick, 2013; Herrenkohl, Klika, Brown, Herrenkohl, & Leeb, 2013; Jaffee et al., 2013; Thornberry et al., 2013; Widom, Czaja, & DuMont, 2015). In a follow-up of participants from the Rochester Youth Development Study, there were pronounced effects of cumulative risk: Only 3% of those who were not at risk in any of 10 developmental domains were involved in perpetrating later maltreatment as adults, whereas 45% of those who were at risk in at least nine developmental domains were involved in perpetrating later maltreatment (Thornberry et al., 2014).

MALTREATMENT AND CHILDREN’S RISK FOR PSYCHOPATHOLOGY This section describes studies that have tested whether maltreated children are at elevated risk for psychopathology. The review is focused on the most methodologically rigorous studies, which include the following features: (a) a prospective research design wherein maltreatment predated the onset of psychopathology, (b) a demographically matched control sample or statistical adjustments for variables that could confound the association between maltreatment and risk for psychopathology, and (c) psychometrically valid measures of psychopathology, including (but not limited to) diagnostic measures. In the majority of these studies, information about maltreatment came from Child Protective Services records, although in some studies maltreatment was reported by caregivers. Because

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official records are likely to underestimate the true prevalence of maltreatment, studies that combine official records with informant reports are likely to provide the most valid information (Cohen, Brown, & Smailes, 2001; Widom et al., 2015).

Maltreatment and Risk for Externalizing Psychopathology Victims of maltreatment are at elevated risk for a range of externalizing problems in childhood and adolescence, including attention deficit/hyperactivity disorder (ADHD), conduct disorder (CD), oppositional defiant disorder (ODD; Cohen et al., 2001; Famularo, Kinscherff, & Fenton, 1992), delinquency (Lansford et al., 2007; Stouthamer-Loeber, Loeber, Homish, & Wei, 2001; Widom, 1989; Williams, Van Dorn, Bright, Jonson-Reid, & Nebbitt, 2010), and antisocial behavior (Jaffee et al., 2004; Jonson-Reid et al., 2010; Lansford et al., 2002; Manly, Kim, Rogosch, & Cicchetti, 2001; Moylan et al., 2010). Some studies also identify elevated symptoms of substance use in maltreated versus nonmaltreated youth (Kaufman et al., 2007; Lansford, Dodge, Pettit, & Bates, 2010; Rogosch, Oshri, & Cicchetti, 2010), but others have not observed this pattern (e.g., Cohen et al., 2001). Risk for externalizing problems extends into adulthood, when victims have significantly elevated rates of antisocial personality disorder (ASPD; Johnson, Cohen, Brown, Smailes, & Bernstein, 1999; Luntz & Widom, 1994), self-reported crime (Thornberry, Henry, Ireland, & Smith, 2010), and criminal arrests (Maxfield & Widom, 1996). Findings with respect to drug and alcohol use are mixed, with some studies identifying elevated rates of drug and alcohol use among young adults with a history of maltreatment versus those without such a history (Cohen et al., 2001; Noll, Trickett, Harris, & Putnam, 2009; Scott, Smith, & Ellis, 2010; Thornberry et al., 2010), and others finding that the relation between these problems and child maltreatment is stronger in women than men—or is detectable in middle age, but not in young adulthood (Widom, Ireland, & Glynn, 1995; Widom, Marmorstein, & Raskin White, 2006).

Maltreatment and Risk for Internalizing Psychopathology Victims of maltreatment are at risk for a range of internalizing problems in childhood as well, including major depressive disorder (Brown, Cohen, Johnson, & Smailes, 1999), anxiety disorders (Cohen et al., 2001), post-traumatic stress disorder (PTSD) and symptoms of trauma (Crusto et al., 2010; Famularo et al., 1992; Milot, Ethier, St-Laurent, & Provost, 2010; Putnam, Helmers, & Horowitz, 1995), and internalizing symptoms (Bolger & Patterson, 2001; Lansford et al., 2002; Manly et al., 2001; Moylan et al., 2010). Risk for internalizing disorders associated with child maltreatment extends into adulthood. Victims have significantly elevated rates of major depressive disorder (Brown et al., 1999; Noll et al., 2009; Scott et al., 2010; Widom, DuMont, & Czaja, 2007), depressive symptoms (Thornberry et al., 2010),

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and anxiety disorders (Cohen et al., 2001; Scott et al., 2010) and PTSD (Scott et al., 2010; Widom, 1999) compared to adults without a history of child maltreatment.

Maltreatment and Risk for Personality Disorders, Psychotic Symptoms, and Suicide In adulthood, victims of child maltreatment are also at risk for borderline personality disorder (Johnson et al., 1999; Widom, Czaja, & Paris, 2009), with one study also showing risk for Cluster B (dramatic, emotional, erratic) and C (anxious, fearful) personality disorders more broadly (Johnson et al., 1999). Indeed, borderline personality symptoms linked to maltreatment are already evident in childhood (Hecht, Cicchetti, Rogosch, & Crick, 2014). Moreover, at least one study demonstrates that child victims of maltreatment experience elevated rates of psychotic symptoms in early adolescence compared with nonmaltreated youth (Arseneault et al., 2011). In addition, victims of child maltreatment are at elevated risk for suicide in adolescence and adulthood (Brown et al., 1999; Thornberry et al., 2010), and engage in elevated rates of self-injury (Yates, Carlson, & Egeland, 2008).

IS THE ASSOCIATION BETWEEN MALTREATMENT AND PSYCHOPATHOLOGY CAUSAL? According to conventional wisdom, maltreatment is a cause of psychopathology. However, alternative explanations are possible. One such possibility is that maltreatment correlates with heritable vulnerabilities to psychopathology, which parents transmit to their children (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). A second possibility is evocative effects in which parents become abusive in response to their child’s difficult behavior or other characteristics that are difficult to manage (Belsky, 1993). Because children cannot ethically be randomly assigned to abusive or neglectful families, quasi-experimental, statistical matching, or randomized control trial data are required in attempts to rule out these alternative explanations. Using propensity score matching methods,1 Thornberry et al. (2010) showed that maltreated youth experience significantly more depressive symptoms and suicidal thoughts, substance use problems, and criminal behaviors in young adulthood compared with nonmaltreated youth who were matched on preexisting individual and family characteristics. Using data from a prospective study of twins, Jaffee et al. (2004) provided four pieces of evidence consistent with the hypothesis that maltreatment is a cause of children’s antisocial behavior: (1) abuse was associated with changes over time in children’s antisocial behavior; (2) a dose-response 1. The propensity score method is an econometric technique developed by Rosenbaum and Rubin (1983) to draw causal inferences from observational data. The method is premised on identifying some “treatment” (e.g., being maltreated or not maltreated). It then matches the treated and the untreated on a variety of background and individual characteristics, thus achieving statistically what randomization to treatment and control conditions would achieve by design.

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relation existed between the severity of the abuse and the severity of children’s antisocial behavior; (3) genetic factors accounted for a small, statistically nonsignificant portion of variation (7%) in children’s experience of abuse, suggesting that genetically mediated child behavior problems did not provoke abusive discipline; and (4) abuse remained a significant predictor of children’s antisocial behavior when parental antisocial behavior was covaried. These data are consistent with the hypothesis that characteristics of parents and families, but not children, explain why some children were more likely than others to be abused. Although quasi-experimental designs allow for stronger causal inference about relations between maltreatment and child psychopathology, many such designs are ill-suited for the study of child maltreatment. In adoption designs, for example, investigators can eliminate the possibility that maltreatment is a marker for genetic risk for psychopathology parents transmit to children because parents and children are not related biologically. With good reason, however, adoptive families are screened for being at low risk of maltreatment, so rates of maltreatment in studies of adoptees are low. The co-twin control design in which researchers test whether twins who are discordant for the experience of maltreatment are similarly discordant for psychopathology is another design that allows for strong causal inference, because twins growing up in the same family are exposed to many of the same risk factors for psychopathology (e.g., family poverty, a parent’s mental illness), and they are genetically similar (virtually identical, in the case of monozygotic twins; see Chapter 3 [Beauchaine et al.]). It is rare, however, for one twin but not the other to have been maltreated (Jaffee et al., 2004) and extremely large, high-risk samples are required to identify discordant cases. Research designs that match maltreated children with sociodemographically similar, nonmaltreated youth may be the most feasible way of estimating unique effects of maltreatment on risk for psychopathology. Whenever prospective, longitudinal data are available, such designs can be used in attempts to adjust for child characteristics that pre-date maltreatment, in order to rule out child evocative effects. Although this design has indeed identified effects of maltreatment on risk for psychopathology, it also demonstrates that socioeconomic disadvantage itself is associated with high rates of emotional and behavioral health problems, poor life course outcomes, and risk for maltreatment perpetration (Nikulina, Widom, & Czaja, 2011; Widom et al., 2015).

ETIOLOGICAL FORMULATIONS Researchers have proposed multiple mechanisms through which maltreatment might increase risk for psychopathology, from epigenetic processes and gene expression, to neuroendocrine, immune, and neurotransmitter systems, to brain structure and function, as well as to social cognition. Although it is likely that alterations at one level of the organism have downstream effects, empirical demonstrations of these pathways among humans are rare. In addition, although

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there is growing evidence that maltreated and nonmaltreated individuals differ physiologically and cognitively, the assumption that such differences increase vulnerability to psychopathology among maltreated children or adults with histories of maltreatment is not always tested. Thus, studies on mechanisms of maltreatment are reviewed by level of analysis, with an emphasis on those that cross levels of analysis and test mediational models.

Epigenetic Modifications and Alterations in Gene Expression Epigenetics refers to chemical changes in DNA (not technically nucleotide structure but in associated “hardware”) that alter functional activity, including, among other processes, chromatin remodeling, histone modification, microRNA activity, and methylation, the last of which has been the focus of much research in rats and humans (Szyf & Bick, 2013). In human and animal studies, early caregiving conditions are associated with glucocorticoid receptor (GR) methylation and gene expression profiles in hippocampal tissue, where the GR is expressed highly in rodents and humans (Wang et al., 2013). For example, GR 17 expression is reduced in offspring of rat dams that engaged in low as compared to high levels of licking and grooming, and offspring of low licking and grooming dams show increased methylation of GR 17 relative to offspring of high licking and grooming dams (Weaver et al., 2004). A similar pattern of findings has been observed in GR1F , the human GR17 homologue. In studies of postmortem hippocampal tissue, suicide completers with childhood histories of abuse show reduced expression and increased methylation of GR1F relative to controls and suicide completers without histories of abuse (McGowan et al., 2009). Maltreatment is also associated with increased methylation among children in exons 1D (Tyrka et al., 2015) and 1F (Romens, McDonald, Svaren, & Pollak, 2015; Tyrka et al., 2015) of the glucocorticoid receptor gene NR3C1 in peripheral tissue. Reduced expression of other GR splice variants including GR1B , GR1C , and GR1H is observed among suicide completers with childhood histories of abuse relative to nonabused suicide completers and controls, although a history of abuse is associated with decreases in methylation across GR1H (Labonte, Yerko, et al., 2012). Abuse-related methylation differences are also observed across the genome (Labonte, Suderman et al., 2012). In the first epigenome-wide study of maltreated youth, methylation differences between maltreated and control youth were identified in 2,868 genes, even taking into account multiple testing and sociodemographic characteristics (Yang et al., 2013). The majority of these genes were in intragenic regions and are involved in adversity-related diseases, including cancer (Yang et al., 2013). It is possible that maltreatment-induced epigenetic changes are allele-specific, which could explain why individuals who carry a particular genotype are at elevated risk for psychopathology when they are exposed to maltreatment. For example, men and women who experience childhood sexual and physical abuse

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have significantly lower levels of methylation at CpG sites in intron 7 of FKBP5 rs1360780 compared with men and women who are not exposed to childhood trauma, but only if they carry the risk (A) allele. Among individuals who are homozygous for the protective (G) allele, early trauma is unrelated to methylation levels (Klengel et al., 2013). Demethylation is associated with increased transcription of FKBP5 in response to a synthetic glucocorticoid and to amplification of the ultrashort feedback loop through which FKBP5 transcription results in decreased glucocorticoid receptor activity (Klengel et al., 2013). Evidence of allele-specific glucocorticoid receptor insensitivity among abuse-exposed individuals is provided by the finding that risk allele carriers show weaker correlations between gene expression levels in glucocorticoid responsive genes and plasma cortisol levels compared with protective allele carriers. Moreover, genes that show the greatest FKBP5-dependent effects on GR sensitivity include transcripts in several immune system pathways, potentially explaining observed associations in the literature between exposure to trauma, low-grade inflammation, and dysregulated immune function (Klengel et al., 2013).

Alterations in HPA Axis Function The HPA axis is activated in response to physical and psychosocial stressors such as maltreatment, resulting in release of corticotropin releasing factor (CRF) and vasopressin from the paraventricular nucleus of the hypothalamus. CRF stimulates release of adrenocorticotropic hormone (ACTH) from the anterior pituitary, which in turn stimulates release of cortisol from the adrenal gland. Cortisol terminates the stress response through feedback at the level of the hypothalamus and the pituitary (Gunnar & Vazquez, 2006). The literature on how the HPA axis is shaped by exposure to early life stress is complex, with disparate findings depending on the level of the HPA axis under examination, whether the HPA axis is being stimulated in response to psychosocial or pharmacological challenge (i.e., synthetic glucocorticoids), and whether participants are currently depressed or experiencing symptoms of PTSD. In addition, relatively few studies have tested whether adversity-related alterations in HPA axis function account for observed associations between maltreatment and psychopathology. Nevertheless, there is growing consensus that abuse and neglect are associated with a blunted cortisol response to psychosocial stressors such as the Trier Social Stress Test (TSST) among children and adolescents (MacMillan et al., 2009; Trickett, Gordis, Peckins, & Susman, 2014), although this pattern is not always observed (Linares, Shrout, Nucci-Sack, & Diaz, 2013). Such a pattern of blunted reactivity is pronounced among maltreated youth who carry at least one copy of the G allele of the corticotropic releasing hormone receptor 1 (CRHR1) variant rs110402 (Sumner, McLaughlin, Walsh, Sheridan, & Koenen, 2014). At least two different designs provide evidence that the effect of exposure to abuse and neglect on HPA axis function is likely to be causal. In the Bucharest Early

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Intervention Project, youth who were randomized to remain in institutional care—where they experienced neglect from caregivers—showed significantly less cortisol reactivity to a psychosocial stressor (the Trier Social Stress Test; TSST) than youth who were randomized to foster care or who were raised by biological parents (McLaughlin, Sheridan et al., 2015). A second study compared 12-year-old monozygotic twins who were discordant for the experience of being bullied or maltreated (Ouellet-Morin et al., 2011). This design controls automatically for genetic differences within the pair that could explain differences in cortisol reactivity, as well as experiences shared by twins who grow in the same family that could confound observed associations between violence victimization and cortisol reactivity. Controlling for nonshared characteristics (e.g., birth weight, IQ, early childhood problem behaviors), youth who were exposed to bullying or maltreatment showed a blunted cortisol response to the TSST compared with their nonbullied or nonmaltreated twin (Ouellet-Morin et al., 2011). Moreover, among youth who were bullied or maltreated, lower levels of cortisol reactivity were associated with higher levels of social and behavioral problems (Ouellet-Morin et al., 2011). In addition to studies of cortisol reactivity, investigators have also focused on whether maltreatment is associated with diurnal variation in cortisol. Cortisol levels typically peak approximately 30 minutes after waking and then decline over the course of the day, reaching their lowest levels around bedtime (Gunnar & Vazquez, 2006). Chronic and uncontrollable stressors tend to be associated with a flat pattern of cortisol production across the day, with relatively low morning levels and relatively high evening levels, a pattern that sometimes leads to higher levels of total cortisol output across the day (Miller, Chen, & Zhou, 2007). This pattern can lead to atrophy and, potentially, loss of hippocampal neurons and to metabolic and inflammatory disease (McEwen, 1998). However, the nature of HPA axis dysregulation depends on several factors, including the timing and severity of maltreatment and the co-occurrence of maltreatment with children’s internalizing problems. For example, youth who experience physical or sexual abuse in early childhood (but not youth who experience abuse in later childhood) show attenuated declines in cortisol from morning to afternoon, although this profile may be specific to youth who also have high levels of internalizing problems (Cicchetti, Rogosch, Gunnar, & Toth, 2010). Other studies demonstrate that effects of maltreatment on diurnal variation vary as a function of the type or severity of abuse. For example, severe neglect is associated with lower morning cortisol levels and a flatter cortisol slope across the day (Bruce, Fisher, Pears, & Levine, 2009; Carlson & Earls, 1997; van der Vegt, van der Ende, Kirschbaum, Verhulst, & Tiemeier, 2009; but see Gunnar, Morison, Chisholm, & Schuder, 2001; Kertes, Gunnar, Madsen, & Long, 2008), whereas moderately severe maltreatment and severe emotional abuse (compared with no abuse) are associated with higher cortisol levels and a steeper cortisol slope (Bruce et al., 2009; van der Vegt et al., 2009). In a study of 5- to 13-year-olds, maltreatment status was associated with (a) greater variability in cortisol levels at the start of the study (measured daily around 4 p.m.) and (b) change over time in cortisol levels

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measured over 20 weeks (Doom, Cicchetti, & Rogosch, 2014). Although maltreated children had more internalizing and externalizing problems than nonmaltreated children, individual differences in cortisol variability did not account for this association (Doom et al., 2014). Investigations of children in foster care show that they typically have lower morning cortisol levels and a flatter cortisol slope than controls (Dozier et al., 2006; Fisher, Stoolmiller, Gunnar, & Burraston, 2007), although interventions to promote sensitive caregiving in a foster care context may normalize diurnal variation in cortisol (Dozier et al., 2006; Fisher et al., 2007; Fisher, Van Ryzin, & Gunnar, 2011). Interestingly, dysregulation of diurnal variation in cortisol is more pronounced among young children who continue to live with their birth parents after investigation by Child Protective Services than in children who are placed in foster care (Bernard, Butzin-Dozier, Rittenhouse, & Dozier, 2010).

Alterations in Immune System Activity Developmental psychopathologists have identified strong associations between early experiences of adversity such as abuse or neglect and both physical and mental health problems later in life, some of which are hypothesized to result from proinflammatory responses (Miller, Chen, & Parker, 2011). Although adversity is most often conceptualized as low childhood socioeconomic position, at least a few studies show that exposure to maltreatment is associated with immune biomarkers such as C reactive protein in adulthood (Danese, Pariante, Caspi, Taylor, & Poulton, 2007) and in 12-year-olds who were physically maltreated and currently depressed, but not in physically maltreated, nondepressed children (Danese et al., 2011). In another study, severe adverse life events at 7 and 8 years of age (e.g., abuse, taken into foster care, separation from mother or father) and cumulative adversity from birth to middle childhood were associated with elevated IL-6 and CRP levels at 10 and 15 years (Slopen, Kubzansky, McLaughlin, & Koenen, 2013). A third study identified an interaction between maltreatment timing and CRH genotype on CRP levels. In a study of 489 children, ages 8 to 12 years, those who carried at least one copy of the A allele of rs1417938 demonstrated significantly higher CRP levels than those who were homozygous for the T allele, but only if they had a recent onset of maltreatment. Among nonmaltreated youth and among those who were maltreated in early childhood (regardless of whether maltreatment persisted), genetic differences in CRP levels were nonsignificant (Cicchetti, Handley, & Rogosch, 2015). In addition, among youth who were maltreated recently, higher levels of CRP were associated with higher levels of internalizing symptoms (Cicchetti et al., 2015). According to inflammation models of mental and physical health problems, dysregulation of immune function is a causal risk factor for depression (Miller, Maletic, & Raison, 2009). Proinflammatory biomarker levels are correlated significantly with depression symptoms in clinical and community samples of adults (Howren, Lamkin, & Suls, 2009), although findings from a small number of

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prospective, longitudinal studies are mixed as to the direction of this association (Copeland, Shanahan, Worthman, Angold, & Costello, 2012). Of the four prospective, longitudinal studies involving children and adolescents, all demonstrate that depressive episodes or symptoms predict later inflammatory biomarkers such as CRP (Copeland et al., 2012; Miller & Cole, 2012; Slopen, Kubzansky, & Koenen, 2013) and IL-6 levels (Miller & Cole, 2012), although one identified an association between depression and subsequent natural killer cell function among older girls only (Caserta, Wyman, Wang, Moynihan, & O’Connor, 2011). Only one of the four also showed that inflammation prospectively predicts the emergence of depression (Miller & Cole, 2012). There, as in other studies (Danese et al., 2011), clustering of depression and inflammation was most pronounced for youth who experienced multiple adversities (Miller & Cole, 2012). Data are consistent with the possibility that effects of adversity on inflammatory markers are mediated by symptoms of depression. However, the only study to test this hypothesis did not detect significant indirect effects of childhood adversity on CRP or IL-6 levels in late childhood or adolescence via symptoms of depression (Slopen, Kubzansky, McLaughlin, & Koenen, 2013).

Alterations in Brain Structure and Function Recent reviews describe research on associations between maltreatment and brain structure and function among both children and adults (Lim, Radua, & Rubia, 2014). Here I focus on studies of children and on studies showing that maltreatment-related alterations in brain structure and function are associated with child problem behaviors. Maltreatment Is Associated With Alterations in Brain Structure. Abuse and neglect are hypothesized to affect regions of the brain that are involved in emotion processing and regulation, including the amygdala, hippocampus, and prefrontal cortex (for a recent review, see Beauchaine, 2015). Although the evidence base is relatively small, research consistently shows that children who have been maltreated have smaller-than-average prefrontal cortical volumes (Lupien, McEwen, Gunnar, & Heim, 2009). At least one study demonstrates that smaller prefrontal cortex volumes in physically abused versus nonabused youth (specifically in the right orbitofrontal cortex) are associated with difficulties in social functioning within the family and in school (Hanson et al., 2010) There is less consistent evidence that maltreatment is associated with amygdala or hippocampal volumes. A meta-analysis of studies of children with maltreatment-related PTSD found no associations between maltreatment and hippocampal volumes (Woon & Hedges, 2008). A more recent meta-analysis also showed that maltreatment was not associated with hippocampal volume in children, but a childhood history of maltreatment was associated with reduced

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hippocampal volumes among adults (Riem, Alink, Out, Van Ijzendoorn, & Bakermans-Kranenburg, 2015). Evidence with respect to maltreatment-related variation in amygdala volumes is similarly mixed, with some studies showing no association (De Brito et al., 2013) and others showing that institutionalization in early childhood is associated with greater amygdala volumes (Mehta et al., 2009; Tottenham et al., 2010). Such inconsistencies might be accounted for by the wide age range of children included across these studies and by cross-study variation in amygdala quantification (Hanson et al., 2015). A recent study that involved careful hand tracing of amygdala and hippocampus brain regions showed that (a) children (ages 9 to 15 years) who were exposed to various forms of early life stress, including early neglect (in the form of institutionalization), physical abuse, and low socioeconomic status had significantly smaller left amygdala volumes and (b) physically abused and low SES children had significantly smaller right hippocampal volumes compared with middle-class control children, with more extensive lifetime exposure to stressors inversely correlated with the size of these regions (Hanson et al., 2015). Mediational analyses suggested that children who were exposed to these various forms of early life stress had elevated rates of behavioral problems, partly because of their smaller hippocampal (but not amygdala) volumes (Hanson et al., 2015). Beyond volumetric differences, maltreated and nonmaltreated adolescents also differ with respect to cortical thickness in right hemispheric prefrontal regions, surface area in the medial temporal area and the left lingual gyrus, and local gyrification in two left hemisphere clusters (Kelly et al., 2013). In another study, effects of early institutional deprivation on increased symptoms of ADHD were accounted for by the fact that institution-reared youth showed reduced cortical thickness in orbitofrontal cortex, insula, supramarginal gyrus, precuneus, superior temporal gyrus, inferior parietal cortex, superior temporal cortex, fusiform gyrus, and lingual gyrus (McLaughlin et al., 2014). Maltreatment Is Associated With Alterations in Brain Function. Maltreatment-related differences in brain function have also been observed. Children who are exposed to family violence (including maltreatment) show greater right amygdala activation in response to angry (but not sad) versus neutral faces compared with nonexposed children (McCrory et al., 2011). Such differences are observed even when emotion expressions are presented subliminally (McCrory et al., 2013). Another study showed that postinstitutionalized youth showed greater amygdala reactivity than control youth to fearful versus neutral faces (Tottenham et al., 2011). Consistent with the findings related to anger stimuli, event related potential studies indicate that children with a history of physical abuse are more attentive to angry cues (vs. other negatively valenced cues) and have more difficulty disengaging from angry versus happy cues (Cicchetti & Curtis, 2005; Curtis & Cicchetti, 2011;

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Pollak, Klorman, Thatcher, & Cicchetti, 2001; Pollak & Tolley-Schell, 2003; Shackman, Shackman, & Pollak, 2007). Such hyperattention to threat mediates associations between a history of maltreatment and current symptoms of anxiety (Shackman et al., 2007). Although maltreated youth are more reactive to negative stimuli than nonmaltreated youth, such responses can be modulated. For example, although adolescents who self-report physical or sexual abuse show greater left and right amygdala activation in response to negative versus neutral images compared with control youth, they also show greater activation of prefrontal cortex during trials in which they are instructed to decrease their emotional response to negative stimuli, thus erasing maltreatment-related differences in amygdala activation on those trials (McLaughlin, Peverill, Gold, Alves, & Sheridan, 2015). The role of amygdala and cognitive control regions (e.g., anterior cingulate cortex and dorsolateral prefrontal cortex) in detection and regulation of emotional conflict has been further explored in tasks in which presentation of emotional expressions are superimposed with emotion terms that are either congruent (e.g., the word “happy” appears over a happy face) or incongruent (e.g., the word “happy” appears over a fearful face). When asked to identify the emotion expression of the face, individuals tend to be slower and less accurate during incongruent versus congruent trials. In a study of 51 children and adolescents (ages 9 to 16 years), youth who were exposed to various forms of trauma (abuse, neglect, domestic violence, repeated separations from parents) were not only slower and less accurate during incongruent versus congruent trials than nonexposed youth, but they also showed greater right and left amygdala activation (Marusak, Martin, Etkin, & Thomason, 2015). In addition, although repeated exposure to incongruent trials resulted in improvements in reaction time and accuracy for non–trauma-exposed participants, such adaptive gains were not observed for trauma-exposed participants, with the failure to improve accuracy correlated with heightened dorsolateral prefrontal cortex activity and reduced coupling of amygdala and anterior cingulate cortex (Marusak et al., 2015). Finally, heightened amygdala activation during incongruent (vs. congruent) trials mediated the association between trauma exposure and lower reward sensitivity (Marusak et al., 2015). During a social rejection paradigm (cyberball), adolescents who were separated permanently in early childhood from their biological parents (often as a result of physical or emotional neglect) and subsequently adopted showed reduced activation in dorsal anterior cingulate cortex (dACC), dorsolateral prefrontal cortex (dlPFC), and anterior insula; heightened activation in left middle temporal gyrus; and reduced connectivity between dACC and dlPFC (Puetz et al., 2014). Youth who experienced early separation reported feeling more excluded during the cyberball game than youth who did not experience early separation, an association partly mediated by dlPFC activation (Puetz et al., 2014).

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Maltreatment-related alterations in neural function have parallels in rodent models, which hold constant genetic and pre- and postnatal environmental conditions that may be confounded with maltreatment among humans (see, e.g., Mead, Beauchaine, & Shannon, 2010). For example, after some of the bedding from a mouse’s cage is removed, mouse dams engage in inconsistent caregiving, which may be homologous to some conditions experienced in orphanage rearing (Cohen et al., 2013). To further simulate the experience of human adoption from an institutional setting to a more enriched environment, removal of bedding was restricted to the preweaning period of postnatal days 2 through 21, after which normal cage conditions were restored. In paradigms in which (a) mice and (b) human children had to inhibit a fear response in favor of goal-directed behavior, both stress-exposed mice and humans were slower to approach the goal than their nonstressed counterparts, where the goal for mice was getting a drink of sweetened milk in a novel and well-lit cage and the goal for human adolescents was detecting a neutral stimuli that was embedded among rare threat nontarget cues. In addition, stress-exposed mice and humans showed greater neural activity in the amygdala (greater c-Fos expression in the basolateral amygdala for mice and higher levels of blood oxygen level-dependent activity in humans; Cohen et al., 2013). Maltreatment Is Associated With Developmental Alterations in Brain Connectivity. Institutionalization in early life has also been associated with accelerated development of connections between the amygdala and medial prefrontal cortex (mPFC). In typically developing children, negative functional connectivity between the amygdala and the mPFC—a prerequisite of effective top-down modulation of anxiety (see Beauchaine, 2015)—is not fully mature until adolescence. In contrast, postinstitutionalized children (ages 6.5 to 10.4 years) show more negative amygdala-mPFC coupling than control children and similar levels of negative amygdala-mPFC coupling as postinstitutionalized and control adolescents (10.5 to 17.6 years; Gee et al., 2013). Parallel findings related to accelerated development are observed in rodent models involving maternal separation (Caldji et al., 1998). Moreover, although postinstitutionalized children exhibited more symptoms of anxiety than control youth, within the postinstitutionalized group, more negative amygdala-mPFC coupling was associated with fewer symptoms of anxiety (Gee et al., 2013). In contrast to accelerated development of amygdala-mPFC coupling, postinstitutionalized adolescents show delayed maturation of the ventral striatum, for which reactivity of the nucleus accumbens to incentives and other pleasurable stimuli typically peaks in adolescence. In contrast to this typical trajectory, postinstitutionalized adolescents show reduced reactivity of the nucleus accumbens in response to happy (vs. neutral) faces than controls (Goff et al., 2013). The postinstitutionalized adolescents also had more symptoms of depression than controls (Goff et al., 2013).

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Importantly, among both children and adults, unipolar depression is associated with reduced nucleus accumbens activity to pleasurable stimuli (e.g., Forbes & Dahl, 2012; Pizzagalli et al., 2009). Consistent with such findings, low levels of nucleus accumbens reactivity were correlated with depressive symptoms in the sample overall, even though nucleus accumbens activity did not mediate the association between early life stress and depressive symptoms (Goff et al., 2013). An adequately powered sample would be needed to determine whether this was a false negative finding (Goff et al., 2013). Importantly, blunted activity to incentives in the striatum, particularly the nucleus accumbens, is associated with symptoms of anhedonia in both externalizing disorders and depression (see Zisner & Beauchaine, in press). Thus, findings of reduced striatal responding to incentives among maltreated children and adolescents may reflect a mechanism of heterotypic comorbidity, which characterizes this population. Analysis of resting state functional connectivity shows that among 18-yearolds, higher scores on a retrospective measure of child maltreatment (Childhood Trauma Questionnaire; CTQ) are associated with lower connectivity (a) between the right amygdala and ventromedial (vm)-PFC, an effect that is more pronounced in females than males, and (b) between the left amygdala and vmPFC (Herringa et al., 2013). Reduced resting state functional connectivity mediated effects of CTQ scores on internalizing symptoms (Herringa et al., 2013). Maltreatment Is Associated With Cognitive, Behavioral, and Socioemotional Processes. Maltreated youth are characterized by a range of cognitive, behavioral, and socioemotional problems that account for their increased risk for externalizing and internalizing problems. These include social-cognitive biases, problems in emotion recognition, understanding, and regulation, and problems in the conceptualization of the self. Externalizing Problems. As described above, physically abused youth selectively attend to angry stimuli compared with nonabused youth. Consistent with these findings, physically abused youth have a tendency to attribute hostile intent to others’ behavior and to respond accordingly (Dodge, Bates, & Pettit, 1990), which can make such youth likely to exhibit chronic aggression. In addition, maltreated youth have difficulty regulating their own emotions (as captured by appropriate displays of emotion, emotional awareness, and empathy). Such emotion dysregulation, in turn, is associated with peer rejection and increased externalizing problems over time (Kim & Cicchetti, 2006). Maltreated preschoolers also have difficulty with emotion understanding, as evidenced by inability to match positive, negative, and neutral events with positive and negative emotions (Perlman, Kalish, & Pollak, 2008). This deficit may affect their ability to predict reactions that their own negative behaviors will elicit from others. Maltreated youth also have more positive beliefs

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about violence, which leads them to antisocial peer groups and increases their risk for violent behavior in adolescence (Herrenkohl, Huang, Tajima, & Whitney, 2003). Physically abused children allocate more attention to angry faces than nonabused children, which may explain their angry affect and aggressive behavior directed toward peers in a subsequent task (Shackman & Pollak, 2014). They also allocate more attention to task-irrelevant angry auditory cues than nonabused children, which may explain their symptoms of anxiety (Shackman et al., 2007). Maltreatment may also lead to behavioral trajectories toward increasingly high-risk conduct. For example, youth who run away from home to escape abuse are likely to drop out of school and become homeless (Paradise & Cauce, 2002; Stein, Leslie, & Nyamathi, 2002). With nowhere to live and no formal education, some of these youth may resort to prostitution (Wilson & Widom, 2009) and other criminal behaviors as a means of supporting themselves (Kim, Tajima, Herrenkohl, & Huang, 2009). This constellation of problem behaviors in adolescence and young adulthood accounts for the association between child maltreatment and women’s illicit drug use in middle age (Wilson & Widom, 2009). Elevated rates of drug abuse among women with childhood histories of abuse and neglect is also explained by the fact that they are more likely than women without such histories to live in neighborhoods characterized by relatively high rates of social disorder and social disadvantage (Chauhan & Widom, 2012). Internalizing Problems. Childhood sexual abuse in particular is linked to a range of problems in self-functioning, defined in terms of self-coherence, self-continuity, self-affectivity, and self-agency (Stern, 1985). Some studies show that abused and neglected youth report elevated symptoms of dissociation compared with nonmaltreated youth (Macfie, Cicchetti, & Toth, 2001), particularly among those who feel shame and blame themselves for the abuse (Feiring, Cleland, & Simon, 2010; Feiring, Taska, & Lewis, 1996). Moreover, when combined with high levels of arousal and avoidant coping, symptoms of dissociation measured during or immediately after disclosure of sexual abuse accounted for substantial variation in symptoms of PTSD among sexually abused youth (Kaplow, Dodge, Amaya-Jackson, & Saxe, 2005). The tendency to feel shame and self-blame is also associated with internalizing and externalizing problems (Feiring & Cleland, 2007; McGee, Wolfe, & Olson, 2001) and, in the short term, low self-esteem (Feiring, Taska, & Lewis, 2002). Sexually abused and neglected children are more likely than nonabused children to develop an external locus of control, with perceived external control accounting substantially for their elevated symptoms of internalizing problems (Bolger & Patterson, 2001). Exposure to Maltreatment Is Associated With Lower Levels of Social Support. Although some studies demonstrate that a supportive adult buffers youth from effects of maltreatment on risk for psychopathology and other undesirable outcomes

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(Spaccarelli & Kim, 1995), maltreated youth tend to have smaller social networks (Negriff, James, & Trickett, 2015) and perceive lower levels of support from individuals within those networks (Lamis, Wilson, King, & Kaslow, 2014; Pepin & Banyard, 2006). Some studies show that low levels of perceived support account for observed associations between a history of abuse and risk for psychopathology (Lamis et al., 2014; Pepin & Banyard, 2006), although perceived support from adults is not consistently associated with psychopathology and other forms of psychosocial adjustment (Ezzell, Swenson, & Brondino, 2000). Efforts to understand whether social support has broadly promotive versus protective functions in the context of maltreatment would be advanced by better data on sources of support (e.g., parental vs. extraparental figures) and by more careful parsing of social support dimensions, such as network size, network quality (e.g., youth perceptions of how much network members care about them), and type of social support. In addition, recent data suggest that genetic factors influence the extent to which maltreated youth perceive support. For example, a variant of the oxytocin receptor gene (rs53576) that is associated with prosocial behavior is also associated with maltreated youths’ perceptions of social support. Those who are homozygous for the major allele (G/G) not only perceive higher levels of social support compared to youth who carry at least one copy of the A allele, but they also have similarly low levels of psychopathology compared to controls (Hostinar, Cicchetti, & Rogosch, 2014). Such findings suggest that some children may be more predisposed biologically to perceive and benefit from social support than other children.

