Developmental Origins of Aggression

DEVELOPMENTAL ORIGINS OF AGGRESSION

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DEVELOPMENTAL ORIGINS OF AGGRESSION

Edited by RICHARD E. TREMBLAY WILLARD W. HARTUP JOHN ARCHER

THE GUILFORD PRESS New York London

© 2005 The Guilford Press A Division of Guilford Publications, Inc. 72 Spring Street, New York, NY 10012 www.guilford.com All rights reserved No part of this book may be reproduced, translated, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise, without written permission from the Publisher. Printed in the United States of America This book is printed on acid-free paper. Last digit is print number: 9 8 7 6 5 4 3 2 1

Library of Congress Cataloging-in-Publication Data Developmental origins of aggression / edited by Richard E. Tremblay, Willard W. Hartup, John Archer. p. cm. Includes bibliographical references and index. ISBN 1-59385-110-3 (hardcover : alk. paper) 1. Aggressiveness. 2. Aggressiveness—Longitudinal studies. 3. Child psychology. I. Tremblay, Richard Ernest. II. Hartup, Willard W. III. Archer, John, 1944– BF575.A3D45 2005 155.2′32—dc22 2004025158

In memory of Joan McCord (1930–2004), colleague, role model, and friend

(left to right): Richard E. Tremblay, Joan McCord, Willard W. Hartup, and John Archer.

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About the Editors

About the Editors

Richard E. Tremblay, PhD, is Professor of Pediatrics, Psychiatry, and Psychology at the University of Montreal and Director of the Inter-University Research Unit on Children’s Psychosocial Maladjustment. He is also Director of the Centre of Excellence for Early Childhood Development, Canada Research Chair in Child Development, Molson Fellow of the Canadian Institute for Advanced Research, Fellow of the Academy of Experimental Criminology, and Fellow of the Royal Society of Canada. For over 20 years, he has conducted a program of longitudinal and experimental studies addressing the physical, cognitive, emotional, and social development of children from conception onward to understand the development and prevention of antisocial behavior. Willard W. Hartup, EdD, is Regents’ Professor Emeritus and former Director of the Institute of Child Development at the University of Minnesota. Dr. Hartup has spent many years researching friendship and peer relations in child development, antipathies and their significance, and conflict and aggression in childhood and adolescence. He obtained an EdD degree from Harvard University, and has received the G. Stanley Hall Award for Distinguished Contributions to Developmental Psychology from the American Psychological Association and Distinguished Scientific Contribution Awards from both the Society for Research in Child Development and the International Society for the Study of Behavioural Development. John Archer, PhD, is Professor of Psychology at the University of Central Lancashire, Preston, United Kingdom. He received a PhD from the University of Bristol in 1970. A Fellow of the British Psychological Society and President of the International Society for Research on Aggression, his research is concerned with human aggression, grief and loss, and sex differences. Dr. Archer is also author of several books, including Sex and Gender (with Barbara Lloyd) and The Nature of Grief; numerous book chapters; and over 100 articles in refereed journals covering psychology, medicine, and biology. In recent years, he has published a number of meta-analytic reviews on topics connected with sex differences in aggression. vii

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Contributors

Contributors

John Archer, PhD, Department of Psychology, University of Central Lancashire, Preston, United Kingdom Chawki Benkelfat, MD, Department of Psychiatry, McGill University, Montreal, Quebec, Canada Michel Boivin, PhD, Research Unit on Children’s Psychosocial Maladjustment, School of Psychology, Laval University, Quebec City, Quebec, Canada Mara Brendgen, PhD, Department of Psychology, University of Quebec at Montreal, Montreal, Quebec, Canada Sylvana Côté, PhD, School of Psychoeducation, University of Montreal, Montreal, Quebec, Canada Ginette Dionne, PhD, School of Psychology, Laval University, Quebec City, Quebec, Canada Joseph L. Flanders, BSc, Department of Psychology, McGill University, Montreal, Quebec, Canada Afra Foroud, MSc, Canadian Centre for Behavioural Neuroscience, Department of Psychology and Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada Uberto Gatti, MD, Section of Criminology and Forensic Psychiatry, University of Genoa, Genoa, Italy Paul L. Gendreau, PhD, School of Psychoeducation, University of Montreal, Montreal, Quebec, Canada Willard W. Hartup, EdD, Institute of Child Development, University of Minnesota, Minneapolis, Minnesota Dale F. Hay, PhD, School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom ix

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Contributors

D. Lynn Homish, BSc, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania David Joubert, MA, MCA, Department of Psychology, University of Quebec at Montreal, Montreal, Quebec, Canada Eric Lacourse, PhD, Department of Sociology, University of Montreal, Montreal, Quebec, Canada Rolf Loeber, PhD, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania Tania Mazzarello, BSc, Department of Psychology, University of Quebec at Montreal, Montreal, Quebec, Canada Daniel S. Nagin, PhD, H. J. Heinz III School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, Pennsylvania Tomáë Paus, MD, PhD, Departments of Neurology and Neurosurgery, and Psychology, McGill University, Montreal, Quebec, Canada Sergio M. Pellis, PhD, Canadian Centre for Behavioural Neuroscience, Department of Psychology and Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada Vivien C. Pellis, PhD, Canadian Centre for Behavioural Neuroscience, Department of Psychology and Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada Daniel Pérusse, PhD, Department of Anthropology, University of Montreal, Montreal, Quebec, Canada Jordan B. Peterson, PhD, Department of Psychology, University of Toronto, Toronto, Ontario, Canada Robert O. Pihl, PhD, Departments of Psychology and Psychiatry, McGill University, Montreal, Quebec, Canada François Poulin, PhD, Department of Psychology, University of Quebec at Montreal, Montreal, Quebec, Canada Elisa Romano, PhD, Department of Psychology, University of Ottawa, Ottawa, Ontario, Canada Jean Richard Séguin, PhD, Research Unit on Children’s Psychosocial Maladjustment, Department of Psychiatry, University of Montreal, Montreal, Quebec, Canada Stephen J. Suomi, PhD, Laboratory of Comparative Ethology, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland Richard E. Tremblay, PhD, Departments of Pediatrics, Psychiatry, and Psychology, University of Montreal, Montreal, Quebec, Canada

Contributors

Tracy Vaillancourt, PhD, Department of Psychology, McMaster University, Hamilton, Ontario, Canada Stephanie H. M. Van Goozen, PhD, School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom Frank Vitaro, PhD, Research Unit on Children’s Psychosocial Maladjustment, School of Psychoeducation, University of Montreal, Montreal, Quebec, Canada Philip David Zelazo, PhD, Department of Psychology, University of Toronto, Toronto, Ontario, Canada Mark Zoccolillo, MD, Department of Psychiatry, Montreal Children’s Hospital, Montreal, Quebec, Canada

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Preface

Preface

It has been over 30 years since the publication of a book giving a detailed overview of the state of knowledge on the developmental origins of aggressive behavior (de Wit & Hartup, 1974). Much has changed during this time. Most of the developmental work published in the 1974 book was based on crosssectional studies of small samples of school-age children. The focus of attention was on aggressive events and the situations that instigate them. Over the past 30 years, investigators have conducted longitudinal studies of large samples of children assessed repeatedly from birth to adulthood. Results from these studies are telling unexpected stories. For example, children appear not to be learning to use physical aggression as they grow older; rather they appear to be learning not to use physical aggression. As expected, girls use physical aggression less often than boys from infancy to adolescence; however, they use another form of aggression (indirect aggression) more often than boys from early childhood to adulthood. Such findings are clearly of interest for our general understanding of human nature. Philosophers have argued for centuries on the origins of antisocial behavior. Rousseau defended the thesis that humans are created good and become evil through the influence of society, and Hobbes argued that a wicked person was simply a child who had not grown up. In 1973, Albert Bandura wrote, “People are not born with preformed repertoires of aggressive behavior; they must learn them in one way or another” (p. 61). The findings from research on the development of aggressive behavior are also extremely important for the prevention and treatment of violent behavior. Violence is still a serious problem in our modern societies. To help children learn alternatives to violent behavior, we need to understand the development of aggression and its alternatives. Every professional who works with children and adolescents needs to understand the developmental origins of aggression. Technological progress over the past 30 years has enabled investigators to combine longitudinal studies of large samples of children over their lifespans with molecular assessments of their genetic material and assessments of xiii

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hormones and neuromodulators through blood and saliva samples and brain imaging. More sophisticated statistical techniques provide researchers with tools to make better use of twin samples and repeated measurements over long periods of time. This volume provides a timely overview of the best research and the key questions at the beginning of a new era, which will lead to a synthesis of genetic, brain, behavior, and environmental research.

REFERENCES Bandura, A. (1973). Aggression: A social learning analysis. New York: Holt. de Wit, J., & Hartup, W. W. (Eds.). (1974). Determinants and origins of aggressive behavior. The Hague: Mouton.

Contents

Contents

I. INTRODUCTION 1

The Development of Aggression: Where Do We Stand?

3

Willard W. Hartup

II. THE DEVELOPMENT OF AGGRESSION IN ANIMALS AND HUMANS 2

Subtypes of Aggression in Humans and Animals

25

Paul L. Gendreau and John Archer

3

Play Fighting: Aggression, Affiliation, and the Development of Nuanced Social Skills

47

Sergio M. Pellis, Vivien C. Pellis, and Afra Foroud

4

Genetic and Environmental Factors Influencing the Expression of Impulsive Aggression and Serotonergic Functioning in Rhesus Monkeys

63

Stephen J. Suomi

5

The Developmental Origins of Physical Aggression in Humans

83

Richard E. Tremblay and Daniel S. Nagin

6

The Beginnings of Aggression in Infancy

107

Dale F. Hay

7

Play and the Regulation of Aggression

133

Jordan B. Peterson and Joseph L. Flanders

8

Indirect Aggression among Humans: Social Construct or Evolutionary Adaptation?

158

Tracy Vaillancourt

9

Proactive and Reactive Aggression: A Developmental Perspective

178

Frank Vitaro and Mara Brendgen

10

Homicide, Violence, and Developmental Trajectories Rolf Loeber, Eric Lacourse, and D. Lynn Homish

xv

202

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III. DETERMINANTS OF AGGRESSION 11

Genetics and the Development of Aggression

223

Daniel Pérusse and Paul L. Gendreau

12

Mapping Brain Development and Aggression

242

Tomáë Paus

13

Neuromodulators in the Development and Expression of Inhibition and Aggression

261

Robert O. Pihl and Chawki Benkelfat

14

Hormones and the Developmental Origins of Aggression

281

Stephanie H. M. Van Goozen

15

Executive Function in Early Physical Aggression

307

Jean Richard Séguin and Philip David Zelazo

16

Language Development and Aggressive Behavior

330

Ginette Dionne

17

The Intergenerational Transmission of Aggression and Antisocial Behavior

353

Mark Zoccolillo, Elisa Romano, David Joubert, Tania Mazzarello, Sylvana Côté, Michel Boivin, Daniel Pérusse, and Richard E. Tremblay

18

Peer Relationships and the Development of Aggressive Behavior in Early Childhood

376

Michel Boivin, Frank Vitaro, and François Poulin

19

Social Capital and Physical Violence

398

Uberto Gatti and Richard E. Tremblay

20

Sex Differences in Aggressive Behavior: A Developmental and Evolutionary Perspective

425

John Archer and Sylvana Côté

IV. CHALLENGES FOR THE FUTURE 21

The Developmental Origins of Aggression: Where Are We Going?

447

Richard E. Tremblay and Sylvana Côté

Index

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Part I INTRODUCTION

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The Development of Aggression INTRODUCTION

1 The Development of Aggression Where Do We Stand? W ILLARD W. H ARTUP

Three changes have occurred in research on the development of aggression. First, both theoretical and empirical attention have shifted from the aggressive act, on one hand, to the development of aggressive individuals, on the other; that is, from aggressive events and the situations that instigate them to aggressive children assessed within ecological systems. Investigators no longer examine the effects of exposure to aggressive models (Bandura & Walters, 1963), for example, but rather the developmental consequences of reciprocities in social interaction involving individuals, bilateral and transactional processes in family and peer interaction, gene–environment permutations, and contextual components (including exposure to aggression and violence in the community). A second change is the emerging synthesis between research on aggression and research on antisocial behavior (Tremblay, 2000). Everyone knows that aggression and antisocial behavior are overlapping but not identical constructs. Nevertheless, because aggressive behavior is relatively stable as an individual characteristic, and because stable aggression predicts antisocial behavior during adolescence and adulthood for males at least (Moffitt, Caspi, Rutter, & Silva, 2001), it no longer seems wise to separate these terms in thinking about social development and adaptation. Third, a trend toward more developmentally oriented studies of aggression has emerged. What was known about aggression in childhood and adolescence in the late 1960s was quite nondevelopmental: The relevant work dealt with contingencies in observation or social interaction that increased aggression in the child, usually in constrained situations and with little attention to age differences. Normative studies encompassed only a few years (in early 3

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INTRODUCTION

childhood), and the events associated with individual differences in the real world were not much remarked on (see Feshbach, 1970). To be concerned with development, however, is to be concerned with continuities and discontinuities in harm-doing activity across the lifespan, especially during the years before maturity, along with changes across time in the morphology and functioning of aggressive behavior, the reorganization of various mental structures as these involve aggression, and the role of violence in the development of attitudes toward oneself and others (Hartup & DeWit, 1974). By the 1980s, new ideas were percolating through the entire field of social and emotional development even though long-term longitudinal data were scarce. Studies linking aggression in early childhood with aggression in adolescence and adulthood were extremely rare; even cross-sectional studies were not abundant. But the zeitgeist was shifting. Ross Parke and Ronald Slaby (1983) knew it, and called their chapter for the Handbook of Child Psychology, “The Development of Aggression.” Ahead of its time, this chapter led the way to fundamental changes in research and research strategy highlighting developmental processes in the emergence of aggression and antisocial behavior. Nowadays, the major studies of aggression and antisocial behavior are definitely developmental, and most use longitudinal data to search for determinants, dynamics, and outcomes of these behaviors. Against the background of these comments, several issues are now discussed in terms of how things have changed and what we might expect in the near future in understanding the development of aggression: First, what changes? Three issues are considered: (1) construct selection, (2) normative change versus individual differences, and (3) child development versus lifespan perspectives. Second, what are the determinants of developmental change in aggression and antisocial behavior? Again, three issues are addressed: (1) nativism versus empiricism, (2) socialization and relationships, and (3) the ecological context.

WHAT CHANGES? Aggression, like most human activity, changes with age both in its incidence and in the processes leading to its instigation. But which changes are meaningful? Not every change in language and cognitive activity at every level of analysis is meaningful, nor is every change in aggression and antisocial behavior. Our first task, then, is to identify those changeworthy behaviors that have some significance in behavioral adaptation across time.

Construct Selection One must proceed cautiously through the thicket of constructs available in the current aggression literature. Merely specifying a workable construct that can

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be called “aggression” is difficult. Saying that aggression is “intentional harm doing” or “harm doing for its own sake” may be reasonable for the ordinary user of the English language, but it is fraught with difficulties for scientists who want to describe relevant phenomena with precision: Intentions cannot be observed easily; instigating conditions are difficult to separate from the structure of the aggressive act; outcomes are difficult to specify; and we can’t always tell whether the act has been aversive to the victim (Bandura, 1973; Hartup & De Wit, 1974; Coie & Dodge, 1998; Tremblay, 2000). Moreover, similar measures across age (if not equivalent ones) must be used in many forms of developmental analysis (e.g., specifying developmental trajectories and pathways), and one cannot always count on this equivalence. Researchers have made much progress by becoming more global in defining aggression and antisocial behavior, that is, by making increasingly greater use of global constructs drawn from natural language. Many investigators rely on ordinary observers (parents, teachers, and children) to tell them when aggression occurs and what some of its implications are. For example, elementary school children are asked to tell us which classmates “start fights.” When they answer, the reliability and validity of these nominations turn out to be substantial even though we do not know the circumstances under which the target child may start fights, the behaviors used in fighting, the consequences to the child’s companions, or the goals achieved by the target child. At certain times, however, these “down and dirty” measurement strategies will not work, that is, for determining whether babies “start fights” or whether 3-year-old and 13-year-old aggression reflect the same functional dynamics. Particulars about instigation, motor patterns, and consequences (functions) are needed in those instances even if it is difficult to obtain them. One endeavor needs to be encouraged strongly: construct selection at intermediate levels of conceptual complexity. First, certain older constructs need to be maintained. Consider that physical and verbal aggression have been distinguished from one another for many years (Goodenough, 1931), and several examples will show that this distinction remains useful: 1. Neither physical aggression nor most forms of antisocial behavior occur as frequently among females as among males, and gender differences in aggression cannot be understood without taking this into consideration. 2. Physical aggression among females during childhood does not predict adolescent antisocial behavior as it does for males (Broidy et al., 2003), and we do not completely understand this. Other midlevel constructs must be preserved, for example, violent versus nonviolent aggression, instrumental versus hostile aggression, and proactive versus reactive aggression. Bullying and victimization are also uniquely useful constructs. It may be time to resurrect other old constructs such as prosocial versus antisocial aggression; this one has languished since Robert Sears and

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INTRODUCTION

his colleagues could not find differential correlates in the doll play of kindergarten children more than 40 years ago (Maccoby, 1992). But we must put this old wine in new bottles. New midlevel constructs are badly needed. Relational (or indirect) aggression has evoked considerable interest in the last decade (Crick et al., 1998; Vaillancourt, Chapter 8, this volume) Research shows that relational aggression is more frequent among females than among males, although its sequelae are not remarkably different (Crick et al., 1998; Vaillancourt, Chapter 8, this volume). It is not really surprising that harm doing may occur in normatively different ways in males and females; it is only surprising that it took us so long to realize this. Natural language may or may not furnish us with the complete conceptual armamentarium needed for research on aggression and antisocial behavior. As a consequence, the research community needs to look beyond the dictionary for constructs that will invigorate their work.