MODERATORS OF CHILD MALTREATMENT Moderators of maltreatment can be conceptualized as factors that exacerbate effects of maltreatment on risk for psychopathology (e.g., in a diathesis-stress framework) or factors that promote competence in mental health, academic, or interpersonal domains despite exposure to maltreatment (e.g., in a resilience framework). In studies where resilience to maltreatment is stringently defined as competence that is sustained over time across more than one domain, between 12–22% of individuals who are maltreated as children are resilient (Cicchetti, Rogosch, Lynch, & Holt, 1993; Jaffee & Gallop, 2007; Kaufman, Cook, Arny, Jones, & Pittinsky, 1994; McGloin & Widom, 2001). In a 2013 review, we concluded that the effect of maltreatment on risk for psychopathology is largely similar across demographic groups (e.g., sex, race/ethnicity) (Jaffee & Maikovich-Fong, 2013). Similarly, evidence that the association between maltreatment and risk for psychopathology varies as a function of maltreatment subtype was weak and inconsistent. In contrast, chronic maltreatment is associated more strongly with risk for psychopathology than maltreatment that occurs sporadically or is confined to a single developmental

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period (Jaffee & Maikovich-Fong, 2011). With respect to age-at-onset, although maltreatment that is first experienced in childhood is associated more strongly with internalizing outcomes than maltreatment that is first experienced in adolescence, the reverse is true for externalizing problems (Kaplow & Widom, 2007; Thornberry et al., 2010). Since our 2013 review, the research base on genetic moderators of maltreatment effects has expanded exponentially, so we focus our review on this topic. A separate section is devoted to a discussion of psychosocial factors as a moderator of maltreatment.

Genetic Moderators of Maltreatment Effects Although there are dozens of reports of Genotype × Maltreatment interactions predicting psychopathology, this review is focused on the best-replicated findings. These include studies testing whether the monoamine oxidase A (MAOA) genotype moderates effects of maltreatment on risk for antisocial behavior, and studies testing whether 5HTTLPR genotype moderates effects of maltreatment on risk for depression. MAOA × Maltreatment. The first published report of an interaction between the MAOA genotype and maltreatment came from Caspi et al. (2002), who showed that men in the Dunedin Longitudinal Study birth cohort who experienced childhood maltreatment (as indicated by retrospective reports of sexual and physical abuse and prospective reports of maternal rejection, harsh parenting, and multiple caregiver changes) exhibited elevated levels of childhood conduct and adult antisocial behavior problems only if they carried the low activity variant of a 30 base-pair variable number tandem repeat polymorphism of the MAOA gene. Men who carried the high activity variant of the MAOA gene were not at elevated risk for antisocial outcomes regardless of their exposure to childhood maltreatment. This finding was supported in a 2007 meta-analysis of eight studies that tested for MAOA × Maltreatment interactions among males (Taylor & Kim-Cohen, 2007). A more recent meta-analysis of 27 studies tested whether the interaction was (a) specific to maltreatment versus adverse life events more generally and (b) specific to males versus females (Byrd & Manuck, 2014). This meta-analysis also supported the association between early life maltreatment and antisocial outcomes for males who carried the low versus the high activity variant of the MAOA gene. In the 11 female cohorts, maltreatment was more strongly associated with antisocial outcomes among carriers of the high versus the low activity variant, although this effect was not robust to sensitivity checks (Byrd & Manuck, 2014). A future direction for research is to identify why males who carry the low activity variant are at elevated risk for antisocial outcomes when they are exposed

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to maltreatment. A growing number of genetic imaging studies suggest possible mechanisms through which the low activity variant increases risk for antisocial behavior. For example, the low activity variant is associated with (a) low resting state activity in areas of the brain related to executive function and inhibitory control (Clemens et al., 2015); (b) poor self-reported anger control and activation of the dorsal anterior cingulate cortex and the amygdala in response to insult (Denson, Dobson-Stone, Ronay, von Hippel, & Schira, 2014); and (c) enhanced amygdala activity in response to negative versus neutral stimuli and reduced coupling of prefrontal cortex and amygdala, which is often interpreted as an indicator of emotion regulation (Buckholtz et al., 2008; Meyer-Lindenberg et al., 2006). Moreover, low MAOA activity in cortical and subcortical regions as measured by positron emission topography is associated with heightened levels of trait aggression (Alia-Klein et al., 2008). In addition, epigenetic studies show that hypermethylation in CpG sites in the promoter region of MAOA in incarcerated men with ASPD, compared with age- and sex-matched nonoffender controls, is associated with decreased promoter activity in functional follow-up assays and lower levels of circulating serotonin (Checknita et al., 2015). Research is needed that shows how maltreatment interacts with these processes to increase risk for antisocial behavior. 5HTTLPR × Maltreatment. The first published report of an interaction between 5HTTLPR genotype and maltreatment also came from the Dunedin Longitudinal Study, and showed that among individuals who were homozygous for the short (s) form of the serotonin transporter allele, a childhood history of maltreatment was associated with elevated risk for depression and depressive symptoms in adulthood (Caspi et al., 2003). This reported interaction was embedded within a broader analysis of an interaction between 5HTTLPR and stressful life events. Two of three subsequent meta-analyses have tested whether the effect of stressful life events (rather than maltreatment specifically) is moderated by 5HTTLPR genotype, and have concluded that evidence for an interaction effect is weak (Munafo, Durrant, Lewis, & Flint, 2009; Risch et al., 2009). In contrast, the meta-analysis by Karg, Burmeister, Shedden, & Sen (2011) stratified studies according to type of stressful life event and found that 5HTTLPR genotype moderated the effect of maltreatment (as opposed to other stressful life events) on risk for depression. Risk for depression may be elevated among individuals who carry the 5HTTLPR s allele because these individuals have a more pronounced physiological response to stress than l allele carriers. For example, a meta-analysis showed that s/s homozygotes mount a significantly greater cortisol response to acute stressors than l-allele carriers (Miller, Wankerl, Stalder, Kirschbaum, & Alexander, 2013), although it is not clear whether s and l allele carriers differ in their physiological response to chronic stress, such as ongoing abuse or neglect. In addition, s allele carriers show enhanced amygdala reactivity to negatively valenced stimuli compared with

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individuals who are homozygous for the l allele (Munafo, Brown, & Hariri, 2008). A handful of investigations also show that, among s allele carriers, (a) elevated cortisol reactivity to acute stressors and (b) amygdala reactivity to negative emotional stimuli is most pronounced among those who have experienced numerous stressful life events (Alexander et al., 2009; Alexander et al., 2012; Williams et al., 2009; but see Canli et al., 2006 and Mueller et al., 2011 for an alternative interaction pattern), thus demonstrating that potential endophenotypes for depression are also predicted by Genotype × Environment interactions. Along with the genetic imaging studies, there is evidence that the s allele is associated with cognitive vulnerabilities to depression, particularly under stressful conditions (Gibb, Beevers, & McGeary, 2013). For example, compared with individuals who are homozygous for the l allele, healthy adults who carry the s allele take longer to disengage attention from facial expressions of emotions (Beevers, Wells, Ellis, & McGeary, 2009), and to appraise recent stressful life events as being more negative (Conway et al., 2012), with negative appraisals correlated with elevations in depressive symptoms (Conway et al., 2012). Children who carry the s allele also show enhanced memory for negative (vs. positive) self-descriptive traits (Hayden et al., 2013)—a cognitive vulnerability for depression. A few studies show that coping and/or perceptions of coping are associated with the 5-HTTLPR genotype. For example, among adults who were asked to recall recent situations in which they had felt strong emotions of fear, sadness, or joy, those who carried the s allele reported that they felt less able to cope with situations that evoke strong feelings of sadness or fear than individuals who were homozygous for the l allele (Szily, Bowen, Unoka, Simon, & Keri, 2008). In another study, healthy young adults who were homozygous for the s allele less frequently endorsed the use of cognitive reappraisals to deal with negative emotions and events (e.g., “When I want to feel less negative emotion, I change what I’m thinking about” or “I look for the positive side of the matter”) than l allele carriers. In turn, less frequent use of cognitive reappraisal strategies explained why individuals who carried two copies of the s allele had more symptoms of social anxiety (Miu, Vulturar, Chis, Ungureanu, & Gross, 2013). Finally, in a sample of 156 healthy adults, Wilhelm et al. (2007) reported that s allele carriers used fewer problem-solving coping strategies in response to a stressor than l carriers. Although the literature provides a growing number of clues as to why s allele carriers may be at heightened risk of depression in the face of stressors like maltreatment, there have been few tests of formal mediation of Genotype × Environment effects. In one of the first such tests, Cline et al. (2015) showed that cumulative exposure to risk indicators (low parental warmth, harsh parental discipline, traumatic life events) was associated with elevations in internalizing symptoms for youth who were homozygous for the s allele but not for youth who carried the l allele. Moreover, among youth who were homozygous for the s allele, those who experienced more cumulative risk indicators less frequently used distraction coping strategies, such

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as playing a video game or playing sports, which partly explained their elevated symptoms of internalizing problems (Cline et al., 2015).

Psychosocial Moderators of Maltreatment Children who are resilient to maltreatment tend to exhibit high ego control and ego resiliency, high self-esteem, high self-reliance, and the tendency to attribute successes to their own efforts (Cicchetti et al., 1993; Feiring et al., 2002; Moran & Eckenrode, 1992). In addition, above-average intelligence emerges as a protective factor in some studies (Herrenkohl, Herrenkohl, & Egolf, 1994; Jaffee, Caspi, Moffitt, Polo-Tomas, & Taylor, 2007) but not others (Cicchetti & Rogosch, 1997; DuMont, Widom, & Czaja, 2007). Such individual characteristics may be protective only as long as children are not exposed to a multitude of stressors in addition to maltreatment (DuMont et al., 2007; Jaffee et al., 2007). Although socially supportive relationships are hypothesized to buffer youth from the adverse effects of maltreatment (Cicchetti, 2013), there is relatively little research on this question that involves children. There is, however, evidence that nonparental mentoring relationships matter for youth who are in foster care, with one study showing that those who report being mentored before the age of 18 are more likely to participate in higher education, have better self-reported physical health, and are less likely to be diagnosed with a sexually transmitted infection, engage in suicidal ideation, or hurt someone in a fight than those who do not report the presence of a mentor (Ahrens, DuBois, Richardson, Fan, & Lozano, 2008).

CONCLUSIONS Maltreatment is a significant public health problem. From a basic research perspective, there is a need for more prospective, longitudinal data on maltreatment to better understand courses of resilience and dysfunction over time, and long-term effects of maltreatment on mental and physical health. A mix of research strategies and research models is needed to understand mechanisms through which neglect and abuse influence basic biological and psychological processes. Research on the biology of maltreatment would benefit from larger and more representative samples, whereas research on psychological sequelae of maltreatment would benefit from designs that allow for stronger causal inference about potential mediators of maltreatment. An integrative, multilevel perspective is needed to trace effects of maltreatment on pathways from genes to brain to behavior. From a clinical perspective, more research is needed to better evaluate treatment efficacy for maltreated children, to improve access to services and the quality of services for maltreated children, and to understand why some maltreated children respond better to treatment than others.

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Tottenham, N., Hare, T. A., Quinn, B. T., McCarry, T. W., Nurse, M., Gilhooly, T., . . . Casey, B. J. (2010). Prolonged institutional rearing is associated with atypically large amygdala volume and difficulties in emotion regulation. Developmental Science, 13, 46–61. Trickett, P. K., Gordis, E., Peckins, M. K., & Susman, E. J. (2014). Stress reactivity in maltreated and comparison male and female young adolescents. Child Maltreatment, 19, 27–37. Tyrka, A. R., Parade, S. H., Eslinger, N. M., Marsit, C. J., Lesseur, C., Armstrong, D. A., . . . Seifer, R. (2015). Methylation of exons 1(D), 1(F), and 1(H) of the glucocorticoid receptor gene promoter and exposure to adversity in preschool-aged children. Development and Psychopathology, 27, 577–585. U.S. Department of Health and Human Services, Administration for Children and Families, Administration on Children, Youth, and Families, and Children’s Bureau. (2015). Child maltreatment 2013. Retrieved from http://www.acf.hhs.gov/ sites/default/files/cb/cm2013.pdf Van der Vegt, E. J. M., van der Ende, J., Kirschbaum, C., Verhulst, F. C., & Tiemeier, H. (2009). Early neglect and abuse predict diurnal cortisol patterns in adults: A study of international adoptees. Psychoneuroendocrinology, 34, 660–669. Wang, Q., Van Heerikhuize, J., Aronica, E., Kawata, M., Seress, L., Joels, M., . . . Lucassen, P. J. (2013). Glucocorticoid receptor protein expression in human hippocampus: Stability with age. Neurobiology of Aging, 34, 1662–1673. Weaver, I. C. G., Cervoni, N., Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R., . . . Meaney, M. J. (2004). Epigenetic programming by maternal behavior. Nature Neuroscience, 7, 847–854. Widom, C. (1989). The cycle of violence. Science, 244, 160–166. Widom, C. (1999). Posttraumatic stress disorder in abused and neglected children grown up. American Journal of Psychiatry, 156, 1223–1229. Widom, C., Czaja, S. J., & DuMont, K. A. (2015). Intergenerational transmission of child abuse and neglect: Real or detection bias? Science, 347, 1480–1485. Widom, C., Czaja, S. J., & Paris, J. (2009). A prospective investigation of borderline personality disorder in abused and neglected children followed up into adulthood. Journal of Personality Disorders, 23, 433–446. Widom, C., DuMont, K., & Czaja, S. (2007). A prospective investigation of major depressive disorder and comorbidity in abused and neglected children grown up. Archives of General Psychiatry, 64, 49–56. Widom, C., Ireland, T., & Glynn, P. J. (1995). Alcohol abuse in abused and neglected children followed-up: Are they at increased risk? Journal of Studies on Alcohol, 56, 207–217. Widom, C., Marmorstein, N. R., & Raskin White, H. (2006). Childhood victimization and illicit drug use in middle adulthood. Psychology of Addictive Behaviors, 20, 394–403. Wilhelm, K., Siegel, J. E., Finch, A. W., Hadzi-Pavlovic, D., Mitchell, P. B., Parker, G., & Schofield, P. R. (2007). The long and short of it: Associations between 5-HTT genotypes and coping with stress. Psychosomatic Medicine, 69, 614–620.

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CHAPTER 6

Impulsivity and Vulnerability to Psychopathology EMILY NEUHAUS AND THEODORE P. BEAUCHAINE

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erms such as impulsive, disinhibited, and hyperactive have long been used to describe individuals with insufficient control over their behaviors. Although normative variation in these traits can reflect spontaneity, exuberance, and extraversion (Sagvolden, Johansen, Aase, & Russell, 2005), individuals who display extreme impulsivity, or fail to acquire age-appropriate self-regulation as they mature, are vulnerable to a host of maladaptive outcomes. According to developmental psychopathology models of externalizing behavior, extreme impulsivity during the preschool years often represents the first stage in a trajectory that can progress, via potentiating and mediating variables, to early onset delinquency and other antisocial behaviors (Ahmad & Hinshaw, 2016; Beauchaine, Gatzke-Kopp, & Mead, 2007; Beauchaine, Hinshaw, & Pang, 2010; Beauchaine & McNulty, 2013; Beauchaine, Shader, & Hinshaw, 2015; Campbell, Shaw, & Gilliom, 2000; Hinshaw, Lahey, & Hart, 1993; Patterson, DeGarmo & Knutson, 2000). Indeed, trait impulsivity underlies most if not all disorders that fall along the externalizing spectrum, including attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), conduct disorder (CD), antisocial personality disorder (ASPD), and substance use disorders (see Barkley, 1997; Beauchaine & Hinshaw, 2015; Beauchaine, Klein, Crowell, Derbidge, & Gatzke-Kopp, 2009; Krueger et al., 2002). In other cases, especially among girls, temperamental impulsivity marks the beginning stages of a developmental trajectory that culminates in self-harm, depression, and internalizing psychopathology (Beauchaine et al., 2009; Hinshaw et al., 2012; Hirshfeld-Becker et al., 2002). Thus, impulsivity observed early in life portends vulnerability to a wide range of adverse, multifinal outcomes. In this chapter, we consider impulsivity as a dimensional construct that represents a biologically based vulnerability trait. In combination with a variety of 178

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environmental and family risk factors, discussed below, impulsivity forms the core of a spectrum of psychological disorders (Beauchaine & McNulty, 2013; Beauchaine et al., 2010; Beauchaine et al., 2015). This form of impulsivity cuts across traditional diagnostic boundaries and derives largely from subcortical substrates of approach behavior. Among impulsive individuals, functioning of this neural system, and its interactions with (a) other subcortical neural systems of emotion generation, and (b) cortical systems of emotion regulation, yield a behavioral predisposition that encourages reward-seeking behaviors that interfere with long-term goals and well-being (see Beauchaine, 2015). We begin our chapter by placing impulsivity within historical context and contrasting different approaches to defining the construct. We then review genetic and neurobiological underpinnings of the trait. We close with a review of environmental risk factors that moderate and/or mediate links between impulsivity and distal psychological outcomes.

HISTORICAL CONTEXT As with nearly all psychological phenomena, ideas about the nature and etiology of impulsivity evolved considerably over the 19th and 20th centuries. Early neurobiological theories of behavioral control focused on frontal regions of the brain. These theories derived largely from observations of altered behavior among those who suffered from traumatic brain injuries, such as Phineas Gage, a railroad foreman (see Chapter 10 [Arnett, Meyer, Merritt, Gatzke-Kopp, & Shannon Bowen]). In 1848, Gage suffered a severe brain injury when a blasting charge propelled an iron rod through his eye socket and out the frontal part of his skull. Despite full recovery of motor and sensory functions, Gage’s personality transformed radically following his injury (Macmillan, 1992). Although previously “quiet and respectful,” he became “gross, profane, coarse, and vulgar to such a degree that his society was intolerable to decent people” (Bigelow, 1850 cited in Macmillan, 1992, p. 86). He was further described as “impatient of restraint or advice when it conflicts with his desires, at times pertinaciously obstinate, yet capricious and vacillating, devising many plans of future operation, which are no sooner arranged than they are abandoned in turn for others appearing more feasible” (Harlow, 1868, cited in Macmillan, 2004). Thus, the most striking result of Gage’s injuries was marked behavioral disinhibition that contrasted starkly with his socially appropriate demeanor prior to the injury. Consistent with theories of the time, explanations of Gage’s behavior relied upon two assumptions. First, particular brain regions located in the frontal lobe were assumed to support specific behavioral traits, and damage to these regions undermined those traits. In Gage’s case, the shift in behavior was attributed to damage to the “regions of the organs of BENEVOLENCE and VENERATION” (Harlow, 1868, cited in Macmillan, 1992). Second, it was assumed that competing factors were at work within the mind, with behavior resulting from the equilibrium established between them. Damage to the brain disrupted this equilibrium, and the changing balance affected behavior. In the absence of the inhibiting influence of the damaged

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areas, the balance between Gage’s “intellectual faculties and his animal propensities” was destroyed (Harlow, 1868, cited in Macmillan, 2004), resulting in impulsive behavior. As later sections of this chapter reveal, this theme—that behavior derives from a relative equilibrium between self-gratifying and precautious motivations—is also central to contemporary theories of impulsivity. Twentieth-century conceptualizations of impulsivity continued to look toward imbalances in competing neurobiological systems. Eppinger and Hess (1915) argued that vagotonia, an imbalance within the autonomic nervous system favoring the parasympathetic over the sympathetic division, accounted for a number of medical and psychological phenomena. They described vagotonia as a chronic disposition caused by an “abnormal irritability of all or only a few autonomic nerves” (p. 39), including the 10th cranial (vagus) nerve, which provides parasympathetic cardiac influence. Occurring relatively frequently in young individuals, vagotonia was hypothesized to cause neurasthenia, hysteria, and nervousness. Eppinger and Hess described patients with vagotonia as “hasty and precipitous” (p. 40), foreshadowing links that would later be made between this condition and hyperactivity. Although the vagotonia hypothesis has since been refuted (see Beauchaine, 2001), by the middle of the 20th century it was a putative cause of restlessness and hyperactivity in children, and was considered a possible predictor of later antisocial behavior (e.g., Venables, 1988). More recent sources indicate compromised sympathetic and parasympathetic functioning among impulsive children and adolescents (Beauchaine & Gatzke-Kopp, 2012; Beauchaine, Katkin, Strassberg, & Snarr, 2001; Beauchaine et al., 2007; Crowell et al., 2006). At about the same time the vagotonia hypothesis emerged, the encephalitis epidemics of 1918 yielded a group of children who displayed marked impulsivity, hyperactivity, inattention, aggression, and impairments in judgment (Carlson & Rapport, 1989; Schachar, 1986). Neurologists of the time attributed these behaviors to some kind of underlying neurological disturbance, and used the term minimal brain damage (later softened to minimal brain dysfunction, or MBD) to describe such children, as well as those with learning disabilities and other problems (Hässler, 1992). Theories varied with respect to which region(s) of the brain was injured, but impulsivity and hyperactivity were assumed to result from brain damage of some sort, even among children with no documented history of head trauma or illness (Lyon, Fletcher & Barnes, 2003). Although problem behaviors included under MBD shifted over the next few decades, variations of the term and concept remained popular until recently (Hässler, 1992). It was not until the DSM-III was published in 1980 that the category of MBD was dropped, and children with learning difficulties were distinguished officially from those with behavioral difficulties (Lyon et al., 2003).

TERMINOLOGICAL AND CONCEPTUAL ISSUES Despite the centrality of trait impulsivity to current theories of ADHD, CD, antisocial behavior, and substance use disorders, the construct lacks both a consistent

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operational definition and a standard method of measurement. Although impulsivity has been defined traditionally by behavioral symptoms, some researchers have attempted to refine these definitions based on results from neuropsychological tests. For example, reaction time during verbal tasks has been used to assess the degree of “short-circuiting of analytic or reflective thought processes” (Oas, 1985, p. 141). Alternatively, errors in maze solving have been interpreted as inattention to detail, carelessness, and lack of planning (Porteus, 1965). Perseverative errors during set-shifting tasks such as the Wisconsin Card Sorting Test have also been attributed to impulsivity (e.g., Avila, Cuenca, Félix, Parcet, & Miranda, 2004), as have errors due to overly quick responding and lack of reflection during match-to-sample tasks (Oas, 1984). Among the most popular neuropsychological measures of impulsivity are drawing tasks such as the Bender Gestalt (Bender, 1938) and the Draw-A-Person test (Koppitz, 1968). With these tests, impulsivity is assessed by scoring drawings on the basis of variables such as completion time, overall quality, omissions, asymmetry, detailing, and shading (Oas, 1984). Continuous performance tests (e.g., Conners & MHS Staff, 2000; Gordon, 1988) are also purported to assess impulsivity by indexing errors of commission, when participants fail to inhibit inappropriate responses. Although these measures provide tightly operationalized definitions of impulsivity, they do not speak to the neural mechanisms underlying the construct, nor do they fully explain relations between impulsivity and psychopathology (see Gatzke-Kopp, 2011). Many of these formulations describe impulsivity in highly cognitive terms, linking it to specific executive functions such as inhibitory control (the ability to interrupt an ongoing action or prevent a prepotent reaction; Kenemans et al., 2005) and effortful control (the ability to control attentional processes and behavior to inhibit a dominant response in favor of a nondominant response; Rothbart & Bates, 1998), two closely related constructs. Although it remains to be determined how such cognitive constructs relate to trait impulsivity, they are likely to show some degree of overlap, as different measures of inhibitory and effortful control correlate with various facets of impulsivity and problem behavior (e.g., Enticott, Ogloff, Bradshaw, 2006; Murray & Kochanska, 2002). More recent cognitive models of disinhibition integrate multiple components of the trait, suggesting several alternative brain mechanisms that may be responsible for impulsive behavior, exemplifying equifinality (see Chapter 1 [Hinshaw]). Nigg (2000, 2005; see also Chapter 13), for example, has suggested that impulsivity results from dysfunction in at least one of two inhibitory systems. He distinguishes between motivational inhibition, which results from behavioral suppression in the context of anxiety-provoking cues, and executive inhibition, or the deliberate process of stopping or suppressing a prepotent but task-inappropriate response. Barkley (1997) also characterizes faulty inhibition, positing a hierarchical inhibitory structure in which behavioral inhibition consists of three subprocesses (inhibiting of prepotent responses, stopping ongoing responses, and controlling interfering stimuli), each supporting a number of executive functions that allow for effective goal-directed behavior.

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Behaviorally, impulsivity has been described as “behavior that is socially inappropriate or maladaptive and is quickly emitted without forethought” (Oas, 1984; 1985). This behavioral rather than neuropsychological definition has a number of strengths. Although distinct from the more heavily cognitive formulations of disinhibition, it does not rule out cognitively mediated mechanisms. Furthermore, it emphasizes impulsivity as a maladaptive trait, distinguishing it from other qualities, such as spontaneity, which are viewed more positively. Finally, it does not include causal assumptions regarding the etiology of disinhibition, allowing for both psychological and biological contributions. Our preferred definition of impulsivity is that described in the DSM-5 (American Psychiatric Association, 2013) as a component of the hyperactive/impulsive presentation of ADHD. According to this definition, impulsivity is demonstrated by “hasty actions that occur in the moment without forethought and have high potential for harm to the individual . . . a desire for immediate rewards or an inability to delay gratification . . . and/or as making important decisions without consideration of long-term consequences” (p. 61). This conceptualization is similar to that of Sagvolden and colleagues (2005), who describe impulsivity as taking action without forethought and failing to plan ahead. Inherent in these definitions is the premise that impulsivity becomes pathological when it interferes with social, academic, and/or occupational functioning. Thus, the degree, context, and consequences of an individual’s behavior are essential considerations, as they differentiate impulsivity from partially related but more normative behaviors such as risk taking, novelty seeking, and sensation seeking (see also Hirshfeld-Becker et al., 2002).

ETIOLOGICAL FORMULATIONS As should be apparent from our discussion, the behavioral (phenotypic) expression of impulsivity may derive from one or more of several sources (see also Sonuga-Barke, 2005). Well-characterized influences on impulsive behavior include brain injuries, which may result from head trauma, hypoxia, or other central nervous system insults (Chapter 10 [Arnett, Meyer, Merritt, Gatzke-Kopp, & Shannon Bowen]); exposure to teratogens such as alcohol, stimulant drugs of abuse, and/or lead (Chapter 9 [Doyle, Mattson, Fryer, & Crocker]); early traumatic experiences including social deprivation, child abuse, and neglect (Lucas et al., 2004; Poeggel et al., 1999; Chapter 5 [Jaffee]); and genetic vulnerabilities that give rise to deficient executive control over behavior (Chapter 13 [Nigg]). Although this list is certainly not exhaustive, it illustrates the heterogeneous nature of broad behavioral traits such as impulsivity (see Beauchaine et al., 2010; Beauchaine & Marsh, 2006). Rather than describing each of these mechanisms in detail, we begin by focusing on neurobiological substrates that (a) give rise to individual differences in impulsivity that are temperamental, present very early in life, and often emerge before

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conditions such as ADHD can be diagnosed; (b) are supported by voluminous literatures derived from both animal models and humans; and (c) confer vulnerability to externalizing disorders across the lifespan, particularly in the context of high-risk environments characterized by violence, trauma, and emotional lability. This focus on temperamental impulsivity is consistent with our main objective in writing this chapter: to describe early-onset impulsivity as a vulnerability for later psychopathology. Readers should note, however, that it may be difficult in clinical practice to distinguish between children who are impulsive due to an inherited temperamental trait versus children who are impulsive due to other etiological influences such as prenatal exposure to various toxic substances or head injuries (e.g., Beauchaine, Neuhaus, Zalewski, Crowell, & Potapova, 2011; Gatzke-Kopp, 2011). Most modern accounts of temperamental disinhibition emphasize structural and functional abnormalities in phylogenetically old brain regions including the mesolimbic dopamine system and the basal ganglia, overlapping neural networks that mature very early in life and subserve individual differences in approach behavior throughout the lifespan (see Beauchaine et al., 2001; Beauchaine et al., 2010; Beauchaine et al., 2012; Gatzke-Kopp, 2011; Gatzke-Kopp & Beauchaine, 2007; Sagvolden et al., 2005). Here, we emphasize vulnerability to psychopathology that is conferred by compromises in functioning of subcortical mesolimbic brain regions, rather than on cortical (prefrontal) theories of impulsivity. Prefrontal brain regions mature throughout adolescence and into the early 20s and therefore contribute less to individual differences in trait impulsivity very early in life (see Beauchaine & McNulty, 2013; Halperin & Schulz, 2006). Nevertheless, we acknowledge the importance of frontal mechanisms of impulsivity, and refer readers to Castellanos-Ryan and Séguin (2016) for an excellent review. It is also important to note that neurodevelopment of frontal regions—through mechanisms of neural plasticity, programming, and pruning—is shaped by early experiences that are themselves a product of subcortically mediated impulsivity (Beauchaine, Neuhaus, Brenner, & Gatze-Kopp, 2008; Sagvolden et al., 2005; see also Shannon, Sauder, Beauchaine, & Gatzke-Kopp, 2009). Thus, heritable compromises in functioning of early maturing brain regions that give rise to impulsivity can alter neurodevelopment of later maturing brain regions that are responsible for executive functioning and planning—especially in high-risk environments. This model highlights the transactional, or ontogenic process nature of brain-behavior linkages (Beauchaine & McNulty, 2013; Beauchaine, Shader, & Hinshaw, 2016). Recognition and description of such transactions between individuals and environments are tenets of the developmental psychopathology perspective (see Beauchaine & Gatzke-Kopp, 2012; Cicchetti, 2006; Hinshaw, 2013; Rutter & Sroufe, 2000; Sroufe & Rutter, 1984; Chapter 1 [Hinshaw]). In later sections, we describe neurodevelopmental mechanisms through which early impulsivity may potentiate vulnerability to deficient executive functioning later in life.

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Temperamental Impulsivity and Central Dopamine Functioning Theories of impulsivity have long focused on the mesolimbic dopamine (DA) system, including the ventral tegmental area and its projections to ventral striatum, including the nucleus accumbens, caudate, and putamen (Swartz, 1999), and on other dopaminergic networks within the central nervous system (Beauchaine & Gatzke-Kopp, 2012; Castellanos, 1999; Gatzke-Kopp, 2011; Gatzke-Kopp & Beauchaine, 2007, Kalivas & Nakamura, 1999; Sagvolden et al., 2005). Many of these theories follow from research on reinforcement motivation and substance dependence conducted with rodents and nonhuman primates. This research demonstrates that (a) electrical and pharmacological stimulation of dopaminergically mediated mesolimbic structures is reinforcing, such that trained animals engage in prolonged periods of operant behaviors (e.g., lever pressing) to obtain these incentives (see Milner, 1991); (b) neural activity increases within mesolimbic structures during both reward anticipation and reward-seeking behaviors and following administration of DA agonists (see Knutson, Fong, Adams, Varner, & Hommer, 2001; Phillips, Blaha, & Fibiger, 1989; Schott et al., 2008); and (c) DA antagonists attenuate—and in extreme cases block—the rewarding properties of food, water, and stimulant drugs of abuse (e.g., Rolls et al., 1974). Based on this set of observations, several authors have offered theories of impulsivity and personality that explain individual differences in approach behavior as variations in activity of mesolimbic structures. Perhaps the most prominent of these theories is that offered by Gray (1987a, 1987b), in which he proposed a mesolimbic behavioral approach system (BAS) as the neural substrate of appetitive motivation. Soon afterward, clinical scientists interested in impulsivity co-opted dopaminergic theories of approach motivation to explain the unbridled reward-seeking behaviors observed in ADHD, CD, and related externalizing disorders (e.g., Fowles, 1988; Rogeness, Javors, & Pliszka, 1992; Quay, 1993). Although early theories correctly identified mesolimbic neural structures implicated in the expression of impulsivity, most researchers at the time subscribed to the face-valid assumption that excessive dopaminergic activity led to impulsive behavior. In other words, they assumed a positive correspondence between neural responding and behavior. This assumption is evident in the formulation of measures such as the BIS/BAS scales (Carver & White, 1994), which presuppose a direct relation between impulsive behaviors and BAS activity (see Brenner, Beauchaine, & Sylvers, 2005). However, several clear and consistent findings present intractable problems for theories that link excessive mesolimbic DA activity to impulsivity. First, several studies indicate that impulsive preschoolers, middle-schoolers, and adolescents display reduced sympathetic nervous system (SNS)-linked cardiac reactivity to reward (Beauchaine et al., 2001; Beauchaine et al., 2007; Crowell et al., 2006). These findings are significant because (a) SNS-linked cardiac reactivity to incentives serves as a peripheral index of central DA responding under such stimulus conditions (Brenner et al., 2005; Brenner & Beauchaine, 2011) and (b) infusions of DA into mesolimbic structures produce SNS-mediated increases in cardiac output (van den

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Buuse, 1998). Thus, reduced cardiac reactivity to reward among impulsive children is likely to signal diminished DA responding—directly opposite to expectations based on the excessive DA theory. Second, studies using both single photon emission computed tomography and positron emission tomography demonstrate that the primary mechanism of action of methylphenidate and related DA agonists is to increase neural activity in the ventral striatum, located within the mesolimbic reward pathway (e.g., Vles et al., 2003; Volkow, Fowler, Wang, Ding, & Gatley, 2002). Thus, pharmacological interventions that increase mesolimbic DA activity by inhibiting reuptake decrease hyperactivity, impulsivity, and related aggressive behaviors (e.g., Hinshaw, Henker, Whalen, Erhardt, & Dunnington, 1989; MTA Cooperative Group, 1999). Theories of excessive DA as a mechanism of impulsivity predict the opposite effect (i.e., increasing striatal DA activity should worsen impulsivity). Finally, infusions of DA into mesolimbic structures are experienced as pleasurable, and individual differences in central DA expression predict trait positive affectivity (see Ashby, Isen, & Turken, 1999; Berridge, 2003; Forbes & Dahl, 2005). In contrast, PET studies indicate that low levels of striatal DA activity are associated with trait irritability (Laakso et al., 2003). When interpreted in the context of positive relations between externalizing behaviors and both negative affectivity and irritability (e.g., Martel & Nigg, 2006; Mick, Spencer, Wozniak, & Biederman, 2005), these findings suggest diminished rather than excessive DA functioning among at least some impulsive individuals. These converging sources of evidence for reduced mesolimbic DA function as a neural substrate of impulsivity led to a reformulation of first-generation models. We and others have suggested that underactivation of striatal DA leads to increased behavioral responding, which functions to raise activation levels within the mesolimbic system (Beauchaine et al., 2007; Beauchaine et al., 2012; Gatzke-Kopp, 2011; Gatzke-Kopp & Beauchaine, 2007; Sagvolden et al., 2005; Volkow et al., 2009). Thus, what has been mistaken for hypersensitivity is more likely to be reward insensitivity, which results in increased impulsive behavior in an effort to temporarily alleviate a chronically aversive mood state—the affective consequence of an underactive mesolimbic DA system (Ashby et al., 1999; Forbes & Dahl, 2005; Laakso et al., 2003). In addition to the literature cited above, this interpretation is supported by research indicating (a) associations between low basal DA activity/blunted DA reactivity and a propensity to use DA agonist drugs of abuse (De Witte, Pinto, Ansseau, & Verbanck, 2003; Laine, Ahonen, Räsänen, & Tiihonen, 2001; Martin-Soelch et al., 2001; Martinez et al., 2007); (b) significant correlations between blunted DA responses to amphetamine administration and the personality trait of novelty seeking (Leyton et al., 2002); and (c) well-replicated neuroimaging studies indicating reduced striatal activity during reward tasks among children and adolescents with ADHD and CD (e.g., Carmona et al., 2012; Durston et al., 2003; Plichta, & Scheres, 2014; Vaidya et al., 1998). Thus, overwhelming evidence

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now supports the hypothesis that trait impulsivity results at least in part from abnormally low mesolimbic DA activity.

GENETICS AND HERITABILITY There are two general approaches to studying the genetic bases and heritability of any behavioral trait—behavioral genetics and molecular genetics (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Each approach offers unique insights into genetic influences relevant to impulsivity, its origins, and its expression over the course of development.

Behavioral Genetics of Impulsivity Behavioral genetics studies are used to parse variability in a behavioral trait into heritable (both genetic and nongenetic) and nonheritable (environmental) components. Impulsivity is among the most heritable of all behavioral traits. Behavioral genetics studies comparing concordance rates of impulsivity and ADHD for monozygotic and dizygotic twins produce heritability coefficients (h2 ) that approach and sometimes exceed .8, indicating that as much as 80% of the variance in impulsive behavior is accounted for by heritable factors (e.g., Levy, Hay, McStephen, Wood, & Waldman 1997; Price, Simonoff, Waldman, Asherson, & Plomin, 2001; Sherman, Iacono, & McGue, 1997; Wood, Rijsdijk, Saudino, Asherson, & Kuntsi, 2008). Furthermore, Krueger et al. (2002) identified a common vulnerability for a wide range of externalizing symptoms including disinhibition, conduct problems, antisocial personality, alcohol dependence, and drug dependence among a sample of 1,048 participants in the Minnesota Twin Family Study. This latent vulnerability for externalizing disorders, which is likely to reflect trait impulsivity (see Beauchaine & Marsh, 2006; Beauchaine & McNulty, 2013; Beauchaine et al., 2016), was 81% heritable. Similar findings have since been reported in child samples (Lahey, Van Hulle, Singh, Waldman, & Rathouz, 2011; Tuvblad, Zheng, Raine, & Baker, 2009). Still, specific categories of externalizing behavior are influenced strongly by environmental effects. This well-replicated finding is important because it demonstrates that a common genetic vulnerability can result in divergent, multifinal outcomes depending on environmental experience (Beauchaine et al., 2010; Beauchaine & Kopp, 2012), a point which we return to below.

Molecular Genetics of Impulsivity Molecular genetics approaches, including both linkage and association studies, are designed to identify specific genes that contribute to the expression of a trait or disorder (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Linkage studies search for chromosomal regions that are shared more often than expected among large numbers of families with two or more affected children, thereby “linking”

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the disorder or trait to those chromosomal regions (Faraone & Mick, 2010). Because linkage analyses scan broad sections of the genome, the approach works best when very few genes with large effects contribute to a behavioral trait or disease— a rare precondition for psychiatric disorders, which are usually multifactorial in nature. Nonetheless, a genome scan meta-analysis combining seven datasets supported a significant linkage for ADHD on chromosome 16, with possible linkages within a number of other regions (Zhou et al., 2008). Chromosome 16 has also been linked with a variety of other neurodevelopmental disorders (e.g., autism, epilepsy; Ramalingam et al., 2011), supporting impulsivity as a trait that cuts across diagnostic boundaries. Despite this finding, no specific gene has been identified through linkage analyses, and failures to replicate continue to plague psychiatric genetics research (see e.g., Gizer, Otto, & Ellingson, 2016). In contrast to linkage studies, genetic association studies begin with a candidate gene that is believed to play an etiological role in the expression of a disorder (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Using this approach, allelic frequencies of specific genetic polymorphisms are compared among those with and without the condition under study. Association studies can be used to detect genes that account for much smaller amounts of variance in behavior. Given well-articulated theories specifying altered DA functioning as a pathophysiological determinant of impulsivity (see above), association studies are well suited for use with this behavioral trait (Galili-Weisstub & Segman, 2003). Not surprisingly, association studies far outnumber linkage studies of impulsivity and ADHD. Historically, the consistency of results and effect sizes from these studies has been mixed, but recent reviews (e.g., Faraone, Bonvicini, & Scassellati, 2014) highlight the DRD4 and DAT1 genes as the most likely and consistent genetic candidates. Vulnerability alleles including the DRD4 gene (chromosome 11p15.5), which codes for DA receptors located throughout the central and peripheral nervous systems, have been associated with higher levels of trait impulsivity and ADHD (Benjamin et al., 1996; Faraone & Mick, 2010; Li, Sham, Owen, & He, 2006; Schilling, Kuhn, Sander, & Gallinat, 2014). They also correspond to less consistent performance on cognitive tasks among individuals with ADHD (Kebir & Joober, 2011) and predict response to methylphenidate administration (Bruxel et al., 2014). The DAT1, or dopamine transporter gene (chromosome 5p15.3), regulates synaptic levels of DA, the principal target of psychostimulants used to treat ADHD (Grace, 2002). Individuals who are homozygous for the DAT1 10-repeat allele demonstrate reduced cortical thickness in prefrontal areas, as well as reduced volume and activation within mesolimbic and prefrontal structures (Durston, 2010; Fernandez-Jaen et al., 2015). In addition, DAT1 vulnerability alleles are associated with increased DAT binding in the caudate in both typical development and ADHD (Spencer et al., 2013). Recent data suggest that DAT1 may be most influential in combination with specific environment risk factors such as familial risk for ADHD and prenatal substance exposure (Durston et al., 2008; Faraone & Mick, 2010; Laucht et al., 2007; Neuman et al., 2007). Impulsive children who carry vulnerability alleles for both DRD4 and DAT1 appear

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to be at particularly high risk for disruptive behavior, suggesting a cumulative effect of genetic vulnerabilities (Kotte, Faraone, & Biederman, 2013). In addition to genes that are involved directly in DA expression, association studies also suggest roles for genes that are involved in synthesis and metabolism of DA—processes that also affect synaptic activity and reuptake. Candidate genes include those that encode for dopamine-𝛽-hydroxylase (DBH), which converts DA to norepinephrine; and both monoamine oxidase (MAO) and catechol-O-methyl transferase (COMT), enzymes involved in DA (and other monoamine neurotransmitter) degradation. Association studies involving these genes have been few and conflicting. With regard to DBH, allelic status has been linked with ADHD in some samples (Carpentier et al., 2013; Hess et al., 2009), but meta-analyses cast doubt on the reliability and strength of this finding (Gizer, Ficks, & Waldman, 2009). Current evidence suggests that polymorphisms in both the MAOA gene (Xp11.23–11.4) and the COMT gene are associated with antisocial behavior among impulsive individuals, particularly in the context of environmental adversity, including problematic parenting (Caspi et al., 2002; Qian et al., 2009; Thapar et al., 2005; Vanyukov et al., 2007). Emerging evidence also indicates that reduced neural responses to reward and decreased white matter connectivity are associated with particular alleles of MAOA (A allele) and COMT (Met allele of the Val158Met polymorphism), respectively (Hong et al., 2015; Nymberg et al., 2013). However, associations between these genes and ADHD are inconsistent in both direction and effect size (see Faraone & Mick, 2010), and MAO may have differential effects on impulsivity according to sex (indeed, it is X-linked; see Biederman et al., 2008). Taken together, DBH, MAOA, and COMT may be less associated with trait impulsivity per se than with externalizing sequelae that arise from Gene × Environment interactions (see Beauchaine et al., 2009). To summarize, behavioral genetics studies indicate impressively high heritabilities, and suggest that impulsivity contributes to a number of externalizing outcomes. However, despite this high heritability, candidate genes identified to date account for very little variance in impulsive behavior. This “missing heritability” problem plagues psychiatric genetics (see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Clearly, considerable work remains in our attempts to understand the genetic bases of impulsivity.

IMPULSIVITY AND VULNERABILITY TO PSYCHOPATHOLOGY In developmental psychopathology, a distinction is often made between vulnerabilities and risk factors for psychiatric disorders (e.g., Shannon, Beauchaine, Brenner, Neuhaus, & Gatzke-Kopp, 2007; Luthar, 2006). Vulnerabilities are usually assumed to be biologically based traits that render individuals susceptible to psychopathology, whereas risk factors are environmental influences that interact with vulnerabilities to potentiate psychopathology. For example, it is now known that distressing experiences (risk factors) elicit posttraumatic stress disorder mainly

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among genetically predisposed (vulnerable) individuals (e.g., Orr et al. 2003; Stein, Jang, Taylor, Vernon, & Livesley, 2002). Although the distinction between vulnerabilities and risk factors breaks down when we consider the interactive roles that genetically influenced traits play in eliciting specific environments (evocative effects; see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]) and that environments play in the expression of genes (see Moffitt, 2005; Shannon et al., 2007), we maintain traditional use of the terms in upcoming sections, where we outline factors that amplify the likelihood of psychopathology among impulsive and therefore vulnerable individuals. Before proceeding, however, it should be noted that temperamental impulsivity is usually not enough (except in perhaps the most extreme cases) to result in psychopathology in the absence of additional vulnerabilities and/or risk factors. Research with impulsive preschoolers indicates that many do not progress to severe externalizing behavior as they mature (e.g., Campbell et al., 2000; Lahey et al., 2016). In sections to follow, we summarize several additional vulnerabilities and risk factors that interact with temperamental impulsivity to increase the likelihood of later psychopathology.

Behavioral Inhibition In addition to impulsivity, a second well-characterized temperamental trait is behavioral inhibition. This term refers to a general tendency to be wary in novel situations, to be “slow to warm up,” and to avoid overly stimulating environments. Kagan, Reznick, and Snidman (1988) identified a group of 3-year-olds who displayed high degrees of behavioral inhibition in unfamiliar laboratory settings. These children avoided approaching and interacting with unfamiliar children and adults, remained in close proximity to their mothers, and ceased vocalizing in the presence of strangers. When they were reassessed at age 7, they remained quiet, cautious, and socially avoidant. Thus, like trait impulsivity, behavioral inhibition can be detected early in life and is stable (although not invariant) across development. It is also mediated largely by heritable factors (see Chapter 7 [Kagan]). It has often been assumed that trait inhibition and trait impulsivity mark extremes along a bipolar continuum of behavioral control. Yet the neural substrates of the two traits are almost completely nonoverlapping. In contrast to impulsivity, behavioral inhibition, which renders individuals vulnerable to anxiety disorders, is mediated by the septo-hippocampal system, a primarily serotonergic network (see e.g., Beauchaine, 2015; Gray & McNaughton, 2000). Moreover, the two systems evolved to subserve distinct functions: approach behaviors promote survival by ensuring engagement in activities such as eating, drinking, and mating, whereas avoidance behaviors promote survival by reducing exposure to danger. In fact, Gray and others (Gray & McNaughton, 2000; McNaughton & Corr, 2004) have argued convincingly that the functional role of the septo-hippocampal system is to suppress approach behaviors under conditions of threat and uncertainty.

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This conceptualization, in which approach tendencies are actively suppressed by avoidance tendencies, is supported by a large literature on experiments with animals and has direct implications for psychopathology (see Beauchaine, 2001; Beauchaine et al., 2011). Given that the approach and avoidance systems operate with substantial independence, an individual can be high or low on either or both dimensions. A person who is temperamentally impulsive due to a heritable DA deficiency may be protected from severe psychopathology if he or she is also high on behavioral inhibition. Although this might seem implausible at first glance, symptoms of anxiety are surprisingly common among impulsive children with ADHD (Angold, Costello, & Erkanli, 1999; MTA Cooperative Group, 1999), and in the absence of additional comorbidities, such children are more responsive to behavioral interventions than their nonanxious counterparts (Jensen et al., 2001). Furthermore, older externalizing youth with comorbid anxiety are less physically aggressive, regarded less negatively by peers, and experience fewer police contacts than those without anxiety symptoms (Walker et al., 1991). Such findings are precisely what one would expect from a more responsive septo-hippocampal system. Consistent with this interpretation, in a structural neuroimaging study, interactions between trait anxiety and trait impulsivity predicted individual differences in gray matter volumes in both septo-hippocampal and mesolimbic brain regions among children with ADHD (Sauder, Beauchaine, Gatzke-Kopp, Shannon, & Aylward, 2012). Those with ADHD who experienced comorbid anxiety showed normal gray matter volumes in these brain regions compared with controls, whereas those who experienced low levels of anxiety exhibited reduced gray matter volumes. As this discussion implies, an impulsive person who is low on trait anxiety may be especially vulnerable to developing more serious externalizing disorders. Psychopathy, a behavior pattern characterized by manipulation of others, superficial charm, callousness, and lack of remorse, is probably the most intractable form of externalizing conduct (see Lykken, 2006). As several authors have noted, individuals who score high on psychopathy measures exhibit excessive approach behaviors coupled with a disturbing lack of fear and anxiety (see Fowles & Dindo, 2006). Thus, their impulsive tendencies are not inhibited by impending consequences, presumably because they are very low on behavioral inhibition. As a result, the condition is largely unresponsive to treatment. Given that temperamental impulsivity and inhibition are both largely heritable, individuals with psychopathy appear to be “doubly vulnerable” to psychopathology. This situation might best be considered a Trait × Trait interaction, with two largely independent heritable attributes contributing to behavioral functioning (see also Derryberry, Reed, & Pilkenton-Taylor, 2003). Although such models are rare in psychopathology research, recent advances in molecular genetics make it much easier to study interactions among underlying genes that potentiate psychiatric morbidity (see e.g., Beauchaine et al., 2009).

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Environmental Risk There is also considerable evidence that environmental risk factors lead to more severe psychopathology among impulsive children, including those with ADHD. These youth are more likely than their non-ADHD peers to develop ODD, CD, antisocial personality disorder, and in some cases substance abuse later in life (see Barkley, 2003; Beauchaine & McNulty, 2013). Longitudinal studies suggest that for many children, hyperactivity/impulsivity constitutes the first stage in a trajectory that progresses via mediating environmental risk factors to antisocial behaviors, eventually culminating in early-onset delinquency (see Beauchaine & McNulty, 2013; Beauchaine et al., 2010; Beauchaine et al., 2016). We outline some of these risk factors below. Parenting. One of the most thoroughly studied environmental correlates of externalizing behavior is parenting. Numerous studies demonstrate that parents of impulsive and aggressive children are more negative, lax, verbose, and overreactive in their discipline practices than parents of control children (Arnold, O’Leary, Wolff, & Acker, 1993; Barkley, Karlsson, & Pollard, 1985). In a groundbreaking longitudinal study of impulsive boys, Patterson et al. (2000) demonstrated that coercive parental discipline fully mediated the longitudinal association between hyperactivity and antisocial behavior. Hyperactivity led to more serious externalizing behaviors only when parents consistently nagged their children and were explosive in their discipline practices. Parental psychopathology, including ADHD and conduct problems, potentiates risk for externalizing symptoms among impulsive and hyperactive children (Biederman et al., 1995; Biederman et al., 1996; Tandon, Tillman, Spitznagel, & Luby, 2014; Tung, Brammer, Li, & Lee, 2015), and this risk is mediated by both heritable factors and parenting practices. Coercive family interaction patterns—those in which both children and their parents escalate aversive behaviors and negative affect in order to assert their respective wills—promote physical aggression, conduct problems, and delinquency (Snyder, Edwards, McGraw, Kilgore, & Holton, 1994; Snyder, Schrepferman, & St. Peter, 1997). Developmental models suggest that these frequently repeated episodes of affective and behavioral escalation also shape and maintain emotional lability, emotion dysregulation, and physiological reactivity, which increase vulnerability to severe conduct problems (Beauchaine & Zalewski, 2015; Beauchaine et al., 2007; Crowell, Beauchaine, & Linehan, 2009; Chapter 14 [Lahey & Waldman]). This coercive model has been extended to the development of self-inflicted injury among female adolescents (Beauchaine et al., 2009), based on the premise that impulsivity is a core underlying trait in the development of self-injurious behavior (see also Meza, Owens, & Hinshaw, 2015). Negative interaction patterns within mother-daughter dyads appear to interact with daughters’ peripheral serotonin levels to account for much of the variance in

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self-inflicted injury (Crowell et al., 2008). Such findings highlight the importance of Biology × Environment interactions, and the potential moderating role of sex in the developmental trajectory of impulsivity. Indeed, emerging research indicates that impulsive girls are vulnerable to developing self-injurious behaviors in adolescence and young adulthood (Hinshaw et al., 2012; Swanson, Owens, & Hinshaw, 2014; Chapter 19 [Kaufman, Crowell, & Lenzenweger]). Although this body of research has been interpreted by some as evidence of direct environmental effects, it is also likely that heritable genetic vulnerabilities shared by parents and children drive coercive behaviors observed by both parties (an example of passive gene-environment correlation; see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). However, genetic versus environmental hypotheses cannot be disambiguated without true experiments in which impulsive children are assigned randomly to coercive and noncoercive caretakers—an ethically indefensible practice. Nevertheless, in a randomized clinical trial, Hinshaw et al. (2000) found that reductions in negative/ineffective discipline among parents of youth with ADHD mediated school-based reductions in disruptive behavior and improvements in social skills, with effects most pronounced for families who received the multimodal combination of medication and intensive behavior therapy. Similarly, a recent randomized clinical trial demonstrated improved parenting and reduced externalizing behavior among preschool children with ADHD following an empirically supported parent intervention (Webster-Stratton, Reid, & Beauchaine, 2011, 2012). Moreover, interventions that successfully reduce coercive parenting behaviors also reduce delinquency (e.g., Hartman, Stage, & Webster-Stratton, 2003; Martinez & Forgatch, 2001; Piquero, Farrington, Welsh, Tremblay, & Jennings, 2009). Child Abuse and Neglect. Those who study child maltreatment have traditionally considered social mechanisms of risk and intergenerational transmission (see Cicchetti & Valentino, 2006). We therefore include child abuse and neglect as environmental risk factors. However, we note that genetic and temperamental factors also appear to play roles in determining who engages in child abuse and neglect and in influencing the likelihood that a person who experiences abuse will become a future offender (Farrington, Jolliffe, Loeber, Stouthamer-Loeber, & Kalb, 2001; Chapter 5 [Jaffee]). On average, maltreated children are more impulsive than nonmaltreated children (Famularo, Kinscherff, & Fenton, 1992), and histories of abuse are associated with higher levels of externalizing symptoms among male children with ADHD (Briscoe-Smith & Hinshaw, 2006). For girls with ADHD, outcomes are decidedly in the direction of internalizing behaviors and suicidality (Guendelman, Owens, Galan, Gard, & Hinshaw, 2015). Such findings suggest that impulsive children may be at higher risk for child abuse and neglect than their nonimpulsive peers. Furthermore, behavior genetics studies indicate that physical abuse amplifies risk

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for conduct problems and often plays a direct role in the development of antisocial behavior among children (Trouton, Spinath, & Plomin, 2002). This effect is particularly marked among children who are genetically vulnerable (Jaffee et al., 2004). For instance, males who are maltreated as children are at especially high risk for adult antisocial behavior if they carry the low-activity allele of the MAOA gene, a prime example of a Gene × Environmental interaction (Caspi et al., 2002). Neighborhood Effects. A third environmental risk factor that interacts with trait impulsivity is neighborhood context (Chapter 12 [Jennings & Perez]). Several studies indicate that impulsive children who are reared in high-risk neighborhoods (typically defined by such factors as low socioeconomic status (SES), high rates of violence and criminality, and low community involvement) are more prone to engage in antisocial behavior than impulsive children reared in low-risk neighborhoods (Meier, Slutske, Arndt, & Cadoret, 2008; Trentacosta, Hyde, Shaw, & Cheong, 2009; Zalot, Jones, Kincaid, & Smith, 2009). For example, Lynam et al. (2000) found that impulsive boys, as assessed by a number of neuropsychological tests and self-report measures, are at higher risk than nonimpulsive boys for engaging in both status offenses and violent crimes, yet only when they live in neighborhoods of low socioeconomic status and high delinquency. No such effects are observed in high SES neighborhoods (see Zimmerman, 2010, for a different pattern of findings). Taken together, these findings exemplify a Trait × Environment interaction, and illustrate the importance of environmental opportunities in the expression of temperamental risk.

Epigenetic Effects Epigenetic effects refer to alterations in gene expression that result from changes in DNA structure or function rather than changes in DNA sequence (Hartl & Jones, 2002; see Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). These alterations are mediated by methylation processes (in addition to other, less well-documented mechanisms) that are triggered by environmental events. For example, Weaver et al. (2004) demonstrated epigenetically transmitted differences in the glucocorticoid receptor gene promoter in the hippocampi of rat pups that received high levels of maternal licking, grooming, and arched-back nursing compared with pups that experienced low levels of these maternal behaviors. This epigenetic effect transmits adaptive variations in stress responding to offspring. Rat pups reared in hazardous environments where maternal behaviors are compromised have more reactive hypothalamic-pituitary-adrenocortical (HPA) responses and are consequently more fearful and wary. They are therefore better prepared for the hazardous environment into which they are born. Mammals are particularly susceptible to such alterations

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in gene expression (Hartl & Jones, 2002), and increasingly divergent patterns of DNA methylation emerge over the lifetimes of monozygotic twin pairs (Fraga et al., 2005). Accordingly, several authors have emphasized the importance of epigenetic effects for child psychopathology research (e.g., Beauchaine et al., 2011; Kramer, 2005; Rutter, 2005; Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]), and theoretical models of antisocial behavior that include epigenetic effects are increasingly common. In the future, greater understanding of processes and timing of epigenetic effects may help in formulating targeted interventions for vulnerable children. Numerous studies illustrate epigenetic effects related to the emergence of impulsivity. The expression of brain-derived neurotrophic factor, which is involved in differentiation of DA neurons in developing mesolimbic structures and is implicated in the pathogenesis of impulsivity, is susceptible to paternally mediated epigenetic effects (Kent et al., 2005). Offspring of male mice that are exposed repeatedly to ethyl alcohol prior to mating display altered DAT expression within the striatum and prefrontal cortex, again suggesting paternally mediated epigenetic effects (Kim et al., 2014). Similarly, the expression of several DA genes within mesolimbic regions is influenced by extreme birth weight (markedly small or large for gestational age; Grissom & Reyes, 2013). Epigenetically mediated effects on impulsivity have also been observed for risk factors including prenatal smoking, childhood exposure to tobacco smoke, exposure to polychlorinated biphenyls (PCBs) and synthetic glucocorticoids, maternal stress during pregnancy, and family distress (Babenko, Kovalchuk, & Metz, 2015; DasBanerjee et al., 2008; Elia, Laracy, Allen, Nissley-Tsiopinis, & Borgmann-Winter, 2011; Kapoor, Petropoulos, & Matthews, 2007; Pagani, 2014).

Neural Plasticity In addition to epigenetic effects, several other mechanisms of neural programming link early impulsivity to later psychopathology. Neural plasticity refers to experience-dependent functional changes in neural networks, including their efficiency, sensitivity, and time course of responding (Pollak, 2005). These experience-dependent changes occur in several neural systems including mesolimbic DA structures (see Beauchaine et al., 2011). For example, Lucas et al. (2004) reported decreased DA transporter densities in mesolimbic brain regions of male rats exposed repeatedly to more dominant males in a stress-inducing paradigm. Similarly, repeated episodes of maternal separation early in the lives of rat pups produce long-term decreases in DA transporter expression (Meaney, Brake, & Gratton, 2002). These effects result in greater sensitivity to behavioral effects of cocaine and amphetamines later in life. Although similar experiments clearly cannot be conducted with humans, such findings illustrate the exquisite sensitivity of the mesolimbic DA system to early experience and suggest the possibility that experience-dependent changes in DA functioning may predispose affected individuals to stimulant use and/or abuse (see Gatzke-Kopp, 2011).

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Perhaps more troubling, stimulants (e.g., cocaine) themselves induce experiencedependent changes in neural function that are similar to those observed following stress exposure. Through this mechanism, alterations in DA expression lead to sensitization and addiction to stimulants including nicotine, amphetamines, and cocaine (e.g., Saal, Dong, Bonci, & Malenka, 2003; Taylor & Jentsch, 2001; Thomas, Beurrier, Bonci, & Malenka, 2001). Chronic elevation of DA neural firing in the nucleus accumbens by stimulants has two other problematic effects. First, it down-regulates basal DA activity (Scafidi et al., 1996), which may worsen impulsive tendencies that emerge from mesolimbic hyporesponding (see above). Second, it suppresses the strength of connections between the mesolimbic DA system and the prefrontal cortex (Thomas et al., 2001), which may alter development of executive functioning and long-term planning, thereby inhibiting a developmental shift from “bottom-up” neural processing in phylogenetically old limbic structures to “top-down” neural processing in phylogenetically newer cortical structures as individuals mature. In typically developing adolescents and adults, these frontal (mesocortical) structures inhibit reward-related behaviors when it is advantageous to do so (Taylor & Jentsch, 2001). Environmental risk factors including stress and drug exposure may prevent this maturational process from unfolding, resulting in an underdeveloped mesocortical DA system that predisposes to further stimulant use and abuse (Prasad, Hochstatter, & Sorg, 1999), and to potential long-term sequelae of early impulsivity, including conduct problems, delinquency, and antisocial personality development. It is important to note, however, that sensitization appears to be limited to early exposure to drugs of abuse and does not appear to extend to the therapeutic use of stimulant medications among children with ADHD. Instead, therapeutic use of stimulants appears to neither increase nor decrease the likelihood of future substance use disorders, although interpretations are limited because naturalistic investigations comprise the database (Humphreys, Eng, & Lee, 2013; Molina & Pelham, 2014; Volkow & Swanson, 2008). Increased rates of substance abuse among individuals with ADHD are likely attributable to the presence of comorbid antisocial behaviors (Mannuzza et al., 2008).

Implications for Learning As many readers may be aware, the same mesolimbic and to a lesser extent mesocortical structures discussed in this chapter are also recruited for associative learning processes (see Berridge & Robinson, 2003; Sagvolden et al., 2005). Thus, alterations in DA responding that arise from genetic, epigenetic, and experience-dependent effects are likely to influence efficiency of knowledge acquisition. This process might occur through at least three mechanisms: (1) reward-seeking tendencies that reduce motivation for learning “mundane” information; (2) reduced efficacy of associative learning due to dampened activation of mesolimbic structures; and (3) compromised executive functioning. Although we do not have space to review the learning

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literature in further detail, these implications underscore the importance of early intervention for impulsive children who may be on an externalizing trajectory.

RESEARCH DOMAIN CRITERIA FRAMEWORK It should be clear that our conceptualization of trait impulsivity exemplifies a core objective of the National Institute of Mental Health’s Research Domain Criteria (RDoC): to identify and characterize transdiagnostic dimensions of observable behavior, to tie them explicitly to neurobiological and genetic bases, and to explore their interactions with other such systems and with environmental factors that shape brain and behavior over the lifespan (Cuthbert, 2014). Along with increasing precision in our behavioral descriptions of impulsivity, research has refined our knowledge of genetic and neural contributors to impulsivity. Similarly, a range of environmental influences, spanning families to cultures, affect the development of impulsivity and its multifinal outcomes, including the unfortunate trajectory to more intractable externalizing behaviors described above. Interactions between neural circuits underlying impulsivity and those associated with other traits, including anxiety and emotion regulation, can act to either curtail or promote externalizing behaviors (Beauchaine, 2015; Beauchaine & Thayer, 2015).

SYNTHESIS AND FUTURE DIRECTIONS In this chapter, we describe (a) heritable biological mechanisms of vulnerability that lead to impulsivity among affected children; (b) environmental risk factors that can potentiate vulnerability, leading to more serious externalizing behaviors that are especially difficult to treat; and (c) the potential importance of gene-environment correlations and Gene × Environment interactions in the expression and development of externalizing behaviors among impulsive children. Although discussion of environmental, epigenetic, and experience-dependent risk factors for delinquency is sobering, it is worth repeating that only about half of impulsive preschool children develop more serious externalizing behaviors (Campbell et al., 2000). Furthermore, progress over the past decade in the specification of mechanisms through which impulsive behaviors escalate is truly astounding. Modern neuroscientific methods provide insights into the development of externalizing behaviors that were unimaginable just a few years ago. When considered in conjunction with findings from more traditional approaches, it becomes apparent that some children face a cascade of cumulative vulnerability and risk that is increasingly difficult to reverse across development. In the worst cases, impulsive children are raised by impulsive parents who, in addition to conferring genetic liability, transmit risk through inconsistent and stressful caretaking during infancy, along with the potential for child maltreatment and coercive, labile parenting (see Beauchaine & McNulty, 2013; Beauchaine et al., 2011). Further accumulation of risk may occur via exposure to violence in high-risk neighborhoods, early escalation

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of substance use, low motivation, and learning difficulties. By middle childhood and adolescence, exposure to stimulant drugs of abuse compromises the development of executive functions and self-regulation, compounding problem behaviors. In contrast, an impulsive child who is raised in a maximally protective environment faces few or none of these additional risk factors and may develop both psychological and biological resilience given enriched educational experiences and competent parenting that teaches strong emotion regulation skills (Beauchaine et al., 2007; Raine et al., 2001). Parenting interventions have proven quite effective in reversing risk for conduct problems, especially when delivered early in childhood (Beauchaine, Webster-Stratton, & Reid, 2005; Nock, 2003; Piquero et al., 2009). Such interventions are even accompanied by improvements in neurobiological indicators of vulnerability among preschoolers (Beauchaine et al., 2014). Thus, there is reason to be optimistic. It is our hope that our knowledge of risk and resilience will continue to grow, and that science will influence public policy so more children on externalizing trajectories receive evidence-based preventive services.

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CHAPTER 7

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability to Psychopathology JEROME KAGAN

HISTORICAL CONTEXT

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sychopathology is no exception to the rule that history continually alters the meanings of words. During most of the 19th century, Americans and Europeans restricted the term psychopathology to a small number of deviant profiles—usually symptoms defining schizophrenia, bipolar disorder, or autism—that disrupted community harmony and/or prevented individuals from carrying out their responsibilities. Freud introduced a seminal change by insisting that a child’s early experiences within the family made a critical contribution to a collection of symptoms in which anxiety was the central feature. This idea, new at the turn of the last century, became popular because historical changes that brought a faster pace of life and the empowerment of women created a vague mood of uncertainty. Freud supplied the public with a source of this feeling by suggesting that its origin lay with improper socialization of children. Freud’s emphasis on early experience, rather than prudishness over sexuality, was an important reason why his ideas were popular among Americans, who celebrated an egalitarian ethos that favored the belief that life history, not a special biology, determined a person’s level of adaptation. This premise meant that everyone was potentially vulnerable to acquiring symptoms of a neurosis. The emphasis on environmental causation, also promoted by behaviorists, motivated psychologists and psychiatrists to conduct studies designed to prove that a child’s early socialization was the main determinant of later problems. At the center of this mission was the belief that a mother’s care for and love of her child were the most important protections against future pathology. John Bowlby 213

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strengthened this premise with a landmark trilogy of books on attachment (Bowlby, 1969, 1973, 1980). The confluence of these events persuaded psychologists and psychiatrists who were active during the half-century between 1910 and 1960 that children and adolescents who developed mental illness probably suffered from insufficient maternal affection. A confident cohort of geneticists, neuroscientists, and molecular biologists, armed with novel methods, interrupted this narrative by reasserting the 19th-century assumption that inherited biological conditions were more important causes of psychopathology. The search for genetic bases of symptoms found a receptive audience in the 1980s because social scientists who advocated a formative role for experience failed to prove that experience alone—independent of a person’s biology and cultural setting—could generate symptoms of psychopathology. A reluctance to blame the rearing practices of poor, less educated parents for their children’s pathology, which followed civil rights legislation of the 1960s, contributed to the political attractiveness of genetic etiologies. No parent can be blamed for transmitting risk genes to their offspring. The media cooperated with these geneticists and neuroscientists, hyping the significance of their findings by telling a vulnerable public that their fate rested with their biology. One trio of experts on psychiatric illness announced the mantra: “The diseases we treat are diseases of the brain” (Ross, Travis, & Arbuckle, 2015). This claim preserves the premise, popular among Western scholars since Democritus, that material entities are the foundation of all natural phenomena. The attractiveness of this idea is exemplified by the receptiveness in the 1830s to Franz Gall’s claim that patterns of bumps on the skull, reflecting variation in the underlying brain tissue, were a clue to a person’s character traits. These and other historical events catapulted biological processes to an alpha position, over complaints of a dwindling number of psychologists who believed that experiences had the power to create symptoms among those without a special biological vulnerability. The pendulum had swung so far toward biological determinism that most investigators who look for a genetic correlate of a symptom or illness category accept the diagnostic category as a biological unity and rarely gather additional psychological information that would strengthen their results. Had they obtained more information on each patient’s history and current circumstances, they may have been able to parse a group of depressed adults into several etiologically distinct categories. Advocates of a determinism between brain states and psychological properties often borrow predicates, such as fear or compute, which assume that humans are the noun agents, attribute the term to one or more brain sites, and imply that the meaning of the predicate has not changed significantly. The practice of equating human psychological states with brain circuits is common among investigators who attribute anxiety to the brain of a rat that fails to explore a brightly lit alley, and fear to the brain of a rat that becomes immobile to a conditioned signal for shock. This prose implies implicitly that the state of anxiety or fear in rats resembles the state experienced by anxious or fearful humans.

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 215 Tovote, Fadoka, and Luthi (2015) suggested that fear is a brain state. They wrote, “Fear and anxiety are brain states,” when they should have written, “Fear of falling while looking down from a tall building, and anxiety over losing a romantic relationship, are human psychological states that emerge from different profiles of brain activity.” When a discipline is young and without a consensual theory, most concepts belong to more than one network of terms and, therefore, have more than one meaning. The social sciences do not have a consensual theory. Therefore, many concepts belong to several networks and possess more than one meaning because sources of evidence introduce terms into the network that influence meaning. The concept of fear provides an example. The meanings of fear are dissimilar when a verbal report, blood flow to the amygdala, potentiated startle, time freezing to a conditioned signal, and rise in cortisol are sources of evidence. LeDoux (2014) agrees with this position for he suggests that defensive, not fear, is the proper name for the circuit that generates several seconds of freezing when a rat is exposed to a conditioned cue for shock. Neuroscientists who study animals should replace the terms fear and anxiety with descriptions of the behaviors that specific circuits generate to various incentives. For example, the bed nucleus of the stria terminalis is the source of an inhibitory, GABA-ergic influence on exploratory behavior. This fact may explain why rats with an excitable bed nucleus do not spend much time in the center of an open field. This description is more faithful to the phenomenon observed than one that attributes anxiety to a rat that fails to explore the center of an unfamiliar open area. The nucleus accumbens provides a second example. The nucleus accumbens receives inputs from many sites that contain representations of the current event in its setting, as well as past experiences in similar settings. These varied inputs create a neural state in the accumbens that biases its output to motor targets that favor one response over alternatives when there is uncertainty over the adaptive action (Floresco, 2015). The accumbens, like the hand that hovers before picking one piece of chocolate from a full box, is not a source of hedonic pleasure (Berridge & Kringelbach, 2015). It is only a critical way station on the way to pleasure. Einstein’s insight in special relativity was that a statement about the simultaneity of two events had to assume a frame of reference. Analogously, a frame of reference is needed to understand the meaning of many predicates that refer to psychological states. The noun representing the agent of these predicates provides the needed frame of reference. The meaning of compute, therefore, depends on whether the noun agent is a collection of neurons, a migrating bird, a chimpanzee gazing at fruit high on a tree, or an engineer working on a laptop. The brain does not enjoy a privileged frame for all psychological outcomes, even though neuroscientists may wish this were the case. The neuroscientists’ desire to award special power to their evidence compared with behavioral or verbal data is reminiscent of the psychologist’s wish, a century ago, to separate their nascent field from philosophy. Although philosophers, psychologists, and neuroscientists have

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each claimed that they provide the most illuminating account of mind, none of these disciplines has been able to explain why or what 3-year-olds mean when they say, “I don’t like myself,” “What’s that?” or “ I love you, mama.”