Normative Change or Individual Differences? Once upon a time, the following item appeared regularly on the exams for my graduate course: “Discuss the similarities and differences between the study of normative issues in developmental psychology and individual differences: Demonstrate how each of these issues informs the other about developmental process.” Historically, developmental psychology has been much concerned with both issues, with students of cognitive development emphasizing normative continuities and change rather than the emergence of individual differences (except for investigators interested in the IQ); students of social and personality development, however, have been interested mainly in individual differences. Normative change, of course, refers to age-related changes that are universal or characteristic of major population groups rather than developmental variations within or between groups. Aggression researchers, especially earlier ones, were interested in normative questions ranging from the ontogeny of anger regulation (Goodenough, 1931), to delinquency (Glueck & Glueck, 1950), to verbal mediation in the child’s response to aggressive modeling (Coates & Hartup, 1969). Contemporary researchers remain interested in normative assessment of aggression, as revealed in Figure 1.1 which shows data on hitting, biting, and kicking in a Canadian sample (Tremblay et al., 1996). These behaviors peak at about 27 months for both boys and girls, with slightly more boys than girls showing them “sometimes” or “frequently.” Frequencies decline steadily thereafter and are not often evident (but not completely absent) by age 12. These data represent one of the most comprehensive normative reports on physical aggression existing anywhere. Normative studies, however, are increasingly difficult to distinguish from differential studies of aggression. Normative and differential research on ag-

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FIGURE 1.1. Hitting, biting, and kicking (boys and girls ages 2–11 years). From Tremblay et al. (1996). Statistics Canada information is used with the permission of the Minister of Industry, as Minister responsible for Statistics Canada. Information on the availability of the wide range of data from Statistics Canada can be obtained from Statistics Canada’s Regional Offices, its website at www.statcan.ca, and its toll-free access number 1-800-2631136.

gression have blurred together, underscoring something we have known all along but have chosen to ignore: Most normative changes in aggression are constrained by variations among individuals. Recent studies show dramatically that individual-to-individual variations in developmental pathways are ubiquitous. Some of these developmental variations are associated with gender, social class, and ethnicity. Indeed, one can describe many relevant differences between the sexes in developmental trajectories, even though the basic processes by which children acquire certain types of aggression may not differ between boys and girls (Moffitt et al., 2001). Even among children of a single race or gender, however, normative changes encompass a range of individual differences. Nowhere is this conclusion more clearly revealed than in a recent manuscript that brings together data from six well-known longitudinal studies (Broidy et al., 2003). In every instance, semiparametric analyses reveal multiple types of developmental change. For example, four trajectories in physical aggression can be identified within a male sample from Montreal studied by Nagin and Tremblay (1999; Tremblay & Nagin, Chapter 5, this volume). Two are similar to those identified in a number of longitudinal studies: (1) high levels of aggression among a relatively small group of boys that persist across childhood and into adolescence and (2) low aggression that persists across childhood and characterizes a much larger group. Two other trajectories were also identified in these data:

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INTRODUCTION

(3) one that begins with high levels of aggression and declines steadily as time goes on (boys sometimes called “desistors” or “recovered” aggressors) and (4) one that begins at more moderate levels and also declines. One other example included in this six-site investigation, the so-called Dunedin (New Zealand) studies of Moffitt and her associates (Moffitt, Caspi, Rutter, & Silva, 1996; Broidy, et al., 2003), revealed three distinct trajectories instead of four: (1) a small group of consistently aggressive boys, (2) a large group of consistently nonaggressive boys, and (3) another stable group of moderately aggressive boys. No cluster of decliners was identified in this study. The remaining studies in the investigation show either three- or fourcluster patterns, with only one (based on a sample from the United States) showing a trajectory of physical aggression that increases across childhood (Broidy et al., 2003). Developmental trajectories derived from longitudinal studies of girls are similar to those obtained with boys but also different: For example, four distinctive patterns were obtained in another Quebec study that are similar to those obtained for boys, but with the following exceptions: (1) Scores were decidedly lower than those for boys across the board, and (2) the desistors among the females declined more sharply across childhood into adolescence than those among the boys (see Broidy et al., 2003). Once again, a small group of chronic aggressors emerged, as well as a larger group of consistently nonaggressive girls. Among the girls in the Dunedin (New Zealand) sample, again, the trajectories are much like the boys’, except scores are lower and the decline in two groups is a bit greater (see Broidy et al., 2003). Normatively, then, the existence of two particular trajectories seems ubiquitous—a high level of aggression that is continuous throughout childhood and into adolescence and a low level of aggression that is equally consistent across age. Other patterns, including those characterized by aggression that declines during childhood and those typified by increases around the time of puberty, occur in some data sets but not others. No one is entirely certain as to why these sample-to-sample variations occur in the types of trajectories identified. Moreover, clear evidence does not yet establish the reasons for the variations that exist. Some investigators believe that persistent and high levels of aggression across childhood (much more common in boys than in girls) may have biological determinants, whereas “adolescence-limited” aggression may be derived from social experience, especially experience with aggressive peers (Moffitt et al., 2001). Other investigators, however, believe that dysfunctional family relationships in early childhood differentiate persistently aggressive boys from those showing other developmental patterns (Aguilar, Sroufe, Egeland, & Carlson, 2000). These questions are now at center stage in the research on the development of aggression. One conclusion, however, cannot be questioned: Normative change in aggressive behavior must be evaluated in the context of individual differences. The obverse is also true, namely, that individual differences must be evaluated in the context of normative change.

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Developmental trajectories in aggression development also differ according to characteristics of the individuals involved. For example, my own work with colleagues (Haselager, Cillessen, Van Lieshout, Riksen-Walraven, & Hartup, 2002; Hartup, Cillessen, Haselager, Scholte, & Van Lieshout, 2002a) shows a connection between developmental trajectories in aggression and sociometric status among boys. We examined, first, trajectories in composite measures of peer-reported and self-reported aggression between the ages of 6 and 11 among rejected boys (that is, boys who were peer rejected at a relatively early age). Groups emerging in a cluster analysis somewhat resembled the normative samples from Montreal and other sites (see Figure 1.2): Three more-or-less stable groups (highly aggressive, moderately aggressive, and persistently nonaggressive), as well as one that showed marked decreases in aggressive activity across the 5 years studied (a desistor subgroup). Discriminant function analysis shows that the highly stable aggressive group differed from the other three in social maladaptation, again consistent with the results of numerous studies. The only distinctive characteristic of the children who declined in aggression is that they also increased in cooperation over the period and were better liked by their peers as time went on. Shown in the Figure 1.3 are trajectories in aggressive behavior that emerged when we examined longitudinally a group of 87 boys who were all popular at age 6 (fair-haired boys, we might call them). Cross-sectional cluster analyses (not shown here) revealed differences among these popular children even at this age: Some were more aggressive and less cooperative than others. Two groups, however, emerged from a cluster analysis of the longitudinal

FIGURE 1.2. Developmental pathways of aggressive behavior in four clusters of initially rejected boys. From Haselager, Cillessen, Van Lieshout, Riksen-Walraven, and Hartup (2002). Copyright 2002 by the American Psychological Association. Reprinted by permission.

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INTRODUCTION

FIGURE 1.3. Developmental pathways of aggression in three initially popular clusters. From Hartup, Cillessen, Haselager, Scholte, and Van Lieshout (2002a).

data—one group composed of individuals who were consistently nonaggressive and another group of individuals (15% of the subjects) who changed decisively in the direction of greater aggressiveness. These increasingly aggressive children were distinctive. Concomitant with their increasing aggression were decreases in cooperativeness and increases in peer rejection. Most interesting, though, are data available for 47 of these boys when they were 14 years of age: Discriminant function analysis identified two functions that successfully discriminated these boys from the other groups: (1) they were more sociable, were less inhibited, and achieved more poorly in school and (2) they were less well liked and more likely to engage in aggression, as well as in more bullying and victimization, than members of the other groups. These results suggest that synergies involving sociometric status and aggressive trajectories must be taken into account in order to describe, on one hand, “model” boys (stable, nonaggressive, popular boys) and, on the other hand, “toughs” (popular kids who are increasingly antisocial and not turned on by school) (Rodkin, Farmer, Pearl, & Van Acker, 2000). The message is clear: Normative change in aggression and antisocial behavior is meaningful only in the context of differential analysis. And the reverse may also be true: individual differences can be understood only in the context of normative analysis. Consideration of these combined forces is necessary to understanding both the development of aggression and social adaptation more generally.

Child Development versus Lifespan Perspectives Owing mainly to child-oriented societal forces, over most of the last century primary attention was given to developmental changes occurring in childhood

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rather than to changes occurring in adolescence or adulthood. Most studies of aggression and its development at the beginning of the child development movement were devoted to young children (Goodenough, 1931; Dawe, 1934); juvenile delinquency was studied among adolescents by sociologists and psychiatrists (Thrasher, 1927; Glueck & Glueck, 1934), but other aspects of adolescent aggressive behavior were largely ignored. These truncated perspectives dominate developmental science even today, although they have been modified in various ways—i.e., the doctrine of early experience is questioned in important aspects (Schaffer, 2002) and lifespan perspectives are promulgated as frameworks for examining developmental changes (Baltes, Lindenberger, & Staudinger, 1998). The bias toward childhood studies of behavioral development stems from theoretical/scientific sources as well as the nature of the early child welfare movement in the United States and elsewhere (Hartup, Johnson, & Weinberg, 2001). First, developmental science was heavily influenced in the early 20th century by psychoanalysis, on one hand, and learning theories, on the other, including their assumptions that development during the early years has pervasive and long-lasting consequences in both cognitive and social development. At the same time, social activists came to believe that the road to general societal progress begins with changes made in the lives of children and families, especially during a child’s early years. Parent education, social welfare services, and early childhood education were expanded greatly in many countries to assist in this effort. Services to adolescents were also improved, especially those relating to juvenile delinquency, but community welfare in the larger sense did not encompass lifespan considerations. Meanwhile, criminologists were discovering that childhood antecedents account for a large amount of variance in adolescent and adult crime (Glueck & Glueck, 1950; McCord, 1979). Clearly, short-term studies of children or adolescents were not going to be able to furnish an adequate basis for social intervention. More recent investigators utilize increasingly longer-term studies of aggression and antisocial behavior. Although infancy and early childhood are not encompassed by most of these studies, longitudinal analysis beginning in childhood and ending in early adulthood teaches us a great deal. We are in debt to David Farrington, Rolf Loeber, Robert Cairns, Leonard Eron and Rowell Husemann, John Coie, Joan McCord, and many others for work like this. It has been difficult to extend these studies through the life course, beginning in infancy and ending in middle or old age. Moffitt et al.’s (2001) work is notable for the fact that the data set begins with measurements at age 3, and newer studies (e.g., Tremblay, 2000) begin prenatally and remain open-ended. Studies ranging from middle childhood to young adulthood are still more common than those covering a longer term, and cradle-to-grave studies do not exist. Nevertheless, the message of lifespan developmentalists is being taken with increasing seriousness: Understanding adaptational problems requires developmental perspectives that extend beyond childhood and adolescence,

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INTRODUCTION

and the coherence of human development, whether outcomes are good or bad, can be assessed only in terms of both growth and decline in behavioral function. Must we wait for geriatric data on the Montreal subjects or the Dunedin sample before studying the decline in aggression and antisocial behavior that is known to mark middle and old age? Probably not. Overlapping longitudinal studies—some beginning in adolescence, some beginning later—can unravel the conditions responsible for decline in antisocial behavior with age. One can argue, then, that normative change must be studied not only within the context of individual differences, but also within the context of the life course.

WHAT ARE THE DETERMINANTS OF BEHAVIOR CHANGE? Our ultimate goal is to identify the conditions responsible for normative development of aggression within the context of individual differences. As everyone knows, explanation in the behavioral sciences is extraordinarily difficult. Most developmental change is multidetermined, and causation is buried deeply within the genome and the mind. Moreover, the time separating “cause” from “effect” in human development is frequently decades, not moments, and change within one behavioral domain is entangled with changes in others. One cannot synthesize everything that has been written about the determinants of aggression in the space available here. Instead, several “tensions” or “dialectics” remaining in this field are discussed.

Nativism versus Empiricism The notion that human beings begin life with “innate ideas” and “inborn proclivities” appears in our most ancient religious and philosophical texts. Also expressed in classical philosophical writing is extreme empiricism, the argument being that nearly everything about human behavior—including aggression—derives from the individual’s commerce with the world. Most modern writers, though, view the development of aggression (like many other traits) as constrained by intrinsic structures (these may include the physiological and neural structures necessary to arousal, anger, learning, attention, language, and emotional regulation). The structures in question are species-wide and both determine the success of individual adaptation and make individual differences possible. Although relatively little is known about the processes through which these innate structures are deployed in behavioral development, especially in social and emotional behavior, the evidence suggests that relationships with others (including caretakers, friends, and enemies) are important vectors. The task, then, is to specify both the intrinsic and experiential contributions to developmental acquisitions and the manner in which they “synthesize” or “interact.”

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Recent studies in molecular genetics suggest that allelic variations may commonly interact with social and relationship experience in determining the aggressive phenotype. Suomi (Chapter 4, this volume) discovered that variations in the serotonin transporter gene (5-HTT) interact with rearing conditions to affect a variety of outcomes, including aggression and position in the dominance hierarchy, among rhesus monkeys. So-called “short” allelic variations are associated with nonaggressive maladaptations—but for peer-reared individuals and not mother-reared individuals. In other words, attachment to a maternal figure moderates the effects of the genetic variations. The findings also partially explain why peer rearing does not produce extremely aggressive animals in all cases. In recent work with human beings, Caspi et al. (2002) discovered an interaction between parental maltreatment and levels of monoamine oxidase A (MAOA) genetic expression (MAOA is a gene located on the X chromosome that encodes an enzyme that metabolizes various neurotransmitters, rendering them inactive). Maltreated boys in a large longitudinal sample possessing the genotype associated with high levels of MAOA expression were less likely to have antisocial problems in the course of their development than those with genotypes associated with low levels of MAOA expression. Results of this study help to account for the fact that, although harsh parental discipline and maltreatment of young boys is related to aggressive and antisocial outcomes, not all maltreated children grow up to victimize others. In addition to these studies, process-oriented prospective studies are needed (beginning earlier than most existing studies) to explain the manner in which so-called biological variations contribute to individual differences in aggressiveness and antisocial behavior. One hopes that investigators will not simplistically consider factors like maternal IQ, maternal age, and maternal social adjustment as well as child IQ, child memory, attention disabilities, and child temperament to be exclusively biological indicators (Moffitt et al., 2001), nor attachment histories to be exclusively social indicators. These constructs are only the roughest indications of intrinsic or social structures, respectively, and the manner in which they work. We need new expertise in psychoendocrine measurement in infancy and beyond, temperament, emotional processes in infancy and early childhood (Thompson, 1998), and behavioral regulation in early relationships between the child and his or her caretakers. Implications of the neuropsychological history for the child’s social and emotional history must be studied along with experience. Overall, refinements in methods for studying psychological processes in the development of aggression are just as important as advances in gene mapping.

Socialization: From Unilateral to Bilateral Constructions Although there were many indications in earlier writings that children are “socializing creatures” as well as “socialized ones” (Baldwin, 1897), a consensus concerning a two-way or bilateral view of childhood socialization was

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reached only recently (Bell, 1968). The notion that social adaptation is the outcome of interaction between the child and others, rather than some sort of one-way social-molding process, is now accepted by almost everybody.

Parent–Child Relationships With respect to the development of aggression, one does not find many studies that deal directly with social interaction or social relationships within the family. Most commonly, investigators enter measures like the following into their regression models as predictors of child or adolescent outcomes: (1) child characteristics—temperament, intelligence, troublesomeness, memory and attention problems, impulsivity, and personality and (2) parent characteristics— warmth versus negativity, family coercion and inconsistent discipline, punishment and punitiveness, along with abusive parenting (Coie & Dodge, 1998). The ensuing regressions allow us to examine main and interaction effects among these child and maternal characteristics, but not the social exchanges between parents and children from which changes over time actually emanate. One of the most brilliant achievements of the last century is the “performance theory” formulated and tested by Gerald Patterson and his associates. This socialization model specifies the parameters and contingencies occurring in family interaction that instantiate troublesomeness among young boys, maintain it, and supply the basis for the attitudes that characterize these same boys in their early interactions with other children outside the home. These relationships, in turn, involve them in increasingly violent behavior (Patterson, Reid, & Dishion, 1992). In other studies, certain mileage can be gained by using global measures of family conflict, maternal punitiveness, and harsh discipline, but the “performance model” makes clear that such measures are only proxies for measures of social interaction. One concludes that microanalytic approaches to socialization studies of the development of aggression are needed as well as macroanalytic ones. Most parent–child measures also do not pass muster as relationships constructs. Relationships are usually defined as aggregates of interaction between individuals who have formed expectations about one another that guide interpersonal behavior over time (Hinde, 1997). It so happens that relationships are the social contexts within which most development occurs: (1) basic skills in language and communication, (2) competence in coping with both social and nonsocial problems, and (3) the attitudes and abilities needed for constructing other relationships. Relationships theory, however, has not penetrated very deeply into research on the development of aggression. Parental punitiveness or harsh discipline (common measures) are parent characteristics, not dimensions of the parent–child relationship. Similarly, maternal warmth does not describe a relationship between mother and child. Exactly what this omission means for research is not really known. Diana Baumrind (1971) had considerable success earlier in describing permissive relationships between parents and children and showing that these were associated with early ag-

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gression. Some investigators have consistently reported cross-time correlations between disorganized attachment patterns in infancy and early childhood with manifestations of aggression and antisocial behavior in middle childhood and adolescence (Renken, Egeland, Marvinney, Mangelsdorf, & Sroufe, 1989). Others report similar findings, especially among vulnerable children, for example, children who live in chaotic, poor families with a single parent (see Coie & Dodge, 1998). And, in the Dunedin data set (Moffitt et al., 2001), a relationships measure (“relationship with parents,” based on items like trust, communication, and lack of alienation between adolescents and their parents) turns out to be a better predictor of adolescent aggression (–.44, –.47) than measures of harsh discipline (.19, .27). No one would argue that relationship constructs are the only ones that account for significant variance in adolescent aggression. We have sufficient evidence to argue, however, that relationships measurement definitely belongs in studies of the family antecedents of aggression, especially as we look forward to research dealing with gene–environment interactions.

Peer Relationships Until recently, the significance of peer relations in the development of aggression and antisocial behavior was considered to be mostly a unidirectional process. That is, the prevailing view was that kids get into trouble because they are exposed to the exhortations and examples of deviant peers and are rejected by better-adjusted associates, an occurrence that lowers self-esteem and restricts access to well-socialized companions. Sometimes the interaction between child characteristics (e.g., earlier disruptiveness or troublesomeness) and peer experience (e.g., social rejection by other children) is examined in relation to aggressive outcomes. In most instances, significant variance in child or adolescent aggression flows additively from both child sources (including earlier aggression or compliance difficulties) and the attitudes and behaviors of other children (Coie & Dodge, 1998). Additional variance in the development of aggression, however, may be traced to close relationships with other children, including (1) friends, (2) enemies, and (3) bully–victim relationships (see Boivin, Vitaro, & Poulin, Chapter 18, this volume).

Friends Friendship dyads, in general, are neither more nor less aggressive or antisocial than “neutral” dyads (Hartup, Verhoeven, DeBoer, Scholte, & Van Lieshout, 2002b). Among individual children and adolescents, those who have friends are not as troubled as those who do not, but “not having friends” does not predict aggression very well either concurrently or over time (Hartup, 1996). Friends, however, are more similar to one another in both aggressiveness and antisocial behavior than nonfriends (Haselager, Hartup, Van Lieshout, &

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Risken-Walraven, 1998; Hartup et al., 2002b), a situation that can also be observed in social networks or cliques (Cairns & Cairns, 1994). Moreover, these similarities reflect more than “birds of a feather flock together.” The day-today interaction that occurs between antisocial friends actually increases their antisocial behavior over time, especially among children already identified as aggressive and rejected (Dishion, 1990; Tremblay, Masse, Vitaro, & Dobkin, 1995). Most likely, this happens because the interaction between aggressive children and their friends is more contentious and conflict-ridden than interaction between nonaggressive friends (Dishion, Andrews, & Crosby, 1995). In addition, overtly aggressive children are not notably intimate with one another nor as exclusive in their relationship attitudes as their nonaggressive counterparts (Grotpeter & Crick, 1996). Thus, aggressive friends are aggressive risks. Friendship quality also contributes significant variance to the development of aggression in childhood and adolescence. In general, unharmonious friendships exacerbate the individual child’s problems in school, create adjustment difficulties, and increase aggressiveness. In many instances, however, friendship quality has a greater effect on children who are at risk in social development than on those who are not. For example, Poulin, Dishion, and Haas (1999) found significant interaction effects between boys’ antisocial behavior (delinquency) at age 13–14 and friendship quality at that same age (harmoniousness) in relation to antisocial behavior one year later, at age 14–15. The greatest effects of low-quality friendships on subsequent delinquency occurred when baseline delinquency levels were high rather than low. In other words, the friendship construct was more strongly related to developmental outcome among vulnerable individuals than among less vulnerable ones. Overall, friends may or may not support good developmental outcome. Empirical studies tell us that aggressive friends (or unharmonious relationships) are risk factors inasmuch as the children are not well socialized, instigate aggressive behavior (e.g., train one another in deviancy), and do not instigate effective regulatory controls. In addition, friendships that are not harmonious instigate increases in aggressive behavior over time, possibly for some of the same reasons, and mainly among children who are at risk (Boivin et al., Chapter 18, this volume).

Enemies Social networks also include relationships that are not based on social attraction but, rather, are rooted in antipathy, animosity, and enmity. The term “mutual antipathies” describes this relationships category; the word encompasses “being enemies” as well as other relationships maintained on the basis of social aversion. Recent studies (Hartup et al., 2002b) show that differences in aggression and antisocial behavior between adolescents who do not like each other are greater than differences between nonenemies (individuals in

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neutral dyads). This confirms the “repulsion hypothesis,” which states that individuals dislike those who are different from themselves (Rosenbaum, 1986). Adolescents in mutual antipathies are also substantially more antisocial and aggressive than in “control” or “neutral” dyads, as well as more internalizing and victimized by others. These differences are consistent with earlier analyses of individual children and adolescents in this same data set, which suggest that involvement in mutual antipathies is a risk marker. That is, both children and adolescents who are involved in mutual antipathies show more fighting and bullying, social ineffectiveness, and victimization than those who are not so involved. Peer rejection was a covariate in these analyses, so the variance associated with mutual antipathies is unique. These results characterize both boys and girls who are involved in same-sex antipathies, and boys, but not girls, who are involved in mixed-sex antipathies (Abecassis, Hartup, Haselager, Scholte, & Van Lieshout, 2002). Results from several other studies of mutual antipathies and their correlates are not entirely consistent, although these results have been replicated in three instances (see Hodges & Card, 2003).

Bully–Victim Relationships Some bullies and victims dislike each other, some are neutral toward one another, and some are friends. The correlation between bully–victim status and friendship attraction is negative but moderate in magnitude (Perry, Finnegan, Hodges, Kennedy, & Malone, 1993). Although the literature on bullying and victimization is substantial, most of the relevant studies are monadically oriented, that is, centered on questions such as “What makes a bully?” or “What makes a victim?” rather than on ongoing bully–victim relationships. Great progress has been made in understanding bullying and victimization during the last 30 years (see Rigby, 2002), but relationships-oriented ideas are only slowly making their way into this area. As it turns out, both friends and enemies bear on these situations: For example, increases in victimization are inversely related to the number of externalizing problems evinced by friends, suggesting that victims with externalizing friends may well be protected by them (Hodges & Perry, 1999). A significant relation also exists between characteristics of children’s enemies and victimization: The aggressiveness, physical strength, and victimization experienced by a child’s enemy uniquely predicts the child’s own victimization (Card & Hodges, 2003). Much more, however, remains to be learned about relationships between bullies and victims, their varieties, and their vicissitudes.

Relations among Relationships The social networks of most children and adolescents include friends, neutral associates, enemies, and sometimes bullies or victims. Do these relationship experiences moderate one another in the development of aggression? Does in-

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INTRODUCTION

volvement in one relationship affect correlates of the other? Recently, my colleagues and I (Hartup et al., 2002b) examined adolescent friendship dyads as a function of whether one or both individuals is also involved in a mutual antipathy (i.e., has an enemy). We also asked whether antipathy dyads vary in psychological adjustment as a function of whether one or both individuals has a mutual friend. First, we gathered together all dyads in a large data set in which the adolescents (14-year-olds) mutually nominated each other as “someone you especially like,” as well as all dyads in which the participants mutually nominated each other as “someone you don’t like at all.” Results show that friends with mutual antipathies are both more antisocial and more aggressive than friends without mutual antipathies or those in which only one child has an enemy. Peer victimization and internalizing behavior are also greater among friends in which one or both children have mutual antipathies. Second, we examined pairs of adolescents who did not like one another as well as whether either adolescent had a mutual friend. Antisocial behavior is less frequent among the adolescent enemies who also have friends than among those who do not. Peer victimization is lower, too, when one or both enemies have a friend. But differences are not significant for aggressive behavior according to whether enemies also have friends. Overall, then, friends are more antisocial when they also have enemies; concomitantly, enemies have lower antisocial behavior scores when they also have friends. Aggressiveness, however, is not moderated in the same way: Friends with enemies are more aggressive than friends without, but friendships do not appear to be strong enough to lessen the aggressiveness that accompanies involvement in a mutual antipathy.

Does Context Make a Difference? Currently, the most advanced ideas being pursued about contextualism and development do not include the notion that person and environment can be conceived dualistically. Gone are notions that persons cause environmental change and vice versa. Instead, the modern view treats the person and the environment as integrated or fused; neither is an entity that can be described sensibly without reference to the other, and development is the story of change over time in this integrated system. One must consider development to be characteristic of biological and social systems, not an attribute of either individuals or contexts. Conventional (dualistic) contextualism is well represented in research on the development of aggression. Cross-national studies show differences in developmental trajectories (Broidy et al., 2003); cross-cultural studies, the same (Whiting & Whiting, 1975). There is also clear evidence that ecological factors like neighborhood violence have a great deal to do with the early onset of aggressive behavior. These scenarios, however, are not simple. As Schwartz and colleagues (Schwartz, Gorman, Toblin, & Abou-ezzedine, 2003) demon-

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strate, exposure to community violence is consistently related to childhood aggression only among children who are involved in a relatively large number of mutual antipathies with other children. Once again, a relationship factor increases risk in the development of aggression among children who are already vulnerable. These results move us a step or two from dualistic notions about individuals and the community because, in this case, relationship systems are seen to moderate the effects of external conditions. Community and societal variables will remain in research on the development of aggression, but notions about the “environment” need to be rethought in terms of ecological systems theory (Gatti & Tremblay, Chapter 19, this volume).

CONCLUSION Conclusions to this survey of research on aggression and its development are relatively straightforward: Conceptualization and empirical studies dealing with the development of aggression need to organized as a series of “nests.” 1. Normative change needs to be nested theoretically in the context of individual differences and within long-term (i.e., lifespan) perspectives. 2. The development of aggression can be understood only when the earliest genetic expressions are examined as nested in early social experience, especially individual social histories and close relationships. 3. The aggressive act must be considered as nested within a broad and complex ecology of harm doing and antisocial behavior. We stand at the edge of the nest, then, regarding what we know about the development of aggression.

REFERENCES Abecassis, M., Hartup, W. W., Haselager, G. J. T., Scholte, R. J. H., & Van Lieshout, C. F. M. (2002). Mutual antipathies and their significance in childhood and adolescence. Child Development, 73, 1543–1556. Aguilar, B., Sroufe, L. A., Egeland, B., & Carlson, E. (2000). Distinguishing the earlyonset-persistent and adolescent-onset antisocial behavior types: From birth to 16 years. Development and Psychopathology, 12, 109–132. Baldwin, J. M. (1897). Social and ethical interpretations in mental development. New York: Macmillan. Baltes, P. B., Lindenberger, U., & Staudinger, U. M. (1998). Life-span theory in developmental psychology. In W. Damon (Series Ed.), R. M. Lerner (Vol. Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (5th ed., pp. 1029–1144). New York: Wiley. Bandura, A. (1973). Aggression: A social learning analysis. Englewood Cliffs, NJ: Prentice-Hall.

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Bandura, A., & Walters, R. H. (1963). Social learning and imitation. New York: Holt, Rinehart & Winston. Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology Monographs, 4(1), 1–103. Bell, R. Q. (1968). A reinterpretation of direction of effects in studies of socialization. Psychological Review, 75, 81–95. Broidy, L. M., Nagin, D. S., Tremblay, R. E., Bates, J. E., Brame, B., Dodge, K. A., Fergusson, D., Horwood, J. L., Loeber, R., Laird, R., Lynam D. R., Moffitt, T. E., Pettit, G. S., & Vitaro, F. (2003). Developmental trajectories of childhood disruptive behaviors and adolescent delinquency: A six site, cross-national study. Developmental Psychology, 39(2), 222–245. Cairns, R. B., & Cairns, B. D. (1994). Lifelines and risks. Cambridge, UK: Cambridge University Press. Card, N. A., & Hodges, E. V. E. (2003) Parent–child relationships and enmity with peers: The role of avoidant and preoccupied attachment. In E. V. E. Hodges & N. A. Card (Eds.), Enemies and the darker side of peer relations (pp. 23–37). San Francisco: Jossey-Bass. Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Martin, J., Craig, I. W., Taylor, A., & Poulton, R. (2002). Role of genotype in the cycle of violence in maltreated children. Science, 297, 851–854, Coates, B., & Hartup, W. W. (1969). Age and verbalization in observational learning. Developmental Psychology, 1, 556–562. Coie, J. D., & Dodge, K. A. (1998). Aggression and antisocial behavior. In W. Damon (Series Ed.), N. Eisenberg (Vol. Ed.), Handbook of child psychology: Vol. 3. Social, emotional, and personality development (pp. 779–862). New York: Wiley. Crick, N. R., Werner, N. E., Casas, J. F., O’Brien, K. M., Nelson, D. A., Grotpeter, J. K., & Markon, K. (1998). Childhood aggression and gender: A new look at an old problem. In D. Bernstein (Ed.), Nebraska Symposium on Motivation: Vol. 45. Gender and motivation. Lincoln: University of Nebraska Press. Dawe, H. C. (1934). An analysis of two hundred quarrels of preschool children. Child Development, 5, 139–157. Dishion, T. J. (1990). The peer context of troublesome child and adolescent behavior. In P. Leone (Ed.), Understanding troubled and troublesome youth (pp. 128–153). Newbury Park, CA: Sage. Dishion, T. J., Andrews, D. W., & Crosby, L. (1995). Anti-social boys and their friends in early adolescence: Relationship characteristics, quality, and interactional process. Child Development, 66, 139–151. Feshbach, S. (1970). Aggression. In P. H. Mussen (Ed.), Carmichael’s manual of child psychology (Vol. 2, pp. 159–259). New York: Wiley. Glueck, S., & Glueck, E. T. (1934). One thousand juvenile delinquents. Cambridge, MA: Harvard University Press. Gleuck, S., & Glueck, E. T. (1950). Unraveling juvenile delinquency. Cambridge, MA: Harvard University Press. Goodenough, F. L. (1931). Anger in young children. Minneapolis: University of Minnesota Press. Grotpeter, J. K., & Crick, N. R. (1996). Relational aggression, overt aggression, and friendship. Child Development, 67, 2328–2338. Hartup, W. W. (1996). The company they keep: Friendships and their developmental significance. Child Development, 67, 1–13.

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Hartup, W. W., Cillessen, A. H. N., Haselager, G. J. T., Scholte, R. J., & Van Lieshout, C. F. M. (2002a). Heterogeneity among popular boys: Subtypes and developmental trajectories. Unpublished manuscript, University of Minnesota. Hartup, W. W., & De Wit, J. (1974). The development of aggression: Problems and perspectives. In J. De Wit & W. W. Hartup (Eds.), Determinants and origins of aggressive behavior (pp. 595–620). The Hague: Mouton. Hartup, W. W., Johnson, A., & Weinberg, R. A. (2001). The Institute of Child Development: Pioneering in science and application. In W. W. Hartup & R. A. Weinberg (Eds.), Child psychology in retrospect and prospect: The 32nd Minnesota Symposium on Child Psychology (pp. 227– 257). Mahwah, NJ: Erlbaum. Hartup, W. W., Verhoeven, M., DeBoer, R., Scholte, R. J. H., & Van Lieshout, C. F. M. (2002b, August). Heterogeneity of mutual friendships and mutual antipathies: A cross-sectional study. Paper presented at the biennial meeting of the International Society for the Study of Behavioural Development, Ottawa (Canada). Haselager, G. J. T., Cillessen, A. H. N., Van Lieshout, C. F. M., Riksen-Walraven, J. M. A., & Hartup, W. W. (2002). Heterogeneity of social behavior in peer rejected boys across middle childhood: Developmental pathways and their correlates. Developmental Psychology, 38, 446–456. Haselager, G. J. T., Hartup, W. W., Van Lieshout, C. F. M., & Riksen-Walraven, J. M. A. (1998). Similarities between friends and nonfriends in middle childhood. Child Development, 69, 1198–1208. Hinde, R. A. (1997). Relationships: A dialectical perspective. Hove, UK: Psychology Press. Hodges, E. V. E., & Card, N. A. (Eds.) (2003). Enemies and the darker side of peer relations. San Francisco: Jossey-Bass. Hodges, E. V. E., & Perry, D. G. (1999). Personal and interpersonal antecedents and consequences of victimization by peers. Journal of Personality and Social Psychology, 76, 677–685. Maccoby, E. E. (1992). The role of parents in the socialization of children: An historical overview. Developmental Psychology, 28, 1006–1017. McCord, J. (1979). Some child-rearing antecedents of criminal behavior in adult men. Journal of Personality and Social Psychology, 37, 1477–1486. Moffitt, T. E., Caspi, A., Dickson, N., Silva, P., & Stanton, W. (1996). Childhood-onset versus adolescent-onset antisocial conduct problems in males: Natural history from ages 3 to 18 years. Development and Psychopathology, 8, 399–424. Moffitt, T. E., Caspi, A., Rutter, M., & Silva, P. A. (2001). Sex differences in antisocial behavior. Cambridge, UK: Cambridge University Press. Nagin, D., & Tremblay, R. E. (1999). Trajectories of boys’ physical aggression, opposition, and hyperactivity on the path to physically violent and nonviolent juvenile delinquency. Child Development, 70(5), 1181–1196. Parke, R. D., & Slaby, R. (1983). The development of aggression. In P. H. Mussen (Series Ed.), E. M. Hetherington (Vol. Ed.), Handbook of child psychology: Vol. 4. Socialization, personality, and social development (pp. 547–641). New York: Wiley. Patterson, G. R., Reid, J., & Dishion, T. J. (1992). Antisocial boys. Eugene, OR: Castalia Press. Perry, D. G., Finnegan, R. A., Hodges, E. V. E., Kennedy, E., & Malone, M. (1993, August). Aggressive and victimized children’s relations with parents and peers. Paper presented at the annual meeting of the American Psychological Association, Toronto.

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Poulin, F., Dishion, T. J., & Haas, E. (1999). The peer influence paradox: Friendship quality and deviancy training within male adolescent friendships. Merrill-Palmer Quarterly, 45, 42–61. Renken, B., Egeland, B., Marvinney, D., Mangelsdorf, S., & Sroufe, L. A. (1989). Early childhood antecedents of aggression and passive-withdrawal in early elementary school. Journal of Personality, 57, 257–281. Rigby, K. (2002). Bullying in childhood. In P. K. Smith & C. H. Hart (Eds.), Blackwell handbook of childhood social development (pp. 549–568). Oxford, UK: Blackwell. Rodkin, P. C., Farmer, T. W., Pearl, R., & Van Acker, R. (2000). Heterogeneity of popular boys: Antisocial and prosocial configurations. Developmental Psychology, 36, 14– 24. Rosenbaum, M. E. (1986). The repulsion hypothesis: On the nondevelopment of relationships. Journal of Personality and Social Psychology, 51, 1156–1166. Schaffer, H. R. (2002). The early experience assumption: Past, present, and future. In W. W. Hartup & R. K. Silbereisen (Eds.), Growing points in developmental science (pp. 24–46). Hove, UK: Psychology Press. Schwartz, D., Gorman, A. H., Toblin, R., & Abou-ezzedine, T. (2003). Mutual antipathies in the peer group as a moderating factor in the association between community violence exposure and psychosocial maladjustment. In E. V. E. Hodges and N. A. Card (Eds.), Enemies and the darker side of peer relations (pp. 39–54). San Francisco: Jossey-Bass. Thompson, R. A. (1998). Early sociopersonality development. In W. Damon (Series Ed.), N. Eisenberg (Vol. Ed.), Handbook of child psychology: Vol. 3. Social, emotional, and personality development (pp. 25–104). New York: Wiley. Thrasher, F. M. (1927). The gang. Chicago: University of Chicago Press. Tremblay, R. E. (2000). The development of aggressive behaviour during childhood: What have we learned in the past century? International Journal of Behavioral Development, 24, 129–141. Tremblay, R. E., Boulerice, B., Harden, P. W., McDuff, P., Perusse, D., Pihl, R. O., & Zoccolillo, M. (1996). Do children in Canada become more aggressive as they approach adolescence? In Human Resources Development Canada & Statistics Canada (Eds.), Growing up in Canada: National longitudinal survey of children and youth (Catalogue 89-550, pp. 127–137). Ottawa: Statistics Canada. Tremblay, R. E., Masse, L. C., Vitaro, F., & Dobkin, P. L. (1995). The impact of friends’ deviant behavior on early onset of delinquency: Longitudinal data from 6 to 13 years of age. Development and Psychopathology, 7, 649–667. Whiting, B. B., & Whiting, J. W. M. (1975). Children of six cultures. Cambridge, MA: Harvard University Press.

Part II THE DEVELOPMENT OF AGGRESSION IN ANIMALS AND HUMANS

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THE DEVELOPMENT Subtypes of Aggression OF AGGRESSION

2 Subtypes of Aggression in Humans and Animals P AUL L. G ENDREAU and J OHN A RCHER

From the elementary fencing behavior of fruit flies to the lunging attack of mice or rats, and from the biting of dogs to the more subtle form of indirect aggression in humans, the expression of aggressive behavior becomes increasingly sophisticated and diversified as animals increase in neural complexity. Comparable transformation is observed during the course of human ontogeny. Children first bite, hit, push, and kick (Tremblay et al., 1999); then gradually, they may come to choose more indirect, socially oriented forms of aggression such as spreading negative rumors about a classmate or attempting to alter relationships (Björkqvist, Lagerspetz, & Kaukiainen, 1992). The expression of aggression undoubtedly reaches a peak of complexity in adulthood, not only in terms of expression but also with regard to its multiple causes and consequences (Loeber & Day, 1997). The fact that aggression is not a unitary or homogeneous phenomenon is clearly not in dispute among scientists. More challenging, however, is the need to provide a definition of aggression that would satisfy researchers from most (or, it is hoped, all) spheres of expertise (Archer & Browne, 1989). Some authors have argued that this is an impossible mission because the concept of aggression involves too many variables and determinants and, more particularly, a significant part of social and moral judgment (e.g., Johnson, 1972). Others avoid using the term aggression because of its diffuse meaning (e.g., Patterson & Cobb, 1973), or declare that reaching a consensus on a definition is not necessary to perform a meticulous analysis of aggression (e.g., Cairns, 1979). Finally, some researchers have maintained that aggression is essentially an inadequate concept that ought to be replaced by more precise terminology (e.g., coercive control; Tedeschi & Felson, 1994; Felson, 2002). 25

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Before reaching a potential agreement about a definition, a first step is to describe and classify the different types of aggression. As Moyer (1968) argued, “progress in understanding the general phenomenon of aggressive behavior can only be made when the various aggressions are carefully and operationally defined” (p. 65). Hence, several attempts have been made to sort the different forms of aggression into discrete categories. Various taxonomies have been offered for both animal and human aggression, based on the similarity of behavioral expression, contextual characteristics of the eliciting stimulus, functional significance, motivational underpinning, or underlying neurophysiological mechanisms. In this chapter we review the diverse forms of aggression in both animals and humans in an attempt to integrate the current knowledge into a coherent theoretical and practical framework. We argue that a better understanding of the concept of aggression requires a systematic examination of the various proximal and distal forces that induce, facilitate, or maintain the development and expression of the different subtypes of aggression in both humans and animals. Comparing the similarities and dissimilarities of these multiple forces in a variety of species, and among individuals within a given species, is the only possible strategy for formulating a universal taxonomy of aggression.

COMPARING DIFFERENT LEVELS OF PHYLOGENETIC AND ONTOGENETIC ORGANIZATION The Risk of Anthropomorphism and Zoomorphism To recognize the phylogenetic sophistication of aggression, it is important to discriminate between subtypes of aggression that are unique to humans and those that are also present in other species. The ontogenetic sophistication of aggression will become manifest only by differentiating subtypes of aggression that are expressed during a specific developmental period from those that occur throughout ontogeny. Distinctions should be articulated behaviorally, functionally, and neurobiologically. At the behavioral level, a number of aggression-related behaviors are strikingly similar among many species, even in those that are extremely distant in phylogenetic terms. For instance, a “boxing” stance (an upright posture observed during fighting) is shown by fruit flies, rats, and humans. Although the behavioral repertoire of flies and rodents is more complex than one would expect (Chen, Lee, Bowens, Huber, & Kravitz, 2002; Barnett & Marples, 1981; Gendreau, Gariépy, Petitto, & Lewis, 1997), it does not reach the range of human behavioral expression. Nevertheless, one may ask how is it possible that such unrelated species exhibit similar forms of aggression. What do flies, rodents, and humans have in common besides possessing pairs of limbs and being able to display a similar motor-expressive pattern? At the functional level, fruit flies and rats do not fight for money or pride, but both can fight for sexual access and territoriality, as humans sometimes do. At the neurobiological level, the divergence is con-

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siderable. The rudimentary nervous system of a fruit fly is made up of a mere 250,000 neurons, and the brain of an adult rat weighs more or less 2 g. With its 100 billion neurons, the 1.4-kg human brain is at a different level of complexity. Nevertheless, rats and humans share similar brain structures and pathways, and, like fruit flies, they can develop addiction to cocaine, nicotine, and alcohol (Bainton, Tsai, Singh, Moore, Neckameyer, & Heberlein, 2000), suggesting a certain degree of neurobiological similarity. Cross-species comparisons call for differentiating behavioral and neurophysiological characteristics that are homologous (i.e., having a common evolutionary origin) from those that are simply analogous (i.e., likeness in function but not in evolutionary origin). When analyzing behavioral and/or physiological similarity between species, we run the risk of anthropomorphism, that is, viewing animals as having human-like qualities, or zoomorphism, that is, mistakenly perceiving human behavior as the mirror image of animal behavior (Cairns, 1979). For instance, contrary to the controversial and sensationalist opinion of authors in the past (e.g., Ardrey, 1966), predatory behavior in animals should not be equated with hunting or warfare in humans. Although these behaviors may share some common neuroevolutionary processes, the function of predatory behavior is to supply food, thus enhancing the probability of survival. Human hunting, at least in modern society, is often motivated only by the pleasure that the activity provides, and not by the necessity to gain food. Predation targets other species, whereas warfare is directed at other humans. Likewise, matching children’s and adults’ behavior on the basis of their expressive similarity, something one could adventurously call “adultomorphism” or “pedomorphism,” depending on the direction of the comparison, is not uncommon. A child hitting another child in kindergarten and an adult hitting a colleague at work are events that—albeit similar in their expression and to some extent in their immediate consequences (i.e., physical hurt)—clearly differ in terms of antecedents and long-term consequences. In sum, any definition of aggression that does not address the issue of phylogenetic and ontogenetic similarity and contrast encourages a static or reified view of a complex phenomenon.