DIAGNOSTIC ISSUES Three issues are relevant to the task of arriving at the most fruitful diagnostic categories: (1) specifying biological vulnerabilities that predispose a person to psychopathology, (2) specifying experiences that contribute to symptom expression, and (3) determining the validity of the evidence used to infer risk conditions and to describe symptoms. All three remain controversial. Although investigators agree that many genes contribute to vulnerability (see Beauchaine, Gatzke-Kopp, & Gizer, this volume), there is little agreement on specific genes that render a person susceptible to particular forms of psychopathology. This issue is complicated by the discovery of reversible, nonheritable epigenetic modifications of coding or regulatory genes that are induced by a variety of experiences that silence or promote the expression of particular genes in specific tissues. Psychologists, as well as neuroscientists, would profit from adopting the biologist’s expectation of extremely specific consequences of an incentive. For example, the molecule bisphenol A, used in the manufacture of plastics, administered to pregnant mice, methylates specific cytosine bases in particular genes in specific brain sites in male but not female fetuses (Kurdakovic et al., 2015). A person’s genome can restrict ranges of possible brain states but cannot determine any particular state. A person’s life history and the local setting select the psychological state most likely to be actualized at that moment. The fact that individuals who possess the same risk gene can develop different symptoms implies that DSM-5 categories do not carve nature at its joints (Gershon & Grennan, 2015; see also Beauchaine & Klein, Chapter 2, this volume). Most investigators and clinicians emphasize risk events that a child or adolescent experiences directly, such as parental abuse, bullying, rape, serious illness, and persistent poverty, and ignore popular forms of child rearing and historical changes in social conditions. A majority of American, middle-class White children born between 1950 and 1980 experienced a relatively gentle childhood marked by parental indulgence and encouragement to perfect the self. Compared to many adults who belong to the generation born between 1920 and 1950, who suffered through the Great Depression and World War II, many in these later generations escaped serious stressors of war, harsh socialization, demeaning acts of prejudice, and economic hardship. As a result, a number of adolescents born after 1980 were not prepared to cope with the anxiety over gaining admission to a favored college, maintaining high grades, cyberbullying, temptations for promiscuous sex, binge drinking, betrayals by close friends, or the burden of deciding which actions were moral and which were immoral because of the loss of consensus on moral standards that earlier generations enjoyed. These conditions rendered them vulnerable to

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 217 a bout of anxiety or depression when one or more of these events occurred. The dramatic rise in student visits to college mental health facilities, and the tripling of prescriptions for anxiolytics by British general practitioners to adolescents from 2003 to 2011, imply that both the public and clinicians have been persuaded that a bout of worry is a sign of an illness that requires medical treatment (John et al., 2015). A serious problem trailing most conclusions about experiences that contribute to pathology, as well its presence, is the fact that evidence is based only on verbal reports, usually on questionnaires or interviews, without additional behavioral or biological measures. This strategy is questionable because every verbal description of a trait, behavior, mood, or memory of a past experience can originate in more than one biological state and life history. Women who grew up in disadvantaged homes are at a higher than average risk for an anxiety disorder (Kagan, 2012). However, when New England mothers from varied class and ethnic groups are asked to rate their daughter’s anxiety level, girls from the most economically disadvantaged homes are described as less anxious than girls from more affluent families (Mian, Wainwright, Briggs-Gowan, & Carter, 2011). A person’s verbal descriptions of his or her past or present traits, or those given by an informant, are phenomena to be understood and explained, rather than valid indices of traits or circumstances described. Leading journals often publish papers claiming relations between parental practices and child outcomes that are based only on the parent’s answers to questionnaires. This is not a new criticism of verbal reports. Rosen (1956) made the same claim over 60 years ago. Rorschach inkblots and the Thematic Apperception Test were popular from about 1930 to 1960 because psychologists hoped these indirect measures would be more sensitive indices of a person’s traits than verbal replies. Unfortunately, these techniques proved wanting. But rather than try to invent more sensitive procedures, many psychologists returned to questionnaires with a naïve faith in their validity. Few six-year-olds in affluent, affectionate, two-parent families would tell an examiner that their father was dirtier, more dangerous, and reminded them more of dark angular designs than their mother. But they offered these replies when shown pairs of objects or animals that differed on the dimensions dirty-clean, dangerous-safe, dark-light, and angular-curved and asked to say which picture reminded them of their father and which their mother (Kagan, Hosken, & Watson, 1961). George Beam, a critic of surveys, captured the problem with verbal reports by suggesting that if we want to know what’s going on, we shouldn’t ask (Beam, 2012).

THE ETIOLOGICAL ROLE OF TEMPERAMENTS Heritable brain structures and functions render some children especially susceptible to feeling states or actions that, in combination with life history, become personality traits, and in more extreme cases symptoms of psychopathology. These collections of

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feelings and behaviors are called temperaments. Analogous collections are present in varied dog breeds. Because we do not yet know the genes and accompanying physiologies that are the bases of the many human temperaments, psychologists have to define a temperament as a pattern of behaviors to specific incentives. Most temperaments appear early in development, and are sculpted by experiences into a large, but nonetheless limited, number of personality traits. The patterns of behavior called extraversion, conscientiousness, and impulsivity in older children are personality dimensions that are the joint products of temperamental bias and personal history. None is a temperament. Temperamental contributions to a trait or symptom are not easily detected in older children or adults with current methods. A temperamental bias, therefore, can be likened to a drop of black ink placed in a vessel containing glycerin. The ink becomes invisible after the liquid is stirred, but it is still present in the vessel. Some infant temperamental biases include prolonged irritability to pain, cold, or hunger compared with a brief interval of crying followed by rapid soothing; high or low levels of vigorous motor movements to varied events; frequency of babbling or smiling, whether spontaneous or to incentives; reactions to sweet and sour tastes; and very short or prolonged attention to salient events. This list is too small considering the number of possible brain profiles that could serve as a foundation of a temperamental bias. If each gene that made a contribution to temperament had an average of five alleles, there could be as many as 3 × 10750 possible neurochemical combinations that provide the foundation of a temperamental bias (Irizarry & Galbraith, 2004). Even if a majority of these profiles had no relevance for temperament, the large number of remaining patterns implies that future scientists will discover many hundreds of temperaments that remain undiscovered.

Genes, Neurochemistry, and Temperaments It is generally assumed, but not yet proven, that heritable neurochemical patterns are the biological foundations of most but not all human temperaments. This hypothesis, which was anticipated more than a century ago (McDougall, 1908; Rich, 1928), was prominent in the writings of ancients, who posited melancholic, sanguine, choleric, and phlegmatic temperamental types, derived from the balance of the four body humors present in each person. There are more than 150 different molecules that, along with the density and locations of more than 2,000 types of receptors, have the potential to influence feelings and behaviors that define human temperaments. These include norepinephrine, dopamine, epinephrine, serotonin, corticotropin releasing hormone (CRH), glutamate, gamma aminobutyric acid (GABA), opioids, vasopressin, oxytocin, prolactin, monoamine oxidase (MAO-A), catechol-O-methyltransferase, (COMT), neuropeptide S, and the sex hormones (Hartl & Jones, 2005). The genes that code for these molecules and their receptors usually have a number of polymorphisms in one or more of the gene’s exons, introns, promoters, or enhancers. Promoters control

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 219 the level of transcription of a coding gene (exon) into messenger RNA; enhancers determine where and when transcriptions occur. The immaturity in our current understanding of relations among genes, brain chemistry, experience, and behavior frustrates scientists seeking reliable relations between a gene, or set of genes, and a temperamental bias or form of pathology. It is chastening to recognize that patterns of hundreds of genes, across many chromosomes, contribute to a person’s height. No single gene has much power, and its heritability varies with the person’s sex and ethnicity. If this is the state of affairs for height, patterns for temperaments and symptoms of mental illness are apt to be far more complicated. Investigators interested in the genetic bases of a form of psychopathology should read papers describing epistatic interactions among the many genes that contribute to formation and function of melanocytes in skin, hair, and eyes. Reflection on these discoveries would protect us from announcing overly optimistic assumptions about the genes that place a person at risk for any DSM-5 category (see also Beauchaine, Gatzke-Kopp, & Gizer, this volume).

Reactions to the Unexpected or Unfamiliar Two classes of behavior that emerge during the final months of the first year and appear to be products of temperamental biases have been studied more extensively than most. These reactions involve the contrast between a restrained, cautious, avoidant posture to unfamiliar or unexpected objects, events, people, or settings— called behaviorally inhibited—and one marked by a spontaneous approach, called uninhibited (Asendorpf, 1989, 1991; Bates, 1989; Buss, 2011; Kagan, 1994; Volbrecht & Goldsmith, 2010). Events that are violations of expectations are a primary source of many biological and psychological reactions, and children vary in their response to such violations (Schomaker & Meeter, 2015). Both inhibited and uninhibited behaviors to unfamiliar or unexpected events are moderately stable over time, relatively easy to measure, and have modest heritabilities (Bartels et al., 2004; Birn et al., 2014; Degnan et al. 2014; Kagan & Saudino, 2001; Muris, Hendriks, & Bot, 2016; Robinson, Kagan, Reznick, & Corley, 1992). These two behavioral profiles are observed within every mammalian species studied, even though the biological bases for these biases are not the same across species (Schneirla, 1959; Scott & Fuller, 1962). Because tameness in different mammalian species is the result of different genes, it is likely that the same is true for inhibited and uninhibited behaviors in different species (see Clauss, Avery, & Blackford, 2015; Fox et al., 2005; and Kagan & Snidman, 2004 for reviews of behavioral inhibition). Particular life settings select the behavioral phenotype likely to develop from one of these biases. The social class of a child’s family, which is a proxy for a host of experiences, represents one of the most important influences on the behavioral phenotype. Social class remains the best predictor of developing an anxiety, depressive, conduct, or addictive disorder as defined by the DSM-5, as well as academic skills,

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teenage pregnancy, values, and occupation (Pickett & Wilkinson, 2010; Werner & Smith, 1982; Xin, Zhang, & Liu, 2010).

HIGH- AND LOW-RISK INFANTS: DEVELOPMENTAL PROGRESSION Some children who display an inhibited or uninhibited profile acquired their behavioral pattern without the contribution of a temperamental bias. In order to discover children whose inhibited or uninhibited profile originated in a specific temperamental bias, rather than experience alone, we studied a large cohort of middle-class, healthy, Caucasian infants from age 4 months to 18 years in order to discover whether any psychological properties of young infants predicted each profile. We restricted the sample to healthy Caucasian infants born to financially secure, two-parent families because of differences in the genomes of Caucasians, Asians, and Africans (Chen, Burton, Greenberger, & Dmitrieva, 1999). Four-month-old infants born in Beijing, as well as Chinese-American infants born in the United States, are less irritable than Caucasian infants, and newborn Chinese-Americans are less reactive than Caucasian newborns (Freedman & Freedman, 1969; Kagan et al., 1994; Liu, unpublished manuscript). In addition, we suspected that infants born to economically disadvantaged single parents might experience conditions that favored development of one of these behavioral patterns. The central hypothesis guiding our infant assessments was that inherited variation in excitability of the amygdala would be accompanied by distinct patterns of motor activity and distress to unexpected and unfamiliar events. The brain circuits responsible for control of motor activity and crying to unexpected events mature after 16 weeks of age. The amygdala consists of a number of neuronal clusters, called the lateral, basal, cortical, medial, intercalated, and central regions. Each cluster has a distinct set of connections, neurochemical patterns, and functions (Stefanacci & Amaral, 2002). Thresholds of excitability in these clusters are influenced by a large number of molecules, including GABA, glutamate, opioids, serotonin, norepinephrine, dopamine, vasopressin, and oxytocin (Kirsch et al., 2005; Nuss, 2015). The balance among the concentrations of these molecules and the activity of their receptors, combined with inputs from other sites, determine the excitability of each cluster. Projections from the basolateral nucleus of the amygdala, which is responsive to unfamiliar or unexpected events, disinhibit the tonically inhibited central nucleus, which, in turn, activates sites that generate a vigilant state and appropriate actions should the event pose a threat (Fitzgerald, Angstadt, Jelsone, Nathan, & Phan, 2006). Hence, infants with an excitable amygdala might be more likely than others to become inhibited children. A variety of factors could create a more excitable amygdala. One is a compromise in the usual suppression of the central nucleus by the medial prefrontal cortex (mPFC). A second possibility is suppression of the intercalated cell mass within the amygdala, which normally inhibits the central nucleus.

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 221 Newborn infants whose rate of sucking increases dramatically following an unexpected change in taste sensation from water to sweet are more inhibited during the second year than infants who show a minimal increase in sucking rate following the same change in taste (LaGasse, Gruber, & Lipsitt, 1989). The unexpected change in taste sensation activates the medial and central nuclei of the amygdala, which is followed by activation of motor centers that control sucking. Infants with more excitable amygdalar nuclei should have larger increases in sucking rates. The more critical fact for our purposes is that activation of the amygdala of many species is accompanied by vigorous limb movements, back arching, and distress cries (Pitkanen, 2000). Human infants display all three behaviors. Infants who possess more excitable amygdalar nuclei should display more vigorous limb activity, more arches of the back, and frequent crying to unfamiliar events, compared with infants born with a different neurochemistry that renders the amygdala less excitable. The display of arches of the back is particularly significant because this response is mediated by a circuit from the central nucleus of the amygdala to the central gray. Hence, frequent arches implies a more active amygdala. This pattern of behavior is in accord with Rothbart’s (1989) emphasis on variation in reactivity as a basic temperamental category. We coded from film records the frequency of vigorous limb movements, back arching, fretting, and crying, along with babbling, smiling, and heart rate in over 450 healthy, 16-week-old Caucasian, middle-class infants during a battery that included presentation of unfamiliar, colorful objects moving back and forth in front of the face, recordings of speech emanating from a schematic face with no human present, and a cotton swab that had been dipped in dilute alcohol applied to the nostrils. These events were unexpected but not sources of pain or serious threat. The 20 percent of infants who showed a pattern that combined high levels of limb activity, back arching, and crying were called high reactive. The 40 percent who showed a pattern of minimal motor activity, few arches, and little crying were called low reactive. It is unlikely we would have detected these two groups if we had interviewed the mothers or given them a questionnaire that asked them to describe their infant, since most parents attend to their infant’s smiling and crying, but do not notice the pattern of actions to unfamiliar events that define high- or low-reactive infants (Bornstein et al 2015.) A small group of 4-month-old infants who combined high levels of limb activity with babbling and smiling, but little or no crying, were biased to become exuberant 5-year-olds (Degnan et al., 2011). A few studies suggest that fetuses who become active or respond with a large change in heart rate to maternal arousal are biased to become high-reactive 4-month-olds (Dipietro, Ghera, & Costigan, 2008). We assessed the high- and low-reactive infants on seven occasions through 18 years of age. Detailed results of these evaluations are summarized elsewhere (Kagan, 1994; Kagan & Snidman, 2004; Kagan, Snidman, Kahn, & Towsley, 2007). A brief summary of findings detailed in these sources follows.

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Child and Adolescent Evaluations. High reactives observed in a laboratory at 14 and 21 months were more avoidant of and fearful to a series of 17 unfamiliar social or nonsocial incentives than low reactives. Fox has affirmed this relation in an independent sample (Fox, Snidman, Haas, Degnan, & Kagan, 2015). The 20 percent of high reactives who were not exceptionally fearful in the second year presumably had experiences that allowed them to gain a measure of control over the behavioral expression of fear. These children were likely to have parents who did not protect them from every minor threat (Lewis-Morrarty et al., 2012). More high- than low-reactive 2-year-olds had narrow faces (ratio of width at the bizygomatic over the length of the face; Arcus & Kagan, 1995). Men with broad faces are a little more aggressive than others (Hasselhuhn, Ormiston, & Wong,2015), and children as well as adults rate photos of men with broad faces as more competent than men with narrow faces (Antonakis & Dalgas, 2009). Moreover, capuchin monkeys with broad faces are most likely to hold the alpha status in the troop (Lefevre et al., 2014). Adults with narrow faces are more likely to possess an ectomorphic body build, which is often a feature of patients with panic disorder (Pailhez, Rosado, Baeza-Velasco, & Bulbena, 2014). High- and low-reactive temperaments contribute to behaviors that 1-year-olds display in the Strange Situation. Some high reactives cry so intensely when the mother leaves them in an unfamiliar room that they are difficult to soothe when she returns. Hence, they are classified as insecure-resistant. Some low reactives are so unperturbed by the maternal departure that they do not cry when the mother leaves and do not rush toward her when she returns. As a result, these children are labeled insecure-avoidant (Marshall & Fox, 2005). Close to half of high-reactive 4-year-olds, compared with 10% of low reactives, were behaviorally inhibited when they played with two unfamiliar children of the same age and sex in an unfamiliar room (Kagan, Snidman, & Arcus, 1998). About one half of high-reactive 7-year-olds were afraid of animals, darkness, thunderstorms, and/or unfamiliar people and places, compared with fewer than 10% of low reactives. It is worth noting that more high than low reactives had an atopic allergy, usually hay fever or eczema (Kagan, 1994), and that behaviorally inhibited macaque monkeys have a hyperresponsive airway tract (Chun, Miller, Schlegle, Hyde & Capitanio, 2013). Eleven- and 15-year-old high reactives displayed fewer spontaneous comments and smiles than low reactives during a laboratory session designed to measure four biological reactions that are indirect signs of an excitable amygdala. One of these measures is asymmetry of activation in the frontal lobe. More high than low reactives displayed greater activation of the right compared with the left frontal lobe at ages 11 and 15. Right frontal activation, defined by less alpha band power in the right compared with the left frontal lobe during a resting baseline, has modest stability and modest relations with an unpleasant sensory state in infants, susceptibility to an anxious or depressed mood in adults, a less effective response to an antidepressant,

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 223 and behavioral signs of fear in animals, although not every study confirms these generalizations (Adamec, Blundell, & Burton, 2005; Blackhart, Minnix, & Kline, 2006; Bruder et al., 2008; Davidson, 2003; Davidson, Jackson, & Kalin, 2000; Degnan et al 2011; Fox, Calkins, & Bell, 1994; Fox et al., 2005; Peltola et al., 2014; Schmidt, 2008; Smit, Posthuma, Boomsma, & De Geus, 2007). Because the amygdala projects ipsilaterally to sites in the frontal cortex, greater activity in the right amygdala is accompanied by greater activation of the right frontal area (Cameron, 2002). Visceral feedback from the body to the central nucleus is greater to the right than to the left amygdala. Therefore, children who experience more frequent visceral activity should have a more active right amygdala and display right, rather than left, frontal activation. High-reactive boys who reported that they often feel bad when a parent criticized them showed right frontal activation (Kagan & Snidman, 2004). More high than low reactives showed a larger brain stem auditory-evoked response from the inferior colliculus at ages 11 and 15 years. Because the amygdala sends projections to the inferior colliculus, this result implies that high reactives possess a more excitable amygdala (Baas, Milstein, Donlevy, & Grillon, 2006; Brandao, Coimbra, & Osaki, 2001). High-reactive adolescents also showed larger N400 waveforms to discrepant visual scenes (for example, a chair with one leg) and greater sympathetic compared with parasympathetic tone in the cardiovascular system (Kagan & Snidman, 2004; see Fox et al., 2005; Movius & Allen, 2005; Schmidt, Fox, Schulkin, & Gold, 1999 for replications of some of these results). However, only a small number of high reactives displayed all of these biological features. This is why investigators must gather a pattern of outcome measures. High- and low-reactive 15-year-olds were interviewed for close to three hours in their homes by a woman who was blind to their history. High reactives smiled infrequently, offered terse answers, and showed more restless activity compared with low reactives. The interviewer asked several questions designed to discover each adolescent’s primary worries. Although all adolescents reported concerns with the quality of their performance in school and when engaged in extracurricular activities, more high than low reactives confessed to worrying about crowds, strangers, unfamiliar situations, or the future. Two thirds of high reactives, but only 20% of low reactives, confessed to one or more of these less realistic worries, which could be sustained by tonic excitability of a circuit from the amygdala to the bed nucleus via the stria terminalis (Tovote et al., 2015). Verbatim excerpts illustrate the concern with unpredictable challenges among high reactives: “In a crowd I feel isolated and left out, I don’t know what to pay attention to because it is also ambiguous”; “I worry about the future, over not knowing what will happen next”; “I wanted to be a doctor but decided against it because I felt it would be too much of a strain”; “I like being alone and, therefore, horses are my hobby, I don’t have to worry about fitting in with others when I am with my horses”; “I get nervous before every vacation because I don’t know what will

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happen.” Similar statements were rare among low reactives. High reactives were also less likely, on a Q-sort procedure, to rank the statement, “Most of the time I’m happy” as a salient characteristic of their personality, and more likely to describe themselves as serious and tense. Adolescents who report these traits are at a higher risk for a later mental illness (Colman, Wadsworth, Croudace, & Jones, 2007). Youth in the contemporary United States are trying to establish a personal philosophy at a time when there is little if any consensus on the meaning of life, or the moral values that all must honor. This condition creates high levels of uncertainty in high-reactive adolescents. As a result, these youth might be expected to seek a means of muting their angst. A religious commitment is one effective strategy because it provides a partial answer to these questions and assures each believer of his or her essential virtue when disappointments, failures, or frustrations occur. Forty-five percent of adolescents who were high-reactive infants said they were very religious, compared with only 25% of the low reactives, despite no difference in the religious commitment of their parents. Age 18 Assessments. Select features of brain anatomy and function were evaluated in 135 high- and low-reactive 18-year-olds. In addition, a clinician who was blind to each youth’s history administered a standard psychiatric interview and assigned DSM-IV-TR (2000) diagnoses to those who met relevant criteria. High- and low-reactives differed significantly on three biological measures that imply a more excitable amygdala. High reactives had a thicker cortex in a small region in the anterior ventromedial PFC of the right hemisphere (Schwartz et al., 2010). Very impulsive boys, a trait rarely seen among high reactives, had a smaller volume in the right ventromedial PFC (Boes et al., 2009). This area is connected reciprocally with the amygdala and projects to sites in the central gray that are responsible for back arching displayed by high-reactive infants. Adults with lesions in this area are less troubled by moral errors (Moretto, Ladavas, Mattioli, & di Pelligrino, 2010) (see also Hill, Tessner, Wang, Carter, & McDermott, 2010; Welborn et al., 2009; Young et al., 2010). High reactives are especially vulnerable to anxiety and guilt following violations of a moral belief. Furthermore, adolescent males who are high in a trait called surgency, which is infrequent among high reactive boys, show less activity in this area when, in the presence of friends, they make an error in a game (Segalowitz et al., 2012). The thicker cortex observed in the right vmPFC of high reactives seems, on the surface, to be inconsistent with many reports suggesting that this area modulates the amygdala and mutes its excitability. This paradox might be resolved by noting that the high reactives do not possess a thicker cortex in the left vmPFC. It is possible that projections from this area in the left hemisphere are more effective in silencing the amygdala. This suggestion is supported by the observation that adults with a thicker left vmPFC show less activation of the amygdala when judging emotional faces (Foland-Ross et al., 2010).

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 225 High reactives showed a larger surge of blood flow (BOLD signal activation) in the right amygdala to the initial presentation of an angry face (the episode contained four presentations of angry, fear, and neutral faces appearing in random order). High reactives also showed a shallower slope of habituation of the BOLD signal in the left amygdala to repeated presentations of ecologically invalid scenes (for example, an infant’s head on an animal’s body) and in the right amygdala to repeated presentations of unfamiliar faces with neutral expressions (Schwartz, Kunwar, Greve, Kagan, & Snidman, 2012; see also Blackford, Allen, Cowan, & Avery, 2010; Eley, 2011; Williams et al., 2015). Clinician’s diagnoses revealed a significantly higher prevalence of depression, social phobia, and/or general anxiety disorder among the 18-year-old high reactives compared with the low reactives (42% vs. 26%; see Frenkel et al., 2015 for a similar result). One reason these diagnoses are high is that they are based on current feelings rather than recall of the past. Moreover, projections from the PFC to limbic sites, which modulate the latter, are not yet fully mature at age 18 (Brendgen, Wanner, Morin, & Vitaro, 2005; Eley, 2011; Gladstone & Parker; 2006; Mick & Telch, 1998). French adults with a combination of social anxiety disorder and depression had the highest scores on a questionnaire that asked them to recall how shy, timid, and fearful they were as children (Rotge et al., 2011). Low-reactive males who were least fearful on every childhood assessment had the lowest rates of depression or anxiety (13%), and were free of drug and alcohol problems, conduct disorder, and ADHD. The combination of a low-reactive temperament, male sex, and growing up in a secure middle-class family generates an unusually relaxed, worry-free adolescent. The biological measures distinguished between high reactives, mainly girls, who reported a bout of depression or anxiety, and low reactives with the same symptoms. More of the former showed a thick vmPFC in the right hemisphere, a large surge of blood flow to the initial appearance of an angry face, and/or a shallow habituation of the BOLD signal to the invalid scenes. Seventy-one percent of anxious or depressed high reactives, but only 23% of depressed or anxious low reactives, had their maximal BOLD signal to the first presentations of angry faces. More high reactives with one of the diagnoses showed very frequent back arches at 4 months and/or high fear scores in the laboratory at 14 months, compared with high reactives who were free of anxiety or depression, and low reactives with either one or both diagnoses. Ninety percent of high reactives with social anxiety or depression had either frequent arches or a high fear score or both, whereas not one low reactive with these same symptoms met either criterion (these data reveal a sensitivity of 90% and a specificity of 100%). Finally, a pattern that combined the display of many fears at 14 months with a thick vmPFC in the right hemisphere at 18 years also separated the high and low reactives given exactly the same diagnoses. Two thirds of the high reactives who were fearful at 14 months

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and had a thick vmPFC received diagnoses of depression, general anxiety, or social anxiety disorder. Not one low reactive diagnosed with depression or anxiety possessed both features. Recall that high reactive children were more likely to suffer from hay fever or eczema due to an allergy. Australian adults diagnosed with depression are also more likely to suffer from an allergy (Sanna et al., 2014). Because female sex hormones activate mast cells of the immune system, which release histamine after binding to immunoglobulin E to produce allergic symptoms, it is of interest that the onset of puberty is marked by more cases of depression in females than in males (Zierau, Zenclussen, & Jensen, 2012). These results imply that DSM-5 diagnostic categories for anxiety and depression can be the product of different physiologies and life histories (i.e., equifinality; Cohen et al., 2015). Hence, biological and behavioral evidence should be gathered on all patients in order to parse those with the same symptoms into theoretically more fruitful categories that might profit from different therapeutic regimens.

SYNTHESIS The evidence contains several implications for those who study or treat psychopathology. First, investigators should be sensitive to the context of observation, which includes the procedure that is a source of evidence. Children who were high-reactive infants are cautious and subdued in unfamiliar settings, but not in familiar contexts (Buss, 2011). Second, investigators should base their inferences about causal cascades that lead to psychological outcomes on patterns of several variables rather than single measures, since most outcomes result from more than one cascade (Kagan, 2011). Too many investigators gather a single outcome variable, whether a score on a questionnaire, salivary cortisol, skin conductance, potentiated startle, a cardiovascular measure, or blood flow to a brain site. A combination of seven biological variables separated high- and low-reactive 11-year-olds far better than any single measure (odds ratio of 7.0). Every DSM-5 category is the product of more than one equifinal cascade. More high- than low-reactive 11-year-olds combined a narrow face with blue eyes (Kagan & Snidman, 2004). Coat color is often linked with behavior in mice, rats, dogs, and ungulates (Ducrest, Keller, & Roulin, 2008). It is worth noting that, among Caucasians, blue-eyed adults have a slightly higher probability of developing a dependence on alcohol and/or social anxiety disorder (Sulovari, Kranzler, Farrer, Gelernter, & Li, 2015). Clinicians who wonder about the origins of social anxiety in a Caucasian patient might note whether she possesses these features. If so, her symptoms might have a temperamental origin. If the patient has dark eyes and a broad face it is more likely that experience, rather than a high-reactive temperament, is the origin of her symptoms. The high frequency of unrealistic worries about future encounters with unfamiliar settings reported by high reactives provides a clue to processes responsible for their

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 227 profile. These adolescents are chronically uncertain over judgments by others as to how they should behave in unfamiliar settings, and often detect a change in heart rate, blood pressure, or muscle tension, which they interpret as signs of anxiety. Self-reported unrealistic fears of monozygotic twins and their spouses show higher heritabilities than realistic fears of illness, a car accident, or criticism for a mistake (Sundet, Skre, Okkenhaug, & Tambs, 2003). High reactives appear to possess a greater susceptibility to unexpected visceral feedback from the gut, muscle, and autonomic nervous systems. High-reactive 11- and 15-year-olds showed larger increases in heart rate to cognitive stressors. When the sensations that are the products of these events pierce consciousness, they create uncertainty because they are unexpected and their origin is ambiguous. High-reactive youth in our culture are biased to interpret this feeling as a sign that they are worried about an encounter with a stranger or an unexpected challenge because these events are the most frequent novelties in their lives. Members of other cultures might impose different interpretations on the same visceral feedback. Cambodian refugees who live in Massachusetts, for example, interpret an unexpected bout of tachycardia as a weak heart, produced by a loss of energy following lack of sleep or diminished appetite (Hinton, Pich, Safren, Pollack, & McNally, 2005; Hinton, Pich, Chean, Pollack, & McNally, 2005). Saulteaux Indians of Manitoba worry about contracting a serious disease because illness is a sign that they violated an ethical norm on sexual, aggressive, or sharing behavior with others (Hallowell, 1941). Social anxiety, often combined with depression, are the most likely symptoms for high reactives brought up in the United States or Europe because strangers and new places are common events and social acceptance is an important motive in these cultures. The fact that biological parents or siblings of patients with social anxiety disorder are more likely to suffer from the same symptoms than second- or third-degree relatives points to a genetic contribution to a vulnerability to visceral reactions to uncertainty (Isomura et al., 2015). A temperamental bias, therefore, renders individuals vulnerable to brain and body reactions that can generate a feeling that is often interpreted as uncertainty. A person’s life history and culture supply the target of uncertainty. Young Chinese women worry more than Americans over losing their virginity, and many Chinese 20-year-olds respond to billboards advertising hymen repair of this tissue (Steinmuller & Tan, 2015). In the contemporary United States, social failure has been added to the seven traditional sins of pride, anger, envy, avarice, sloth, gluttony, and lust as a basis for anxiety, shame, or guilt. Although White, middle-class, high-reactive infants who grow up in the United States are at higher than normal risk for becoming socially anxious, introverted adolescents, most will neither meet criteria for social anxiety disorder nor be unusually shy. About half of a sample of social phobics did not remember being excessively shy as young children, although they may distort their recollections of their childhood personality (Cox, MacPherson, & Enns, 2005).

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Many high-reactive infants did not develop an anxiety disorder during adolescence because they acquired effective coping defenses. One high-reactive boy who was fearful at 14 and 21 months learned to control his timidity after school entrance. At age 12 he wrote an essay for a class assignment that explained how he overcame his anxious feelings. He ended the essay by writing, “Because I now understand my predisposition to anxiety, I can talk myself out of simple fears.” The belief that one can control public signs of anxiety is accompanied by increased functional connectivity between the ventrolateral PFC and the amygdala and reduced activity in the amygdala (Salomons, Nusslock, Detloff, Johnstone, & Davidson, 2015). However, this boy, like more than 90 percent of high reactives, was not a consistently ebullient, relaxed, sociable, bold, risk taker because his temperament was an obstacle to acquiring this pattern. A temperamental bias makes it difficult to acquire certain traits, but does not guarantee any particular property. The same is true for experiences. The probability that children who are reared by economically secure, well-educated parents will not become prostitutes or homeless drug addicts is very high, but the probability that they will pursue a specific vocation, marry late, prefer solitary hobbies, or acquire any of a hundred different properties is much lower. Temperaments and life histories constrain a small number of extreme outcomes, while leaving the future open for a broad set of possibilities. A temperament can be likened to the basic form of song sung by a bird species. The bird’s genome imposes a serious constraint on its basic form, but does not determine variations on that form, which are dependent on which songs of conspecifics the young bird hears. Knowing that a bird is a finch rather than a meadowlark allows one to predict with confidence the many songs it will not sing, but not the specific song it will sing. So too with temperaments.

Anhedonia The brain chemistry of high reactives could interfere with the intensity as well as the frequency of subjective feelings of pleasure that occur when a person receives an unexpected or larger-than-anticipated desirable experience. Perhaps one reason why high-reactive adolescents do not like new activities (whether risky or not), even though they promise excitement, is that these youth fail to experience a great deal of pleasure when they anticipate visiting a new city, meeting a new person, or engaging in a novel activity (Netter, 2006). This argument is supported by a study of 111 college students who initially filled out a questionnaire measuring social anxiety, then rated their mood on each of 21 consecutive days. Students with high scores on the social anxiety scale were least likely to report pleasurable experiences, and more likely to confess to a melancholic mood across the 3 weeks (Kashdan & Steger, 2006).

Hyping Biology American and European scientists prefer materialistic explanations of natural phenomena. Genes, neurons, transmitters, and circuits are material entities whose

High-Reactive Temperament, Behavioral Inhibition, and Vulnerability 229 forms can be observed and imagined. Neither feelings nor thoughts, which the Greeks assigned to the soul, possess this quality. Indifference to a person’s subjective interpretation of an experience means that investigators typically ignore the pride or shame that accompanies identification with family pedigree, ethnic group, or religion, which can render a person vulnerable to psychopathology. If 12-year-old Rainer Hoess had not been told for the first time that his grandfather was Rudolf Hoess, the commandant at Auschwitz from 1941 to 1943, he may not have developed the deep depression that followed his learning this fact about his family pedigree (Grieshaber, 2011). It is rare to read a paper on the contribution of genes or brain states to pathology in which the influence of identifications are considered, even though these psychological states affect the brain’s response to incentives (Derks & Stedehouser, 2015). Ethnic identification can also influence blood cytokine levels. Among African-American 20-year-olds who report being frequent victims of discrimination, those who are proud of being Black have lower cytokine levels than those with a weaker identification with their ethnicity (Brody, Yu. Miller, & Chen, 2015). Although the study of genetic and neural correlates of psychopathology has value, it has a serious disadvantage. It fails to raise public consciousness over the substantial contributions of social experiences. Genes cannot explain why rates of teenage pregnancy in European and North American nations is highest in the United States and England, and lowest in Switzerland and Germany (Sedgh, Finer, Bankole, Eilers, & Singh, 2015). A single-minded approach to finding vulnerability genes tempts clinicians to ignore therapeutic strategies that alter the patient’s life circumstances, and instead persuade the public that genes are the major determinant of criminal behavior, marital infidelity, and symptoms of anxiety, depression, and restlessness in the classroom. Every river is capable of becoming polluted and losing its capacity to sustain life. However, ecologists do not attribute an inherent flaw to a river that has become polluted. Rather, they urge changes in the practices of industry and agriculture that are the root causes of the pollution. Psychiatrists and psychologists should adopt a similar strategy with mood and character disorders.

REFERENCES Adamec, R. E., Blundell, J., & Burton, P. (2005). Neural circuit changes mediating a lasting bias and behavioral response to predator stress. Neuroscience and Biobehavioral Reviews, 29, 1225–1241. Antonakis, J., & Dalgas, O. (2009). Predicting elections: Child’s play! Science, 323, 1183. Arcus, D., & Kagan, J. (1995). Temperament and craniofacial variation in the first two years. Child Development, 66, 1529–1540. Asendorpf, J. B. (1989). Shyness as a final pathway for two different kinds of inhibition. Journal of Personality and Social Psychology, 57, 481–492.

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CHAPTER 8

The Adaptive Calibration Model of Stress Responsivity Concepts, Findings, and Implications for Developmental Psychopathology BRUCE J. ELLIS, MARCO DEL GIUDICE, AND ELIZABETH A. SHIRTCLIFF

HISTORICAL CONTEXT

T

he stress response system (SRS) has a central role in orchestrating physical and psychosocial development of both humans and nonhuman species (Ellis, Jackson, & Boyce, 2006; Korte, Koolhaas, Wingfield, & McEwen, 2005). For many organisms, the SRS contributes crucially to responding flexibly to challenges and opportunities in the environment. One of the most remarkable features of the SRS is the wide range of individual variation in its physiological parameters. Some individuals respond quickly and strongly even to minor events, whereas others show flat response profiles across most situations. Furthermore, the balance of activation among primary SRS subsystems—the parasympathetic nervous system (PNS), the sympathetic nervous system (SNS), and limbic-hypothalamic-pituitary-adrenal (LHPA) axis—can vary considerably across individuals. It is difficult to overstate the real-world relevance of such individual variability. Decades of research demonstrate not only that physiological patterns of stress responsivity constitute a primary integrative pathway through which psychosocial environmental factors are transmuted into the behavioral, autonomic, and immunologic manifestations of human pathology (reviewed in Boyce & Ellis, 2005), but also that patterns of stress responsivity regulate variation in a wide range of adaptive processes and behaviors including (but not limited to) growth and metabolism, reproductive status and fertility, aggression and risk taking, pair bonding and caregiving, and memory and learning (reviewed in Del Giudice, Ellis, & Shirtcliff, 2011; 237

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Ellis & Del Giudice, 2014). Clearly, understanding the causes of such individual differences and their development over the life course has important implications for medicine, psychology, and psychiatry, among other disciplines. One approach has been to view individual differences in stress reactivity through a pathology lens. Indeed, a common assumption in the stress literature is that there is an optimal level of stress responsivity and that overly heightened or dampened SRS reactivity is dysfunctional and tends to undermine emotional and behavioral regulation (e.g., Evans & English, 2002). This purported biological dysregulation of the SRS is typically interpreted in an allostatic load framework (e.g., Juster, McEwen, & Lupien, 2010), whereby the wear and tear of chronic stress is presumed to impair SRS functioning (see extended discussion below). Although the allostatic load model (ALM) has proven useful in predicting health-related endpoints, it is not consilient with current theory and research from evolutionary biology. The key limitation of the ALM and related theories (e.g., toxic stress, Shonkoff & Bales, 2011) that employ a pathology lens is that they do not provide a theory of adaptive individual differences in physiological mediators and related patterns of social and physical development. As an alternative approach, we present the adaptive calibration model of stress responsivity (ACM; Del Giudice et al., 2011; Ellis & Del Giudice, 2014). We begin by reviewing concepts of developmental programming and adaptive calibration more generally. We then summarize key ACM concepts, including the theory of biological sensitivity to context, upon which the ACM builds, and discuss implications for developmental psychopathology. At this juncture, 5 years after the original publication, we review the current empirical status of the ACM and highlight potential updates and revisions that may be needed going forward. We conclude by comparing the ACM and ALM explicitly, arguing that the field needs to expand beyond allostatic load to incorporate an adaptive calibration framework that addresses the functional role of stress response systems in regulating alternative developmental pathways. Central to the ACM is the assumption that gaining a better understanding of the functional developmental changes that occur under stressful conditions will enable us to gain a better understanding of the costs of these changes (e.g., allostatic load and its consequences) and thus develop more effective interventions for the crucial goals of risk prevention and management.

CONDITIONAL ADAPTATION AND MALADAPTATION Developmental exposures to stress have always been part of the human experience. For example, almost half of children in hunter-gatherer societies—the best model for human demographics before the agricultural revolution—died before reaching adulthood (Kaplan & Lancaster, 2003). Thus, from an evolutionary-developmental perspective, stressful rearing conditions, even if those conditions engender sustained stress responses that must be maintained over time, should not so much impair SRS functioning (“dysregulation” in the ALM) as direct or regulate it toward response patterns that are biologically adaptive (i.e., tend to increase an

The Adaptive Calibration Model of Stress Responsivity 239 individual’s fitness) under stressful conditions, even if those patterns are harmful in terms of the long-term welfare of the individual or society as a whole (e.g., Ellis, Boyce, Belsky, Bakermans-Kranenburg, & van IJzendoorn, 2011; Mead, Beauchaine, & Shannon, 2010). From an evolutionary perspective, there is no optimal level of stress responsivity; adaptation is context-specific. Consider the extensive experimental work conducted by Michael Meaney and colleagues, which shows that low-quality maternal care in rats (i.e., low levels of maternal licking and grooming) alters pups’ stress physiology and brain morphology. Although such changes seem disadvantageous (as indicated, for example, by higher corticosterone levels, shorter dendritic branch lengths, and lower spine density in hippocampal neurons), they actually enhance learning and memory processes under stressful conditions (e.g., Champagne et al., 2008; Oomen et al., 2010). Moreover, such physiological and morphological changes mediate the effects of maternal behavior on central features of defensive and reproductive strategies: behavior under threat, open-field exploration, play behavior, pubertal development, sexual behavior, and parenting (Cameron et al., 2005; Cameron et al., 2008; Franks, Champagne, & Curley, 2015). In total, enhanced learning under stressful conditions, increased fearful and defensive behaviors, accelerated sexual maturation, increased sexual behavior, and reduced parental investment in offspring apparently represent functional ways of developing when the young organism is neglected. In such contexts, neglect itself may be regarded as a behavioral mechanism through which rats guide their offspring’s development toward optimal survival and reproductive strategies under conditions of adversity. It would seem mistaken, therefore, to simply view diminished licking and grooming as “poor maternal care” or the development induced by such care as “disturbed,” even though this is how they are often characterized. From an evolutionary perspective, altered care provided by parents may (at least in part) function to prepare offspring to survive and reproduce under harsh ecological conditions.

Conditional Adaptation The evolutionary perspective thus emphasizes conditional adaptation: “evolved mechanisms that detect and respond to specific features of childhood environments, features that have proven reliable over evolutionary time in predicting the nature of the social and physical world into which children will mature, and entrain developmental pathways that reliably matched those features during a species’ natural selective history” (Boyce & Ellis, 2005, p. 290; for a comprehensive treatment of conditional adaptation, see West-Eberhard, 2003). From this perspective, variation in SRS functioning results largely from individuals tracking different environmental conditions and altering their SRS profiles to match those conditions in ways that are likely to enhance survival and reproductive success. For conditional adaptations to evolve, the fitness of the alternative phenotypes must be predictable on the basis of reliable cues that can be observed by the

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individual (Pigliucci, 2001). Reliable cues to adversity are especially relevant because they may signal the need to develop a secondary (alternative) phenotype that is adversity-adapted, with resulting benefits and costs that are often reflected in health trade-offs. For example, tadpoles (Rana sylvatica) alter their size and shape based on the presence of dragonfly larvae in their rearing environment (Van Buskirk & Relyea, 1998). These alterations involve development of smaller and shorter bodies and deep tail fins. Although tadpoles that do not undergo these morphological changes are highly vulnerable to predation by dragonflies, those that do but end up inhabiting environments that are not shared with dragonflies have relatively poor developmental and survival outcomes. In short, the predator-induced phenotype is only conditionally adaptive. This process highlights that, in many cases, natural selection favors a primary phenotype that yields high payoffs under favorable circumstances and a secondary phenotype that “makes the best of a bad situation” (West-Eberhard, 2003). Developmentally, conditional adaptation is often implemented through physiological and neurobiological “switches,” or mechanisms that integrate environmental and genetic information to steer developmental trajectories along alternative trajectories. Developmental switch points are junctures during which those mechanisms become activated; they are typically located at the transition between different life stages and are regulated by hormonal signals (see Del Giudice, 2014; Ellis, 2013; West-Eberhard, 2003). For example, puberty is a critical switch point in the development of sexual, reproductive, and social behavior, including individual and sex differences in risk taking (Ellis et al., 2012).

The Meaning of Adaptive The foregoing discussion highlights that the term adaptive has different meaning when viewed from an evolutionary perspective (with its functional lens) versus a public health or standard psychological perspective (with its pathology lens; see also Ellis et al., 2012; Mead et al., 2010). Because evolution by natural selection is driven by differences among individuals in reproductive success, the evolutionary significance of any behavior, or its “adaptive value,” depends ultimately on its costs and benefits with respect to the organism’s fitness (i.e., the contribution of offspring to future generations). Even high-risk behaviors that result in net harm in terms of a person’s own well-being or long-term survival (e.g., producing miserable feelings or a shortened life), the welfare of others around them, or the society as a whole can still be adaptive in an evolutionary sense. Consider, for example, risky behaviors that expose adolescents to danger and/or inflict harm on others but increase dominance in social hierarchies and leverage access to mates (Ellis et al., 2012). Yet from a public health perspective, different patterns of behavior are regarded as “adaptive versus maladaptive” depending on the extent to which they promote versus threaten people’s health, development, and safety. Adaptive developmental outcomes are thus equated with “desirable” outcomes (as defined by dominant Western values;

The Adaptive Calibration Model of Stress Responsivity 241 e.g., health, happiness, secure attachment, high self-esteem, emotion regulation, educational and professional success, stable marriage), whereas maladaptive developmental outcomes are equated with “undesirable” outcomes constituting the opposite poles of these traits and variables. For the remainder of this paper, we use “adaptive” only in the evolutionary sense of the term. In contrast, the word “desirable” is used to connote outcomes that are typically viewed as “adaptive” from a public health perspective. That adaptive is not equivalent to desirable is an important distinction: It clarifies that hypotheses rooted in evolutionary biology do not, by default, imply that adaptations are “good” or should never be targeted for intervention. The use of evolutionary models, however, allows for adaptations to be precisely targeted based on environmental inputs and their developmental consequences.

Maladaptation The converse of adaptation is maladaptation. Biological maladaptation can occur for many reasons. Sometimes, an evolved mechanism ceases to perform its intended function because of, for example, harmful genetic mutations, accidents, or manipulation by other organisms (e.g., pathogens). Even when biological mechanisms perform normally, an organism may develop a phenotype that is poorly suited for its environment and as a consequence experiences a diminution in fitness (often accompanied by other “undesirable” outcomes). Thus, maladaptation is closely connected to the concept of developmental miscalibration or mismatch (see Frankenhuis & Del Giudice, 2012, for an extended discussion). There are a number of causes of such developmental miscalibration or mismatch. First, an individual may experience novel environments that are outside the range recurrently encountered over evolutionary history. In this case, all developmental bets are off and the person may experience abnormal outcomes. For example, Romanian or Ukrainian orphanages (Dobrova-Krol, Van IJzendoorn, Bakermans-Kranenburg, & Juffer, 2010; Nelson et al., 2007) constitute genuinely substandard, novel environments that are beyond the normative range of conditions encountered over human evolution. Children’s brains and bodies simply could not have been selected to respond adaptively to collective rearing by paid, custodial, non-kin caregivers providing minimal human contact (Hrdy, 1999). Exposures to such challenging and (evolutionarily) unprecedented conditions are likely to induce pathological development rather than evolutionarily adaptive strategies. Second, individuals may become maladapted to their environments because of a lack of behavioral plasticity. For example, one of the responsivity profiles highlighted by the ACM is the unemotional pattern (described in detail below); this pattern is characterized by low susceptibility to environmental influence (i.e., dampened physiological stress reactivity), which generally inhibits social learning and sensitivity to social feedback. One hypothesized pathway here is a genetic disposition toward SRS hypoarousal. Such a disposition could translate into a wide

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distribution of unemotional phenotypes across a range of familial and ecological conditions, including supportive and well-resourced rearing environments (Del Giudice, Hinnant, Ellis, & El-Sheikh, 2012). Maladaptation may occur in this context because unemotional phenotypes are relatively unsusceptible to environmental influence and thus may not adjust their behavioral strategies to match the high levels of support and resources that might be available to them (e.g., they may not adequately detect positive opportunities and learn to capitalize on them, such as seeing a teacher as a prospective mentor or taking advice from a loving parent; and/or they may develop a manipulative, antagonistic social strategy when trust and cooperation would better fit their social context). In total, increased probability of mismatch is a clear cost of low developmental plasticity. Third, mismatch can occur because the validity of environmental cues that guide conditional adaptation is limited spatially, so such cues become invalid in other contexts. For example, according to developmental models based on life history theory (LHT), children’s brains and bodies tend to respond to dangerous or unpredictable environments by growing up fast and “living for the here and now” (e.g., Belsky, Steinberg, & Draper, 1991; Ellis, Figueredo, Brumbach, & Schlomer, 2009). This “get it while you can” strategy often translates into high-risk activities such as early initiation of sexual behavior, greater numbers of sexual partners, violence, and, in contemporary societies, behaviors such as substance use and risky driving. These high-risk strategies may only be locally adaptive, however. Research by Gibbons et al. (2012) on African American males is instructive in this context. Youth who are exposed to greater stress while growing up (e.g., more dangerous neighborhoods, lower quality parental investment, greater racial discrimination) develop “fast” life history strategies that may be adaptive in their local context (e.g., participation in risky behaviors that leverage positions in dominance hierarchies, increased access to mates) but clearly undesirable—and possibly biologically maladaptive—in wider American society (e.g., dropping out of school, high rates of arrest and incarceration). A similar logic may apply to effects of early stress on cognitive processes (Frankenhuis & de Weerth, 2013). Fourth, mismatch can occur because the validity of environmental cues that guide conditional adaptation is temporally limited, so that those cues may become invalid at later times. One hypothesis is that individuals calibrate to environmental parameters early in life, even prenatally. When these values differ from those experienced later in life, normative processes of developmental plasticity can become maladaptive, resulting in a mismatched phenotype with increased likelihood of physical health problems (e.g., Gluckman, Low, Buklijas, Hanson, & Beedle, 2011). For instance, prenatal exposure to undernutrition may result in development of metabolic processes designed to retain and store insulin and fatty acids (Barker, 1994). However, if resources are plentiful in the postnatal environment, the individual may be at increased risk for obesity and metabolic syndrome throughout life. This hypothesis is supported by data showing that detrimental effects are often absent when the postnatal environment continues to be lacking in resources

The Adaptive Calibration Model of Stress Responsivity 243 (Stanner & Yudkin, 2001), suggesting that mismatch (rather than undernutrition per se) may be the root cause. Finally, mismatch can occur due to a restricted range of niches that undermine the ability of organisms to choose environments that match their phenotypes. For example, in a study of semi–free ranging rhesus macaques (Boyce, O’Neill-Wagner, Price, Haines, & Suomi, 1998), the troop lived in a 5-acre wooded habitat in rural Maryland, on the grounds of the National Institutes of Health Primate Center. In 1993, the troop encountered a 6-month period of protective confinement to a small, 1,000-square-foot building, during a construction project on the habitat grounds. The confinement proved highly stressful, however, and the incidence of violent injuries increased fivefold during the 6-month period. During this period, when behavioral strategies available to troop members were severely curtailed, monkeys previously characterized as high in biobehavioral reactivity to stress suffered dramatically higher rates of violent injuries than their less reactive peers. In the free-ranging wooded habitat, however, where a wide range of behavioral strategies could be used, including escape from conflict, highly reactive monkeys suffered comparatively low rates of violent injury. In summary, processes of conditional adaptation and phenotype-environment matching are fallible, and a number of circumstances can lead to maladaptation. Understanding this set of circumstances can be critical to understanding the developmental origins of psychopathology. More importantly, these forms of maladaptation are comparatively rare; the organism most commonly responds to environmental conditions by adapting to its local circumstances, regardless of whether this adaptive process is desirable for the individual or society.

FUNCTIONS OF THE STRESS RESPONSE SYSTEM Environmental events that signal threats to survival or well-being produce a set of complex, highly orchestrated responses within the neural circuitry of the brain and peripheral neuroendocrine pathways that regulate metabolic, immunologic, and other physiological functions. The SRS comprises primarily three anatomically distinct systems: the PNS and SNS branches of the autonomic nervous system, and the LHPA axis. Activity of these systems is integrated and cross-regulated, so they can be considered as partially independent yet interrelated components of a coordinated functional system, despite being anatomically distinct and physiologically diverse (e.g., Boyce & Ellis, 2005; Porges, 1995; Schlotz et al., 2008). All the components of the SRS are regulated by top-down cognitive and affective processes; conversely, SRS activation modulates brain activity at multiple levels (through direct neural connections and indirect hormonal effects) in a neuroendocrine feedback loop. Additional components of the SRS may be discovered as neurobiological methods become more sophisticated, as long as—following the ACM—the component (a) coordinates the organism’s allostatic response to physical and psychosocial

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challenges; (b) encodes and filters information from the environment, thus mediating the organism’s openness to environmental inputs; and (c) functions to shift physical or behavioral endpoints. Epigenetic, cellular, immune, or neuropeptiderelated processes may, for example, emerge as SRS components. This does not imply that all new neurobiological measures index components of the SRS. Without these three criteria, new measures may instead be better conceptualized as moderators of the SRS or substrates of other systems. Here we focus on the most common SRS components. In the absence of stress, the PNS promotes vegetative functions (i.e., rest and restorative behavior), inhibits cardiac activity and cardiac output, and enables sustained attention as a consequence of regulatory mechanisms that occur in the prefrontal cortex (see Beauchaine & Thayer, 2015; Del Giudice et al., 2011; Porges, 2007). When a stressor is encountered, the PNS responds quickly by withdrawing this inhibitory influence (i.e., vagal withdrawal), allowing the excitatory SNS to operate unopposed, which results in rapid increases in cardiac output to cope with the stressor (Lovallo & Sollers, 2007). PNS withdrawal promotes rapid, flexible responding to stress and coping with mild to moderate stressors (such as solving a difficult puzzle). More extreme defense reactions associated with freezing and fainting also involve changes in PNS activity, albeit via different brainstem nuclei and efferent fibers (Porges, 2007). In most stressful situations, ranging from mild to severe, increases in cardiac output are effected via coupled PNS withdrawal and SNS activation. However, SNS effects are delayed by a few seconds because they are mediated through a second messenger system. PNS withdrawal and SNS activation also facilitate fight/flight responses via noradrenergic innervation of visceral organs and a slower, hormonal pathway through innervation of the adrenal medulla (e.g., Goldstein & Kopin, 2008; Gunnar & Vazquez, 2006). Following SNS activation, the adrenal medulla secretes epinephrine (E) and norepinephrine (NE) to increase heart rate, respiration, blood supply to skeletal muscles, and glucose release in the bloodstream. The third component of the SRS is the LHPA axis, which mounts more delayed, long-term responses to environmental challenge (although traditional distinctions between rapid and delayed responding have become increasingly blurred; Joëls & Baram, 2009). The endpoint of the LHPA response is cortisol release by the adrenal cortex, typically within 5 minutes after the triggering event, with a cortisol peak between 10 and 30 minutes (Sapolsky, Romero, & Munck, 2000). The main effects of cortisol release are to (a) mobilize physiological and psychological resources (e.g., energy release, alertness and vigilance, memory sensitization; e.g., Flinn, 2006; van Marle, Hermans, Qin, & Fernández, 2009), and (b) counterregulate physiological effects of SNS activation, thereby facilitating stress recovery (Munck, Guyre, & Holbrook, 1984). Joint effects of the SNS and LHPA axis are complex (Hastings et al., 2011) and they can be synergistic (especially in the short term) or antagonistic (especially at later phases of responding).

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Biological Sensitivity to Context The foregoing summary of the SRS provides a brief description of how peripheral neuroendocrine responses prepare the organism for challenge or threat. However, according to the theory of Biological Sensitivity to Context (BSC; Boyce & Ellis, 2005), these “stress response” systems also function to increase susceptibility to resources and support in the ambient environment (e.g., positive social opportunities, cooperative information; see also Porges, 1995, 2007). This dual function signifies a need to conceptualize stress reactivity more broadly as biological sensitivity to context, which Boyce and Ellis (2005) defined as neurobiological susceptibility to both cost-inflicting and benefit-conferring features of the environment—operationalized biologically by heightened reactivity in one or more components of the stress response system (PNS, SNS, LHPA). Depending on levels of nurturance and support versus harshness and unpredictability in their developmental environments, highly reactive children experience either the best or the worst of psychiatric and biomedical outcomes within the populations from which they are drawn (reviewed in Ellis et al., 2011). BSC theory therefore posits that individual differences in the magnitude of biological stress responses function to regulate openness or susceptibility to environmental influences, ranging from harmful to protective (see Sijtsema et al., 2013, for a review and critical analysis of BSC assumptions). Given past evidence that early trauma increases stress reactivity and newer evidence that high reactivity may enhance developmental functioning in highly supportive settings, Boyce and Ellis (2005) postulated a curvilinear, U-shaped relation between levels of early support-adversity and the magnitude of biological response dispositions. They hypothesized that (a) exposure to acutely stressful childhood environments upregulates BSC, increasing the capacity and tendency of individuals to detect and respond to environmental dangers and threats; (b) exposure to especially supportive childhood environments also upregulates BSC, increasing susceptibility to social resources and support; and (c) by contrast, and typical of the majority of children, exposure to childhood environments that are not extreme in either direction downregulates BSC, buffering individuals against chronic stressors in a world that is neither highly threatening nor consistently safe. Exploratory analyses in two studies offered confirmatory evidence that the lowest rates of high-reactivity phenotypes are found in conditions of moderate stress, and that both tails of the support-adversity distribution are associated with higher proportions of reactive children (Ellis et al., 2005; see also Bush, Obradovic, Adler, & Boyce, 2011; Gunnar, Frenn, Wewerka, & Van Ryzin, 2009). Although BSC theory has helped move the field toward a new conceptualization of stress responsivity, it has a number of significant limitations. First, BSC theory does not systematically link different stress reactivity patterns to functional variation in behavior, such as individual differences in social and reproductive behaviors that are specified by LHT. Second, although BSC theory advances a general developmental prediction (the U-shaped curve), it does not model the developmental

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trajectories leading to individual differences in a more fine-grained way (e.g., by discussing the development of stress responsivity at different life stages and identifying “switch points” when plasticity is preferentially expressed). Third, BSC does not address the adaptive meaning and developmental origins of sex differences in responsivity. Fourth, BSC focuses on explaining heightened reactivity to stress and does not afford a theory of hypoarousal (or dampened reactivity), in terms of its development or functional significance. Fifth, BSC does not address the development or functions of basal (tonic) levels of activity of the SRS. Finally, BSC theory does not advance discriminative predictions regarding PNS, SNS, and LHPA. The ACM, an extension and refinement of BSC, was formulated to address these issues.

The Adaptive Calibration Model of Stress Responsivity Goals of the ACM are to provide (a) a coherent, systematic account of the biological functions of the SRS; (b) a theory of individual differences capable of explaining adaptation of stress physiology and behavior to local environmental conditions; and (c) a functionally valid taxonomy of stress response profiles, including neurobiological correlates (e.g., serotonergic function), behavioral correlates (e.g., aggression, self-regulation), and developmental trajectories, integrating across baseline activity and responsivity measures of the SRS (Del Giudice et al., 2011). Achieving these goals would enable scientists to move beyond the inductive theory building that now dominates the field and increase their ability to advance targeted hypotheses about individual differences and their development. The ACM has its main theoretical foundations in LHT, an evolutionary biological framework for describing developmental “decisions” of organisms and their allocation of resources over the life course (Ellis et al., 2009; Del Giudice, Gangestad, & Kaplan, 2015), as well as the theory of adaptive developmental plasticity (West-Eberhard, 2003). In the ACM, individual differences in SRS functioning are thought to result, at least in part, from the operation of evolved mechanisms that match the individual’s physiology and behavior to local environmental conditions (i.e., calibration to the environment). Thus, patterns of stress responsivity are seen as generally adaptive in the biological sense, as they function in a way that ultimately tends to maximize the individual’s survival and reproduction in specific environmental contexts. The ACM can be summarized in seven points (see Del Giudice et al., 2011, for complete explication of the model, and Ellis & Del Giudice [2014] for extended discussion of its theoretical background). The first three points make broad statements about the functions of the SRS which constitute the backbone of the model: 1. The SRS has three main biological functions: to coordinate the organism’s allostatic response to physical and psychosocial challenges; to encode and filter information from the environment, thus mediating the organism’s openness to environmental inputs; and to regulate a range of life history-relevant traits and behaviors.

The Adaptive Calibration Model of Stress Responsivity 247 2. The SRS works as a mechanism of conditional adaptation, regulating development of alternative life history strategies (i.e., suites of reproductively relevant traits such as sexual maturation, intrasexual competitive behaviors and risk taking, and patterns of mating and parenting). Different patterns of baseline activity and responsivity in early development modulate differential susceptibility to environmental influence and shift susceptible children on alternative pathways, leading to individual differences in life history strategies. 3. Activation of autonomic, neuroendocrine, metabolic, and immune system responses during the first years of life (including the prenatal phase) provides crucial information about life history–relevant dimensions of the child’s environment, especially danger and unpredictability (see Ellis et al., 2009). This information is used to adaptively regulate stress responsivity and associated development of life history strategies. The following four points rely on additional assumptions about the behavioral correlates of SRS functioning to make specific predictions about the development of individual differences: 4. At a general level, a nonlinear relation exists between exposures to environmental stress during development and optimal levels of stress responsivity (see Figure 8.1). This nonlinear relation gives rise to four prototypical responsivity patterns (labeled sensitive [I], buffered [II], vigilant [III], and unemotional [IV]). The four patterns constitute combinations of physiological parameters indexing functioning of the PNS, SNS, and LHPA axis and include neurobiological indicators, behavioral outcomes, and developmental trajectories. 5. Sensitive and vigilant individuals display relatively high responsivity to the environment, whereas buffered and unemotional individuals display relatively low responsivity. Although comparisons between the two patterns of high responsivity (sensitive vs. vigilant) and the two patterns of low responsivity (buffered vs. unemotional) show substantial convergence in SRS baseline activity and responsivity (Figure 8.1), there is marked divergence in both antecedent environmental conditions and behavioral outcomes. 6. Because of sex differences in optimal life history strategies, sex differences are expected in the distribution of responsivity patterns and in their specific behavioral correlates. Sex differences should become more pronounced at increasing levels of environmental stress; in particular, contexts characterized by severe/traumatic stress should favor the emergence of a male-biased pattern of low responsivity (the unemotional pattern) and a female-biased pattern of high responsivity (the vigilant-withdrawn pattern). 7. Prenatal and early postnatal development, the transition from early to middle childhood, and puberty are likely “switch points” for calibration of stress responsivity. Individual and sex differences in SRS functioning emerge according to the evolutionary functions of each developmental stage.

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Vulnerabilities and Risk Factors for Psychopathology Life history strategy Slower

Faster

High

III Vigilant

agonistic ♂ withdrawn ♀

♀

Responsivity

I Sensitive

II Buffered IV Unemotional ♂

Low Low stress, safe environment

Moderate stress

Dangerous/unpredictable environment

Severe/traumatic stress

Developmental Context

Figure 8.1 Predicted curvilinear relation between developmental context and optimal levels of stress responsivity. Developmental context refers to variation in rearing experiences (i.e., individual differences in developmental exposures to key dimensions of environmental stress and support). The figure does not imply that all components of the SRS will show identical responsivity profiles, nor that they will activate at the same time or over the same time course. Male/female symbols indicate sex-typical patterns of responsivity, but the model also predicts substantial within-sex variation. Adapted from Del Giudice, Ellis, and Shirtcliff, 2011, p. 1577.

ENVIRONMENTAL INFORMATION A crucial function of the SRS is to collect and integrate information about changing states in the environment—including presence of threats, dangers, and opportunities—to adjust the state of the whole organism accordingly. This information can be encoded by the SRS in its functional parameters and, in the long run, provides the organism with a “statistical summary” of key dimensions of the environment. In the ongoing process of physiological adjustment, the system’s level of responsivity acts as an amplifier (when highly responsive) or filter (when unresponsive) of various types of contextual information. In this section we consider this function of the SRS

The Adaptive Calibration Model of Stress Responsivity 249 in more detail, and take a closer look to ecological information that can be encoded through repeated SRS activation.

Key Dimensions of the Environment The conceptualization of key dimensions of environmental influence in the ACM is based on LHT—a general framework for understanding biological trade-offs involved in development, such as those between growth and reproduction, current and future reproduction, and quality and quantity of one’s offspring. According to LHT (Charnov, 1993; Stearns, 1992), variation in life history traits results from trade-offs in allocation of resources to competing life functions: bodily maintenance, growth, and reproduction. Because of structural and resource limitations, organisms cannot maximize all components of fitness simultaneously and instead are selected to make trade-offs that prioritize resource expenditures, so that greater investment in one domain occurs at the expense of investment in competing domains. For example, resources spent on an inflammatory host response to fight infection cannot be spent on reproduction. Thus, the benefits of an inflammatory host response are traded off against the costs of lower fertility. Each trade-off constitutes a decision node in allocation of resources, and each decision node influences the next decision node (opening up some options, foreclosing others), in an unending chain over the life course (Ellis et al., 2009). At the broadest level, these trade-offs result in covarying sets of traits (i.e., life history strategies) that generally fall along a dimension of “slow” versus “fast.” Fast life history strategies are comparatively high risk and present oriented (taking benefits opportunistically with little regard for long-term consequences) and prioritize mating effort (e.g., competitive risk taking, aggression); they are also characterized by earlier ages of sexual development and reproduction, and focus on producing a greater number of offspring with less investment of resources, time, and energy in each. In contrast, slow life history strategies are comparatively long-term oriented and low risk (e.g., longer time horizons, more delay of gratification, better self-regulation and behavioral control), characterized by later timing of sexual development and reproduction, and focus on producing a smaller number of offspring and investing heavily in each of them. As discussed below, trade-offs incurred by the fast strategy include reduced health, vitality, and longevity—of self and offspring. Most important for the present discussion, LHT can be used to predict how organisms adjust their life history strategies according to ecological conditions. Key dimensions of the environment relevant to life history development are availability of resources, extrinsic morbidity-mortality (i.e., external sources of disability and death that are relatively insensitive to the adaptive decisions of the organism), and predictability of environmental change. Energetic resources—caloric intake, energy expenditures, and related health conditions—set the baseline for development, slowing growth and delaying sexual maturation and reproduction under energetic stress (i.e., favoring a slow life history strategy). When bioenergetic resources

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are adequate to support growth and development, however, cues to extrinsic morbidity-mortality and unpredictability gain importance (Ellis et al., 2009). In this context, LHT predicts that individuals will respond to extrinsic morbidity-mortality cues (e.g., exposures to violence, premature disability, death of people around you) and unpredictability (e.g., stochastic changes in ecological context, resource availability, family composition) by entraining faster life history strategies (see Belsky, Schlomer, & Ellis, 2012; Simpson, Griskevicius, Kuo, Sung, & Collins, 2012, for supporting longitudinal data). Developmental models based on LHT emphasize that these ecological factors tend to operate indirectly on children through more proximal processes, including those mediated by family characteristics (e.g., harsh parental discipline vs. warm and supportive parenting behaviors, family chaos vs. routines). For example, parental investment can buffer the impact of extrinsic mortality cues and heighten controllability or predictability by providing a stable, caregiving environment. Indeed, much of the effect of “toxic stress” on children’s development works through the mechanism of both exposure and failure of supportive parental relationships to buffer the child from stress exposure (Shonkoff & Bales, 2011). The SRS is attuned exquisitely to life history–relevant features of the environment. Of particular interest, the level of extrinsic morbidity-mortality is conveyed both by frequent SNS activation (signaling a potentially dangerous ecology) and by repeated LHPA activation. Because it responds strongly to uncontrollable challenges and novel situations, the LHPA axis also encodes information about environmental unpredictability/uncontrollability, thus giving LHPA functioning a central role in regulating life history strategies (see Del Giudice, et al., 2011). Across development, environmental information collected by the SRS (in interaction with the child’s genotype) canalizes physiological and behavioral phenotypes to match local ecological contexts.

The SRS as an Information Filter/Amplifier If the SRS encodes environmental information as an aggregation of repeated responses to challenge, it follows that SRS responsivity can function as an information filter. Low SRS responsivity results in a number of potential costs (e.g., reduced alertness, reduced sensitivity to social feedback) and potential benefits (e.g., resource economization, avoidance of immune suppression). In contrast, a highly responsive SRS amplifies signals coming from the environment and maximizes the chances that the organism will be modified by current experience. Potential costs of a highly responsive SRS include adverse physiological events, hypersensitivity to social feedback, and exposure to psychological manipulation. In addition, the organism’s action plans can get interrupted easily by minor challenges, and the ability to deal with future events may be reduced if physiological resources are already overwhelmed. On the other hand, a highly responsive system facilitates social learning and social bonding, enhances mental activities in localized domains,

The Adaptive Calibration Model of Stress Responsivity 251 focuses attention, and primes memory storage, thus tuning cognitive processes to opportunities and threats in the environment. Empirical studies (e.g., Pruessner et al., 2010) illustrate how SRS thresholds for responding to environmental stimuli differ dramatically from one person to another. It is also intriguing that such thresholds may show domain specificity, as when challenges related to competition or achievement are more salient for males but challenges related to social exclusion or rejection are more salient for females (Stroud, Salavey, & Epel, 2002; Stroud et al., 2009). Moreover, sex is not the only individual difference factor capable of influencing which domain shows a low threshold for activation (e.g., Wobber et al., 2010). Close social relationships can also filter/amplify more distal environmental factors, such as when cortisol reactivity is buffered by the presence of a warm, supportive caregiver (Hostinar & Gunnar, 2013a; Hostinar, Johnson, & Gunnar, 2015). Although ACM terminology tends to emphasize the role of responsivity, components of the SRS operate at both state (situation-specific) and trait (basal) levels. Basal functioning indicates a level of physiological preparedness or anticipation of the individual’s context (Pruessner et al., 2010), exerting a permissive effect on the individual’s ability to respond to novel events and encode environmental information (e.g., Gunnar & Quevedo, 2007). It may also provide a rough index of physiological accumulation of prior stressful events. High basal SRS activity is expected when the individual anticipates or needs to be engaged, aroused, or active in that context. High basal activation of the PNS, which reflects upstream regulation from prefrontal areas, promotes calm, concentration, and self-regulation (e.g., Beauchaine & Thayer, 2015; Fabes and Eisenberg, 1997; Porges, 2007), whereas high SNS baseline relates to anxiety (El-Sheikh, Erath, Buckhalt, Granger, & Mize, 2008), and baseline cortisol secretion regulates energy mobilization and engagement with the physical and social environment (Booth, Granger, & Shirtcliff, 2008). This role of the SRS in relation to anticipation is emphasized, for example, in an extensive literature demonstrating high cortisol reactivity in contexts characterized by unpredictability (Dickerson & Kemeny, 2004). Empirical findings that cortisol levels elevate prior to laboratory arrival (e.g., Ellis, Essex, & Boyce, 2005; Hastings et al., 2011) or in anticipation of challenges of the day (e.g., Fries, Dettenborn, & Kirschbaum, 2009; Schmidt-Reinwald et al., 1999) bolster the interpretation that basal SRS activity serves an anticipatory or preparatory function. Over time, repeated SRS responses to environmental challenges may accumulate, so that state-specific activity patterns become biologically embedded as part of the individual’s trait-like functional parameters (Shirtcliff, Granger, Booth, & Johnson, 2005). Basal functioning of the SRS achieves set-points that calibrate the individual’s physiology with the expected environmental demands, but as the environment changes, so too may the optimal set-point (McEwen & Wingfield, 2003). This process implicates one of the most important functions of the SRS: to change according to anticipated or current context, using those changes to optimize physiological functioning for the expected future conditions.

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Implications for Developmental Psychopathology Looking at the SRS through the lens of information filtering and encoding provides useful insights into the developmental processes that ultimately lead to psychopathological outcomes. First, and foremost, this reconceptualization of SRS functioning as a mechanism of susceptibility to environment influence (Boyce & Ellis, 2005) helps to explain bivalent effects of stress responsivity on mental and physical health, whereby highly reactive children experience either the best or the worst of psychiatric and biomedical outcomes depending on levels of stress and support encountered over development (see above, BSC). A radical implication of this theory is that the very children whose heightened responsivity appears to make them vulnerable to developing psychopathology may also benefit most from positive, supportive environments and interventions. Thus, the very qualities that appear to increase children’s frailties may also constitute their strength given supportive contexts, thus inspiring the metaphor of “orchid children” (Boyce & Ellis, 2005). In addition, LHT delineates basic dimensions of environmental stress and support—underscoring resource availability, morbidity/mortality risk, and unpredictability as key dimensions of the environment that regulate development of SRS responsivity patterns and their behavioral correlates (see the next section). This has already proved a valuable tool in empirical research (e.g., Belsky et al., 2012; Simpson et al., 2012), given the confusing abundance of environmental/contextual variables that might be measured and correlated with developmental outcomes. Furthermore, LHT provides organizing principles needed to understand the broad network of interactions between the SRS and other physiological response systems, such as the immune system (see Miller, Chen, & Parker, 2011). Another important implication of the concepts reviewed in this section is that both high and low SRS responsivity can be adaptive precisely because they modulate the organism’s openness to environmental information. As discussed earlier, there is no optimal level of responsivity; rather, the value of high versus low informational openness varies depending on local ecologies, and in some cases an unresponsive system can be highly functional in the context of an individual’s life history strategy. This idea will be developed in the next section.