Early Taxonomies of Aggression Animal models of aggression provide a strong conceptual base for approaching the study of human aggression. Moyer (1968) established seven categories of aggressive behavior based on their functional values and stimulus-bound characteristics: predatory aggression, intermale aggression, fear-induced aggression, irritable aggression, territorial defense, maternal aggression, and instrumental aggression. A possible eighth category, sex-related aggression, was also suggested. As Moyer himself mentioned five years later, however, “definition of the kinds of aggression on that basis alone now appears too restrictive: the kinds of aggression vary on a number of different dimensions,

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and all of them must be considered in the definition of each kind” (Moyer, 1973, p. 12). The dimensions that Moyer referred to were the specificity of the eliciting stimulus, the presence or absence of an emotional display, the sex of the attacker, and the neurophysiological correlates. With these four “dimensions” in mind, Moyer (1973) finally rejected territorial defense as a subtype of aggression. Although Moyer’s taxonomy was primarily targeting animal aggression, reference was also made to human behavior; however, the uniqueness and complexity of human aggression was not specifically addressed. The use of the categories to describe and differentiate human aggression undoubtedly leans toward zoomorphism. A similar comment can be made regarding Wilson’s sociobiological taxonomy (Wilson, 1980). Although most of the subtypes of aggression (i.e., territorial, dominance, sexual, parental disciplinary, weaning, moralistic, predatory, and antipredatory aggression) were meant to be theoretically applicable to both animals and humans, there are obvious exceptions. Weaning aggression, for example—that is, occurring when parents “gently attack” their offspring to make them stop begging for food—is clearly more relevant to animal behavior. The opposite can be said of moralistic aggression, which for Wilson (1980) represents advanced forms of reciprocal altruism that reduce the manifestation of aggression via rules, codes of punishment, or enforced conformity. In conjunction with the risk of zoomorphism and/or anthropomorphism, a major problem with Moyer’s and Wilson’s taxonomies is that they are based on an eclectic set of criteria. These involve a specific target (e.g., prey, predator, another male), a specific context (e.g., territorial, maternal, weaning), a specific function (e.g., to dominate, to obtain sexual access) or the concomitant occurrence of an emotional state (e.g., fear, anger), or a learning process (e.g., instrumental, moralistic). As argued by Archer and Browne (1989), one should try to be more explicit, and perhaps more restrictive, in terms of which criteria are used to divide aggression into distinct classes. Archer (1988) proposed a simpler classification on the basis of function by distinguishing forms of aggression that are “competitive,” “protective,” and “parental.” Parental aggression can be viewed as an extension of protective aggression, involving the protection of those recognized as genetically related and dependent. Predation was omitted from this scheme because, as argued in an earlier article (Archer, 1976), Moyer (1968) actually presented good evidence for the neural and motivational separation of the two forms of behavior. The argument was that the motivational systems underlying aggression and predation had evolved independently of one another; a good example is provided by cats, who show very different types of behavior and emotional states when fighting one another and when stalking prey. However, it is undoubtedly the case that the systems controlling predation and aggression are more related in some cases, for example, in the case of mouse killing by rats (e.g., Karli, 1956), in cannibalism in chimpanzees (Bygott, 1972), and more widely in the case of male infanticide. In humans, the link between hunting and aggression may be more complex.

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At about the same time that Moyer proposed his taxonomy and suggested four dimensional criteria to discriminate subtypes of aggression in animals, similar attempts were made to categorize the different forms of aggression in humans. Buss (1961) suggested that aggression be dichotomized along three behavioral dimensions: physical–verbal, active–passive, and direct–indirect. In 1969, Pulkkinen formulated a bidimensional (and bicriteria) model characterizing human aggression (see Pulkkinen, 1987). A first dimension was related to the expression of aggression, ranging from indirect forms to more direct ones. A second dimension concerned the defensive–offensive dichotomy, which was determined by the presence or absence of proximal threatening stimuli. Although these models have the merit of being parsimonious, they are not truly pertinent to animal aggression, as indirect forms of aggression are exclusive to humans and, possibly, nonhuman primates (Campbell, 1999). In addition, a model depicting behavioral or contextual features in terms of a continuum (poles or axes) may not be appropriate for some distinctions, because it postulates quantitative differences between the different forms of aggression. An aggressive act can fluctuate in intensity, but it cannot be half direct and half indirect.

A MULTILEVEL ANALYSIS OF AGGRESSION IN ANIMALS AND HUMANS Aggression is a dynamic, multifaceted social-emotional process that calls for a careful examination of its various antecedents, expressions, and consequences (or functions). The adoption of a dynamic and multifactorial perspective when investigating the foundations of aggression and other types of social behavior in humans and animals was ardently advocated by Cairns (1979). Cairns stressed the importance of using adequate criteria in order to generalize from one phylogenetic level to another and from one developmental stage to another. Observing a similar feature in two or more species (e.g., boxing) or in a child and an adult (e.g., hitting) is not enough to conclude that these behaviors serve the same function and derive from the same proximal or distal antecedents. This principle has a significant impact on how aggression is ultimately defined and how the different forms of aggression can be grouped. Figure 2.1 summarizes the major domains or themes of investigation in aggression research. This is an extended representation of Cairns’s model of what he called “polythetic analysis,” that is, the examination of aggression from multiple conceptual angles. The first three domains encompass the proximal (eliciting context and neurophysiological mechanisms) and the more distal antecedents of aggression, which are perceptible only through a longitudinal, developmental analysis. The fourth domain relates to the expression of aggression, whereas the fifth and the sixth cover the consequences of aggression to others (harm) and to self and society (social/emotional function), respectively. One must recognize that there are important differences between, as well

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FIGURE 2.1. Polythetic analysis of aggression. Based on Cairns (1979).

as within, species in terms of variables that influence the development and expression of aggression. Nevertheless, this thematic framework probably covers most subtypes of aggression found in the scientific literature and can be generally applied to both animal and human research. Obviously, dichotomizing aggression as direct versus indirect or as producing physical versus mental harm may be more appropriate and applicable to human behavior than to rat or fruit fly aggression. It is also important to note that even if most subtypes of aggression have been established on the basis of a single criterion, it is always possible to relate them to other criteria. Therefore, overlap between criteria is clearly the rule rather than the exception. For example, parental aggression in animals serves an obvious long-term function (i.e., survival of offspring), but it can also be described in terms of antecedents, either proximal (e.g., perception of a prey, underlying neurophysiological mechanism) or more distal (e.g., genetic predisposition). Common sense would dictate that we follow the temporal sequence of aggression, beginning with its antecedents, then considering its expression, and finishing with its consequences for others and the self. We decided to go the opposite way, starting with the first and most obvious outcome of aggression (its consequences for others and self) and then considering elements that necessitate a more thorough examination of the problem (e.g., distal antecedents and developmental issues). This upward presentation of the different components of aggression ends with a provisional integrative representation of the most significant subtypes of aggression and their underlying processes.

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SUBTYPING AGGRESSION ON THE BASIS OF ITS CONSEQUENCES ON OTHERS AND SELF Based on Harm and Injury Harm or injury to others is the foremost indicator that an aggressive act has occurred. This is perhaps why it has been a common criterion for qualifying aggression (Berkowitz, 1981; Rule, 1974). In its most simplified form, aggression has been defined as the delivery of noxious or painful stimuli to another individual (Buss, 1961) or as a response resulting in injury (Rule, 1974) or as “damage or destruction of some goal entity” (Moyer, 1968). Some authors specified that the targeted individual ought to “be motivated to avoid such treatment,” in order to exclude cases of sadomasochism (Baron, 1977). Research has traditionally focused on physical harm, but with increasing frequency, has been including mental or psychological harm as a potential consequence of aggression, as in the case of indirect aggression or persistent bullying. A number of issues have been raised concerning the validity of harm as a criterion for assessing or qualifying aggression. First, as potential harm, either physical or psychological, seems inherent to all forms of aggression, it has little discriminatory value. In addition, assessment of harm is not only contingent upon the nature of the aggressive action (a hit by a 2-year-old may not hurt an adult), but it is also conditional on the victim’s sensibility. Some individuals may be hypersensitive to external stimulation and may be more prone to feel physically and/or mentally harmed. Assessment of harm is indeed a highly subjective matter. Even from a behaviorist perspective that targets the observable behavior of the aggressor (delivery of noxious stimuli), a judgment must be made to determine whether pain or harm has been inflicted or not. Furthermore, the harm criterion has little value for subtyping aggression in animals. Automated bite-recording devices to measure the intensity of noxious delivery by aggressive primates and rodents have been designed (Ulrich, Dulaney, Arnett, & Mueller, 1973) but the devices turned out to be too impractical and restrictive (Knutson, 1973).

Based on Intent, Motivation Descriptive models of aggression have often emphasized the cognitive/motivational antecedent of aggression. An influential paper by Feshbach (1964) was critical in establishing two major types of aggression based on harm, or, more specifically, on the motivation to harm. If injury (to a person or object) was the primary goal of the action (pleasure or satisfaction following injury being the main reward), it was labeled hostile aggression. If injury was not the main purpose and the action was executed for reward other than the pleasure of injuring, then it was termed instrumental aggression. More specifically, Feshbach (1964) defined instrumental aggression as any act that produces harm and that “is directed toward the achievement of nonaggressive goals.” These

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“nonaggressive” goals include getting attention and acquiring an object or a resource. Although differentiating aggression based on the presence of hostile intention has been a dominant and relatively valid conceptual dichotomy in aggression research (Atkins, Stoff, Osborne, & Brown, 1993), it raises theoretical problems. First, aggression can be both hostile and instrumental (Bushman & Anderson, 2001; Hartup & De Wit, 1974). Second, labeling aggression as hostile is rather tautological. Are there nonhostile, friendly forms of aggression? This semantic glitch should not hinder the fact that some people may gain a considerable satisfaction or pleasure from hitting and injuring someone, whereas others may benefit more from the social or materialistic consequences of their aggressive action. It is important to note that getting pleasure from producing harm to someone may not be the most common motivational antecedent of aggression. Indeed, for many explanatory models (e.g., Archer, 1976; Berkowitz, 1993; Dollard, Doob, Miller, Mowrer, & Sears, 1939), bringing an end to a situation that is annoying and removing an irritant or a discrepancy from what is expected are frequent motivational precursors of aggression. Nonetheless, both pleasure-motivated aggression and relief-motivated aggression imply an emotional outcome or reward that is either pleasurable (positive reinforcement) or a release from a previously noxious state (negative reinforcement). Whether we call Feshbach’s categories of aggression hostile versus instrumental, annoyance-motivated versus incentive-motivated (Zillman, 1978), or emotionally rewarding versus materialistically/socially rewarding, does not really matter if an unambiguous definition is provided. Researchers with a social-interactionist perspective (Tedeschi & Felson, 1994) view aggression (which they term “coercive power”) as being motivated by interpersonal goals—to control others, to maintain justice, or to defend social identity. From the perspective of the actor, all aggression is therefore instrumental in that it pursues one of these social goals. However, these situations can just as readily be viewed as removing an irritant (i.e., negative reinforcement), and it may be confusing to regard such situations—which inevitably involve anger—as instrumental in nature. For the purposes of clarity, it is probably better to restrict the term “instrumental” to cases involving positive reinforcement of aggression by a reward unconnected with activation of the aggression system. This would highlight the parallels between such human cases as robbery and rape (Felson, 2002) and the use of conventional reinforcers such as food or water to facilitate animal aggression (e.g., Ulrich, Johnston, Richardson, & Wolff, 1963). Feshbach (1971) and Rule (1974) proposed a different taxonomy by subdividing instrumental aggression into personally motivated aggression and socially motivated aggression. Personally motivated aggression is different from hostile aggression in that the primary goal is not to hurt but to obtain reward via inflicting injury. Yet aggression is said to be socially motivated when the primary goal is to gain a social advantage. Even in the authors’ views, however, the distinction between these subtypes of aggression was problematic,

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because of the difficulty in assessing motivation, intent, or feeling. Sears (1961) suggested the term prosocial aggression to distinguish aggressive behavior considered as socially and morally acceptable. However, to the same extent that the term hostile aggression is certainly a truism, the expression “prosocial aggression” appears to be an oxymoron. Naming an aggressive act as prosocial or antisocial depends too much on individual viewpoints to be a useful categorization criterion. Physically punishing a child to prevent the occurrence of a life-threatening situation (e.g., crossing a high-traffic road) may have a justifiable intention and long-term benefits. From the child’s perspective, however, the immediate consequences of being spanked by a parent or being slapped by a peer may not differ much. Moreover, any act of terrorism or war can be considered legitimate and morally acceptable from the aggressor’s perspective. From the victim’s point of view, the immediate and harmful consequences do not depend on how good the intention was. It has been claimed that behavior should be at once intentional (motivation to injure) and harmful to be classified as being aggressive (Berkowitz, 1993; Dollard et al., 1939). As with the nature and intensity of harm, however, intent is a concept that is difficult to prove and easy to deny (Loeber & Hay, 1997). It also imposes serious limitations in investigating aggression in children or animals (Tremblay, 2000). For these reasons, although intent is certainly central to the definition of aggression, it may not be an adequate criterion in practical terms for establishing a taxonomy of aggression applicable to both animals and humans (children and adults). Intention may be also problematic in cases of indirect aggression where the perpetrator seeks to cover up his or her actions.

SUBTYPING AGGRESSION ON THE BASIS OF ITS EXPRESSION Categorizing aggression on the basis of its behavioral expression has been a popular criterion as it circumvents the pitfalls of intrinsic notions such as instinct, motivation, drive, or intent to harm. Unfortunately, too many behavioral responses that have little in common have been subsumed under the label of aggression. Display of aggressive behavior is species-typical and agedependent, as it is manifestly constrained by morphogenetic, neurophysiological, and maturational factors unique to each species and developmental stage. Topographical descriptions of aggressive interactions in animals have been performed systematically (Barnett & Marples, 1981; Grant & Mackintosh, 1963; see also Pellis, Pellis, & Foroud, Chapter 3, this volume). Although attempts have been made to extend the ethological approach in children (Blurton-Jones, 1967; McGrew, 1972) much less has been achieved regarding the operationalization of specific aggressive behavior in humans (Knutson, 1973; Tremblay, 2000). Buss (1961) was among the first to offer a behavioral taxonomy of human aggression by dichotomizing it along the physical–verbal, active–passive, and direct–indirect dimensions. The active–passive dimension is

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debatable, however, because it is difficult to determine whether behavioral inactivity (e.g., not helping someone in need) was intended or not. The physical– verbal and the direct–indirect dimensions are more defendable. They are more useful when applied to humans, although animals often begin aggressive encounters with threat displays, including vocalizations (Archer, 1988). In animals, direct aggression is straightforward, involving bodily contact such as biting, hitting, or pushing. Some behavioral elements that do not involve any physical contact, such as threat and thrust (Grant & Mackintosh, 1963), are clearly direct and aggressive, as their objective is to intimidate and they are often precursors of genuine attack. In humans, Blurton-Jones (1972) also labeled as aggressive a number of nonphysical behaviors that were temporally related to other more obvious aggressive actions. In humans, however, the expression of aggression is far more complex and includes a broader assortment of direct and indirect actions. Direct forms of aggression comprise physical assault and a range of verbal behaviors that may be hostile in content or in tone. These verbal behaviors may occur with or without physical attack. In humans, direct aggression is somehow equivalent to overt aggression (Crick, 1996). Indirect aggression is at the other end of the behavioral dichotomy, consisting of actions aimed at harming others that involve some kind of social intermediary between the aggressor and the victim. The course of action is often delayed and subtle, as there is no physical contact. The psychological effects, however, may persist over a long period. This can be achieved through gossiping and ostracizing, which ultimately may damage peer relationships or social status, or through actions aiming at reducing accessibility to resources. Research on indirect aggression has grown substantially in the last few years, as this may be the most prevalent form of aggression during adolescence and adulthood (Björkqvist et al., 1992). It is the only form of aggression that may be more prevalent in females than in males (Campbell, 1999). Indirect aggression overlaps with two further categories, relational (Crick, Grotpeter, & Bigbee, 2002) and social (Galen & Underwood, 1997) aggression. Relational aggression emphasizes damage to relationships as a way of harming someone. As this can include face-to-face statements such as “I’m not friends with you anymore,” relational aggression is therefore not always direct (Coyne, Archer, & Eslea, 2004). Social aggression is a wider category that includes both relational and indirect forms, along with expressions such as negative facial expressions or body movements.