PATTERNS OF RESPONSIVITY The ACM builds on the theoretical principles outlined in the previous sections to derive a taxonomy of four prototypical responsivity patterns. Each pattern describes an integrated mode of SRS functioning, life history–relevant behavioral tendencies, and plausible neurobiological correlates. Three of the patterns correspond to regions on the U-shaped curve of the BSC theory; the fourth pattern is a novel addition, and accounts for the development of hypoarousal in severely stressful conditions.

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The Logic of Hypoarousal Some individuals show a persistent pattern of markedly reduced SRS basal activity and responsivity, even following stimuli that elicit strong physiological reactions in most people. So-called hypoarousal or hyporesponsivity is reliably associated with externalizing behaviors, conduct disorders, and psychopathic traits (especially from middle childhood on; e.g., Ortiz, & Raine, 2004), which makes it especially interesting from the perspective of developmental psychopathology. Hypoarousal is usually treated as a sign of physiological dysregulation (e.g., Lupien et al., 2006); interestingly, chronic early adversity can lead to both hyper- and hyporesponsivity of the SRS (e.g., Gustafsson, Anckarsäter, Lichtenstein, Nelson, & Gustafsson, 2010; De Bellis et al., 1999; Tarullo & Gunnar, 2006; Yehuda, 2002). The ACM suggests that dampened responsivity may actually follow an adaptive logic, as a way to maximize fitness benefit/cost ratios in severely dangerous and unpredictable environments. When danger becomes severe, engaging in high levels of risk taking (e.g., antagonistic competition, impulsivity, and extreme discounting of the future) can become the optimal response from an evolutionary perspective (see Ellis et al., 2012). Note that such strategies require outright insensitivity to threats, dangers, and social feedback. An unresponsive SRS has a higher threshold for letting environmental signals in: many potential threats will not be encoded as such, and many potentially relevant events will fail to affect physiology to a significant degree. For an extreme risk-taker, however, informational insulation from environmental signals of threat can be an asset, not a weakness (see also Korte et al., 2005). In particular, adopting an exploitative/antisocial interpersonal style requires one to be shielded from social rejection, disapproval, and feelings of shame (all amplified by heightened LHPA responsivity). In summary, generalized low responsivity can be evolutionarily adaptive (i.e., fitness maximizing) at the high-risk end of the environmental spectrum, despite possible negative consequences for the social group and for the individual’s subjective well-being. This type of chronic low responsivity should be carefully distinguished from temporary “exhaustion” periods, usually arising after prolonged SRS activation in highly responsive individuals exposed to enduring stressors (Miller, Chen, & Zhou, 2007).

The Logic of Sex Differences In sexually reproducing species, the two sexes differ predictably on life historyrelated dimensions. They are thus expected to use different strategies in response to the same environmental cues (e.g., Geary, 2002; James, Ellis, Schlomer, & Garber, 2012). In mammals, including humans, males tend to engage in higher mating effort and lower parental effort than females (Geary, 2002; Kokko & Jennions, 2008; Trivers, 1972). In addition, males usually undergo stronger sexual selection, i.e., their reproductive success is more variable than that of females,

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leading to higher risk propensity (Trivers, 1972; see also Frankenhuis & Del Giudice, 2012). The extent of sex differences in life history–related behavior, however, is not fixed but depends in part on the local environment. At the slow end of the life history continuum, both sexes tend to engage in high parental investment, and male and female interests largely converge on long-term, committed pair bonds. Thus, sex differences in behavior are thus expected to be relatively small. As environmental danger and unpredictability increase, males benefit by shifting to low-investment, high-mating strategies; females, however, do not have the same flexibility as they benefit much less from mating with multiple partners and incur higher fixed costs through childbearing. Thus, male and female strategies should diverge increasingly at moderate to high levels of danger/ unpredictability. In addition, sexual competition takes different forms in males and females, with males engaging in more physical aggression and substantially higher levels of risk-taking behavior. As life history strategies become faster, sexual competition becomes stronger, and sex differences in competitive strategies become more apparent. For these reasons, sex differences in responsivity patterns and/or in the associated behavioral phenotypes should be relatively small at low to moderate levels of environmental stress, and increase as the environment becomes more dangerous and unpredictable. In particular, we predicted that males should be more likely to develop unresponsive phenotypes in highly stressful contexts. Another possibility is that the behavioral correlates of high and low responsivity in dangerous environments may differ between the sexes. Finally, we do not expect sex differences in responsivity to be present from birth, but rather to emerge gradually during development, as social and mating competition become more biologically salient (see Del Giudice, 2014; Ellis, 2013).

The Four ACM Patterns It is now possible to present a brief outline of the four ACM patterns (see Del Giudice et al., 2011 for a detailed description). Each pattern represents a stable configuration of SRS activity. Sensitive Pattern (Type I). Sensitive patterns are hypothesized to develop in safe, predictable conditions and warm family environments. High stress responsivity among sensitive individuals increases their openness to social and physical environments. Physiological profiles of those with this pattern (high LHPA and PNS responsivity, moderate SNS responsivity) favor sustained but flexible attention and sensitivity to social feedback. Sensitive individuals are reflective, self- and other-conscious, and engaged with the environment. They are high in inhibitory control, delay of gratification, and executive function. These traits promote

The Adaptive Calibration Model of Stress Responsivity 255 sustained learning and cooperation. Other plausible correlates are high serotonergic function and slow sexual maturation (for details see Del Giudice et al., 2011). Buffered Pattern (Type II). Buffered patterns (marked by moderate to low SRS responsivity across the board) are predicted to develop preferentially in conditions of moderate environmental stress, where they strike a balance between costs and benefits of responsivity. Compared to Type III and IV patterns, buffered individuals should be lower in anxiety, aggression, and risk taking. Vigilant Pattern (Type III). Highly responsive vigilant patterns develop in stressful contexts, where they enable people to cope effectively with dangers and threats in the physical and social environment. Their SNS-dominated physiological profile mediates heightened attention to threats and high trait anxiety. Increased SRS responsivity in dangerous environments can be expected to co-occur with increased responsivity in other neurobiological systems. For example, hyperdopaminergic function may contribute to the vigilant phenotype by boosting attention to threat-related cues and fast associative learning (Gatzke-Kopp, 2011). In the ACM, vigilance is not associated with a single behavioral pattern but rather with a distribution of patterns involving different mixtures of aggressive/externalizing (“fight”) and withdrawn/internalizing (“flight”) behaviors. In males, vigilant responsivity should be associated more often with increased risk taking, impulsivity, agonistic social competition, and reactive aggression (the vigilant-agonistic subtype). In females, the typical pattern should involve social anxiety and fearful/withdrawn behavior (the vigilant-withdrawn subtype). Vigilant children who display high levels of both agonistic and withdrawn behaviors (typically females; Zahn-Waxler, Crick, Shirtcliff, & Woods, 2006) may be best described as belonging to a third subtype, the vigilant-agonistic/withdrawn pattern. Unemotional Pattern (Type IV). Unemotional patterns are marked by a profile of low stress responsivity across systems, with the possible exception of strong autonomic responses when facing immediate physical threats. Generalized unresponsivity inhibits social learning and sensitivity to social feedback; it can also increase risk taking by blocking information about dangers and threats in the environments. Predicted correlates of this pattern are low empathy and cooperation, impulsivity, competitive risk taking, and antisocial behavior, including high levels of proactive/instrumental aggression, especially in males. As explained above, we predicted the distribution of Type IV to be male-biased; moreover, we anticipated that behavioral correlates of this pattern would differ between sexes. For example, one key feature of unemotional responsivity among females may be a generalized pattern of aloof social relationships with parents, siblings, and peers. Low serotonergic activity is a likely neurobiological correlate of Type IV.

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Empirical Investigations of the ACM Responsivity Patterns Many empirical studies have attempted to link child and adolescent physiological profiles with the kinds of contextual factors and behavioral outcomes theorized in ACM (reviewed in Del Giudice et al., 2011; Obradovi´c, 2012; see also below, Implications for Developmental Psychopathology). Although not explicitly designed to test the ACM, some of these studies have used the model as a framework for interpreting their results (e.g., Essex et al., 2011; Peckins, Susman, Negriff, Noll, & Trickett, 2015). Most relevant, a small number of studies have attempted to test for the ACM responsivity profiles across multiple SRS subsystems. Del Giudice, Hinnant, Ellis, and El-Sheikh (2012) was the first explicit attempt to empirically validate the four-pattern classification of the ACM. In this study, which examined stress responsivity patterns in an at-risk sample of 8- to 10-year-old children, we identified four classes of autonomic nervous system activity during resting conditions and in response to a stressful task. SNS activity was indexed by skin conductance level and PNS activity was indexed by respiratory sinus arrhythmia. Physiological differences between the classes were dominated by SNS activity and (to a lesser extent) PNS basal activity. Furthermore, the four patterns were associated with different levels of family stress. Two components of environmental stress emerged as significant predictors of class membership: (1) negative family relationships and (2) family warmth/predictability. As predicted, high-responsivity and low-responsivity patterns were found under both low-stress and high-stress conditions. Although the study by Del Giudice et al. (2012) provided a first step toward testing the ACM responsivity patterns, it had several limitations. First, measures of physiological activity were limited to the autonomic nervous system; however, LHPA axis functioning is central to the ACM and needs to be taken into account when determining responsivity patterns. Second, Del Giudice et al. (2012) used the star-tracing task (a cognitive challenge) to elicit stress responsivity. Although the star-tracing task is a valid procedure, social-evaluative threats—and particularly exposure to challenging conditions that reliably elicit LHPA-axis activation—are necessary to obtain all of the responsivity data needed to classify individuals into the four responsivity patterns of the ACM. Finally, and most critically, Del Giudice et al. (2012) did not examine links between the identified responsivity patterns and indicators of life history strategy. Testing for these links is necessary to evaluate the theory, and especially to distinguish sensitive from vigilant phenotypes and buffered from unemotional phenotypes, which are hypothesized to display overlapping patterns of stress physiology but different life history strategies. Two studies since Del Giudice et al. (2012) have attempted to address some of these limitations. Both Quas et al. (2014; Peers and Wellness Study [PAWS]) and Ellis,

The Adaptive Calibration Model of Stress Responsivity 257 Oldehinkel, and Nederhof (in press; Tracking Adolescent Lives Study [TRAILS]) conducted a latent profile analysis (LPA) that incorporated all three SRS subsystems, assessed relations with environmental conditions, and elicited stress responses based on socio-emotional or social-evaluative threat. TRAILS also included indicators of life history strategy. These studies further differed from Del Giudice et al. (2012), and from each other, regarding age of the participants at the time of the stress physiology assessments (PAWS: 5 years of age; TRAILS: 16 years of age) as well as levels of environmental risk that characterized the samples (PAWS: moderate risk; TRAILS: low risk), and sex (TRAILS included only boys in the analyses). Given that the ACM is a developmental theory that posits changes in responsivity over child and adolescent development, differences in responsivity patterns under different levels of environmental stress and support, and sex differences, these three studies are inherently difficult to compare. Nonetheless, a discussion of similarities and differences between the results of these studies should provide a useful first step toward evaluating the ACM. The ACM predicts that a buffered pattern (without either hyperresponsivity or hyporesponsivity) emerges among most children who develop in normative environments that are not characterized by extremes of either nurturance and support or adversity and trauma. In all three empirical studies, the largest number of participants fit the buffered response pattern, displaying roughly average levels of psychosocial stress, stress responsivity, and (in TRAILS) behavioral indicators of life history strategy. TRAILS constituted a relatively low-risk sample, and the LPA placed about three quarters of its participants into the buffered profile (74%). In contrast, PAWS had more diverse socio-demographic and ethnic characteristics than TRAILS, and the LPA resulted in a buffered group with 52% of participants. Finally, the at-risk U.S. sample studied by Del Giudice et al. (2012) had a buffered group with only 45% of participants. Thus, there is emerging empirical support for the high prevalence of the buffered pattern among low-risk samples, as well as variation across samples in the relative proportion of this pattern depending on background stressor exposures. Consistent with the ACM, the LPAs of both the TRAILS and PAWS data sets resulted in two patterns of high stress responsivity: one profile characterized by heightened multisystem reactivity across PNS, SNS, and LHPA axis parameters and the other characterized by PNS-specific reactivity (i.e., strong vagal withdrawal). In the TRAILS analyses, the pattern of multisystem reactivity was labeled sensitive because it was characterized by significantly elevated scores on quality of family environment (i.e., more warmth/support and less stress/rejection in the family environment) and the lowest levels of aggressive/rule-breaking behavior (indicating a slow life history strategy), whereas the PNS-dominated responsivity pattern was labeled vigilant because it was characterized by the highest levels of prenatal/perinatal risk factors and childhood stress,

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the highest levels of depressed/withdrawn behavior, and moderately elevated levels of aggressive/rule-breaking behavior. In contrast, in the PAWS analyses, multisystem reactivity was labeled vigilant because it was associated with high family adversity. These opposing findings regarding the environmental contexts of multisystem reactivity will need to be addressed in future research. However, the two studies were markedly different, especially in the age of the participants (early childhood vs. adolescence) when stress responsivity was assessed. The substantial reorganization of neurobiological stress responses at puberty (Dahl & Gunnar, 2009; Forbes & Dahl, 2010), as emphasized in the ACM, may be especially relevant to explaining these divergent results. More generally, these initial findings call into question some of the original predictions of the ACM concerning the prevalence of SNS reactivity in vigilant pattern versus PNS reactivity in sensitive patterns (Del Giudice et al., 2011). Those predictions were based on the assumption that high PNS reactivity is a consistent marker of self-control and positive social engagement. However, this assumption may need some revision in light of later research showing that strong PNS withdrawal in response to emotional stimuli correlates with indices of behavioral problems (see Beauchaine, 2015; Beauchaine & Thayer, 2015). Moreover, tonic activity and reactivity of the PNS increase markedly with age from infancy to adulthood; PNS parameters in child and adolescent samples may be confounded with the rate of physical and sexual maturation (Beauchaine & Webb, in press; Graziano & Derefinko, 2013), which is especially problematic from the standpoint of evaluating life history models. Consistent with the ACM, the LPA of TRAILS data resulted in two responsivity patterns that were characterized by relatively high levels of environmental stress and faster life history strategies, with opposing patterns of stress responsivity. One of these profiles was characterized by high stress responsivity (the vigilant pattern, as described above) and the other by low stress responsivity (labeled unemotional); both were PNS dominated. The unemotional profile was associated with strong vagal augmentation, as well as low LHPA axis reactivity. This profile was clearly linked to a fast life history strategy (highest scores on aggressive/rule-breaking behavior; lowest scores on effortful control) and to low scores on withdrawn/depressed behavior. In addition, membership in this profile was predicted by low scores on quality of family environment and associated with elevated scores on various childhood adversity measures. Again, the centrality of the PNS in distinguishing these two higher-risk profiles highlights the need, as the ACM is further developed and revised, to more fully delineate the role of PNS activity, especially in relation to the vigilant profile. The contrast between vigilant and unemotional profiles converges with past developmental research showing that a pattern of strong vagal withdrawal in response to social or cognitive challenges (as in the TRAILS vigilant responsivity pattern) is associated with internalizing symptoms or co-occurring internalizing-externalizing behavior problems whereas weak vagal withdrawal or

The Adaptive Calibration Model of Stress Responsivity 259 vagal augmentation (as in the TRAILS unemotional responsivity pattern) is associated with externalizing behavior problems (Boyce et al., 2001; Calkins & Keane, 2004; Calkins, Graziano, & Keane, 2007; El-Sheikh, Hinnant, & Erath, 2011; Gazelle & Druhen, 2009; Hinnant & El-Sheikh, 2009). These relations are complex, however, and not always consistent, particularly when comparing clinical and normative samples (see Zisner & Beauchaine, in press). For example, Hinnant and El-Sheikh (2013) found that vagal augmentation in boys was associated with co-occurring high internalizing and high externalizing trajectories across middle to late childhood, and Pang and Beauchaine (2013) documented excessive vagal withdrawal specifically in response to an emotionally evocative video in 8- to 12-year-old children who were extremely high in conduct problems. In the ACM, both vigilant and unemotional patterns are associated with higher rates of externalizing behavior, but they reflect different patterns of SRS activity. One of the developmental hypotheses of the ACM is that boys who grow up under highly stressful conditions will initially display a vigilant profile of heightened stress responsivity—but following chronic severe stress, shift toward a male-biased pattern of low responsivity (the unemotional pattern) under the influence of adrenal androgens in middle childhood. This pattern is then expected to further intensify in adolescence in relation to the pubertal transition. Consistent with this prediction, a clear unemotional profile did not emerge in the PAWS analysis of 5-year-olds but did emerge in Del Giudice et al.’s (2012) analyses (8- to 10-year-olds) and in the TRAILS analysis (16-year-olds). This age trend converges with past research showing that, over the course of development from childhood to young adulthood, females with histories of child sexual abuse shift from initially upregulated to downregulated morning cortisol levels (Trickett, Noll, Susman, Shenk, & Putnam, 2010), and to blunted feedback of the HPA axis (see e.g., Beauchaine, Crowell, & Hsiao, 2015). On the other hand, Del Giudice et al. (2012) failed to find the predicted malebiased distribution in unemotional patterns. Most of the sample was still prepubertal, however, so caution is warranted interpreting any sex differences or lack thereof. Nonetheless, many studies have shown that both men and women become hyporesponsive under conditions of severe stress (e.g., Bruce et al., 2009; Gustafsson et al., 2010; Miller, Chen, & Zhou, 2007; Tarullo & Gunnar, 2006; Vigil et al., 2010). A possibility to be explored in future research is that, even if unemotional patterns are equally frequent in males and females, similar physiological profiles may have different manifestations in behavior in the two sexes, as discussed above (see Del Giudice et al., 2011 for a more in-depth treatment of sex differences across behavioral domains). In conclusion, theoretical models such as the ACM are useful insofar as they explain known facts and make novel, testable predictions. The ACM is a complex model, and it can be used to derive dozens of predictions at different levels of analysis, including hypotheses about relations between childhood stress and stress responsivity, stress responsivity and behavior, individual differences in neuromodulation, Gene × Environment interactions, sex differences in life history strategies,

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and responses to domain-specific stressors (such as agonistic confrontations). Clearly, no single study can address all of these predictions, and multiple studies will be required even to evaluate the more basic ones. This first set of three studies (Del Giudice et al., 2012; Ellis et al., in press; Quas et al., 2014) provide initial empirical tests of the four responsivity patterns of the ACM. To varying degrees, these investigations provide support for the ACM by documenting complex, nonlinear relations between (a) childhood indices of familial and ecological conditions and life stress, (b) multisystem/multiphasic patterns of stress responsivity in adolescence, and (c) behavioral indicators of life history strategy in adolescence. Since its original publication, many other studies have also used the ACM as a guiding framework to explain biobehavioral links, yielding results that are consistent with the theory even within studies not originally designed to tease apart complexities of the ACM. Thus, the ACM has emerged as a useful theory in the field, helping us to move toward a more coherent “big picture” of the biosocial processes involved in developmental adaptation to the environment. At the same time, each of the three empirical studies that have specifically tested for the ACM responsivity patterns displays substantial limitations; their results both show support for and deviations from the ACM predictions, highlighting important theoretical challenges and empirical issues for future research.

Implications for Developmental Psychopathology The logic sketched in this section has several implications for developmental psychopathology. First, it provides a functional account of hypoarousal that goes beyond “dysregulation,” begins to explain why early adversity can have divergent outcomes (hyper- versus hypoarousal), and suggests that sex-related factors (such as sex hormones) may play an important role in determining the behavioral and physiological outcomes of early stress. For example, the hypothesis that some children shift from vigilant to unemotional patterns across middle childhood and adolescence may explain the puzzling finding that externalizing and aggressive behavior are associated with high cortisol levels in preschoolers but low cortisol levels from middle childhood on (Alink et al., 2008; Shirtcliff, Granger, Booth, & Johnson, 2005). Second, an evolutionary focus permits a better understanding of comorbidity patterns. For example, many superficially different traits and behaviors (e.g., aggression, early and promiscuous sexuality, substance abuse, reduced empathy) can be seen as manifestations of high-risk life history strategies that discount the future and increase mating effort. Consistent with this perspective, externalizing problems and precocious sexual behaviors in children not only co-vary but also share many etiological factors (see Lévesque, Bigras, & Pauzé, 2010). Finally, the ACM helps clarify complex relations between psychosocial environmental factors and stress responsivity patterns. Although the theory is rooted in biology and evolution, in practice the ACM emphasizes the importance of the

The Adaptive Calibration Model of Stress Responsivity 261 environment for shaping children’s biosocial development. Specific predictions can be made about the effects of key dimensions of the environment—resource availability, extrinsic morbidity-mortality, and unpredictability—rather than catchall concepts such as “cumulative stress” or “lifecourse adversity.” Moreover, moderators such as supportive caregiving can be specified within each key dimension (i.e., Does the moderator change environmental unpredictability? Does it shield the child from external morbidity or mortality threats? Does it provide necessary bioenergetic resources?), rather than tautologically defining a buffer as something that acts as a buffer. Making sense of these key dimensions of environmental risk and support has tremendous implications for treatment and prevention efforts, as the theory helps sort through the wide range of possible stressors to focus on the most likely targets for successful intervention. The ACM can be criticized for suggesting that stress and adversity over development can either upregulate or downregulate levels of SNS, PNS, and LHPA responsivity and thus that “any outcome” can be consistent with the ACM. Nonetheless, this situation is reflective of the state of the empirical literature on this topic: For every study linking stressful rearing experiences to hyperarousal (e.g., De Bellis et al., 1999; Essex, Klein, Cho, & Kalin, 2002; Yehuda, 2002) another study links such experiences to hypoarousal (as reviewed above). The ACM potentially explains both hyperarousal and hypoarousal by specifying nonlinear relations between environmental conditions and development of stress responsivity (Figure 8.1). According to the theory, developmental exposures to low to moderate levels of stress either upregulate (in the sensitive pattern) or downregulate (in the buffered pattern) responsivity. Likewise, developmental exposures to high levels of stress either upregulate (in the vigilant pattern) or downregulate (in the unemotional pattern) responsivity. Thus, if one considers the environment-responsivity curves shown in Figure 8.1, it is apparent that results of any single study that examines linear statistical relationships can range from positive to null to negative, depending on the portion of the curve sampled in each case (Boyce & Ellis, 2005; Ellis et al., 2005). Many inconsistent results in the stress literature may depend, at least in part, on failures to consider nonlinear relationships between environmental factors and SRS parameters, the tendency to view SRS functioning as divergent from some optimal base-point rather than a wide range of starting points, or difficulties with assessing the full range of environmental variance necessary to capture all four patterns of responsivity and associated behavioral strategies specified by the ACM. Of equal importance, the ACM predicts that it will be difficult to discriminate between functionally different profiles of responsivity without including information about life history–relevant traits such as risk taking, self-regulation, sexual maturation, and so on. What distinguishes the sensitive and vigilant patterns in the model is not LHPA reactivity per se, but rather the constellation of traits that go with it and clarify its functional meaning (increased social sensitivity in one case versus readiness to face social or physical danger in the other). If the model is correct, attempts to discriminate between meaningful individual types based

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exclusively on SRS parameters will yield weak and inconsistent findings, as SRS profiles are only one component of the predicted responsivity patterns.

ADAPTIVE CALIBRATION AND THE ALLOSTATIC LOAD MODEL With the ACM, we are seeking an integrative theoretical framework for the study of stress, stress responsivity, and health across development. The ACM both complements and provides a counterpoint to the ALM, which has become quite popular in developmental psychopathology (e.g., Beauchaine, Neuhaus, Zalewski, Crowell, & Potapova, 2011; Lupien et al., 2006). In recent years, researchers have started adopting the ALM as a foundation for interdisciplinary integration (e.g., Ganzel, Morris, & Wethington, 2010; Juster et al., 2011). As Hostinar and Gunnar (2013b, p. 400) conclude: “The field has two major theories for talking about stress and health: the Allostatic Load Model, which grew out of biological and neuroscience approaches to understanding health and disease, and the Adaptive Calibration Model, which developed out of an explicitly evolutionary-developmental framework.” In this section, we review key points of convergence and divergence between the models, in order to clarify some of the advantages of the ACM (for a more detailed exposition, see Ellis & Del Giudice, 2014).

The Allostatic Load Model The process by which the regulatory parameters of the SRS (as well as other neurobiological systems) are modified in the face of challenge is termed allostasis (i.e., “stability through change”; Sterling & Eyer, 1988). Allostasis is a key concept of the ALM; it refers to the moment-to-moment process of increasing or decreasing vital functions (i.e., adaptively adjusting physiological parameters within the organism’s operating range) to new steady states in response to the demands of the environment and the organism’s resources (McEwen & Stellar, 1993; see also Lupien et al., 2006). Allostasis functions to help the organism cope with challenging events or “stressors,” enabling short-term adaptation to environmental perturbations. However, the term allostasis is not always used consistently; for example, some authors (e.g., Beauchaine et al., 2011) restrict the meaning of allostasis to long-term, potentially permanent changes in the system’s parameters in contexts of protracted stress (what McEwen and Wingfield [2003] labeled allostatic states and is now more commonly referred to as biological embedding). The SRS is a crucial mediator of allostasis, though many other central and peripheral structures initiate and sustain allostatic responses (see Ganzel et al., 2010). Allostatic load is a label for the long-term costs of allostasis; it is often described as “wear and tear” that results from repeated allostatic adjustments (i.e., adaptation to stressors), exposing the organism to adverse health consequences. The ALM emphasizes that biological responses to threat, while essential for survival, have negative

The Adaptive Calibration Model of Stress Responsivity 263 long-term effects that promote illness. Thus, short-term benefits of mounting biological responses to threat are traded off against long-term costs to mental and physical health, and these costs (allostatic load) increase as the organism ages. Among other adverse outcomes, allostatic load is thought to cause SRS dysregulation, resulting for example in excessive or insufficient responses to stressors and increasing vulnerability to mental and physical health problems (e.g., Juster et al., 2010; Juster et al., 2011). The idea of physiological dysregulation is integral to the ALM, which assumes that there is an optimal level of biological responsivity to social and environmental challenges. Accordingly, both “hyperarousal” and “hypoarousal”—recurring overactivity or underactivity of physiological mediators—are routinely described as dysfunctional deviations from the norm (e.g., Adam, 2012; Juster et al., 2011; Lupien et al., 2006), usually caused by a combination of excessive stress exposure and genetic or epigenetic vulnerability. Sometimes, models based on allostatic load assume that these response patterns evolved to meet the demands of more dangerous ancestral environments, but are mismatched to less perilous modern environments, thus setting in motion pathogenic processes that eventuate in mental and physical illness (e.g., Miller et al., 2011).

ACM Versus ALM We note at the outset that there are significant points of convergence between the ACM and the ALM. First, the ACM explicitly embraces the concept of allostasis and describes the coordination of allostatic responses as one of the main biological functions of the SRS. The ACM also acknowledges that chronic SRS activation does carry substantial costs, in terms of biological fitness as well as subjective well-being. Finally, whereas the ACM focuses on conditional adaptation, it leaves open the possibility that, for a number of reasons, some developmental outcomes are biologically maladaptive (see earlier discussion). From an evolutionary standpoint, the biggest limitation of the ALM is that no distinction is made between the two meanings of “adaptive” (and maladaptive) described above: positive versus negative biological fitness outcomes, on the one hand, and desirable versus undesirable mental and physical health outcomes, on the other. Maladaptation is inferred whenever there are costs for the organism. For example, if elevated cortisol levels among children are associated with a negative outcome, such as reduced working memory, then elevated cortisol is classified as a marker of allostatic load (Juster et al., 2011). This reasoning ignores the crucial fact that biological processes are adaptive when their fitness benefits outweigh their costs, not when they are cost-free. As discussed above, even large costs can be offset by large enough expected benefits. For example, in dangerous and unpredictable environments, organisms often accept the risk of severe damage in exchange for a chance of improving their condition (see Ellis et al., 2012; Frankenhuis & Del Giudice, 2012), as illustrated by the high levels of risk taking and aggression

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that characterize the adversity-adapted unemotional responsivity pattern. Similarly, when health and reproductive success conflict, natural selection favors the latter at the expense of the former (see Nesse, 2001). Because of persistent confusion underlying the distinction between (mal)adaptive and (un)desirable outcomes, most applications of the ALM do not address the trade-offs involved in the development of physiological and behavioral phenotypes; as a consequence, the ALM literature often lacks a theory of adaptive individual variation in stress responsivity (but see Korte et al., 2005, for a notable exception). Although the ALM is sophisticated in explaining the costs of allostasis, it only captures the short-term benefits of allostasis and does not consider the long-term benefits in terms of regulating conditional adaptation to varying environmental conditions. As a result, the development of enduring individual differences is usually traced to pathogenic processes. In contrast, the ACM is built on the notion of inherent trade-offs in the life cycle of organisms; explicit consideration of these trade-offs is at the heart of the ACM taxonomy of responsivity patterns. For example, consider heightened SRS responsivity in vigilant patterns (Type III). In the ACM, it is hypothesized that the costs of repeated SRS activation are offset by improved management of danger. Although the system is on a hair trigger, with the resulting burden of anxiety and/or aggression, few instances of actual danger will be missed. In addition, engaging in a “fast,” present-oriented life history strategy discounts the long-term health costs of chronic SRS activation if the immediate benefits are large enough (for in-depth discussion, see Del Giudice et al., 2011). In the manner in which the ALM framework is often applied, the same pattern of responsivity is treated as dysfunctional, because the stress response is deployed even in absence of true dangers (“excessive” response, “unnecessary” triggering; see Beauchaine et al., 2011; Lupien et al., 2006) and because of the associated unpleasant states and health risks. This approach, however, fails to consider that natural defenses are usually designed by natural selection to accept a high rate of false positives (the so-called “smoke detector principle”; Nesse, 2005). Moreover, adaptive defenses, from environmentally triggered surges in catecholamines and glucocorticoids to development of fever in response to an infection, are often aversive, disabling, and occasionally harmful (or even fatal); but mistaking them for diseases because of these features is a fallacy, though one that is exceedingly common in the psychopathology literature (see Nesse & Jackson, 2006). A related point of divergence between the ACM and the ALM concerns responses to acute versus chronic stress. In the ALM, adaptive responses to acute stress are contrasted with the biological “wear and tear” caused by chronic stress and resulting long-term modifications of SRS regulatory parameters. In the ACM, responses to both acute and chronic stress can be adaptive (though not cost-free); and, as a rule, long-term adjustment of SRS parameters (as in the development of different responsivity profiles) is seen as adaptive calibration rather than maladaptive dysregulation. Indeed, we anticipate that many of the allegedly “toxic” effects of chronic

The Adaptive Calibration Model of Stress Responsivity 265 stress (e.g., its effects on immune function, brain physiology, memory, learning, and so forth) will ultimately find a better explanation as mediators of biological fitness trade-offs (such as the well-documented trade-offs between faster life history strategies and health; reviewed in Ellis & Del Giudice, 2014). In total, the ALM, relative to the ACM, overemphasizes the costs of allostasis and underappreciates its benefits. A comparison and contrast between the core assumptions of the two theories is presented in Table 8.1. In conclusion, we are not arguing that the ALM is wrong per se, nor that the extensive body of research documenting negative effects of allostatic load on health is incorrect, but rather that the overemphasis of the ALM on the costs of allostasis weakens its conceptual power. The ALM does not address the adaptive role of allostasis in regulating developmental plasticity, which is the main objective—and strength—of the ACM. Be that as it may, conceptual differences between the ACM and ALM should not be irreconcilable, and greater integration of the two models in the future could potentially strengthen both approaches. Most relevant to the current volume, the ACM and ALM have rather different implications for understanding the development of psychopathology and, consequently, may support different intervention strategies (Ellis & Del Giudice, 2014).

Implications for Developmental Psychopathology The ALM and the concept of allostatic load have become remarkably popular in developmental psychopathology. Here we argue that the ALM has substantive limitations, especially regarding the current manner in which it uses a pathology lens to explain influences on human development. In practice, this focus has moved the field away from the roots of the ALM, which began in evolutionary biology and an exploration of allostasis and allostatic states, toward a context-free view about optimal health outcomes or pathological deviations from normative SRS profiles. The ACM attempts to swing the pendulum back to be more consilient with theory and research in evolutionary biology, providing researchers with a broader theory of stress responsivity that acknowledges the central importance of calibration to local environmental conditions. We recognize that the ALM is attractive because it conforms to implicit assumptions of the standard mental health approach, particularly regarding stress-disease relationships, and therefore does not require a fundamental shift in thinking and logic. However, it also fails to deliver the insight and heuristic power of a modern evolutionary-developmental framework. In the long run, the field of developmental psychopathology may be better served by a model that is informed by life history theory, modeling of strategic trade-offs, and a more explicit consideration of the relations between adaptation, health, and well-being. In total, we believe that the ACM embodies the main insights of the ALM while addressing some of its key limitations. Even more importantly, most of the work that is presently carried out under the ALM umbrella could be reframed in the perspective of the ACM. For example,

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Responses to Psychosocial Stress/ Unpredictability

Examples of Response

• Acute SNS and LHPA responses Activation of mobilize energy reserves, protect autonomic, against septic shock and nutrient neuroendocrine, deprivation, permit fight or flight metabolic, and responses that are normally immune systems protective against danger. • Inflammation accelerates the healing of wounds. • Increased inflammatory tone Changes in • Elevated cortisol and allostatic catecholamines mechanisms • Muted cardiovascular responses to stress • Reduced scores on standard tests Cognitive, of intelligence, language, memory, behavioral, and and other abilities emotional • Early onset and increased impairments in prevalence of psychopathology children • Tailoring of emotion systems, Cognitive, arousal responses, and perceptual behavioral, and abilities to the detection and emotional monitoring of danger adaptations to stress in children • Development of insecure attachments, mistrustful internal working models, opportunistic interpersonal orientations, oppositional-aggressive behavior • Cognitive and physical impairments Long-term • Depression deleterious • Increased risk of cardiovascular outcomes disease and all-cause mortality Long-term adaptive • Adaptive calibration of autonomic, neuroendocrine, metabolic, and changes in immunological systems biobehavioral • Regulation of alternative life history systems strategies to match ecological conditions

ACM

ALM

Central to theory

Central to theory

Central to theory

Central to theory

Not inconsis- Central to tent with theory theory

Central to theory

Not inconsistent with theory

Not inconsis- Central to tent with theory theory Central to theory

Beyond the scope of the theory

Note. Light shading indicates a difference in emphasis between the ACM and ALM. Dark shading indicates a qualitative divergence between the two theories. SNS: sympathetic nervous system; LHPA: limbic-hypothalamic-pituitary-adrenal axis. Adapted from Ellis and Del Giudice, 2014.

The Adaptive Calibration Model of Stress Responsivity 267 the theory of developmental stages and switch points embodied in the ACM might serve as a detailed, biologically grounded foundation for the analysis of the effects of stress exposure at different points in the life cycle (Ganzel & Morris, 2011). Finally, the ACM addresses major anomalies in the field regarding complex relations between psychosocial environmental factors, stress responsivity, life-history relevant traits and behaviors, and health. In the ALM, both hyperarousal and hypoarousal are considered indicators of stress dysregulation resulting from allostatic load, and the developmental pathways leading to systematic upregulation versus downregulation of SRS parameters are not theoretically modeled (rather, hyperarousal and hypoarousal are grouped together as dysfunctional deviations from an optimal setpoint). Valid explanatory models of developmental pathways leading to both hyper- and hyporesponsivity are critical to explaining the development of psychopathology because both heightened and dampened responsivity can appear either good or bad in terms of behavioral adjustment and health. Such bivalent effects of the SRS have been documented in PNS, SNS, and LHPA studies focusing on both baseline arousal and responsivity (e.g., Bauer, Quas, & Boyce, 2002; Burke, Davis, Otte, & Mohr, 2005; Evans & English, 2002). The ACM potentially explains these anomalous findings by specifying two patterns of heightened stress reactivity (sensitive and vigilant phenotypes) and two patterns of dampened stress reactivity (buffered and unemotional phenotypes). Most importantly, each phenotype is characterized by different developmental histories and behavioral and health trajectories. Accordingly, heightened reactivity may appear to be a protective factor in sensitive phenotypes and a risk factor in vigilant phenotypes, whereas dampened reactivity may appear to be a protective factor in buffered phenotypes and a risk factor in unemotional phenotypes. This contrast highlights the critical importance of examining larger responsivity patterns in the context of environmental antecedents and life history outcomes.

CONCLUSION In this chapter, we presented and elaborated an evolutionary-developmental theory of individual differences in stress responsivity—the ACM—that reorganizes many empirical findings from different research fields, weaves them together in a theoretically coherent manner, and advances novel and testable predictions about behavior, development, and neurobiology. Built explicitly on the foundation of modern evolutionary biology, the ACM provides a framework for research on stress and development that takes us beyond the ALM; it delineates coherent, functional responses to stress, including regulation of alternative life history strategies, which reliably emerge in given developmental contexts. These responses have to be taken into account to more fully and accurately capture child and adolescent development under conditions of psychosocial stress and unpredictability. Ultimately, our ability to translate research on stress-health relationships into effective interventions for the

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crucial goals of risk prevention and management depend on understanding when and how adaptations to stress emerge and can be changed.

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CHAPTER 9

Exposure to Teratogens as a Risk Factor for Psychopathology LAUREN R. DOYLE, NICOLE A. CROCKER, SUSANNA L. FRYER, AND SARAH N. MATTSON

INTRODUCTION AND ETIOLOGICAL FORMULATIONS

A

teratogen is an agent that causes birth defects by altering the course of typical development. Examples of human teratogens exist in several classes of substances including drugs of abuse (e.g., alcohol, cocaine, nicotine), prescription medications (e.g., retinoic acid, valproic acid, thalidomide), environmental contaminants (e.g., pesticides, lead, methylmercury), and diseases (e.g., varicella, herpes simplex virus, rubella). Pregnant women are exposed to teratogens for a variety of reasons. Some women may be unaware of the teratogenic nature of certain substances. Or, in the case of viruses such as varicella, even if awareness exists, prevention of exposure may not be possible. A recent outbreak of Zika virus linked with an increased rate of microcephaly (small head circumference) in Brazil has prompted international alarm. The connection between in utero exposure to Zika virus and congenital defects has yet to be established, but preliminary investigations strongly suggest a causal relationship between the two (Mlakar et al., 2016; Victora et al., 2016). Similarly, with medical conditions such as seizure disorder or severe depression, termination of pharmacologic treatment during pregnancy may not be advisable. Furthermore, given that about half of pregnancies

Acknowledgments: Preparation of this chapter was supported in part by National Institute on Alcohol Abuse and Alcoholism Grant numbers U01 AA014834, R01 AA019605, R01 AA010417, F31 AA020142, and T32 AA013525. We gratefully acknowledge the assistance and support of the Center for Behavioral Teratology, San Diego State University.

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in the United States are unplanned, and given that pregnancy detection may not occur until fetal development is well underway, many teratogenic exposures occur prior to pregnancy recognition (Henshaw, 1998). For example, more than 130,000 pregnant women per year in the United States consume alcoholic beverages at levels believed to pose teratogenic risk to their fetuses (Lupton, Burd, & Harwood, 2004), and 10% of women who know they are pregnant report drinking alcohol during pregnancy (Centers for Disease Control and Prevention, 2004). These rates exist despite more than four decades of research on the effects of alcohol-induced birth defects and the presence of government-mandated labels on alcoholic beverages that warn of the association between drinking during pregnancy and harmful fetal effects. Thus, teratogenic exposures are common, and birth defects that result from prenatal exposures constitute a major public health concern. Behavioral teratogens are agents that alter central nervous system functions that subserve cognitive, affective, sensorimotor, and/or social behaviors following exposure during gestation (Vorhees, 1986). Behavioral teratogens can cause damage to fetuses even in the absence of gross physical or structural abnormalities. Effects of behavioral teratogens may be subtle and may not be recognizable at birth. The purpose of research aimed at identifying and characterizing effects of behavioral teratogens is to determine the degree and nature of behavioral dysfunctions attributable to fetal exposure to drugs and other agents that cause birth defects. The hope is that by identifying behavioral teratogens and increasing public awareness, we will reduce teratogen exposures and resulting fetal damage. As already noted, effects of behavioral teratogenic exposures are diverse and include structural damage to the developing brain, which may result in cognitive impairments, behavior dysregulation, and emotional dysfunction. In this chapter, we focus on associations between teratogenic exposures and the development of mental illnesses. The etiology of psychopathology is complicated by gene-environment interactions (including epigenetic effects) through which only some genotypes may be sensitive to certain environmental risks—including behavioral teratogens (cf. Rutter, 2005; Chapter 3 [Beauchaine, Gatzke-Kopp, & Gizer]). Gene-environment correlation is also possible. For example, genes that predispose to maternal substance abuse may co-occur with maladaptive childrearing environments. Vulnerability to psychopathology is also multifactorial, with many genes interacting with both one another and with environmental risk factors to eventuate in mental illness. Thus, complex behaviors that comprise psychopathology manifest in an emergent fashion from continuous interplay between an individual’s genetic predispositions and his/her environmental risk exposures. Factors such as family placement (e.g., being raised in a biological, foster, or adoptive home; Viner & Taylor, 2005), socioeconomic status (SES; Rutter, 2003), and general intelligence (Dykens, 2000) are potential sources of variance in mental health outcomes and may be of particular concern in evaluating the mental health status of individuals with teratogenic exposures.

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Alcohol is the main focus of this chapter, as it is both an archetypal and widely studied behavioral teratogen. Associations between psychopathology and fetal exposure to nicotine, stimulant drugs, methylmercury, lead, and antidepressant medication are discussed briefly, as effects of these exposures on mental health outcome are less well studied.

HISTORICAL CONTEXT Knowledge of birth defects and their associations with teratogenic exposures has evolved over the course of history. Early depictions, including carvings and drawings, indicate knowledge of birth defects as early as 6500 B.C., and early written records indicate beliefs that birth defects were caused by various factors including witchcraft. Birth defects were also thought to portend adverse events. By the 20th century, it was thought that the fetus was afforded significant protection by the uterus, and it wasn’t until 1941 that an association between prenatal exposure to the rubella virus and subsequent birth defects was reported in the scientific literature. Even so, it took the experience with thalidomide in the late 1950s to confirm association between teratogens and resulting birth defects (Vorhees, 1986). An association between gestational alcohol exposure and adverse fetal effects was also described anecdotally for centuries. Some contend that the association was documented in Greek and Roman mythology and in the Bible. Yet throughout most of the 20th century, alcohol was not recognized as a human teratogen. In fact, physicians used alcohol to treat premature labor in a procedure referred to as an ethanol drip. Perhaps in part due to this medical use, the first descriptions in the scientific literature of alcohol as a human teratogen were met with considerable resistance. Instead, it was posed that the constellation of symptoms later identified as fetal alcohol syndrome (FAS) was due to other factors such as inadequate prenatal nutrition or genetic effects (“Effect of alcoholism at time of conception,” 1946). Because of their ability to control confounding factors, preclinical animal models were crucial in establishing the causal role of alcohol in bringing about fetal alcohol spectrum disorders (FASD). After more than 40 years of research on alcohol teratogenesis, prenatal alcohol exposure is now recognized as a major public health concern. As an example of this increased public awareness, in 1989 the U.S. government passed the Alcoholic Beverage Warning Label Act, which mandates that alcoholic beverages contain labels that warn of alcohol’s harmful effects on the developing fetus. In addition, in February 2005, the U.S. surgeon general issued an updated “Advisory on Alcohol Use and Pregnancy,” which recommended that (a) pregnant women not drink alcohol, (b) pregnant women who have already consumed alcohol during pregnancy stop drinking to minimize further risk, and (c) women who are considering pregnancy or who might become pregnant abstain from alcohol (http://www.hhs.gov/ surgeongeneral/pressreleases/sg02222005.html) (Warren & Hewitt, 2009). Despite this progress, women continue to drink in pregnancy (see above).

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TERMINOLOGICAL AND CONCEPTUAL ISSUES Since the first descriptions of FAS in the literature ( Jones & Smith, 1973; Jones, Smith, Ulleland, & Streissguth, 1973; Lemoine, Harousseau, Borteyru, & Menuet, 1968), patterns of birth defects associated with maternal alcohol consumption have been studied extensively. FAS is characterized by a triad of presenting symptoms, including (1) pre- and/or postnatal growth deficiency, (2) dysmorphic facial features (short palpebral fissures, indistinct philtrum, and a thin upper lip), and (3) central nervous system (CNS) dysfunction. Although CNS dysfunction is required for the diagnosis of FAS, cognitive deficits and behavioral abnormalities are commonly observed following prenatal alcohol exposure even in the absence of growth deficiency and facial stigmata required for clinical recognition of FAS (e.g., Mattson, Riley, Gramling, Delis, & Jones, 1997, 1998). FASD encompasses the entire range of effects attributable to prenatal alcohol exposure (Bertrand, Floyd, & Weber, 2005). These effects may range from full manifestation of FAS, to subtle neurobehavioral or physical defects. FASD is a diagnostic umbrella term under which both dysmorphic (i.e., FAS) and nondysmorphic cases of prenatal alcohol exposure fall. FASD encompasses historical terms such as fetal alcohol effects (FAE), and current diagnoses of partial FAS (pFAS), alcohol-related birth defects (ARBD), alcohol-related neurodevelopmental disorder (ARND), and the new term neurobehavioral disorder associated with prenatal alcohol exposure (ND-PAE). Incidence rates of FAS average about 1 per 1,000 live births (Bertrand et al., 2005), making FAS the leading preventable cause of intellectual disability (Pulsifer, 1996). More subtle birth defects related to prenatal alcohol exposure occur more frequently. The combined rate for dysmorphic (i.e., FAS) and nondysmorphic FASD cases is estimated conservatively to be 9.1 cases per 1,000 live births (Sampson et al., 1997), although recent studies in North America find rates as high at 48 per 1,000 (May et al., 2014; May et al., 2015). The costs of fetal alcohol effects pose a heavy burden on society, ranging between $4 billion and $9.7 billion annually (Lupton et al., 2004; Thanh, Jonsson, Dennett, & Jacobs, 2011). Costs related to FASD are considerably higher. With the recent transition to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013), new terminology has been introduced to identify effects of prenatal alcohol exposure. ND-PAE is included under “conditions for further study,” indicating a need for future research to validate proposed criteria. In addition to a confirmed history of more than minimal prenatal alcohol exposure (>13 drinks per month), ND-PAE criteria require significant impairment in three domains of neurobehavioral functioning: neurocognition, self-regulation, and adaptive functioning (APA, 2013). The effects of prenatal alcohol exposure on neurocognitive function have been studied extensively (Mattson, Crocker, & Nguyen, 2011), although describing such findings in full detail is beyond the scope of this chapter. However, it should be noted that combined effects of dysfunction in these three domains, and their interaction with

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environmental factors, contributes to the adverse consequences of prenatal alcohol exposure (Kable et al., 2015). Deficits in self-regulation can manifest as impaired mood/arousal regulation and/or impaired attention/impulse control (APA, 2013). As described below, impairments in adaptive function persist throughout life, and may become more pronounced with age (Kable et al., 2015). Criteria for impairment in adaptive function include deficits in communication, social interaction, daily living skills, and/or motor skills (APA, 2013). Impairment in self-regulation and adaptive function can contribute to psychopathology in FASD (Kable et al., 2015), as outlined in this chapter. When establishing an ND-PAE diagnosis, certain issues must be considered. For example, individuals who are exposed to alcohol prenatally have high rates of co-occurring mental health disorders (Fryer, McGee, Matt, & Mattson, 2007). Thus, it is essential to determine whether symptoms associated with a possible secondary diagnosis, such as oppositional defiant disorder (ODD), are merely a manifestation of issues attributable to prenatal alcohol exposure (Kable et al., 2015). Because of such overlapping symptoms between FASD and other mental health disorders, there are high rates of missed diagnoses and misdiagnosis (Chasnoff, Wells, & King, 2015). Missed diagnoses may represent ignorance or denial of etiological factors in individual cases, and therefore missed opportunities for intervention. Specific criteria for ND-PAE, and empirical evidence supporting those criteria, are essential to aid in differential diagnosis. Finally, current substance use or misuse (e.g., prescription medication, alcohol, drugs) must be ruled out, along with any general medical condition(s) that may better account for symptoms (Kable et al., 2015). Thus, comprehensive, multidisciplinary assessment is imperative (Doyle & Mattson, 2015; Kable et al., 2015).

MENTAL HEALTH OUTCOMES IN FASD Although not as well studied as cognitive deficits associated with prenatal alcohol exposure, there is a sizeable literature on mental health outcomes. Studies of affected individuals consistently demonstrate deficits in both parent and self-reported behaviors (Coles, Platzman, Brown, Smith, & Falek, 1997; Coles, Platzman, & Lynch, 1999; Mattson & Riley, 2000; Nash et al., 2006; O’Leary et al., 2009; Sayal et al., 2009; Sayal, Heron, Golding, & Emond, 2007; Steinhausen, Willms, Metzke, & Spohr, 2003). In one early longitudinal investigation of children with FAS, a large portion of whom were intellectually disabled (Steinhausen, Willms, & Spohr, 1994; Steinhausen, Nestler, & Spohr, 1982; Steinhausen, Willms, & Spohr, 1993), increased rates of many maladaptive behaviors were observed, including stereotypies, sleeping problems, tics, head and body rocking, peer relationship difficulties, and phobic behaviors. Moreover, an index of psychopathological behavior, created from the sum of symptom scores, correlated with the degree of dysmorphology (Steinhausen et al., 1982). A follow-up report demonstrated persistence of psychopathological symptoms through late childhood, including

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hyperkinetic (i.e., overactive) behaviors, sleep disturbances, abnormal habits, stereotyped behaviors, and emotional disorders (Steinhausen & Spohr, 1998). In another investigation that used IQ-matched controls, alcohol-exposed children exhibited significantly more parent-report behavioral and emotional disturbances on 5 of 8 subscales on the Child Behavior Checklist (Mattson & Riley, 2000). As a group, children with prenatal alcohol exposure demonstrated clinically significant scores in several externalizing behavior domains, including social problems, attention problems, and aggressive behavior. Children with FASD also demonstrated elevated internalizing behaviors, but differences on these scales were not as large as on externalizing behaviors. Studies that have used criteria from the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; APA, 1994, 2000) show that rates of clinical diagnoses are also elevated among children with FASD. In one sample of 23 children with histories of heavy prenatal alcohol exposure, ages 5 to 13 (O’Connor et al., 2002), 87% met criteria for at least one psychiatric disorder, with mood disorders (major depression and bipolar disorders) most common. Somewhat surprisingly, these data revealed comparable mental health outcomes regardless of the severity of fetal alcohol effects. Indeed, nondysmorphic individuals were just as likely to have clinically significant psychopathology as children with hallmark facial features of FAS. In an effort to focus on the development of psychiatric illness in children with FASD independent of intellectual disability, children with an intelligence quotient (IQ) below 70 were excluded from this study. The authors noted that because the sample was clinical-referred, high rates of observed psychopathology may not generalize to the entire alcohol-exposed population (O’Connor et al., 2002). In a later study, also of a clinical-referred FASD sample, Fryer, McGee, Matt, Riley, and Mattson (2007) found that 97% of alcohol-exposed children met criteria for at least one DSM-IV disorder, compared with 40% of control children. Among children with FASD, 28% met criteria for a mood and/or anxiety disorder, and 59% met criteria for externalizing disorders such as attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), and/or ODD. These rates were higher than those observed among children in the control group and in the general population. A more recent study compared rates of general anxiety disorder, major depressive disorder, ODD, and CD among children with FASD to those of nonexposed children with ADHD (Ware et al., 2013). Both groups displayed elevated rates of all diagnoses. However, participants with ADHD and histories of prenatal alcohol exposure had higher rates of CD than those with ADHD without prenatal alcohol exposure. As already suggested above, because these studies included participants who were identified based on clinically significant behavioral problems or recognition of fetal alcohol effects, mental health outcomes may not generalize to the entire alcohol-exposed population. Such clinical samples exclude individuals who were exposed to alcohol prenatally but experience few or no symptoms. Moreover, although retrospective studies are important in characterizing individuals most in need of clinical services, studies that identify participants prospectively (i.e., at or

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near the time of teratogenic exposure) can increase the external validity of research findings. Also, prospective studies typically enable better control of confounding factors, because environmental and demographic information can be collected more accurately and closer to the time of exposure. The Seattle Study on Alcohol and Pregnancy, a large-scale population-based study of alcohol’s behavioral teratogenicity, used a prospective design. Streissguth and colleagues identified 1,529 pregnant women in the mid-1970s, and collected information about their use of alcohol, cigarettes, caffeine, and other recreational and prescription drugs (Barr et al., 2006). Importantly, these pregnancies were not considered high risk, and all women received prenatal care. A cohort of 500 mother-infant pairs was selected—oversampling for alcohol use—and followed through adulthood. Of this birth cohort, 400 young adults, including individuals with and without prenatal alcohol exposure, were interviewed at about age 25 using Structured Clinical Interviews for DSM-IV. The purpose of this study was to determine whether high rates of psychiatric illness observed in clinical samples of individuals with FASD would replicate in a nonclinical, community sample. The odds of developing somatoform and substance use disorders, and paranoid, passive-aggressive, and antisocial traits, were at least doubled in individuals who were exposed to one or more binge drinking episodes versus those who were not. Substance use disorders and both passive-aggressive and antisocial personality traits remained at least a twofold risk among alcohol-exposed individuals, even after adjusting for confounding factors including prenatal nicotine and marijuana exposure, family placement, low SES, poor maternal nutrition, breastfeeding, and family history of psychiatric problems and alcoholism. The authors noted that given the epidemiological focus of their study, including thorough covariation of many other factors that predict mental health, prenatal alcohol exposure is likely to play a causal role in increased rates of the disorders noted. Taken together, these mental health outcome studies suggest that individuals with fetal alcohol exposure histories suffer from substantial psychiatric illness. Moreover, the diversity of study methodologies (e.g., both prospective and retrospective subject ascertainment, longitudinal versus cross-sectional design, different portions of the age span) supports generalizability of the association between FASD and psychopathology. To date, empirical studies that examine psychiatric illness among individuals with FASD have relied on DSM-IV criteria. Thus, future research is needed to determine rates of psychopathology based on new DSM-5 criteria.

Disruptive Behavior Disorders The available literature suggests that certain types of psychopathology are more likely than others following gestational alcohol exposure. Among these are disorders on the disruptive behavior spectrum (e.g., ADHD, ODD, CD). As stated earlier, findings from the Fryer et al. (2007) study indicate group differences between alcohol-exposed and typically developing peers in rates of ADHD, ODD,

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CD, depressive disorders, and specific phobias. The largest group difference pertains to ADHD behaviors. This finding is consistent with research suggesting that increased attention difficulties and ADHD are among the most notable psychopathological outcomes within the FASD population (Burd, Klug, Martsolf, & Kerbeshian, 2003; Coles, Platzman, Lynch, & Freides, 2002; Mattson & Riley, 1998; Steinhausen & Spohr, 1998; Steinhausen et al., 1993; Streissguth, Barr, Kogan, & Bookstein, 1996). Given the high rates of ADHD in FASD, an entire body of research comparing these two clinical groups has formed, with the goal of differentiating them on cognitive and behavioral function to aid in better identification of alcohol exposed individuals (Burden et al., 2010; Coffin, Baroody, Schneider, & O’Neill, 2005; Coles, Platzman, Raskind-Hood, et al., 1997; Crocker, Vaurio, Riley, & Mattson, 2009, 2011; Greenbaum, Stevens, Nash, Koren, & Rovet, 2009; Jacobson, Dodge, Burden, Klorman, & Jacobson, 2011; Kooistra, Crawford, Gibbard, Kaplan, & Fan, 2011; Kooistra, Crawford, Gibbard, Ramage, & Kaplan, 2010; Kooistra et al., 2009; Nanson & Hiscock, 1990; Nash et al., 2006; Vaurio, Riley, & Mattson, 2008; Glass et al., 2014; Ware et al., 2013). In one such investigation, parent-report items reflecting hyperactivity, inattention, lying and cheating, lack of guilt, and disobedience were particularly useful at discriminating children with FASD from children with ADHD (Nash et al., 2006). Additionally, children with prenatal alcohol exposure appear to show different profiles of hyperactivity and inattention than children with ADHD. In one recent study, both children with ADHD and children with prenatal alcohol exposure showed similar patterns of inattention throughout a sustained attention task, but children who were exposed prenatally to alcohol showed activity levels more similar to those of a typically developing control group (Glass et al., 2014). Several studies have examined the interaction between prenatal alcohol exposure and ADHD on behavioral and psychiatric outcomes. These studies suggest differential behavioral outcomes in alcohol-exposed children with and without ADHD, particularly on externalizing behavior domains (Graham et al., 2013; Ware et al., 2013). Interestingly, the same does not appear to be true for neuropsychological abilities; alcohol-exposed children with and without ADHD seem to have similar neuropsychological profiles (Glass et al., 2013). Increased delinquent behavior and deficient moral decision making have also been reported in alcohol-exposed youth (Alvik, Aalen, & Lindemann, 2013; Roebuck, Mattson, & Riley, 1999; Sayal et al., 2014; Schonfeld, Mattson, & Riley, 2005; Streissguth et al., 1996), and rates of ODD and CD are high among these individuals (Disney, Iacono, McGue, Tully, & Legrand, 2008; Fryer et al., 2007; Hill, Lowers, Locke-Wellman, & Shen, 2000). In one population study of 626 adolescent twin pairs, prenatal alcohol exposure was associated with high rates of CD symptoms even after covarying parental externalizing disorders, prenatal nicotine exposure, monozygosity, gestational age, and birth weight (Disney et al., 2008). In another study, children with low IQs and prenatal alcohol exposure exhibited less moral maturity than typically developing children. In addition, children with

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FASD displayed a specific deficit in moral value judgments in their relationships with others (Schonfeld et al., 2005). Other studies demonstrate that children with prenatal alcohol exposure are more likely to lie about their behavior, and are more skilled liars at younger ages than their nonexposed peers (Rasmussen, Talwar, Loomes, & Andrew, 2008). Given the increase in delinquent behavior demonstrated by individuals with prenatal alcohol exposure, it is not surprising that alcohol-exposed youth are overrepresented in the criminal justice system (Boland, Burrill, Duwyn, & Karp, 1998; Fast & Conry, 2009, 2004). Interestingly, corrections staff are largely unaware of this phenomenon (Burd, Selfridge, Klug, & Bakko, 2004). One of the few systematic FASD screens of a delinquent group undertaken by a forensic psychiatric facility in Canada revealed that 23% of juvenile detainees were exposed to significant amounts of alcohol prenatally (Fast, Conry, & Loock, 1999). Of the 67 individuals who were identified as having birth defects related to alcohol exposure, only 3 had been given an alcohol-related diagnosis prior to the screen. Overall, the association between prenatal alcohol exposure and disruptive behavior appears to be reliable and persistent, and it is evident at relatively low exposure levels. For example, when researchers in the Seattle project conducted psychosocial assessments of 14-year-old exposed offspring, misbehaviors were among the outcomes most strongly associated with alcohol exposure (Carmichael Olson et al., 1997). However, whether the association between prenatal alcohol exposure and delinquency is direct—or is mediated by a more proximal linkage between FASD and early-appearing attention/impulse control problems and/or learning difficulties, which themselves predict later conduct problems—is indeterminate, yet both are mediated by similar central nervous system processes (e.g., Gatzke-Kopp, 2011; Hinshaw, 1992).

Mood Disorders Psychopathology associated with alcohol teratogenesis is not limited to disruptive behaviors. Elevated rates of depressive features and depressive disorders are also found among children with FASD based on parent interviews and questionnaires (Fryer et al., 2007; Mattson & Riley, 2000; O’Connor et al., 2002; Roebuck et al., 1999). Furthermore, as in the general population (Angold, Costello, & Erkanli, 1999), internalizing-externalizing comorbidities are common among children with FASD. Thus, some degree of overlap among those needing services for disruptive behaviors and mood disorders is expected.

Potential Mediating and Moderating Factors As discussed previously, factors such as IQ, SES, and family placement are important sources of variance in mental health outcomes, and several authors have attempted to tease apart effects of environmental risk factors from prenatal alcohol exposure when evaluating behavioral difficulties among affected children (D’Onofrio et al.,

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2007; Hill et al., 2000; Rodriguez et al., 2009; Staroselsky et al., 2009). Some findings suggest that maternal psychopathology is a better predictor of internalizing problems among children with FASD, whereas alcohol exposure is related more directly to externalizing problems (Staroselsky et al., 2009). One longitudinal study examined the relation between prenatal alcohol exposure, negative infant affect, and subsequent symptoms of childhood depression (O’Connor, 2001). Results indicated that gestational alcohol exposure was a significant risk factor for depressive features at age 6 years, both as a direct effect and as an indirect effect mediated through negative infant affectivity. Interestingly, associations between alcohol exposure and depressive symptoms may be moderated by factors such as sex and maternal depression, as girls whose mothers had high levels of depression were among those most affected (O’Connor & Kasari, 2000). More recent work indicates that prenatal alcohol exposure is a possible etiological factor in increased negative affect and depressive symptoms (O’Connor & Paley, 2006). However, this association appears to be mediated by the quality and nature of mother-child interactions. Other studies fail to find strong associations between prenatal alcohol exposure and externalizing difficulties once environmental factors are taken into account (D’Onofrio et al., 2007). For example, regarding delinquent behaviors noted in cases of FASD, factors such as amount of exposure (Lynch, Coles, Corley, & Falek, 2003) and home placement (biological, foster, or adoptive; Schonfeld et al., 2005) are likely to exacerbate the relation between prenatal alcohol exposure and delinquency. In one investigation of a low-SES community sample, investigators did not find increased delinquency when alcohol-exposed youth were compared to either nonexposed peers (also low SES) or a special education comparison group (Lynch et al., 2003). Rather, delinquency was related to environmental and behavioral variables such as low parental supervision, adolescent life stress, and self-reported drug use. In addition, higher rates of delinquent behavior were endorsed by alcohol-exposed adolescents in biological and foster homes versus those in adoptive homes (Schonfeld et al., 2005). However, these findings are to be expected with the interaction of genes and environment (e.g., genes may be expressed differently in different environments, or environmental effects may have varying impacts with different genetic makeup). Thus, findings do not suggest prenatal exposure history is unimportant. Several studies have examined moderating effects of genes and impact of prenatal alcohol exposure on the fetus. For example, one recent study demonstrated that children born to mothers with at least one ADH1B*3 allele showed no adverse effects of alcohol exposure, whereas children of mothers without this allele showed impairments associated with prenatal alcohol exposure, such as externalizing behaviors and attention deficits (Dodge, Jacobson, & Jacobson, 2014). The mechanism of this protective effect is unknown. It is hypothesized that peak blood alcohol concentrations are reduced in mothers with the ADH1B*3 allele, and as such less alcohol reaches the fetus (Dodge et al., 2014; McCarver, Thomasson, Martier, Sokol, & Li, 1997). Others have suggested those with the ADH1B*3 allele present with a stronger

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physiological response to alcohol consumption, thus resulting in a protective factor against alcohol dependence among those individuals (McCarthy, Pederson, Lobos, Todd, & Wall, 2010). More studies are needed to determine the exact role of genes in moderating/mediating effects of prenatal alcohol exposure.

Adaptive Dysfunction As might be expected in a population characterized by cognitive impairments and increased rates of mental illness, adaptive dysfunction is well documented among individuals with prenatal alcohol exposure (Carr, Agnihotri, & Keightley, 2010; Crocker et al., 2009; Jirikowic, Carmichael Olson, & Kartin, 2008; Streissguth et al., 1991; Thomas, Kelly, Mattson, & Riley, 1998; Ware et al., 2014; Whaley, O’Connor, & Gunderson, 2001). The Seattle study found that as alcohol-exposed individuals reached adulthood, their overall adaptive abilities were equivalent to those of typically developing 7-year-olds, with social skills showing the most severe detriment (Streissguth et al., 1991). More recent studies confirm that socialization of children with FASD is the most affected domain of adaptive function (Crocker et al., 2009; McGee, Bjorkquist, Price, Mattson, & Riley, 2009; McGee, Fryer, Bjorkquist, Mattson, & Riley, 2008; Thomas et al., 1998; Whaley et al., 2001). Based on these studies, adaptive dysfunction is one of the domains included in the DSM-5 criteria for ND-PAE (APA, 2013; Kable et al., 2015). Furthermore, these abilities often fail to improve with increasing age, suggesting an arrest in development rather than a delay (Crocker et al., 2009; Thomas et al., 1998; Whaley et al., 2001). A similar arrest in development in communication skills was documented in an investigation comparing children with FASD to children with ADHD and controls (Crocker et al., 2009). Thus, children with prenatal alcohol exposure are likely to have increasing difficulty meeting greater demands in social and communication function as they become teenagers and adults.

Psychopathology Among Adults With FASD Evidence suggests that behavioral difficulties and psychopathology among children with FASD persist into adulthood (Barr et al., 2006; Famy, Streissguth, & Unis, 1998; Spohr, Willms, & Steinhausen, 2007; Streissguth, 2007), and correlate with adverse outcomes such as substance abuse problems (Alati et al., 2006; Alati et al., 2008; Baer, Barr, Bookstein, Sampson, & Streissguth, 1998; Baer, Sampson, Barr, Connor, & Streissguth, 2003) and trouble with the law (Fast et al., 1999; Streissguth et al., 2004). In the Seattle cohort, prenatal alcohol exposure was associated with alcohol problems at age 21 years, an effect that remained after covarying family history of alcohol use disorders, other prenatal exposures, and other environmental factors such as postnatal parental use of other drugs (Baer et al., 2003). These findings are supported by more recent studies (Alati et al., 2006; Alati et al., 2008) and demonstrate the persistent

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nature of the behavioral effects of prenatal alcohol exposure. Furthermore the wide range of clinical difficulties associated with prenatal alcohol exposure, including impulsivity, mood disorder, and substance abuse, place affected individuals at high risk for suicide. Indeed, individuals with FASD have an increase in lifetime suicide attempts relative to the general population (Baldwin, 2007; O’Malley & Huggins, 2005; Streissguth et al., 1996). In one account, 43% of adults with FASD reported suicide threats and 23% reported a history of suicide attempts throughout their lifetime (Streissguth et al., 1996).

Possible Mechanisms of Action Because of the infeasibility of controlling for confounding factors such as maternal nutrition and timing and dose of alcohol exposure in humans, research focused on identifying mechanisms of alcohol teratogenesis is typically derived from preclinical animal models of FASD and in vitro tissue culture studies. It is unlikely that the variable and wide-ranging effects associated with prenatal alcohol exposure are produced via a single process or pathway. Rather, a multitude of possible pathophysiological mechanisms associated with FASD have been identified, including oxidative stress, changes in glucose metabolism, mitochondrial damage, abnormal growth factor activity, dysregulation of developmental gene expression, anomalous cell adhesion, and abnormalities in the development and regulation of neurotransmitter systems (e.g., excitotoxicity; Goodlett & Horn, 2001; Uban et al., 2011). The majority of these potential mechanisms may result in CNS damage by inducing either necrotic or apoptotic cell death, although disturbance to normal cell division and maturation could also be operative. Unfortunately, pinpointing exact mechanisms through which alcohol exerts teratogenic effects in any given individual is complicated by a host of factors, including variations in timing, dose, and pattern of exposure, maternal characteristics, and genetic factors. Further complicating matters, mechanisms of damage are likely to vary by brain region and cell type (Goodlett, Horn, & Zhou, 2005). Despite these complexities, mechanistic studies have been invaluable in clarifying alcohol’s negative effects on the developing fetus and will continue to be of great utility in the future, particularly in development of prevention and treatment efforts, which are lacking for this population. With regard to treating the psychopathology associated with FASD, preclinical studies can inform intervention efforts by refining our understanding of the structural and functional CNS deficits that contribute to mental illness in this population. Such translational research is crucial to developing effective, evidence-based treatments. In summary, prenatal alcohol exposure is associated with clinically significant psychopathology that is often severe. Moreover, certain psychiatric sequelae, including disruptive behavior disorders, delinquency, substance use disorders, and depressive disorders, are more prevalent among individuals with FASD than comparison populations. As discussed above, etiologic pathways are likely to be complex (i.e., equifinality, see Chapter 1 [Hinshaw]). Indeed, it is not always possible to disentangle direct effects of prenatal alcohol exposure from important

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correlates. Nevertheless, we now know that alcohol teratogenesis is an etiological factor for diverse forms of mental illness and that many individuals with histories of prenatal alcohol exposure may need to be referred for psychiatric evaluation.

PSYCHOPATHOLOGY RELATED TO OTHER PRENATAL EXPOSURES In comparison to alcohol, less is known about effects of other potential teratogens on behavioral and psychopathological outcomes, although the research base is expanding. In this section, we describe findings related to prenatal nicotine, stimulant drugs, methylmercury, lead, and antidepressant medication exposures.