SUBTYPING AGGRESSION ON THE BASIS OF ITS ANTECEDENTS Proximal Contextual and Emotional Elicitors Proximal antecedents, either contextual or emotional, are the most frequently used criteria for discriminating subtypes of aggression, particularly in animals. A wide range of social and nonsocial contextual/situational variables have

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been used to elicit aggressive behavior in animals (Archer, 1976, 1988). Social elicitors include the presence of a prey or exposure to a same-species, samesex conspecific either in the home cage (resident–intruder paradigm) or in a novel environment. These social encounters are often combined with prior or concomitant experimental manipulations (e.g., social isolation, food deprivation, electric shock) that alter the neurobehavioral state of the potential aggressor. These predisposing factors, which influence the potency of the elicitors (Hinde, 1974), represent an important issue in aggression research. A decisive factor is the presence or absence of a threatening elicitor. When a situation is clearly threatening or perceived as threatening, an arsenal of behavioral responses is put in motion to protect the individual from pain, injury, and, possibly, death. Responses to threat range from harmless reactions, such as heightened immobility (i.e., freezing, crouching), escape, and holding off the threatening assailant with stretching of the upper limbs (boxing), to fierce attack and delivery of noxious stimuli. This constellation of responses has been traditionally subsumed under the label “agonistic behavior” (Scott & Fredericson, 1951). The notion of aggression as a response to potential threat to an animal’s welfare is central to theories that conceive of aggression as an aversion, whereby the animal is motivated to avoid a situation. This contrasts with an appetite, whereby the animal is motivated to approach or seek out a situation (Craig, 1928). Aversion-based theories seek to identify the mechanism through which animals or humans detect threats, and they include the frustration– aggression hypothesis (Dollard et al., 1939), the discrepancy model of animal aggression (Archer, 1976), and the theory of threatened egotism (Baumeister, Smart, & Boden, 1996). Pain is another “emotional” antecedent of aggressive behavior. Animals exposed to painful stimulation (e.g., electrical shocks, sudden heat, bite) will start fighting against each other or will attack an inanimate object if tested alone (Archer, 1989/1990; Ulrich & Azrin, 1962). Blanchard and Blanchard (1981) have convincingly argued that such pain-induced aggression is analogous to fear-induced defensive aggression. Archer (1989/1990) suggested that, although this is the case in laboratory setups involving repeated painful shocks, an isolated single painful stimulus may under natural conditions evoke anger-induced offensive aggression. Overall, aggressive behavior can be generated by a variety of external stimuli that are threatening or painful, and these stimuli activate, to different degrees, both the peripheral and the central nervous systems. In pain-induced aggression, activation of the nociceptors and/or thermal receptors sets in motion neural pathways that control the expression of aggressive behavior, and, in this case, the threshold for fear is easily reached. Then, determining whether aggression is mediated by fear or anger will depend on which brain regions are activated during attack. Under threatening circumstances, aggression may be offensive or defensive (Blanchard & Blanchard, 1989), that is, anger or fear motivated. In humans, responses to provocation broadly similar to threats in animals have

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been termed reactive aggression. Thus, reactive aggression is an impulsive, negatively valenced act displayed in response to a threat or provocation (Dodge, & Coie, 1987; Vitaro, Gendreau, Tremblay, & Oligny, 1998). It stems from the frustration–aggression hypothesis that viewed aggression as a “primordial reaction . . . whenever pleasure-seeking or pain-avoiding behavior is blocked” (Dollard et al., 1939, p. 21). Interestingly, it is not so much contextual stimuli per se that determine whether aggression will be labeled as reactive, but the perception that the individual has and what he or she makes of it. Indeed, an interesting finding in human research is that reactively aggressive children more readily perceive an ambiguous situation as threatening or hostile (Dodge & Coie, 1987; Vitaro, Brendgen, & Tremblay, 2002). This attributional/perceptual bias and behavioral hypersensitivity to what typically should be mild, nonthreatening stimulation is reminiscent of what is observed in animals after prolonged social isolation (Gendreau, Gariépy, Petitto, & Lewis, 1998) or after successive defeat experiences (Keeney & Hogg, 1999). These animal paradigms may be more relevant to human reactive aggression than paradigms using clear life-threatening conditions. Conversely, proactive aggression occurs with more forethought and does not seem to be associated with any apparent proximal elicitor. It is more controlled, more premeditated, and less emotionally reactive. It can be understood in terms of social learning, as a result of previous external reinforcement (Bandura, 1973; Patterson & Cobb, 1973). Discriminant and convergent validity of these subtypes of aggression has been provided by an increasing number of empirical reports (Dodge & Coie, 1987; Poulin & Boivin, 2000; Pulkkinen, 1996; Vitaro et al., 1998, 2002). Contrary to the dichotomy hostile–instrumental, which is determined by the nature of the motivation (goal is to hurt vs. goal is to gain), reactive and proactive forms of aggression are differentiated by the presence of a prior provocative event and the short delay before enactment. The distinction between reactive and proactive aggression, however, is problematic, as it depends on no provocation being identified, and what constitutes a provocation varies considerably between individuals. Looking at someone the wrong way may be classed as a provocation in a subculture where everyone is on the lookout for signs of disrespect. Having said this, the category proactive aggression (i.e., aggression without obvious provocation or threat) may alert us to cases, primarily among young men, where fights are sought for no apparent reason other than to inflict a physical defeat on another person.

Brain Mechanisms The use of psychic or inner states to qualify aggression is not necessary when examining the direct and observable effects of lesions and stimulations of specific areas of the brain. The brains of humans and other mammals share many structures, pathways, and neurochemical properties, reflecting the long and progressive transformation of the brain during evolution. In the last four de-

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cades an increasing body of evidence has accumulated describing the role of specific neural circuits in the expression of different types of aggression. Numerous sites within the neocortex and subcortical structures have been identified as central in mediating aggressive behavior. Moyer (1968, 1973) was among the first to relate specific neural circuitries and distinctive neuroendocrinological status to subtypes of aggression. Particular attention was given to the amygdaloid complex, the various hypothalamic nuclei, and other parts of the so-called limbic system (e.g., septum, cingulate cortex). Moyer (1973) argued that each of the subtypes of aggression that he had previously identified (except for instrumental aggression) had its own set of neural circuits. Functions associated with the expression of specific forms of aggressive behavior have indeed been localized in the brain (Valzelli, 1981; Panksepp, 1998). As Panksepp pointed out, however, there are more subtypes of aggression based on the proximal contextual antecedents than there are subtypes based on neural processes. In other words, similar brain circuitry may allow different types of aggression to be expressed; what differs are the eliciting circumstances and the perceptual processing. As we will see, this has a significant impact on our attempt to produce a parsimonious taxonomy of aggression. Panksepp (1998) denoted distinct neural circuitry for no more than three subtypes of aggression in the brains of rats and cats: predatory aggression, affective or rage-like aggression (which may coincide with defensive aggression identified by Blanchard & Blanchard, 1989); and intermale aggression (what the Blanchards called offensive aggression). So-called predatory aggression (or quiet-biting attack in the laboratory) can be generated by stimulation of the dorsolateral hypothalamus and involves activation of the ventral part of the periaqueductal gray. It is believed to be primarily mediated by what Panksepp (1998) termed the seeking or the appetitive motivational system of the brain. If so, this contrasts with the emphasis on aversive motivation in most theories of aggression (see above). This system involves not only the lateral hypothalamus but also most structures that are innervated by neurons releasing dopamine and serotonin. Abnormal development of the prefrontal cortex has been associated with antisocial personality disorder (Raine, Lencz, Bihrle, LaCasse, & Colletti, 2000), and people diagnosed with this disorder have been shown to display more proactive forms of aggression (Chase, O’Leary, & Heyman, 2001). This would be consistent with their seeking out situations in which to display aggressive actions. In contrast, the affective subtype of aggression is mediated by different and more primitive (Archer, 1988) interactive neural circuits, what Panksepp (1998) termed the fear system and the rage system. Affective aggression involves the ventrolateral–medial hypothalamus, several amygdaloid nuclei, and the dorsal part of the periaqueductal gray, to cite just a few (Gregg & Siegel, 2001). It is important to note that this subcortical circuitry operates relatively independently of neocortical input. The neurophysiological basis of intermale (or intrasexual) aggression has not been well established. Panksepp (1998) mentioned that the brain circuitry of intermale aggression may interact with

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both the seeking and rage systems, but is somehow relatively independent. The evidence for this is clearly not overwhelming, but Panksepp (1998) reported that brain lesions that impair predatory and affective aggression do not affect intermale aggression. Obviously, this is an extremely simplified account of very complex brain mechanisms involving many more structures and neurotransmitter systems (see Gregg & Siegel, 2001). Although primitive forms of aggression, such as those elicited by stimuli perceived as painful, threatening or annoying, may be processed through brain circuitry highly similar to that of other species, the sophistication and diversification of aggression in humans necessarily implies the existence of brain processes unique to our species. Our neocortex, which does not complete its maturation before adulthood (Giedd et al., 1999), plays an important inhibitory role in more primitive brain structures, therefore controlling the expression of social/emotional reactivity. The gradual transformation of the brain during development may explain the progressive shift in the expression of aggression from early childhood to adulthood, that is, direct, reactive, and physical forms of aggressive behavior being gradually substituted by more indirect, controlled, and nonphysical forms (see Vaillancourt, Chapter 8, this volume).

Developmental Issues What differentiates humans from animals is not only the increased complexity of the human brain, the advanced cognitive skills and social world, but the longer developmental period that is necessary for organizing behavior (Cairns, 1979; Hinde, 1974). As mentioned in the preceding section, the expression of aggression changes throughout ontogeny, with physical aggression reaching its peak in early childhood (Tremblay et al., 1999) and relationally oriented forms of aggression gradually emerging in late childhood/early adolescence (Björkqvist et al., 1992). Hartup (1974) observed that aggression develops from being first object-oriented (instrumental) to being more person-oriented (hostile) aggression (see also Caplan, Vespo, Pedersen, & Hay, 1991). Hinde (1992) proposed one of the few categorizations of aggression exclusive to childhood. He discriminated instrumental (or specific) aggression (aiming at gaining or retrieving an object or situation), teasing aggression (aggression unrelated to acquiring a specific object or situation), defensive aggression (in response to an attack), and game aggression (that results from rough-and-tumble play). Hinde suggested that childhood instrumental and defensive aggression were somehow equivalent to reactive–impulsive aggression as observed in adulthood. Teasing aggression had its adult counterpart under the label of “spontaneous aggression.” No further distinction between impulsive and spontaneous aggression and no adult correspondence for game aggression were provided. A social–developmental analysis of the functional and expressive characteristics of aggression from early childhood to adulthood is indispensable for

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our understanding of the different ontogenetic pathways to more sophisticated forms of aggression. Hinde’s distinction between subtypes of aggression in childhood was clearly a step toward establishing a developmental topology of aggression. One may question, however, the need to use different taxonomical labels for children and adult aggression, especially when there is correspondence between the different subtypes. In addition, characterizing one form of aggression as impulsive and another as spontaneous is confusing. Finally, game aggression (or rough-and-tumble play) is clearly motivationally distinct from other forms of aggression (Blurton-Jones, 1972; Smith, 1974). In the end, we need to agree on a general taxonomy that is applicable throughout development, not only to a specific period. Once this is achieved, the developmental trajectory of the different subtypes of aggression can be investigated. The onset and stability of aggression during ontogeny has been an important issue in developmental and clinical sciences. Moffitt (1993) proposed a developmental taxonomy of conduct disorders based on the onset and persistence of antisocial behavior (which relates to aggression). Specifically, conduct disorders could be described as life-course persistent (behavioral problems start during childhood and persist throughout childhood up to adolescence and adulthood) or as adolescence-limited (when problems emerge and end during adolescence) Discriminating between early- versus late-onset conduct disorders has been a valuable clinical classification (American Psychiatric Association, 1994). The relationship between individual development and the transformation of aggression over time in boys and girls, in both expression and function, is central to the science of aggression. We now recognize the gender-dependent development and use of physical aggression (Tremblay et al., 1999) and the gradual emergence of hostile (Caplan et al., 1991; Hartup, 1974) and indirect (Björkqvist et al., 1992) aggression. Similarly, reactive aggression seems to appear first (as tantrums) or may be a more prevalent form of aggression early on (Loeber & Hay, 1997). However, children prone to display proactive forms of aggression may be more at risk of exhibiting delinquent activities in adolescence (Vitaro et al., 2002). Finally, recent evidence suggests that reactive and proactive aggression in boys and girls may have different etiological antecedents (Connor, Steingard, Anderson, & Melloni, 2003). Many important issues remain to be investigated regarding the onset and developmental trajectory of the different forms of aggression across gender and sociocultural background.

AN INTEGRATIVE MODEL OF AGGRESSION The goal of this chapter is to provide a summary of conceptual and theoretical issues related to the categorization of different subtypes of aggression in humans and animals. Finding an appropriate taxonomy seems to be a recurrent problem in aggression research. A taxonomy is, by definition, a classification based on similarities of a specified characteristic. Suggesting a taxonomy for

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subtypes of aggression based on a single criterion or for a single species is one thing, but conceiving one that encompasses the multiple ontogenetic and phylogenetic aspects of this phenomenon is more challenging. Aggression is not a behavior, or a set of genes, or a brain mechanism. It is a complex social phenomenon that conveys so many meanings, takes so many forms, results from so many proximal and distal antecedents, and has so many consequences that a universal taxonomy seems an unachievable puzzle. It has identifiable underlying brain processes, but those are dependent upon context, emotional state, and previous learning experience (reinforcement). It is important to note that aggression is a phenomenon in constant transformation, both phylogenetically and ontogenetically. Hinde (1974) summarized well the challenge of elaborating a taxonomy for subtypes of aggression in both humans and animals: “The range validity of any generalizations we make is inversely related to their precision. As more diverse phenomena are included within our category of aggressive behavior, our generalizations inevitably become less precise” (p. 4). The primary problem with respect to categorizing aggression into different subtypes is to select a parsimonious set of criteria that integrate most forms of aggression. In this regard, some criteria, despite being relevant to our better understanding of aggression, do not appear to be essential for establishing a categorization. Harm to others, for instance, either physically or psychologically induced, may be the first, more expeditious consequence of aggression, but it has little taxonomic value. Therefore, we settled on a simplified taxonomic model that encompasses the most significant and discriminative features of aggression (Figure 2.2). These include the antecedent (to determine whether aggression is proactive or reactive), the expression (to determine whether aggression is direct or indirect), and the function (to determine whether aggression was produced only to hurt or to benefit socially). Other important elements of aggression, such as distal antecedents (past experience, biological or genetic predisposition), aggressor’s emotional–perceptual bias, basic neurobiological mechanisms, and learning, were also integrated. The first step in identifying the form of aggression should be to determine whether there is a proximal contextual elicitor. If there is no apparent proximal antecedent, then aggression is proactive. This form of aggression is primarily controlled by the neocortex, more particularly the prefrontal cortex and the descending corticolimbic pathways. When a proximal antecedent can be identified, then aggression is said to be reactive. This behavioral output involves various motivational/emotional states (e.g., fear, pain, anger, or annoyance) that are under the control of subcortical, primarily limbic, structures. In reactive aggression, perception of the eliciting stimulus is the key for judging the pathological nature of the response. Hypersensitivity to certain contexts and stimulations may indicate heightened anxiety or heightened fearfulness (paranoia). Both proactive and reactive aggression can be expressed directly or indirectly, and they can target either the source of stimulation or a substitute person/object (displaced aggression). Then the aggressive action may pro-

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FIGURE 2.2. A simplified taxonomical model of aggression based on context, neuroaffective processes, consequences on self, and learning.

vide a pleasurable reward from harming (hostile aggression), a social/materialistic reward (instrumental aggression), or both. Following these consequences, learning (reinforcement) will take place and certainly influence individual development.

CONCLUDING REMARKS Aggression is always a timely topic. The news media provide an incessant flow of information on the shocking nature of human behavior. We were just finishing this chapter when we heard the news that three teenage girls were facing charges of attempted murder for allegedly trying to poison a classmate by adding copper sulfate, a highly toxic substance, to her drink. What aggressive category does poisoning fit into? It undoubtedly relates to physical harm, but without a clear, direct physical action. It is a physical action but with an indirect, concealed behavioral twist. Although it is a planned, proactive-like aggressive action, it is likely a retaliatory response to some prior event or situation. This is a good example of the difficulty in fitting every act of aggression into a definite category or model. Do we need more research to produce a better taxonomy? Reaching a consensus on this issue may not be as necessary as continuing our thorough analysis of the wide range of proximal and distal

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forces that influence the development and expression of aggression (Cairns, 1979). It is important to refine our knowledge of the many genetic, biological, and social factors that induce, facilitate, or maintain aggression throughout development. Eventually, a universally agreed-upon taxonomy, at once parsimonious and comprehensive and integrating both animal and human aggression, may emerge.

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Moyer, K. E. (1973). The physiological inhibition of hostile behavior. In J. F. Knutson (Ed.), The control of aggression: Implications from basic research (pp. 9–38). Chicago: Aldine. Panksepp, J. (1998). Affective neuroscience: The foundations of human and animal emotions. New York: Oxford University Press. Patterson, G. R., & Cobb, J. A. (1973). Stimulus control for classes of noxious behavior. In J. F. Knutson (Ed.), The control of aggression: implications from basic research (pp. 145–199). Chicago: Aldine. Poulin F., & Boivin, M. (2000). Reactive and proactive aggression: Evidence of a two-factor model. Psychological Assessment, 12, 115–122. Pulkkinen, L. (1987). Offensive and defensive aggression in humans: A longitudinal perspective. Aggressive Behavior, 13, 197–212. Pulkkinen, L. (1996). Proactive and reactive aggression in early adolescence as precursors to anti- and prosocial behavior in young adults. Aggressive Behavior, 22, 241– 257. Raine, A., Lencz, T., Bihrle, S., LaCasse, L., & Colletti, P. (2000). Reduced prefrontal gray matter volume and reduced autonomic activity in antisocial personality disorder. Archives of General Psychiatry, 57, 119–127. Rule, B. G. (1974). The hostile and instrumental functions of human aggression. In J. De Wit & W. W. Hartup (Eds.), Determinants and origins of aggressive behavior (pp. 121–141). The Hague: Mouton. Scott, J. P., & Fredericson, E. (1951). The causes of fighting in mice and rats. Physiological Zoology, 24, 273–309. Sears, R. R. (1961). Relation of early socialization experiences to aggression in early childhood. Journal of Abnormal and Social Psychology, 63, 466–492. Smith, P. K. (1974). Aggression in a preschool playgroup: Effects of varying physical resources. In J. De Wit & W. W. Hartup (Eds.), Determinants and origins of aggressive behavior (pp. 97–105). The Hague: Mouton. Tedeschi, J. T., & Felson, R. B. (1994). Violence, aggression, and coercive actions. Washington, DC : American Psychological Association. Tremblay, R. E. (2000). The development of aggressive behaviour during childhood: What have we learned in the past century? International Journal of Behavioral Development, 24, 129–141. Tremblay, R. E., Japel, C., Pérusse, D., Boivin, M., Zoccolillo, M., Montplaisir, J., & McDuff, P. (1999). The search for the age of “onset” of physical aggression: Rousseau and Bandura revisited. Criminal Behavior and Mental Health, 9, 24– 39. Ulrich, R. E., & Azrin, N. H. (1962). Reflexive fighting in response to aversive stimulation. Journal of the Experimental Analysis of Behavior, 5, 511–520. Ulrich, R. E, Dulaney, S., Arnett, M., & Mueller, K. (1973). An experimental analysis of nonhuman and human aggression. In J. F. Knutson (Ed.), The control of aggression: Implications from basic research (pp. 79–111). Chicago: Aldine. Ulrich, R. E., Johnston, M., Richardson, J., & Wolff, P. (1963). The operant conditioning of fighting behaviour in rats. Psychological Record, 13, 465–470. Valzelli, L. (1981). Psychobiology of aggression and violence. New York: Raven Press. Vitaro, F., Brendgen, M., & Tremblay, R. E. (2002). Reactively and proactively aggressive children: Antecedents and subsequent characteristics. Journal of Child Psychology and Psychiatry, 43, 495–505.

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THEFighting Play DEVELOPMENT OF AGGRESSION

3 Play Fighting Aggression, Affiliation, and the Development of Nuanced Social Skills S ERGIO M. P ELLIS, V IVIEN C. P ELLIS, and A FRA F OROUD

In traditional New Guinean society, if two men—strangers to each other— were to meet on a path between their respective villages, they would then likely, if they wished to avoid bloodshed, begin to list all the people to whom they were related in the hope of discovering some common ground between them (Diamond, 1997). Although having the skill to win in a potentially aggressive encounter is important, this New Guinean practice illustrates that having the skill to avoid unnecessary aggression may be just as important. It is becoming clear that aggression is but a part of a larger tool kit for gaining advantage in a complex social world. This appears to be true not just for humans, but for many social mammals (de Waal & Aureli, 2000). In such a world, knowing who and when to fight becomes important, and thus so does having the cognitive skills to gather the information required to make the appropriate decisions. Placing aggression into a broader social context has implications for the understanding of the developmental processes that shape aggression. The problem lies not only in learning how and when to use aggression, but also in knowing how to assess the situation so as to determine whether a nonaggressive approach would be a more suitable solution. In this chapter we show that play fighting can provide a vehicle for the development of such skills. Play fighting resembles serious fighting in that the partners compete for access to some advantage. Most often, this advantage takes the form of biting or striking another individual on a particular body target (Aldis, 1975). The targets competed over during play fighting can be those that in adulthood are 47

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used in conspecific aggression, sex, or predation. Despite these differences in targets, all forms of play fighting have play-typical rules of attack and defense in common (Pellis & Pellis, 1998a). In contrast, during conspecific aggressive encounters, in the early stages of sexual encounters and in predatory encounters, the opponents follow the rules of attack and defense typical of serious fighting. For play fighting to remain playful, it needs to follow the 50:50 rule (Aldis, 1975; Altmann, 1962). That is, each pairmate has to win close to 50% of the playful encounters. Such a win:loss ratio requires that the rules of attack and defense differ from those that apply to serious fighting (Pellis & Pellis, 1998a). When an attack is launched during a serious fight, the attacking animal has to guard against retaliation from the opponent. Typically, in order to do so, the attacker simultaneously incorporates some defensive tactic into its attack, which limits the defender’s opportunity to counterattack (Pellis, 1997). Similarly, when defending itself against a serious attack, the defender uses an intensity in its defense that reduces the likelihood of a successful penetration by the attacker (Pellis, 1997). In contrast, during play fighting, the attacker rarely incorporates defensive maneuvers in its attack, thus facilitating successful counterattacks by the defender (Pellis & Pellis, 1998a). In addition, when defending itself against a playful attack, the defender will use an intensity of defense that is lower than that in serious fights, increasing the likelihood of a successful contact by the attacker (Pellis & Pellis, 1998a). That is, in play fighting, the tactics of attack and defense are decoupled so as to ensure that each animal can successfully contact the partner. This contrasts sharply with serious fighting, in which an animal may deliver injurious, or even lethal, attacks if the opponent leaves its target exposed (Blanchard, Blanchard, Takahashi, & Kelly, 1977; Geist, 1971; Pellis & Pellis, 1992). In the following text, we show that given its rule structure, play fighting can provide fertile ground for learning a variety of social skills. Detailed studies of the development of play fighting in rats (Pellis, 2002b) provide a model for understanding how play fighting may be used for sharpening the social skills needed to straddle the subtle divide between competition and cooperation effectively (Pellis, 2002a).