Nicotine Perhaps because of the high frequency at which fetuses are exposed to cigarette smoke, effects of gestational nicotine exposure have been studied fairly extensively, although less is known about behavioral and psychopathological outcomes. It is estimated that about 15% of pregnant women in the United States continue to smoke during pregnancy (Substance Abuse and Mental Health Services Administration, 2014). The most commonly reported effects include increases in ADHD, delinquency, and antisocial behavior. Several studies have focused on the effects of nicotine exposure on antisocial and/or delinquent behavior. Converging data from criminal records (Brennan, Grekin, & Mednick, 1999; Gibson, Piquero, & Tibbetts, 2000; Piquero, Gibson, Tibbetts, Turner, & Katz, 2002; Rantakallio, Läärä, Isohanni, & Moilanen, 1992; Räsänen et al., 1999), parental reports of child behavior (Gatzke-Kopp & Beauchaine, 2007a; Maughan, Taylor, Taylor, Butler, & Bynner, 2001; Ruckinger et al., 2010; Wasserman, Liu, Pine, & Graziano, 2001), and structured psychiatric clinical interviews (Langley, Holmans, van den Bree, & Thapar, 2007; Nigg & Breslau, 2007; Wakschlag et al., 1997; Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002; Wakschlag, Pickett, Kasza, & Loeber, 2006; Weissman, Warner, Wickramaratne, & Kandel, 1999) support a relation between prenatal nicotine exposure and increased delinquency. Importantly, the relation between conduct problems among offspring and fetal nicotine exposure remains after covarying potential confounds (Ruckinger et al., 2010), such as genetic factors (Maughan, Taylor, Caspi, & Moffitt, 2004), parental antisocial behavior (Gatzke-Kopp & Beauchaine, 2007a; Maughan et al., 2004), income, prematurity, birth weight, and poor parenting practices (Gatzke-Kopp & Beauchaine, 2007a). The relation between prenatal nicotine exposure and ADHD is also supported by several studies. Offspring exposed to nicotine during gestation are at increased risk for ADHD symptoms (Batstra, Hadders-Algra, & Neeleman, 2003; Fried, Watkinson, & Gray, 1992; Holz et al., 2014; Langley et al., 2007; Mick, Biederman, Faraone, Sayer, & Kleinman, 2002; Naeye & Peters, 1984; Rodriguez & Bohlin, 2005;

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Romano, Tremblay, Farhat, & Côté, 2006), and effects of fetal nicotine exposure on attention may be independent of those associated with antisocial behaviors (Button, Thapar, & McGuffin, 2005; Langley et al., 2007) and genetic transmission (Thapar et al., 2003). In a study comparing a large sample of boys with ADHD to their peers, increased rates of maternal smoking were documented retrospectively in the ADHD group (Milberger, Biederman, Faraone, Chen, & Jones, 1996). Importantly, the relation remained significant after adjusting for SES, parental IQ, and parental ADHD diagnosis. Similarly, a case-control study estimated that maternal smoking was associated with a threefold increase in developing a hyperkinetic disorder, although other predictive factors such as SES and family psychiatric history weakened this association (Linnet et al., 2005). Despite this evidence, the relation between nicotine exposure and disruptive psychopathology is not universally accepted, and some researchers have contested the degree of risk once confounding factors are controlled (D’Onofrio et al., 2010; Hill et al., 2000; Knopik et al., 2005; Nigg & Breslau, 2007; Roza et al., 2009; Silberg et al., 2003). In one study, researchers evaluated offspring of women who were conceived using assisted reproduction technologies in an attempt to remove the confound of inherited genetic risk for ADHD, as these children are genetically unrelated to the women who carry them during pregnancy. This study demonstrated that the association between prenatal smoking exposure and ADHD was significantly higher in genetically related mother-child pairs than in genetically unrelated pairs, suggesting ADHD is linked to inherited genetic effects rather than prenatal smoking exposure per se (Thapar et al., 2009). This study and others highlight the need to test causal hypotheses regarding behavioral teratogenesis with careful consideration for confounding factors. Prenatal nicotine exposure is also associated with other indicators of disruptive behavior, such as increases in dimensional measures of externalizing behavior, delinquency, and ADHD-like symptoms (Cornelius et al., 2011; Fergusson, 1999; Griesler, Kandel, & Davies, 1998; Indredavik, Brubakk, Romundstad, & Vik, 2007; Obel et al., 2009; Orlebeke, Knol, & Verhulst, 1997; Piper, Gray, & Birkett, 2012; Stene-Larsen, Borge, & Vollrath, 2009; Williams et al., 1998). In some samples, these effects survive statistical covariation of potentially confounding influences including child variables (e.g., sex, ethnicity), maternal variables (e.g., education, age, emotional responsiveness), SES, and parental histories of substance use and criminality (Cornelius et al., 2011; Fergusson, Horwood, & Lynskey, 1993; Indredavik et al., 2007; Obel et al., 2009). There is some evidence that teratogenic exposure may interact with genetic factors to produce psychological outcomes. In one study, for example, a polymorphism in the dopamine transporter (DAT1) gene was associated with increases in hyperactive/impulsive and oppositional behaviors, but only in children who were prenatally exposed to nicotine (Kahn, Khoury, Nichols, & Lanphear, 2003). Another study demonstrated an interaction between prenatal exposure to smoking and variations in the DAT1 and DRD4 loci among children with ADHD. Children who inherited the DAT1 440 allele or the DRD 7-repeat allele and were exposed were almost 3 times more likely than nonexposed children

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to be diagnosed with ADHD (Neuman et al., 2007). Some research suggests that the interaction between DAT1 genotype and prenatal smoke exposure increases risk for hyperactivity and impulsivity only among males (Becker, El-Faddagh, Schmidt, Esser, & Laucht, 2008), but more recent prospective investigations reveal predictive associations in females (Gard, Owens, & Hinshaw, 2015). Although the etiology of such behaviors is clearly multifaceted, these studies identify potential mechanisms through which gene-environment interactions increase vulnerability to psychopathology. The association between disruptive, externalizing behaviors and prenatal nicotine exposure appears to manifest among offspring at a young age. Assessments of toddlers whose mothers smoked during pregnancy reveal higher rates of negative conduct, including aggressive, oppositional behaviors, and/or hyperactive behaviors, even after controlling for socioeconomic and child-rearing variables (Brook, Brook, & Whiteman, 2000; Day, Richardson, Goldschmidt, & Cornelius, 2000; Linnet et al., 2006; Stene-Larsen et al., 2009). Poor peer relations and increased tantrums are also observed among toddlers exposed to nicotine, even when covarying effects of other drug exposures such as alcohol, marijuana, and cocaine (Faden & Graubard, 2000). Finally, maternal smoking during pregnancy is a risk factor for persisting generalized behavioral problems from ages 3 to 8 years (Gray, Indurkhya, & McCormick, 2004). Although disruptive disorders are the most commonly studied, a smaller body of literature suggests that higher rates of substance use problems, depression, and other internalizing symptoms are associated with nicotine exposure (Ashford, van Lier, Timmermans, Cuijpers, & Koot, 2008; Brennan, Grekin, Mortensen, & Mednick, 2002; Ekblad, Gissler, Lehtonen, & Korkeila, 2010; Fergusson, Woodward, & Horwood, 1998; Indredavik et al., 2007; Weissman et al., 1999). In summary, prenatal nicotine exposure increases vulnerability to psychiatric symptoms, particularly those on the externalizing spectrum, although other important explanatory variables, such as concurrent prenatal exposures and family history, are likely to contribute to the association. Future research with greater adjustment for confounding variables will be useful in further defining the role that prenatal nicotine exposure plays in the development of psychiatric symptoms.

Other Stimulant Drugs Teratogenic effects of other drugs of abuse are less studied than those of alcohol and nicotine, but there is evidence that prenatal exposure to stimulants may be associated with certain neurobehavioral alterations. Although early depictions of fetal cocaine exposure in the popular press were somewhat exaggerated, more recent research has helped to clarify this issue. Increased levels of aggressive behavior have been reported in cocaine-exposed children (Bada et al., 2007; Bada et al., 2011; Bendersky, Bennett, & Lewis, 2006; Griffith, Azuma, & Chasnoff, 1994; Linares et al., 2006; Minnes et al., 2010; Richardson, Goldschmidt, Leech, & Willford, 2011; Singer, Minnes, Min, Lewis, & Short, 2015; Sood et al., 2005), although moderating effects of sex and comorbid alcohol exposure are important to consider (Nordstrom

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Bailey et al., 2005). Nevertheless, several studies demonstrate that group differences remain even after covarying potential confounds (Bada et al., 2007; Bada et al., 2010; Minnes et al., 2010; Richardson et al., 2011)—and that behavior problems manifest in boys more than girls (Bendersky et al., 2006; Bennett, Bendersky, & Lewis, 2007; Delaney-Black et al., 2004; Dennis, Bendersky, Ramsay, & Lewis, 2006). However, a few more recent investigations have found the opposite, with cocaine-exposed girls being at greater risk for delinquent behaviors (McLaughlin et al., 2011; Minnes et al., 2010; Sood et al., 2005). Prenatal cocaine exposure may also relate to increased infant and toddler irritability and mood lability (Behnke, Eyler, Garvan, Wobie, & Hou, 2002; Chaplin, Fahy, Sinha, & Mayes, 2009; Richardson, Goldschmidt, & Willford, 2008; Richardson, 1998). Additionally, cocaine exposure may result in impaired self-regulation, heightened excitability, more passive-withdrawn negative affect, and decreased adaptability in infants (Lambert & Bauer, 2012). Still, it is not clear whether these behaviors observed in infancy correlate directly with increased psychopathology later in life. One follow-up study of 6-year-olds did not find effects of prenatal cocaine exposure on teacher ratings of child behavior after adjusting for the influences of race, child IQ, school grade, and fetal exposure to alcohol, marijuana, and tobacco (Richardson, Conroy, & Day, 1996).1 However, another investigation that evaluated prenatal cocaine exposure during the first trimester of pregnancy versus exposure throughout pregnancy demonstrated that school-aged children of mothers who used cocaine through the third trimester showed increased levels of externalizing behaviors after addressing confounding variables (Richardson et al., 2011). Furthermore, a recent study indicated that prenatal cocaine exposure was related to teen use of cocaine at age 14 (Delaney-Black et al., 2011). These findings suggest that the neurobehavioral effects of cocaine may manifest differently as a factor of the exposed child’s age, as well as the dose and the timing of maternal cocaine use, all of which may interact with a host of other risk factors. Interestingly, cognitive deficits, particularly deficits in attention, are associated with prenatal cocaine exposure (Ackerman, Riggins, & Black, 2008; Bandstra, Morrow, Anthony, Accornero, & Fried, 2001; Heffelfinger, Craft, White, & Shyken, 2002; Noland et al., 2005; Savage, Brodsky, Malmud, Giannetta, & Hurt, 2005); however, the relation of these deficits to the development of ADHD remains unclear. Despite effects noted above, many studies have failed to find a significant association between prenatal cocaine exposure and the development of psychopathology such as behavior problems (Accornero, Morrow, Bandstra, Johnson, & Anthony, 1. Concerns arise whenever one covaries influences that are highly correlated with a primary independent variable from relations between that independent variable and a focal dependent variable. This practice creates statistical circumstances that do not exist in reality (see Miller & Chapman, 2001). In this instance, since cocaine use and alcohol use are highly correlated, covarying alcohol use from the relation between cocaine use and child psychopathology creates a situation that is rare in practice (cocaine use without concurrent alcohol use). Because considerable shared variance between cocaine use and alcohol use was removed from the prediction equation, this study and similar studies likely underestimate the effects of prenatal cocaine exposure on children’s behavioral outcomes.

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2002; Azuma & Chasnoff, 1993; Bennett, Bendersky, & Lewis, 2002; Frank, Augustyn, Knight, Pell, & Zuckerman, 2001; Messinger et al., 2004; Nair, Black, Ackerman, Schuler, & Keane, 2008; Phelps, Wallace, & Bontrager, 1997; Warner et al., 2006), depressive symptoms (Lambert & Bauer, 2012; O’Leary et al., 2006), and poor impulse control (Bendersky & Lewis, 1998). Rather, research suggests that postnatal variables such as the mother’s continued drug use, level of mental functioning, and depressive symptoms are better predictors of mental health status in cocaine-exposed children than exposure-related variables per se. In one previously discussed study that focused on alcohol exposure and development of depressive features among children, exposure to cocaine was associated with negative infant affect but not with subsequent development of depressive features (O’Connor & Paley, 2006). Nicotine, marijuana, and caffeine were also examined in this sample. They were not associated with childhood depression, although it is unclear whether exposure to these other drugs occurred at rates high enough to afford adequate statistical power to detect effects, were they to exist.

Possible Mechanisms of Action As with the study of FASD, preclinical animal models of gestational stimulant drug exposure have been invaluable in elucidating the role of drugs of abuse on the developing CNS. In particular, monoaminergic systems (dopamine, serotonin, norepinephrine) are affected by such exposure (cf. Mayes, 2002; Middaugh, 1989), although factors such as age and sex may be important moderators of outcome (Glatt, Bolaños, Trksak, & Jackson, 2000). Atypical development of monoamine neurotransmission may help to explain attention and arousal dysfunctions observed in prenatal exposure to strong stimulants. For example, one possible causal model of arousal dysregulation following prenatal cocaine exposure is impairment in the ability to switch between executively versus automatically driven arousal (Mayes, 2002), functions subserved by the prefrontal cortex that rely on intact dopamine and norepinephrine neurotransmission. Because of effects of cocaine and methamphetamine on developing monoaminergic systems (e.g., uncoupling of the D1 receptor, increased D2 receptor binding), (a) midbrain dopamine responding, which is crucial for healthy hedonic capacity and associative learning (see Gatzke-Kopp, 2011; Gatzke-Kopp & Beauchaine, 2007b), is altered into adulthood (e.g., Bubenikova-Valesova et al., 2009); and (b) the normal balance between dopiminergically mediated and noradrenergically mediated arousal regulatory systems is disrupted (e.g., Mayes, 2002). Similar to human studies, animal models have shown an increased response to stimulants and limited alterations in behavioral functioning among rats exposed to cocaine in utero (Glatt, Bolaños, Trksak, Crowder-Dupont, & Jackson, 2000; Peris, Coleman-Hardee, & Millard, 1992). As compared to nonexposed rats, rats exposed to cocaine in utero displayed heightened responses to amphetamine exposure as adults. It is hypothesized that dopaminergic pathways are largely unaffected

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by prenatal cocaine exposure, as behavioral functioning appears to be intact in exposed rats. Instead, observed differences in sensitivity to amphetamine use in adulthood appear to be mediated by changes specifically in striatal dopaminergic functioning (Glatt, Bolaños, Trksak, Crowder-Dupont et al., 2000). Additionally, the observed change in sensitivity to stimulant use in adulthood appears to be mediated by sex (Peris et al., 1992), with prenatally exposed males and females displaying differential neurochemical responses to stimulant exposure. Findings on other aspects of behavioral functioning have been mixed. One study showed that in utero exposure to cocaine increased rates of anxiety in adult male and female rats (Salas-Ramirez, Frankfurt, Alexander, Luine, & Friedman, 2010), while other incidental findings suggest similar levels of anxiety between cocaine exposed and control rabbits (Thompson, Levitt, & Standwood, 2005). In sum, behavioral effects of prenatal stimulant exposure may be less pronounced than those associated with alcohol and nicotine teratogenesis, although problems with statistical covariation of confounds may have caused a literature-wide underestimation of such effects. In addition, environmental factors related to caregiving may be especially important to consider in stimulant exposure cases. Ultimately, more research is needed to clarify the extent to which exposure to stimulants increases vulnerability to psychopathology.

Methylmercury and Lead Methylmercury toxicity is also associated with neurobehavioral deficits following both pre- and postnatal exposures (Debes, Budtz-Jorgensen, Weihe, White, & Grandjean, 2006; Julvez, Debes, Weihe, Choi, & Grandjean, 2010; Mendola, Selevan, Gutter, & Rice, 2002). However, there is little existing evidence that low-level exposures are associated with marked alterations in typical behavioral development (Davidson et al., 2011; Davidson, Myers, Shamlaye, Cox, & Wilding, 2004; Myers et al., 2003). Much of the research on methylmercury derives from one longitudinal study of relatively low levels of exposure resulting from fish consumption (for review, see Davidson, Myers, Weiss, Shamlaye, & Cox, 2006). Findings do not indicate an association between prenatal methylmercury exposure and later adverse developmental outcomes. The most recent study evaluated the main cohort at age 17 years and found improved performance or no association between prenatal methylmercury exposure on 26 of 27 cognitive and behavioral measures (Davidson et al., 2011). However, in another cohort exposed to methylmercury through maternal consumption of whale meat, mercury-related cognitive deficits were found (Grandjean et al., 1997; Julvez et al., 2010). Although developmental outcome studies of prenatal exposure to methylmercury yield inconsistent findings (e.g., Spurgeon, 2006), only a few have examined behavior. Of the studies in which a behavioral measure was used, prenatal exposure to methylmercury was not related to negative outcomes (reviewed in Davidson et al., 2011; Myers & Davidson, 1998). Thus, although existing data do not suggest a link between methylmercury teratogenesis and psychopathology, more research is needed to confirm this conclusion, particularly in cases with higher exposure levels.

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In considering teratogenic exposure to lead, it is often difficult to differentiate between prenatal and postnatal exposure, given the likelihood of continued environmental exposure after birth (Burns, Baghurst, Sawyer, McMichael, & Tong, 1999; Needleman, McFarland, Ness, Fienberg, & Tobin, 2002; Thapar, Cooper, Eyre, & Langley, 2013; Wasserman, Staghezza-Jaramillo, Shrout, Popovac, & Graziano, 1998). Lead exposure in childhood gained considerable attention in 2014 when it was discovered that blood lead levels of children in Flint, Michigan were notably higher than accepted standards (5 μg/dL). After switching the city’s water supply from the Detroit water system to the Flint River, the percentage of children with elevated blood lead levels (>5 μg/dL) in affected zip codes increased from 2.1 to 4.0, a statistically significant change (Roy, 2015). With almost 45,000 homes affected by increased water lead levels, the mayor of Flint declared a state of emergency (Lew, 2015). Currently, no studies have been conducted examining impacts on prenatal health or effects of the elevated water lead levels on child development in Flint. However, previous studies investigating effects of elevated lead exposure have shown an increased rate of fetal deaths (Edwards, 2014) and risk of serious health impacts among sensitive populations (e.g., formula-fed infants) even at low levels of exposure (Triantafyllidou, Gallagher, & Edwards, 2014). Future research will be necessary to determine the exact consequences of elevated water lead levels among children and pregnant women in Flint, but public health implications are immense. Research aimed at disambiguating effects of timing of lead exposure suggests that postnatal lead exposure may be more influential than prenatal exposure (Bellinger, 1994; Leviton et al., 1993). However, there is some evidence for increased rates of delinquency among children exposed prenatally to lead. The Cincinnati Lead Study, which identified a cohort of pregnant women prospectively in order to examine effects of lead toxicity on child development, found increased rates of both selfand parent-reported delinquency and antisocial behavior associated with prenatal lead exposure (Dietrich, Ris, Succop, Berger, & Bornschein, 2001). This relation was independent of birth weight, parental IQ, quality of home environment, and SES. In a later investigation conducted on the same cohort, prenatal lead exposure was related to high numbers of arrests in early adulthood (Wright et al., 2008). Thus, although developmental lead exposure has received the most attention regarding cognitive and behavioral outcomes in children, the potential importance of prenatal lead exposure should not be underestimated as there is some evidence that it can lead to deleterious consequences throughout the lifespan. Regardless of time of exposure, the seemingly irreversible deleterious effects associated with lead exposure have prompted increased focus on primary prevention (Betts, 2012).

Antidepressant Medication Research findings on effects of prenatal exposure to selective serotonin reuptake inhibitors (SSRIs) are inconsistent. Limited evidence shows delayed motor control and motor development (Casper et al., 2003) and higher levels of internalizing behaviors (Hanley, Brain, & Oberlander, 2015) among young children exposed

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to SSRIs. However, some studies found no evidence to suggest that exposure in utero to antidepressant medications adversely affects cognitive or behavioral development (Grzeskowiak et al., 2015; Nulman et al., 1997). Instead, maternal illness and attachment/interaction with infant may provide a stronger predictor of adverse behavioral outcomes among those children (Grzeskowiak et al., 2015; Misri et al., 2006). Several studies that have investigated the relation between autism spectrum disorder (ASD) and prenatal exposure to antidepressant medications show increased vulnerability (Gidaya et al., 2014; Rai et al., 2013), with exposure during the first trimester being most dangerous (Harrington, Lee, Crum, Zimmerman, & Hertz-Picciotto, 2014; Croen, Grether, Yoshida, Odouli, & Hendrick, 2011). Others, however, have found no increase in vulnerability to development of ASD (Sørensen et al., 2013; Hviid, Melbye, & Pasternak, 2013). Similarly, findings on perinatal complications (e.g., preterm birth, low birth weight, small gestational age) due to prenatal exposure to SSRIs have been mixed (see Ellfolk & Malm, 2010). One study found that both exposure to SSRIs or untreated maternal depression increased the chance of preterm birth (Wisner et al., 2009). Since untreated maternal depression also imparts vulnerability to the fetus, the importance of weighing costs and benefits of medication use is imperative (Gidaya et al., 2014; Harrington et al., 2014). Further investigation is warranted to disentangle the effects of maternal illness and medication exposure and the impact of each on prenatal and postnatal health of the fetus (Misri et al., 2006).

CONCLUSIONS Available data underscore the need for clinicians to take thorough prenatal exposure histories and consider possible influences of teratogens when assessing psychiatric symptoms. Examples discussed in this chapter demonstrate that teratogenic exposure increases risk for several common psychiatric disorders. However, effects of potential mediating and moderating factors underscore a common theme: Fetal exposures to teratogenic agents are not necessarily the sole or direct cause of mental illness. Rather, it seems that teratogenic exposures act in concert with other risk factors, and a combination of interacting determinants is likely necessary to lead to the development of psychopathological behavior, exemplifying multifinality (see Chapter 1 [Hinshaw]). Importantly, individuals with teratogenic exposures, such as those to alcohol, may not respond in the same manner as other mental health patients to psychotherapeutic and/or pharmacological treatments (Doig, McLennan, & Gibbard, 2008; O’Connor et al., 2002). Thus, taking an accurate prenatal history could be important for determining the most effective treatment.

RISK AND PROTECTIVE FACTORS Although complete prevention of teratogenic exposure is clearly ideal, this may not always be possible or practical. In addition, given the multifactorial nature

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of the etiology of psychiatric illness, it is important to identify factors that may prevent or limit the development of mental health problems in the face of teratogenic exposure. Such protective factors can form the cornerstone of effective mental health intervention and prevention efforts. An equally important task is to identify variables that increase the likelihood of developing psychopathology in cases of teratogenic exposures. Hopefully, once identified, exposure to such risk factors can be minimized. For example, in the case of alcohol, potential aspects that may protect individuals against a negative mental health outcome status include disability service eligibility, a nurturing and stable home (Streissguth et al., 1996), and early identification and treatment of children (Streissguth et al., 2004). Based on caregiver interviews, children who are reared in more stable home settings are three- to fourfold less likely to experience the majority of adverse life events examined (i.e., disrupted schooling, legal trouble, substance abuse, inappropriate sexual behaviors; Streissguth et al., 2004). In a more recent study, behavior problems in alcohol-exposed children were related to the length of time spent in out-of-home placements (Fagerlund, Autti-Rämö, Hoyme, Mattson, & Korkman, 2011). This is an important point to underscore, as it highlights the interactive nature of biology-environment relationships that drive the development of psychopathology. Thus, a stable and nurturing home is one potential and salient environmentally mediated pathway to protect children with prenatal alcohol exposure from developing psychopathological behavior.

SYNTHESIS AND FUTURE DIRECTIONS Insufficient data exist to determine conclusively whether associations exist between some known teratogens and psychopathology. Furthermore, the behavioral teratogenicity of many additional compounds, such as common prescription medications, remains virtually unknown. However, effects of prenatal alcohol exposure reviewed above provide clear evidence that teratogenic exposures confer vulnerability to psychopathology. More research is needed to provide pregnant women and their health care providers with adequate information to promote the health of both the mother and her child. In particular, future studies might focus on developing a profile of potential mental health problems for exposed individuals, while also distilling factors that may prevent development of mental health problems in these children. To promote factors that protect against mental illness and to deliver interventions effectively, valid early detection methods and increased awareness of teratogenic exposures, especially among pediatric healthcare providers, are necessary.

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Wakschlag, L. S., Pickett, K. E., Kasza, K. E., & Loeber, R. (2006). Is prenatal smoking associated with a developmental pattern of conduct problems in young boys? Journal of the American Academy of Child and Adolescent Psychiatry, 45, 461–467. Ware, A. L., Glass, L., Crocker, N., Deweese, B. N., Coles, C. D., Kable, J. A., . . . the CIFASD. (2014). Effects of prenatal alcohol exposure and attention-deficit/ hyperactivity disorder on adaptive functioning. Alcoholism: Clinical and Experimental Research, 38, 1439–1447. Ware, A. L., O’Brien, J. W., Crocker, N., Deweese, B. N., Roesch, S. C., Coles, C. D., . . . the CIFASD. (2013). The effects of prenatal alcohol exposure and attention-deficit/hyperactivity disorder on psychopathology and behavior. Alcoholism: Clinical and Experimental Research, 37, 507–516. Warner, T. D., Behnke, M., Hou, W., Garvan, C. W., Wobie, K., & Eyler, F. D. (2006). Predicting caregiver-reported behavior problems in cocaine-exposed children at 3 years. Journal of Developmental and Behavioral Pediatrics, 27, 83–92. Warren, K. R., & Hewitt, B. G. (2009). Fetal alcohol spectrum disorders: When science, medicine, public policy, and laws collide. Developmental Disabilities Research Reviews, 15, 170–175. Wasserman, G. A., Liu, X., Pine, D. S., & Graziano, J. H. (2001). Contribution of maternal smoking during pregnancy and lead exposure to early child behavior problems. Neurotoxicology and Teratology, 23, 13–21. Wasserman, G. A., Staghezza-Jaramillo, B., Shrout, P., Popovac, D., & Graziano, J. (1998). The effect of lead exposure on behavior problems in preschool children. American Journal of Public Health, 88, 481–486. Weissman, M. M., Warner, V., Wickramaratne, P. J., & Kandel, D. B. (1999). Maternal smoking during pregnancy and psychopathology in offspring followed to adulthood. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 892–899. Whaley, S. E., O’Connor, M. J., & Gunderson, B. (2001). Comparison of the adaptive functioning of children prenatally exposed to alcohol to a nonexposed clinical sample. Alcoholism: Clinical and Experimental Research, 25, 1018–1024. Williams, G. M., O’Callaghan, M., Najman, J. M., Bor, W., Andersen, M. J., Richards, D., & Chinlyn, U. (1998). Maternal cigarette smoking and child psychiatric morbidity: A longitudinal study. Pediatrics, 102, e11. Wisner, K. L., Sit, D. K. Y., Hanusa, B. H., Moses-Kolko, E. L., Bogen, D. L., Hunker, D. F., . . . Singer, L. T. (2009). Major depression and antidepressant treatment: Impact on pregnancy and neonatal outcomes. American Journal of Psychiatry, 166, 557–566. Wright, J. P., Dietrich, K. N., Ris, M. D., Hornung, R. W., Wessel, S. D., Lanphear, B. P., . . . Rae, M. N. (2008). Association of prenatal and childhood blood lead concentrations with criminal arrests in early adulthood. PLoS Med, 5, e101.

C H A P T E R 10

Brain Injury and Vulnerability to Psychopathology PETER ARNETT, JESSICA E. MEYER, VICTORIA C. MERRITT, LISA GATZKE-KOPP, AND KATHERINE E. SHANNON BOWEN

HISTORICAL CONTEXT

T

he 1848 accident incurred by railroad worker Phineas Gage is legendary in psychology and neuroscience, and is described commonly in introductory textbooks. Gage attained fame after surviving an extraordinary accident in which an explosion propelled a 3-foot-long iron rod through the frontal portion of his skull and brain. Merely surviving such an accident is uncommon, but more remarkable was his apparent recovery of memory, communication, and most other basic mental functions. However, reports from those close to Gage indicate that the injury conferred permanent changes to his personality, resulting in self-destructive and socially inappropriate behaviors stemming from poor judgment. As indicated by his friends, he was “no longer Gage” (see Kotowicz, 2007, p. 117). Continued fascination with this story over the past 150 years follows from its demonstration that the brain is responsible for fundamental aspects of our individuality. This story illustrates the importance of brain function for psychological health, and the brain’s sensitivity to acute trauma.

TERMINOLOGICAL AND CONCEPTUAL ISSUES Gage’s story describes an instance of open head trauma. More recently, scientists have gained increased understanding of the consequences of traumatic force that occurs without skull penetration—referred to as closed head injury. Closed head injuries and their sequelae continue to be a prominent focus of medical research. This is especially the case for mild head injuries, commonly known as concussions. A concussion is usually defined as neurological impairment caused 316

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by biomechanical strain on central nervous system (CNS) tissue. As McCrory et al. (2009) note, a concussion occurs as a result of “a complex pathophysiological process affecting the brain, induced by traumatic biomechanical forces” (p. 37). However, the term concussion is often used inconsistently among clinicians to refer to varying severities of brain injury. When children are injured, terms such as concussion may be used to ease parental concern, with the implication of a lack of lasting consequences (Dematteo et al., 2010). Despite the lack of formal definition, concussions are usually diagnosed when symptoms are observed in one or more of the following domains: (a) cognitive— including confusion, poor concentration, inability to follow directions or answer questions, amnesia, and/or loss of consciousness; (b) medical—including headaches, nausea and/or vomiting; (c) sensory—including dizziness, poor coordination, and/or loss of balance, alterations in vision or hearing (e.g., seeing stars or hearing ringing); and (d) psychological—including irritability, changes in personality, and/or context-inappropriate emotions (McCrory et al., 2005). Merritt and Arnett (2014) found that symptoms from the commonly used Postconcussion Symptom Scale (PCSS) load on four distinct factors involving cognitive, affective, physical, and sleep symptoms. Interestingly, one of the most common and often debilitating postconcussion symptoms, headache, does not load clearly on any factor. Concussions were long believed to be transient physical states with complete resolution of symptoms expected within three months. Thus, it was believed that no permanent changes in brain structure, function, or behavior were incurred by concussion victims (Gaetz, Goodman, & Weinberg, 2000). However, more recent research indicates that detrimental effects can persist for many individuals for extended periods of time, even in cases classified as mild (see Slobounov, Sebastianelli, & Hallett, 2012; Yeates, 2010). Some evidence also suggests that impairment can increase rather than decrease in weeks following injury (Scherwath et al., 2011). Some research also shows that EEG abnormalities can persist weeks after clinical symptoms subside (Slobounov et al., 2012). Thus, full brain recovery may take longer than indicated by self-reported symptoms. Importantly, detrimental effects of mild head injuries are extended and exacerbated when such injuries are experienced repeatedly. Repetitive head injuries are common among both amateur and professional athletes, from childhood through adulthood. High-contact sports such as football, soccer, and hockey, where head-to-head contact occurs between athletes, and where the head may hit the ground or strike a ball, are associated with high concussion rates (Delaney, Puni, & Rouah, 2006). Consequently, organized sports have become a focus of both research and policy developments with regard to brain injury. In 2009, the Zackery Lystedt Law (2009) (Federal House Bill 1824) was passed, which prohibits young athletes from returning to play after a suspected concussion without approval from a medical professional. This law follows in part from evidence that concussions result in metabolic changes that temporarily enhance susceptibility of the brain to further

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damage. Unfortunately, recent neuroimaging research suggests that resolution of these metabolic changes may not coincide with remission of cognitive symptoms or recovery time (Slobounov et al., 2012; Vagnozzi et al., 2008). Considerably more work is needed before more accurate decisions can be made about when vulnerability subsides. In addition to traumatic head injury, the brain is susceptible to insults from other sources, most notably teratogenic substances (i.e., substances ingested by children or pregnant mothers, which affect the developing brain; see Chapter 9 [Doyle, Mattson, Fryer, & Crocker]), and insufficient supply of oxygen (hypoxia) or blood flow (ischemia). The brain may be especially vulnerable to these influences prenatally. In particular, hypoxia and ischemia result in extensive cell death (see Ment, Hirtz, & Huppi, 2009; Vannucci, 2000), although behavioral and psychological consequences are not specific or well understood. In this chapter, we review basic brain injury mechanisms, discuss specific developmental aspects of brain injury, and consider how injury contributes to the development of psychopathology.

PREVALENCE Brain injuries occur most often among children between ages 0 and 4 years, and among adolescents between ages 15 and 19 years (Faul, Xu, Wald, & Coronado, 2010). Children between ages 5 and 9 years are less likely to sustain injury (Toledo et al., 2012). Each year an estimated half million children are brought to emergency rooms for treatment of traumatic brain injury (TBI), of whom less than 1% die. An unknown number of additional individuals sustain injuries that are unreported and receive no medical attention (Faul et al., 2010). Abuse is a common cause of head injuries among infants and toddlers, representing an estimated 22% of all TBIs among children between ages 0 and 3 years (Leventhal, Martin, & Asnes, 2010). Factors that result in even mild levels of oxygen desaturation—including medical conditions such as congenital heart disease, sleep-disordered breathing, and severe or poorly treated asthma, as well as accidents such as near drownings or carbon monoxide poisoning—can also result in significant cell death (Bass et al., 2004; Hori, 1985). However, such injuries are difficult to quantify and may go unrecognized in mild cases, making occurrence rates difficult to estimate. In addition to age, other individual differences are also associated with susceptibility to brain injury. Rates of occurrence are higher among males than among females, and among those of low socioeconomic status (Bruns & Hauser, 2003; Faul et al., 2010; Toledo et al., 2012). Researchers who reviewed medical charts across more than 70 hospitals found that children who are impulsive, including those with attention-deficit/hyperactivity disorder (ADHD), are more likely to sustain injuries to all areas of the body, with the head being no exception. In this study, children with ADHD were also more likely to sustain severe injuries (DiScala, Lescohier, Barthel, & Li, 1998). Some have suggested that the apparent link between ADHD and head injury is due in large part to poor parental supervision commonly experienced by externalizing children (Schwebel, Hodgens, & Sterling, 2006).

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Furthermore, although impulsivity is highly heritable (see Chapter 6 [Neuhaus & Beauchaine]), child-specific environmental factors are better predictors of head injury than either genetic or family environmental factors, suggesting little support for a heritable “injury/accident proneness” trait among children (Ordoñana, Caspi, & Moffitt, 2008). Adeyemo et al. (2014) conducted a recent meta-analysis of the mild Traumatic Brain Injury (mTBI)-ADHD relation among over 3,000 mTBI patients and almost 10,000 controls. They found an association between ADHD and mTBI, with a relative risk ratio of 2.0, which indicates that an individual with ADHD has two times the risk of mTBI compared with controls. For studies in which ADHD was present prior to mTBI, there was no association between the two variables. In contrast, for studies in which ADHD emerged after mTBI, a significant relation was found, with a pooled relative risk of 2.2. This finding supports the contentious suggestion that ADHD does not confer vulnerability to mTBI; rather, it is sometimes an adverse sequela of mTBI. It is important to note that other studies have failed to report such findings (see Davidson, 1987; Olsson, Le Brocque, Kenardy, Anderson, & Spence, 2008). Debate continues regarding impulsivity as a risk factor for head injuries, including whether head injuries and externalizing behaviors are multifinal consequences of other environmental risks.

ETIOLOGICAL FORMULATIONS As noted above, causes of brain injury include accidental trauma (e.g., falls, car accidents, bicycle accidents, sports collisions), nonaccidental trauma (e.g., child abuse), and hypoxic-ischemic events (e.g., pregnancy and birth complications, infections, damage secondary to trauma). Research over the past several decades highlights that brain injuries can occur at any time during development and that multiple causes of injury can result in similar types of brain damage (signifying equifinality). Animal studies and postmortem studies with humans, along with advanced neuroimaging techniques, have helped elucidate mechanisms through which brain injuries and related impairments are effected. In sections to follow, we focus on the most common and most basic factors that result in brain cell death—trauma and hypoxia—and we describe neuroimaging methods that can detect various types of brain injury, and identify causes of cell death.

Mechanisms of Brain Injury In this section, we discuss two key mechanisms of brain injury, trauma and hypoxia. Trauma. Traumatic brain injury is defined as a change in brain function that manifests as confusion, altered level of consciousness, coma, seizure, acute sensory or motor neurological deficit, neuropsychological deficit, or behavioral change, resulting from any blunt or penetrating force to the head (Bruns & Hauser,

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2003). TBI occurs when rapid deceleration of the brain against the bony inner surface of the skull produces tissue compression, resulting in neuronal and vascular damage (Finnie & Blumbergs, 2002). The nature of mechanical forces applied to the head produces different types of tissue damage, which are often classified as focal or diffuse (Gennarelli & Meaney, 1996). Focal tissue damage occurs most often in injuries that result from translational forces applied along the linear axis of the brain (Yeates, 2000). Under conditions insufficient to penetrate the skull, such force results in a localized deformation of the bone and compression of underlying tissue (Gennarelli & Meaney, 1996). When the brain compresses against the skull, small hemorrhages develop on its gyral surfaces, which cause a contusion or focal tissue damage (Finnie & Blumbergs, 2002). Such injuries also result in contrecoup contusions, defined as compressive tissue damage at regions remote from the initial contact point. This occurs when a force applied to the head causes the brain to rebound and contact the skull a second time at a point opposite the initial injury (Gennarelli & Meaney, 1996). These types of injuries can result in significant tissue damage, most commonly without loss of consciousness (Gennarelli & Meaney, 1996). Given the degree of tissue damage that can occur without loss of consciousness, unconsciousness is a poor surrogate for radiological and/or neuropsychological assessments (Schutzman & Greenes, 2001). This consideration is reflected in recent updates to sports concussion grading systems, in which postconcussion self-reported symptoms have taken on an increasingly prominent role in defining severity, above and beyond issues relating to loss of consciousness per se (Arnett et al., 2014). In contrast to focal damage caused by translational injuries, diffuse damage results from rotational forces, producing angular movement around the brain’s center of gravity. This damage occurs when the head strikes against a broad object, such as the interior of a car, diffusing the force across the surface of the skull (Gennarelli & Meaney, 1996). Rotational force produces a shearing strain on the brain, tearing axonal tissue. By destroying axons, both afferent and efferent activity may be interrupted in any brain region. Destruction of axonal communication between and across regions can produce functionally similar impairments as those associated with direct focal damage to the disrupted region. For instance, a disruption in the connection between the frontal cortex and subcortical structures can produce frontally mediated impairment without observable damage to the frontal lobe (Schnider & Gutbrod, 1999). In fact, axonal damage is frequently undetectable by standard neuroimaging protocols and thus requires advanced imaging techniques such as volumetric analysis and diffusion tensor imaging (DTI) (Ashwal, Holshouser, & Tong, 2006; Van Boven et al., 2009). Wäljas et al. (2015) recently reported that a high proportion (about 50%) of their mTBI sample showed microstructural abnormalities in the brain, as detected by DTI,