PLAY FIGHTING IN RATS1 In rats, play fighting involves attack and defense of the nape (Figure 3.1). Successful contact with the nape involves gently rubbing the nape with the nose (Pellis & Pellis, 1987; Siviy & Panksepp, 1987). Nape contact is a target typical of adult sexual encounters (Pellis, 1988, 1993), whereas agonistic attacks involve bites directed at the lower dorsum or the face (Blanchard et al., 1977; Pellis, 1997). To defend themselves against playful nape contact, rats use the same tactics of defense that are used in serious aggression, but modify them to match both the differences in targets (Pellis & Pellis, 1987) and the differences

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FIGURE 3.1. A sequence of play fighting is shown for a pair of 31-day-old rats. Note that the attacking rat (on the left), lunges toward its partner’s nape. The defending rat avoids nape contact by turning to supine. From this on-top/on-bottom position, both rats make attempts to contact each other’s napes. Adapted from Pellis and Pellis (1987). Copyright 1987 by Wiley. Adapted by permission.

in the rules of execution of those tactics (Pellis & Pellis, 1998a). Even though most common in the juvenile phase (Meaney & Stewart, 1981; Panksepp, 1981; Thor & Holloway, 1984), play fighting in rats persists well into young adulthood (Adams & Boice, 1983, 1989; Pellis & Pellis, 1991b). Indeed, play fighting between adults occurs among many mammalian species, in both sexual and nonsexual encounters (Pellis & Iwaniuk, 1999b, 2000). However, whether the context is sexual or nonsexual, such play fighting appears to be used to assess and manipulate the other animal, be it human or nonhuman (Breuggeman, 1978; Pellis & Iwaniuk, 1999b). When it occurs in subadults and adults, play fighting appears to be used in two general contexts—for social bonding and for social testing (Pellis & Pellis, 1996; Pellis & Iwaniuk, 1999b, 2000; Smith, Fantella, & Pellis, 1999). Social bonding may include courtship and pair bonding, as well as nonsexual social affiliation. Social testing most typically involves some form of jostling for social status. The distribution of these functions vary across species, with some species using them only for affiliation, some using them only for dominance testing, and some using them for both (Pellis, 2002a). In rats, play fighting is used for both these purposes (Pellis, Pellis, & McKenna, 1993; Smith et al., 1999). It should be noted that in rats, as in many other mammals, play fighting is more frequent among males (Pellis & Pellis, 1990, 1997), although preferences for which sex is the most attractive as a play partner may change during

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development (Meaney & Stewart, 1981). With regard to the social uses of play fighting, only male rats show the context-specific modulation of content that is consistent with such uses (Pellis, Field, Smith, & Pellis, 1997). In some other species of mammals, females also appear to use play fighting for social assessment and manipulation (Pellis, 2002a; Pellis & Iwaniuk, 2000). For the present purposes, in this discussion of rats, males are the focus of consideration. Play fighting in rats has several features useful for the analysis of the development of social skills. First, the difference in targets between play fighting and serious fighting makes it easy to differentiate between these two forms of fighting. This is very useful for identifying cases where play fights escalate into serious fights. By using a switch in target as a marker, it was found that playful encounters escalate into serious ones if one of the partners breaks the playtypical rules of attack and defense. That is, if one of the pair stops allowing the partner an opportunity for reciprocal contact, the partner may switch to an aggressive attack (Pellis & Pellis, 1998a). Second, adults use play fighting in clearly functional contexts, allowing us to identify the social skills needed and so evaluate play fighting earlier in development to ascertain whether the opportunity to acquire such skills is present. To explain what those skills entail, we describe the social uses of play fighting among adult male rats. This understanding then sets the stage for interpreting the developmental changes in play fighting present in this species.

THE ADULT USES OF PLAY FIGHTING Within a colony, adult male rats form a dominance hierarchy (Blanchard & Blanchard, 1990; Calhoun, 1962; Flannery & Lore, 1977) in which subordinates initiate more playful encounters with dominants than they do with each other (Pellis et al., 1993). When playfully contacted by a dominant, subordinates are more likely to roll over onto their backs, a response typical of juveniles (Panksepp, 1981; Pellis & Pellis, 1987), whereas when contacted by another subordinate, they are more likely to remain standing and push against the attacker with their flanks (Pellis et al., 1993), a response typical of a dominant male (Pellis & Pellis, 1991a, 1992). In the absence of dominance relationships, postpubertal males are more likely to stand and push than to roll over to supine (Pellis & Pellis, 1990; Smith, Field, Forgie, & Pellis, 1996; Smith, Forgie, & Pellis, 1998, Smith et al.,1999). Thus, the increased soliciting of playful contact by subordinates toward dominants, and the juvenile-like response toward those dominants, suggests that the play fighting is used as a means of maintaining “friendly” relations with dominants (Pellis et al., 1993). However, not all subordinates are equally obsequious. The greater the dominance asymmetry between pairmates, the more juvenile-like the playful responses by the subordinate (Pellis & Pellis, 1992).

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Indeed, it is those pairmates that are the least asymmetrical in their play relations that are the most likely to escalate the playful encounter into a serious fight (Pellis & Pellis, 1991a). Similarly, when male rats that are unfamiliar with each are placed into a neutral arena, it is the dominant–dominant combination that is the most likely to escalate into a serious fight (Smith et al., 1999). Close inspection of these escalations suggests that the play fighting preceding the serious fight is “rougher.” These observations also suggest that when animals are testing each other in regard to their opponent’s capability to maintain or gain a position of superior dominance, the play can then be escalated into a quasi-aggressive intensity. Therefore, there are two extremes in the style of play that are available to an individual—a gentler form, which is seen when a subordinate is maintaining familiarity with a dominant, and a rougher form, which is seen when one rat is probing another one for its weaknesses. As previously described, these differences in play intensity among adult male rats can be explicitly converted into formal rules of engagement and can provide a rat with the basis for judging how such play can be used to assess and manipulate its partner. For example, when a subordinate rat uses play fighting as a means of social bonding with the dominant male in the colony, it bends the 50:50 rule in the dominant’s favor, whereas when a subordinate uses play fighting to probe the dominant for weakness, or when it encounters an unfamiliar rat, it bends the rule in its own favor. In the latter case, the rat can assess how much of a deviation from equality the opponent will tolerate before retaliating aggressively. A simple rule of thumb may operate in such a scenario. If the dominant or unfamiliar rat tolerates the bending of the 50:50 rule in the opponent’s favor, the opponent may then bend the rule further, until the relative status of the pair is reversed. However, if the dominant starts to respond forcefully, there is still time for the opponent to back down before the encounter escalates into a serious fight. Many primates and carnivores that have affiliative signals that can be used to indicate playful intention may have a capacity for greater flexibility along this playful–serious gradient, as such signals can be used to diffuse unwanted escalations (see Bekoff, 1995; Boulton, 1994; Pellis & Pellis, 1996, 1997). What all these social uses of play fighting have in common is that they involve assessment and manipulation of the partner. As such, they are consistent with evolutionary game theory models that show that if an animal can assess the opponent’s fighting ability relative to its own, potentially damaging fights can be avoided (Parker, 1974). The benefits derived from such assessment could thus have been the selective advantage for the evolution of play fighting as a social tool in rats and other mammals. What the present analysis offers is a window into the causal mechanisms that make such an assessment possible. Furthermore, given the cognitive demands associated with such functions, the question arises as to whether play in the juvenile phase is organized so as to facilitate the development of these skills.

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IMPLICATIONS FOR OUR UNDERSTANDING OF THE PLAY OF JUVENILES All muroid rodents studied thus far appear to have a form of play fighting that resembles the species-typical patterns of adult precopulatory behavior (Pellis, 1993). The resemblance is in both the body targets attacked and in the defensive maneuvers that are used to block these attacks. During postweaning development, these playful interactions grow increasingly like the adult sexual encounters (Pellis & Pellis, 1998b). The rat, however, exhibits a strikingly different developmental pattern. Although in the rat the target competed over during play fighting is the same as for sexual encounters (Pellis & Pellis, 1987), the pattern of defense differs. During sexual encounters the female rat primarily evades the male’s contact, while during play fighting the attacked partner does so in only 20–25% of contacts (Pellis & Pellis, 1987). Moreover, the form of the contact promoting defense also differs. During precopulatory encounters, female rats rarely flip over onto their backs (<10%), typically doing so only when mounted (work in progress). However, during play fighting, juvenile rats flip over onto their backs in response to more than 50% of contacts. With the onset of puberty, the males switch to partially rotating their body axes and pushing the attacker with their flanks (Pellis & Pellis, 1987, 1990). When play fighting emerges before weaning, the predominant pattern of defense is the same as that seen in postpubescent male rats—the partially rotated defense. This is striking because the partially rotated defensive posture requires the rat to shift its body weight backward onto its hind feet and to balance its forequarters in a horizontal, cantilevered position, a feat of postural coordination beyond the capacity of preweanling rats, which typically fall over. In the days following weaning, the full rotation to supine defensive tactic becomes predominant (Pellis & Pellis, 1997) and remains so until puberty (Pellis & Pellis, 1990). Therefore, in rats, not only is the defensive component of play fighting different from that which is present in adulthood at all developmental stages, but the juvenile phase is also marked by a reversal of the pattern of defense initiated before weaning and regained at puberty (Pellis, 2002b). These highly structured developmental changes suggest that the play present in the juvenile phase is organized so as to maximize specific experiences. The question is, what are those experiences? When, in the juvenile phase, a rat is introduced to a partner following short-term social isolation (6–24 hours), there is an increase in the level of play relative to other social behavior, such as social investigation (Panksepp, 1981; Panksepp & Beatty, 1980; Pellis et al., 1997). Increasing the length of the isolation (1–2 weeks) also leads to a preferential increase in play (Varlinskaya, Spear, & Spear, 1999), but such longer-term deprivation also results in long lasting deficiencies of social behavior in adulthood (Hol, van den Berg, van Ree, & Spruijt, 1999; van den Berg et al., 1999a). These deficits seem to be more in the motivation to engage in social behavior than in the ability to engage in appropriately sequenced bouts of the social interaction

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(van den Berg, van Ree, & Spruijt, 1999b). More prolonged social deprivation, lasting for all of the juvenile phase, leads to more generalized deficits in social and nonsocial behavior (DaSilva, Ferreira, Carobrez, & Morato, 1996; Einon, Morgan, & Kibbler, 1978). With regard to social and sexual behavior, these deficits appear to involve a reduced ability to respond to the movements of the partner (e.g., Larsson, 1978; Einon et al., 1978; Pellis, Field, & Whishaw, 1999). It is important to note that rats that have been socially isolated as juveniles have deficits in regulating the intensity of their defensive responses to social partners (Byrd & Briner, 1999; Potegal & Einon, 1989; van den Berg et al., 1999a) and to the stresses arising from such contact (Von Frijtag, Schot, van des Bos, & Spruijt, 2002). How, then, does wrestling, which arises from supine defense and leads to one partner standing on top and the other lying on its back (on-top/on-bottom), provide for the development of valuable social and nonsocial skills? When in this on-top/on-bottom configuration, the on-top rat has two ways of standing and thus supporting its weight (Foroud & Pellis, 2003). In both cases, the on-top rat stands on the on-bottom rat with its forepaws and uses them to restrain its partner’s movements. The difference between the two postures is in the placement of the hind paws. In the first posture, the on-top rat places its hind paws on the ground (see Figure 3.1e), whereas in the second posture the hind paws are placed on its supine partner’s body. However, in the latter case, the wriggling and squirming supine partner provides an unstable base; this makes it difficult for the on-top rat to maintain its balance and successfully restrain its supine partner. When the on-top/on-bottom configuration first appears, at about the time of weaning, the on-top rat adopts a more stable on-the-ground placement of its hind paws in approximately 80% of cases (Foroud & Pellis, 2002). This is true for puberty and thereafter (Foroud & Pellis, 2003). Surprisingly, during the juvenile phase, the rate of adopting the more stable placement declines to about 30–40% (Foroud & Pellis, 2002, 2003). This decline does not arise as a byproduct of the greater level of playfulness in the juvenile phase (Foroud & Pellis, 2002), nor is it dependent on social experience (Foroud, Whishaw, & Pellis, 2004). Rather, just as in the case of the pubertal switch to using the complete rotation tactic more often in the juvenile phase, the switch to the less stable on-top configuration appears to be a programmed pattern of development. However, there is a major consequence associated with adopting the less stable postural configuration—it facilitates the partner’s ability to counterattack and so gain the upper hand. The context of 22 role reversals from the ontop/on-bottom position in 11 pairs of male juvenile rats was analyzed. Role reversals arise when the on-bottom rat successfully counterattacks and reverses its position relative to its partner. In 70.5% of the role reversals, the ontop rat adopted the less stable postural configuration. That is, role reversals are significantly more likely when the on-top rat stands on its partner with its hind feet (sign test: X = 9, p < .05). Thus, by standing in the less stable position, the on-top rat increases its chances of losing the encounter, or perhaps,

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more accurately, increases the opportunity for allowing the partner to reciprocate the contact. These data show that the juvenile phase is peculiar not only because of the increase in the use of the supine defense by defenders (Pellis & Pellis, 1990, 1997), but also because of the change that occurs at this time in the behavior of the attacking partner (Foroud & Pellis, 2002, 2003). It is as if by combining an increased likelihood of rolling over to supine by the defender with an increased likelihood of standing on the supine partner by the attacker, the rats are exaggerating the possibility for reciprocation by placing themselves in a more disadvantageous position. This combination is unique to the juvenile phase. That is, when play fighting is at its most gentle (defense mostly involves rotation to supine and the on-top attacker mostly adopts the unstable standing position), it is at its most frequent. Conversely, when play fighting is at its most frequent, it is at its least rough (Figure 3.2). Not only may such an exaggerated reciprocation allow for an elevated level of play fighting to occur in the juvenile phase, but it also may provide the learning experiences useful for adults to make fine-grain judgments about themselves in relation to their conspecifics. The on-top/on-bottom configuration with the less stable standing posture provides an experience of continuous change. That is, the on-top rat must continuously recalibrate its own position because of the changes that occur in its stability. These changes arise from a combination of its own movements with those of its supine partner. But at what level of vigor in the supine animal’s squirming should the on-top animal increase or decrease its own vigor in

FIGURE 3.2. The developmental changes in “roughness,” as measured by whether the rats use the partial rotation defense tactic and adopt the stable on-top posture, are contrasted with the developmental changes in the frequency of play fighting in rats. During the infantile and adult phases, when the frequency of play fighting is low, play is rougher. In contrast, during the juvenile phase, when the frequency of play fighting is at its highest, play is less rough.

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its attempt to gain the advantage? By having to make these judgments in the context of having its own sensorimotor skills compromised, the rat may be learning to integrate cues from its own body with those of its partner and so, at the same time, be learning how to apply appropriate levels of force to a highly dynamic situation. Several lines of evidence support this possibility.

THE MODIFIED PATTERN OF PLAY FIGHTING IN JUVENILE RATS AS A TOOL FOR ENHANCING SOCIAL–COGNITIVE SKILLS We have shown that the rat is a species in which the adults use play fighting for various social functions and the juveniles have a highly modified form of play. This is not true for all species that play as juveniles (Pellis & Iwaniuk, 1999a). Most other rodents that have been studied do not use play fighting as adults. Indeed, the play fighting of these juveniles mimics that of the adulttypical context from which the play elements are derived (Pellis & Pellis, 1998b). Thus, for example, voles not only attack and defend the targets typical of sexual encounters when they play fight, but they also use the tactics of attack and defense with the same frequencies as are typical of adults (Pellis, 1993). Furthermore, species differences between voles, such as the use of these tactics during play fighting, are consistent with adult differences in the use of these same tactics in sexual encounters (Pellis & Pellis, 1998b). As has been noted, in rats, the discordance between the use of tactics in play fighting and their use in adult sexual encounters cannot be so explained. This implies that the play fighting present in extant species cannot be viewed as having the same content for all species. Rather, with the advent of novel functions, new control systems must have evolved so as to regulate the behavior appropriately (Pellis, 1993). Again, the rat provides some clues as to how such layering of functions and control systems may have evolved. Rats decorticated at birth engage in play as juveniles (Panksepp, Normansell, Cox, & Siviy, 1994; Pellis, Pellis, & Whishaw, 1992) and are able to follow the 50:50 rule. However, they fail to exhibit the juvenile reversal in complete and partial rotation. That is, they preferentially use the partial rotation tactic before weaning and on into adulthood (Pellis et al., 1992). Decorticated rats also fail to show the modulation of the on-top rat in its standing posture, in that at all ages they most frequently use the least stable position (Foroud et al., 2004). Furthermore, as adults, decorticates do not modulate their defensive tactics with a change in partner. Rather, they mostly use the partial rotation tactic whether confronted by a dominant or a subordinate pairmate (unpublished observations based on data collected in Pellis et al., 1992). These findings suggest that interacting with a partner using the 50:50 rule involves subcortical neural mechanisms, but that modulating the pattern of defense with age, or with different partners, involves cortical systems. Furthermore, we have found that these two forms of cortical modulation are, in themselves, dissociable. Although neonatal ablation of the prefrontal cortex

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does not disrupt the age-related modulation, it does appear to disrupt the relationship-based modulation (work in progress). We have also found that rats that are reared in isolation during the juvenile phase fail to exhibit the relationship-based modulation (work in progress). Given that the prefrontal cortex is not fully mature until puberty (van Eden, Kros, & Ulings, 1990)—that is, after the peak period of play in the juvenile phase—it is highly likely that this structure is involved in learning the subtle skills needed to assess and manipulate other rats during social interactions. The rat thus provides a basis for a model for the evolution of play fighting. As has been argued, for play fighting to occur, an animal must have the ability to use the 50:50 rule. As the neural control systems needed for this appear to be subcortical, they may provide the basis for commonality in the presence of such play in mammals, birds (Fagen, 1981), and, perhaps, reptiles (Burghardt, 1998).2 Most species that play fight do not exhibit the same range of elaboration of the 50:50 rule as do rats; most have only the basic, subcortical reciprocation mechanism. In rats, the developmental and partnerbased modifications of the 50:50 rule appear to involve additional cortical systems. Furthermore, cortical mechanisms appear to be needed to gain the cognitive benefits of such play (Pellis et al., 1992). Therefore, we predict that only species with a modified form of play, such as that which exists in rats, would suffer from cognitive deficiencies if deprived of play experience in the juvenile phase. Data from experiments by Einon and her colleagues appear to support this prediction. Rats, but not three other commonly used laboratory rodents, suffer long lasting cognitive deficits if socially isolated in the juvenile phase (Einon, Humphreys, Chivers, Field, & Naylor, 1981). Clearly, for a variety of species, there is a necessity for detailed comparisons of the organization, development, and functions of play fighting to be mapped against the effects of social isolation. Another aspect of the comparative distribution of play fighting is that even for species that have the additional rat-like mechanisms for modulating the 50:50 rule, the pattern of juvenile play experience is likely to vary with species-specific demands in the subtlety needed to modulate social interactions. We predict that the degree of rehearsal in moving along the 50:50 gradient should correlate with the degree of flexibility (and hence uncertainty) in adult social relationships. A preliminary comparison of the play fighting of two species of macaques suggests such a possibility (work in progress). Although the targets and tactics of the two species are the same, the magnitude of the deviations from the 50:50 rule that are tolerated before play fights are terminated differ. Whereas Japanese macaques (Macaca fuscata) tolerate only a narrow range of rule attenuation, in Tonkean macaques (Macaca tonkeana) the range is quite large. The social organization of Japanese macaques is rigidly hierarchical, with subordinates usually accepting punishment from a dominant. In contrast, the social hierarchy of Tonkean macaques is more relaxed, with subordinates likely to retaliate against transgressions by a domi-

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nant (Thierry, 2000). Thus, the need to assess subtle cues and to be more cognizant of the boundaries of manipulation is likely to be more important in Tonkean than in Japanese macaques. Individual differences also offer an opportunity to study the developmental, social, and neural processes that regulate reciprocity during play fighting. For example, some rats are more playful than others, and there are individual differences in regard to responsiveness to the movements of a partner. Some of these individual differences are related to endogenous levels of dopamine activity (Pellis & McKenna, 1992). A more striking example has been shown for populations of rhesus macaques (Macaca mulatta). About 5–10% of the juvenile males are hyperactive and impulsive. After a few playful interactions with these animals, other juveniles avoid further contact with them. It appears that because of their impulsiveness, their play quickly becomes rough, often escalating into serious aggression. These impulsive individuals have deficits in their serotonin metabolism (Suomi, 2002). Thus, both for rats and monkeys, individual differences in behavior can be linked to differences in the activity of particular neurochemical systems. In regard to behavior, the example of the rhesus monkeys (described earlier) serves to underscore the importance of following the rules governing play fighting so as to avoid escalation into full-blown aggression (Boulton, 1994). Also of relevance to the present discussion is the finding that rearing conditions with appropriate social experiences can attenuate the impulsiveness of these individuals (Suomi, 2002). These data thus reinforce the claim made here, that for mammals with at least the level of play organization that exists in rats, emotional and cognitive skills that are relevant to social behavior can be influenced by the experiences gained from play fighting as juveniles. The neural and comparative data presented here support the idea that when play fighting is used by adults for social assessment and manipulation, juveniles’ play fighting is modified so as to enhance the opportunity to maximize the experiences that refine the social–cognitive skills useful for adulthood. Rats show all facets of these combined changes—play is retained for adult purposes, the content of juvenile play is modified relative to that of preand postjuvenile play, and the addition of novel cortical mechanisms enable age- and context-specific modulation of the tactics of attack and defense, and thus of the 50:50 rule. Furthermore, there is evidence that during the juvenile phase, social experiences, such as those provided by play fighting, are critical for rats to learn how to modify their responses so as to take into account the movements of conspecifics (Pellis et al., 1999), and that such learning is dependent on cortical mechanisms (Pellis et al., 1992). As can be seen, there are, in rats, nonlearned, maturational changes that occur in the content of play fighting during development. Further, there appear to be neural mechanisms that permit learning to occur from the experiences arising from these changes in play. These changes may be present in a variety of species, including humans. Several lines of evidence support this suspicion.

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CONCLUSION The sequential use of attack and defense during play fighting ensures that the 50:50 rule is followed. Having the ability to modify the sequential pattern of use of these tactics to exaggerate the win:loss ratio either in the partner’s favor or in the performer’s favor provides a means for using play fighting as a tool for social assessment and manipulation. Social assessment and manipulation can occur in two seemingly opposite functional contexts: Play fighting can be used to maintain the status quo or to overturn the status quo. To maintain unchanging relationships, repeated play fights can reveal that no change in the win:loss ratio has occurred. That is, the relative advantage in play has remained unchanged. Such use of play fighting for the reinforcement of existing relationships has been described in a variety of species, including rats (Pellis, 2002a) and New World deer (Geist, 1981), and among familiar boys (Pellegrini, 1994, 1995). To change social relationships, repeated play fights can be used to alter the win:loss ratio. That is, the relative advantage to one of the participants is changed; this permits the one that is doing the testing to ascertain whether the partner is able to tolerate such a change; this may then provide the testing partner with an opportunity to reverse the current relationship. This use of play fighting, for testing and reversing existing relationships, has also been described in a variety of species, including rats (Pellis, 2002a), Old World deer (Geist, 1982), adolescent chimpanzees (Paquette, 1994), and boys in unstable social relationships (Pellegrini, 1994, 1995). The social–cognitive skills that enable play fighting to be used to assess and manipulate conspecifics are the ones that are probably of general use in social interactions. Most critically, these skills are the ones that enable animals to make subtle decisions about the correct course of action to take—an action that carefully straddles competition and cooperation so as to maximize the advantage to the performer. We have suggested here that the experiences gained by juveniles when play fighting can enhance the development of these skills in some species, such as rats. If, in this regard, humans are found to be similar to rats—and there is some evidence that they are (Pellegrini & Smith, 1998)— then it may be necessary to reconsider policies that prevent children, especially boys, from engaging in playful contests.

NOTES 1. The work described here is mostly based on domesticated Norway rats (Rattus norvegicus). Even though domestication can greatly modify developmental processes and behavior (Coppinger & Coppinger, 2001), the little evidence available from wild rats observed in free-living and captive conditions suggests that the basic patterns of play described for the domestic form are also present in the wild type (Boreman & Price, 1972; Robitaille & Bovet, 1976; Seward, 1945). 2. The origin of the 50:50 rule is beyond the scope of the present chapter, but it is likely to have arisen from the reciprocity needed for copulation to occur. That is, at its most primitive, play

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fighting may be a precocial expression of sexual behavior by juveniles (Kramer & Burghardt, 1998; Pellis, 1993).

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Pellis, S. M., Pellis, V. C., & McKenna, M. M. (1993). Some subordinates are more equal than others: Play fighting amongst adult subordinate male rats. Aggressive Behavior, 19, 385–393. Pellis, S. M., Pellis, V. C., & Whishaw, I. Q. (1992). The role of the cortex in play fighting by rats: Developmental and evolutionary implications. Brain, Behavior and Evolution, 39, 270–284. Potegal, M., & Einon, D. (1989). Aggressive behavior in adult rats deprived of playfighting experience as juveniles. Developmental Psychobiology, 22, 159–172. Robitaille, J. A., & Bovet, J. (1976). Field observations on the social behaviour of the Norway rat, Rattus norvegicus (Berkenhout). Biology of Behavior, 1, 289–308. Seward, J. P. (1945). Aggressive behavior in the rat: I. General characteristics: Age and sex differences. Journal of Comparative Psychology, 38, 175–197. Siviy, S. M., & Panksepp, J. (1987). Sensory modulation of juvenile play in rats. Developmental Psychobiology, 20, 39–55. Smith, L. K., Fantella, S.-L., & Pellis, S. M. (1999). Playful defensive responses in adult male rats depend on the status of the unfamiliar opponent. Aggressive Behavior, 25, 141–152. Smith, L. K., Field, E. F., Forgie, M. L., & Pellis, S. M. (1996). Dominance and age-related changes in the play fighting of intact and post-weaning castrated male rats (Rattus norvegicus). Aggressive Behavior, 22, 215–226. Smith, L. K., Forgie, M. L., & Pellis, S. M. (1998). Mechanisms underlying the absence of the pubertal shift in the playful defense of female rats. Developmental Psychobiology, 33, 147–156. Suomi, S. J. (2002). How gene–environment interactions can shape the development of socioemotional regulation in rhesus monkeys. In B. S. Zuckerman, A. F. Zuckerman, & N. A. Fox (Eds.), Emotional regulation and developmental health: Infancy and early childhood (pp. 5–26). New Brunswick, NJ: Johnson & Johnson Pediatric Institute, L.L.C. Thierry, B. (2000). Covariation of conflict management patterns across macaque species. In F. Aureli & F. B. M. De Waal (Eds.), Natural conflict resolution (pp. 106–128). Berkeley, CA: University of California Press. Thor, D. H., & Holloway, W. R., Jr. (1984). Social play in juvenile rats: A decade of methodological and experimental research. Neuroscience and Biobehavioral Reviews, 8, 455–464. van den Berg, C. L., Hol, T., van Ree, J. M., Spruijt, B. M., Everts, H., & Koolhaas, J. M. (1999a). Play is indispensible for an adequate development of coping with social challenges in the rat. Developmental Psychobiology, 34, 129–138. van den Berg, C. L., van Ree, J. M., & Spruijt, B. M. (1999b). Sequential analysis of juvenile isolation-induced decreased social behavior in the adult rat. Physiology and Behavior, 67, 483–488. van Eden, C. J., Kros, J. M., & Ulings, H. B. M. (1990). The development of the rat prefrontal cortex. In H. B. M. Ulings, C. G. van Eden, M. A. Corner, & M. G. P. Feenstra (Eds.), Progress in brain research: Vol. 85. The prefrontal cortex. Its structure, function and pathology (pp. 169–183). Amsterdam: Elsevier. Varlinskaya, E. I., Spear, L. P., & Spear, N. E. (1999). Social behavior and social motivation in adolescent rats: Role of housing conditions and partner’s activity. Physiology and Behavior, 67, 475–482. Von Frijtag, J. C., Schot, M., van des Bos, R., & Spruijt, B. M. (2002). Individual housing during the play period results in changed responses to and consequences of a psychosocial stress situation in rats. Developmental Psychobiology, 41, 58–69.

THE DEVELOPMENT Genetic and Environmental OF Factors AGGRESSION in Rhesus Monkeys

4 Genetic and Environmental Factors Influencing the Expression of Impulsive Aggression and Serotonergic Functioning in Rhesus Monkeys S TEPHEN J. S UOMI

This chapter is dedicated to the memory of Markku Linnoila, who passed away 5 years ago following a sudden recurrence of cancer. At the time of his death at age 50, Dr. Linnoila was the Scientific Director of the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and was clearly expanding an already extraordinary research career. I first met him more than 20 years ago; at that time he was a recently appointed laboratory chief in the NIAAA and I was being recruited from the University of Wisconsin to develop a new laboratory in a different institute of the National Institutes of Health (NIH), the National Institute of Child Health and Human Development (NICHD). Within minutes of being introduced to each other, we decided to form a longterm collaboration, wherein his laboratory would analyze cerebrospinal fluid (CSF) concentrations of monoamine metabolites collected from rhesus monkeys that would be reared in different physical and social environments at the new primate facility that was being developed in the Maryland countryside. Moreover, he proposed to provide postdoctoral support for my senior graduate student from Wisconsin, J. D. Higley, in order to maintain our collaboration. At that time I had no idea how unusual this collaboration was, given the tradition of intense competition for resources between the different institutes within the NIH. Higley is now a tenured scientist in the NIAAA, our collaborative efforts actually have expanded over the years, and although Markku is no longer with us, his remarkable vision and his spirit persist in full force. 63

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This chapter summarizes a program of research inspired by Linnoila that has focused on the development of excessive physical aggression in a subgroup of young male rhesus monkeys, with an emphasis on findings linking such patterns of behavior to an apparent deficit in central serotonin metabolism. I begin by describing the social organization of rhesus monkeys in natural settings and how aggression typically emerges and is subsequently socialized during the juvenile years. Next, I summarize evidence that demonstrates a striking association between excessive physical aggression and deficits in central serotonin metabolism for rhesus monkeys, as has been found in humans and other primate species. I then characterize the biobehavioral developmental trajectories of individuals prone to engage in inappropriate and excessive aggression and present evidence regarding the relative heritability of these phenomena. Next, studies of the long-term consequences of excessive aggression for monkeys growing up in free-ranging environments are examined, followed by a summary of the ubiquitous effects of differential early social rearing experiences. Finally, I present some recent findings demonstrating that allelic variation in a specific gene implicated in serotonin metabolism can have dramatically different developmental consequences for monkeys as a function of their early social rearing history.

SOCIAL ORGANIZATION, SOCIAL DEVELOPMENT, AND THE SOCIALIZATION OF AGGRESSION IN RHESUS MONKEYS The primate facility that was built by NICHD in the Maryland countryside near the town of Poolesville has enabled us to study rhesus monkeys growing up under conditions that simulate most basic aspects of their natural physical and social environments. In nature, rhesus monkeys reside in large social groups (troops) that can range in size from several dozen to several hundred individuals. Each troop is composed of several different female-headed families (matrilines) that each span several generations of kin, plus numerous immigrant males. This pattern of social organization derives from the fact that rhesus monkey females stay in the troop in which they were born for their entire lives, whereas virtually all rhesus monkey males emigrate from their natal troop around the time of puberty, usually in their 4th or 5th year of life, and most eventually join other troops. Rhesus monkey troops in nature are also characterized by multiple social dominance relationships, including distinctive hierarchies both between and within families, as well as a hierarchy among the immigrant adult males (Lindburg, 1971). Although male status superficially appears to be a function of relative tenure—that is, the longer a male has been living in the troop, the more likely he is to be high in rank—in point of fact male dominance status seems to be more a function of social skill in joining and maintaining coalitions, not only with other males but especially with high-ranking females in the troop (Berard,1989). In sum, the dominance status of a rhesus monkey de-

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pends not so much on how big and strong it is, but rather who its family and friends are—and the latter is clearly dependent on the development of complex social skills during ontogeny. Rhesus monkey infants spend virtually all of their initial days and weeks of life in physical contact with their biological mother, during which time they form a strong and enduring specific attachment bond with her. In their 2nd month of life, infant monkeys begin to explore their immediate physical and social environment, using their mother as a secure base to support such exploration (cf. Suomi, 1995). Over the next few months these infants spend increasing amounts of time engaging in extensive social interactions with other group members, especially peers. Social play with peers soon becomes their predominant social activity and remains so until puberty. During this time play interactions become increasingly gender-segregated and involve patterns of behavior that appear to simulate virtually all adult social activities, including various forms of aggression (Ruppenthal, Harlow, Eisele, Harlow, & Suomi, 1974; Suomi & Harlow, 1975). Aggression is a normal and necessary part of every rhesus monkey’s overall behavioral repertoire—indeed, most primatologists consider rhesus monkeys to be among the most aggressive of all primate species. Rhesus monkey aggression can range in intensity from mere facial threats and vocalizations to vigorous chases and actual physical attacks, including slapping, hitting, hair pulling, and biting with sufficient intensity to produce lasting tissue damage or even death. The capability for aggression is crucial for survival in the wild, not only from the standpoint of defending one’s self and offspring from predators and nonspecific competitors, but also in maintaining social order and enforcing the complex dominance hierarchies characteristic of all rhesus monkey troops. However, uncontrolled, unpredictable, and violent aggression within any troop could drive members apart and destroy it as a social unit. Therefore, aggression must be socialized—it must be minimized or at least largely ritualized in intragroup interactions, but it must also remain a viable response in order to counter external threats or other dangers. Socialization of aggression for young rhesus monkeys involves not only learning in which circumstances and toward what targets aggressive behavior might be appropriate, but also gauging the relative intensity of the attack or response called for and the appropriate time and means for terminating an aggressive bout or for avoiding it altogether. Indeed, learning whom not to attack, as well as how to moderate aggressive impulses, is as important in the socialization process as is honing one’s fighting skills. Aggression typically emerges in a rhesus monkey’s behavioral repertoire at about 6 months of age, and it initially appears in the context of rough-andtumble play (Symonds, 1978). Biting, hair pulling, wrestling, and other forms of physical contact are basic components of rough-and-tumble play directed toward peers, which occurs with increasing frequency among males in the second half of their first year of life and becomes the predominate type of play for the rest of their juvenile years (Harlow & Lauersdorf, 1974). Although

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some form of virtually all behavioral components of adult aggressive exchanges can be seen in the rough-and-tumble play bouts of young males, the intensity of such interactions is usually quite controlled and seldom escalates to the point of potential physical injury—if it does, the play bout is almost always terminated immediately, either via adult intervention or by one or more of the participants backing away themselves. The importance of these play bouts with peers for the socialization of aggression becomes apparent when one considers that rhesus monkey infants reared in laboratory environments that denied them regular access to peers during their initial months consistently exhibited excessive and socially inappropriate aggression later in life (e.g., Alexander & Harlow, 1966; Harlow & Harlow, 1969).

INDIVIDUAL DIFFERENCES IN AGGRESSION AND SEROTONIN METABOLISM Both laboratory and field studies of rhesus monkeys and other nonhuman primate species have reported striking individual differences in the levels and types of aggression exhibited by monkeys of like age and gender, especially when displayed in circumstances where the aggression is neither provoked nor socially appropriate (e.g., Bernstein, Williams, & Ramsay, 1983; Steklis, Brammen, Raleigh, & McGuire, 1985), much as has been the case in recent human surveys and clinical investigations (cf. Lahey, Moffitt, & Caspi, 2003). Over the past two decades numerous studies, including several by Linnoila (e.g., Linnoila, 1988; Linnoila, DeJong, & Virkkunen, 1989; Linnoila et al., 1983), of child, adolescent, and adult males who engaged in unusually and violently aggressive activities have reported links between such aggression and apparent deficits in serotonergic functioning, such that those aggressive individuals tended to have unusually low CSF concentrations of the primary central serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA). Given these findings from the human clinical literature and with the strong encouragement of Linnoila, my colleagues and I decided to test the so-called serotonin hypothesis (cf. Coccaro & Murphy, 1990) in the rhesus monkey colony. Accordingly, we collected and assayed CSF samples for concentrations of 5-HIAA from a cross-sectional sample of infant, juvenile, and young adult monkeys representing both genders and three different early-rearing backgrounds. We also had considerable background data regarding levels of aggression exhibited by monkeys of comparable age, gender, and rearing history, although nobody had previously put those two data sets together. When we then did so, what seemed striking was the degree to which differences in CSF 5-HIAA concentrations were inversely related to differences in the incidence of aggression, whether the comparison involved age, gender, or rearing condition differences. For example, infant monkeys display minimal levels of aggression, juvenile monkeys show some, typically in the context of play, and adolescents and young adults, especially males, tend to exhibit the highest levels of aggressive behavior for any age-gender subgroup. We found exactly the

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opposite to be true for 5-HIAA concentrations: Infants had the highest levels, juveniles’ concentrations were significantly lower, and postpubertal monkeys (especially males) had the lowest concentrations (Higley, Suomi, & Linnoila, 1990b). Equally striking was the finding that short-term longitudinal CSF 5HIAA data obtained from a subset of these monkeys, collected under vastly different environmental circumstances, revealed remarkable stability across both situations and individuals, suggesting a trait-like characteristic for the CSF 5-HIAA measure (Higley, Suomi, & Linnoila, 1990a). Given the findings, we began a concentrated effort to explore this apparently inverse relationship more fully in our Poolesville rhesus monkey population. A series of prospective longitudinal studies replicated and extended our basic findings from the initial cross-sectional analyses. We found that approximately 5–10% of our monkeys exhibited impulsive behavioral tendencies and general social incompetence. Males in this subgroup became involved in a disproportionate number of aggressive exchanges with other group members. Females in this subgroup typically engaged in fewer overt acts of physical aggression than those males, but more than most other females. They also were less likely to engage in positive affiliative behaviors such as social grooming. Monkeys in this subgroup also consistently had lower CSF 5-HIAA concentrations than their peers of like age and gender (Higley & Suomi, 1996).

DEVELOPMENTAL TRAJECTORIES FOR IMPULSIVELY AGGRESSIVE MONKEYS We now know that rhesus monkeys with chronically low CFS 5-HIAA concentrations typically begin to distinguish themselves from their peers in their early play interactions. This is especially true for low–5-HIAA males: They seem to lack the ability (or perhaps the motivation) to moderate their behavioral responses to playful initiations from peers, and by late childhood their rough-and-tumble play bouts often escalate into more serious aggressive exchanges. Not surprisingly, most of these males soon come to be avoided by those around them, and as a result they become increasingly isolated socially (Figure 4.1). Moreover, low–5-HIAA juvenile males often seem unable (or unwilling) to follow social rules inherent in rhesus monkey dominance hierarchies (Higley, Suomi, & Linnoila, 1996d). For example, they may directly challenge a dominant adult male, a foolhardy act that often leads to serious injury, especially when they seemingly refuse to back down or exhibit appropriate submissive behavior once defeat becomes obvious. Juvenile females with chronically low CSF 5-HIAA concentrations tend to exhibit low levels of social grooming, and although they are generally involved in fewer overtly aggressive acts than their male counterparts, they too tend to become relatively isolated socially as they are growing up, typically drifting to the bottom of the dominance hierarchy within their social group (Higley et al., 1996a).

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FIGURE 4.1. Aggressive male rhesus monkey.

Longitudinal studies (e.g., Higley, Suomi, & Linnoila, 1992) have demonstrated that individual differences in CSF 5-HIAA concentrations tend to be remarkably stable from infancy to early adulthood, despite steady and significant developmental decreases in overall CSF 5-HIAA concentrations throughout childhood and adolescence. Given this stability and the inverse relationship between CSF 5-HIAA concentrations and impulsive aggressiveness (cf. Higley et al., 1996d), it appears possible to predict an individual’s likelihood of becoming impulsively aggressive later in life from its CSF 5-HIAA values exhibited during infancy. Moreover, as previously noted, individual differences in CSF 5-HIAA concentrations remain relatively stable across a variety of both stressful and benign environmental circumstances, unlike most indices of central nervous system activity. These findings therefore suggest that the CSF concentration of 5-HIAA can serve as a marker of an individual’s propensity to engage in impulsively aggressive actions, even when assessed under circumstances in which no overt aggression is being displayed (Higley, Suomi, & Linnoila, 1991b). Recent research has shown that individual differences in impulsive aggressiveness and CSF 5-HIAA concentrations are also predictive of individual differences in the propensity to consume alcohol in a “happy hour situation.” Over the past decade Higley and his colleagues have developed an experimental paradigm in which group-living rhesus monkeys are given the opportunity to consume an aspartame-flavored 7% alcohol (ETOH) beverage, a nonalcoholic aspartame-flavored beverage, and/or plain tap water for

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daily 1-hour periods within their familiar social group (e.g., Higley et al., 1991a). Impulsive adolescent monkeys who have low CSF 5-HIAA concentrations tend to consume excessive amounts of alcohol when placed in this happy hour experimental paradigm (Higley et al., 1996c). Researchers have also demonstrated a significant relationship between degree of alcohol intoxication and serotonin transporter availability in these monkeys (Heinz et al., 1998).

GENETIC FACTORS AND STRAIN DIFFERENCES Several studies involving rhesus monkeys whose genetic backgrounds have been well characterized and who have been raised from birth in controlled laboratory environments have demonstrated significant heritability for individual differences in CSF 5-HIAA concentrations. One investigation compared paternal half-siblings (same father, different mothers, with no physical exposure to their biological father at any time) and unrelated individuals reared under identical conditions. Heritability analyses revealed significantly greater concordance of CSF 5-HIAA concentrations among same-gender paternal half-siblings than among unrelated same-sex control subjects matched for age and rearing history. Another study utilized cross-fostering procedures, in which infants were separated from their biological mothers within the first week of life and raised thereafter by an unrelated multiparous female. CSF concentrations for the cross-fostered infants, assessed at 6 and 18 months of age, more closely resembled the CSF 5-HIAA concentrations of their biological mothers than those of their foster mothers (Higley et al., 1993). These findings provide compelling (albeit indirect) evidence of heritable influences on central serotonin metabolism, as well as risk for the development of impulsive aggressiveness, in laboratory-reared rhesus monkeys. A completely different line of research linking low serotonin metabolism with impulsive behavioral tendencies originated from serendipitous observations by the personnel caring for and testing rhesus monkey infants in the Poolesville facility’s neonatal nursery. Our colony has had a self-sufficient breeding program since its inception; that is, we have not had to bring in any rhesus monkeys from outside sources in order to carry out our basic research program. All of our breeders were either born in the laboratory or were part of the original colony that had been moved to the Poolesville facility from the University of Wisconsin Harlow Primate Laboratory in the mid-1980s; all of the Wisconsin monkeys, in turn, were descendents of wild rhesus monkeys imported from India prior to 1971. In contrast, some other primate facilities at the NIH have imported rhesus monkeys from China over the past two decades. Anecdotal reports by researchers and animal caretaking staff alike have suggested that rhesus monkeys of Chinese origin were unusually aggressive, difficult to train, and otherwise generally intractable. One NIH laboratory using rhesus monkeys imported from China was

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carrying out contraception research; because that laboratory lacked nursery facilities, unwanted infants that were the product of contraceptive failures were sent to us to be raised in our neonatal nursery. Maribeth Champoux, who oversees the nursery research and caretaking staff, soon noticed that those infants with parents of Chinese origin were unusual in several respects, not the least of which was their tendency to bite nursery staff while being hand-fed during their first week of life, a phenomenon we had never previously experienced with our own infants. Champoux subsequently tested other Chinese-origin infants with the lab’s standardized neonatal test battery and found significant deficits in their activity state control and their visual orienting capabilities during their first month of life, relative to the normative standards established for infants whose parents came from the lab’s breeding colony (Champoux, Suomi, & Schneider, 1994). CSF samples were obtained from Chinese-derived infants throughout their first 6 months of life, and their CSF 5-HIAA concentrations were compared with those of the lab’s Indian-derived infants. The Chinese-derived infants were found to have significantly lower CSF 5-HIAA concentrations from 3 to 4 months onward (Champoux, Higley & Suomi, 1997). Moreover, behavioral observations of these youngsters of Chinese origin revealed higher frequencies of impulsive and aggressive behaviors during their first 2 years of life than those observed in like-reared peers born into the lab colony (followup observations are currently under way). In addition to providing an empirical basis for insights based on anecdotal observations, these studies comparing Indian- and Chinese-derived infants established a predictive relationship between measures of basic biobehavioral characteristics during the neonatal period and patterns of serotonergic function and behavioral tendencies later in life.

FIELD STUDIES Given that low CSF 5-HIAA is associated with a host of behavioral tendencies throughout development that seem, at best, problematic for rhesus monkeys maintained in captive environments, a reasonable question is whether similar phenomena can be found in wild populations of rhesus monkeys—and if so, what the adaptive consequences for such individuals might be. Through Linnoila’s good offices, we established a collaboration with David Taub and Patrick Mehlman, and more recently continued with Greg Westergaard, that gave us access to a free-ranging population of approximately 4,000 rhesus monkeys that have been living for many years on Morgan Island, a sea island on the South Carolina Atlantic coast. These monkeys are provisioned but receive no special veterinary treatment, and except for periodic trapping of specified individuals for biological sampling, these monkeys are not subject to any experimental interventions. Analyses of CSF samples obtained from free-ranging juvenile, adolescent,

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and adult male rhesus monkeys residing on this sea island found 5-HIAA concentrations closely resembling those obtained from males in the Poolesville colony in terms of absolute values, age-related differences, and stability of individual differences across repeated sampling and across major developmental transitions (e.g., natal troop emigration). Moreover, the strong inverse relationship between CSF 5-HIAA concentrations and the rate of escalating aggression consistently reported in laboratory studies was at least as strong in this field population of rhesus monkey males and, similarly, first appeared in the context of play with peers. Like their captive counterparts, these wild rhesus monkey juveniles with low CSF 5-HIAA concentrations frequently turned routine rough-and-tumble play bouts into episodes involving serious aggressive exchanges, and they were also more likely to commit obvious social blunders that typically elicit physical attacks from larger and more socially dominant troop members (Higley et al., 1992a). Juvenile males with low CSF 5HIAA concentrations were also more likely to take long, potentially dangerous leaps from treetop to treetop, sometimes falling to the ground and injuring themselves. We found a significant inverse linear relationship between the relative frequency of such leaps and CSF 5-HIAA concentrations that paralleled the negative relationship between CSF 5-HIAA values and the incidence of escalating aggression (Mehlman et al., 1994; Figure 4.2). The long-term outlook for young rhesus monkey males with low CSF 5HIAA concentrations is not very promising in free-ranging environments such as Morgan Island. Ostracized by their peers and frequently attacked by adults of both genders, most of these young males are physically driven out of their

FIGURE 4.2. Impulsive juvenile male monkey taking dangerous leap.

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natal troop prior to 3 years of age, long before the onset of puberty (Mehlman et al., 1995). These impulsive young males generally lack the social skills to be able to join another troop; indeed, they even seem unable to join an all-male gang. As a result, most of these males become solitary, and virtually all of them perish within a year, long before becoming physically capable of reproduction (Higley et al., 1996b). Given the previously noted finding that individual differences in CSF 5HIAA concentrations appear to be highly heritable, along with the fact that most male rhesus monkeys with unusually low CSF 5-HIAA concentrations fail to survive to reproductive age, one might reasonably ask how it could be possible for as many as 10% of rhesus monkeys in wild populations to have chronically low CSF 5-HIAA concentrations. Three possible explanations readily come to mind. One possibility is that the few males with low CSF 5HIAA that do survive to adulthood sire a disproportionately large number of offspring (the “silver bullet” hypothesis). Recent observational data obtained from the Morgan Island population suggest that this hypothesis is exceedingly unlikely. In point of fact, the low CSF 5-HIAA males who do survive tend to be actively avoided by most females. In the few circumstances in which consort behavior with a female actually occurs, those males tend to engage in fewer mounts per copulatory sequence (rhesus monkeys are serial mounters), are less likely to ejaculate before the sequence is terminated, and have a lower probability of inseminating the females when they do ejaculate than do other males in the population (Mehlman et al., 1997). A more plausible possibility is that the propensity for developing chronically low central serotonin metabolism is passed on to the next generation of rhesus monkeys primarily through the female, rather than the male, genome. Young female rhesus monkeys with low–5-HIAA concentrations are indeed impulsive and aggressive and tend to be generally incompetent socially (Westergaard et al., 2003). Unlike males, however, they are not expelled from their natal troop but instead remain in their respective families for the rest of their lives. Moreover, they engage in relatively normal reproductive behavior, and they clearly produce and rear offspring—offspring that therefore may well be at increased genetic risk for low CSF 5-HIAA concentrations.

EFFECTS OF DIFFERENTIAL EARLY SOCIAL EXPERIENCE A third possible mechanism for cross-generational transmission of deficits in serotonergic functioning is derived from recent studies of maternal behavior in captive rhesus monkey groups. We have found that females with chronically low CSF 5-HIAA concentrations tend to exhibit significant abnormalities in their maternal behavior, often resulting in the development of insecure and/or disorganized attachment relationships with their infants. Other recent data suggest that infants who develop the least secure attachment relationships with their mothers are also the most likely to develop deficits in their central

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serotonin metabolism (cf. Suomi, 1999). Thus, an alternative possible means of cross-generational transmission of the propensity for having chronically low CSF 5-HIAA concentrations may be via aberrant maternal care, or other forms of social stimulation, that offspring might experience during development. According to this view, the mother’s behavior toward offspring may be more relevant for cross-generational transmission of the phenomenon than her genes. Of course, these two potential pathways are not necessarily mutually exclusive (Suomi & Levine, 1998). In fact, an increasing body of data from laboratory studies of monkeys reared under different social circumstances has demonstrated that early social experiences can profoundly affect both the development of impulsive aggressive tendencies and central serotonin metabolism alike. Some of the most compelling findings have come from longitudinal studies of peer-reared monkeys, that is, infants that were permanently separated from their mothers at birth, hand-reared in the neonatal nursery for their first month of life, and then placed in small social groups with like-reared age mates (cf. Harlow & Harlow, 1969). In most of the relevant studies the peer-reared subjects were moved into larger social groups containing both peer-reared and motherreared age mates at 7 months of age, and they remained in these larger social groups at least until puberty, if not beyond (e.g., Higley & Suomi, 1996). During their initial months these infants readily developed strong social attachment bonds to each other, much as mother-reared infants develop attachment relationships with their own mothers. However, because peers are not nearly as effective as a normal monkey mother in reducing fear in the face of stress or in providing a secure base for exploration, the attachment relationships that these peer-reared infants developed were almost always “anxious” or “insecure” in nature (Suomi, 1995). As a consequence, whereas the peer-reared monkeys exhibited relatively normal physical and motor development, their early exploratory behavior was somewhat limited. They seemed reluctant to approach novel objects, and they tended to be shy in their initial encounters with unfamiliar peers. Moreover, even when peer-reared infants interacted with their same-age cage mates in familiar settings, their emerging social play repertoires were generally retarded in both frequency and complexity. For example, peer-reared monkeys were more likely to play with only one partner at a time rather than with multiple partners simultaneously, as mother-reared youngsters quickly come to prefer, and their play bouts were usually limited to relatively brief exchanges rather than the extended interactions that may go on for several minutes at a time among mother-reared peers. One explanation for the relatively poor play performance of peer-reared monkeys is that their cage mates had to serve both as attachment objects and as playmates, a dual role that neither mothers nor mother-reared peers have to fulfill. Perhaps as a result, they typically dropped to the bottom of their respective dominance hierarchies when they were eventually grouped with mother-reared monkeys their own age (Higley et al., 1996d).

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Early peer-rearing also tended to make young rhesus monkey males more impulsive. Like the previously described impulsive monkeys growing up in the wild, peer-reared males initially exhibited aggressive tendencies in the context of juvenile play; and as they approached puberty, the frequency and severity of their aggressive episodes exceeded that of mother-reared group members of similar age. Peer-reared females tended to groom (and be groomed by) others in their social group less frequently and for shorter durations than their mother-reared counterparts and, as before, they usually remained at the bottom of their respective dominance hierarchies. These differences between peerreared and mother-reared age mates in aggression, grooming, and dominance continued to be relatively robust when the monkeys were subsequently moved into new social groups, and they generally remained quite stable throughout the juvenile and adolescent years. An important finding was that early peer-rearing was also associated with diminished central serotonin metabolism throughout development. Significant group differences between peer-reared infants and their mother-reared counterparts appeared within the first month of life, and these differences were maintained throughout the rest of the 7-month period of differential rearing, even though CSF 5-HIAA concentrations dropped dramatically for both rearing groups during this period. Moreover, peer-reared subjects continued to have significantly lower CSF 5-HIAA concentrations than their motherreared counterparts after they were moved into the same large social groups, and these differences persisted through puberty. Finally, peer-reared adolescent monkeys consistently consumed larger amounts of alcohol under comparable conditions than their mother-reared age mates (Higley, Hassert, Suomi, & Linnoila, 1991a). Follow-up studies also demonstrated that the peer-reared subjects quickly develop a greater tolerance for alcohol, which can be predicted by their CNS serotonin turnover rates, which in turn appear to be associated with differential serotonin transporter availability (Heinz et al., 1998).

GENE–ENVIRONMENT INTERACTIONS The previously described association between turnover rate and serotonin transporter availability led Markku Linnoila to help us establish a collaboration with Peter Lesch at the University of Wurzburg. Lesch and his colleagues recently characterized the serotonin transporter gene (5-HTT), a candidate gene for impaired serotonergic function in that it mediates serotonin neurotransmission, plays a critical role in brain serotonin homeostasis, and is a target for both selective serotonin reuptake inhibiting (SSRI) antidepressant compounds and certain drugs of abuse (Lesch et al., 1996). They have shown that length variation in the 5-HTT gene-linked polymorphic region (5-HTT-LPR) results in allelic variation in 5-HTT expression. The short allele of the 5-HTTLPR confers low transcription efficiency to the 5-HTT gene promoter, and lower 5-HTT mRNA levels are found in humans with the short allele, suggest-

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ing that the low 5-HTT expression may result in decreased serotonergic function (Heils et al., 1996). Although this genetic polymorphism was first detected in humans, it also appears in rhesus monkeys and, in fact, is found uniquely among simian primates and humans (Lesch et al., 1997). We recently have characterized a total of 237 rhesus monkeys in our Poolesville colony using polymerase chain reaction (PCR)-based genotype analysis in order to determine allelic frequency involving the short (398bp) and long (419bp) PCR fragments in the promoter region of the 5-HTT gene. These analyses revealed that the relative frequency of the homozygous long allele (LL) was approximately three times that of the relative frequency of the heterozygous short allele (LS). Curiously, only two subjects in the entire sample had the homozygous short allele (SS). However, among the 237 monkeys that were genotyped, 34 were of Chinese descent or were Chinese–Indian hybrids, and among these monkeys the relative frequency of the LS allele was more than twice as high (55% vs. 23%) as it was for monkeys of exclusively Indian origin. Moreover, consistent with our previous findings, as a group the Chinese/hybrid monkeys had significantly lower concentrations of CSF 5HIAA than their Indian-derived counterparts when age and gender factors were statistically partialled out. The suggestion that these subgroup differences in 5-HIAA concentrations, not to mention the behavioral differences described earlier, might be in part attributable to strain differences in the relative frequency of 5-HTT genetic polymorphisms represents an attractive, albeit as yet unproven, hypothesis. Some of the monkeys in the previously described Indian-derived subgroup had been peer-reared, whereas others had been reared by their biological mothers since birth. We found that the relative frequency of subjects possessing the short 5-HTT allele did not differ significantly between the two rearing groups, which was not surprising given that these monkeys had been more or less randomly preassigned to their respective rearing conditions at birth. Because we had collected CSF samples from those monkeys during their 2nd and 4th years of life under comparable experimental conditions (and while they were all living in comparable social groups), it was possible to determine whether their 5-HIAA concentrations differed as a function of their 5-HTT polymorphic status, as might be expected from the extant literature. Interestingly, we did find such a predicted relationship, with individuals possessing the LS allele having significantly lower 5-HIAA concentrations—but only among peer-reared subjects. For mother-reared subjects, 5-HIAA concentrations were essentially identical (and well within the normative range) for monkeys possessing either allele (Bennett et al., 2002; see Figure 4.3). Thus, these analyses demonstrated a significant genotype–environment interaction, wherein the ultimate effect of a polymorphism in a specific gene for a given individual appeared to be highly dependent on the specific early experience of that individual. In this case, mother-rearing appeared to buffer the infants from potentially deleterious effects of the LS allele on serotonin metabolism.

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FIGURE 4.3. CSF concentrations of 5-HIAA in peer-reared LL, peer-reared LS, mother-reared LL, and mother-reared LS monkeys. The gene x rearing environment interaction is the result of significantly lower CSF 5-HIAA concentrations in peer-reared LS monkeys than the other three subject groups. From Bennett et al. (2002).

A different form of gene–environment interaction was suggested by the analysis of alcohol consumption data: Whereas peer-reared monkeys with the LS allele consumed more alcohol than peer-reared monkeys with the LL allele, the reverse was true for mother-reared subjects, with individuals possessing the LS allele actually consuming less alcohol than their LL counterparts (Bennett, Lesch, Heils, & Linnoila, 1998). A similar reversal was found for relative levels of alcohol intoxication (Barr et al., 2004). In other words, the LS allele was a risk factor for excessive alcohol consumption among peer-reared monkeys but was apparently a protective factor for mother-reared subjects. We are currently carrying out additional analyses involving other behavioral and physiological measures that had already been collected on these same mother- and peer-reared monkeys of known 5-HTT allelic status. For example, Champoux et al. (2002) examined the relationship between early rearing history and 5-HTT allelic status on measures of neonatal neurobehavioral development during the first month of life and found further evidence of maternal buffering. Specifically, infants possessing the LS allele who were being reared in the laboratory neonatal nursery showed significant deficits in measures of attention, activity, and motor maturity relative to nurseryreared infants possessing the LL allele, whereas both LS and LL infants who were being reared by competent mothers exhibited normal values for each of these measures. Other analyses (e.g., Barr et al., 2003) have yielded similar gene–environment interactional patterns of apparent maternal buffering of aggressive behavior. We believe that this buffering pattern will prove to be ubiquitous across a wide range of measures of rhesus monkey behavioral and biological functioning throughout development.

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SUMMARY AND PERSPECTIVES This chapter has outlined a program of research investigating the development of excessive and socially inappropriate aggression in a subgroup of rhesus monkeys, biological correlates, and factors that can shape such development. The chapter described how aggression is typically socialized during the infant and juvenile years and contrasted this developmental pattern with that of the subgroup of individuals who consistently exhibit such aggression, as well as other behavioral manifestations of impulsivity and consistent deficits in a measure of central serotonin metabolism. These biobehavioral patterns emerge early in development, are maintained through puberty if not beyond, and are at least in part heritable. Male monkeys that develop these patterns in nature seldom survive beyond puberty, whereas females developing parallel patterns of inappropriate aggression and serotonergic dysfunctioning usually survive to bear and rear offspring—unfortunately, often in less than optimal fashion. Early rearing experiences can clearly influence the development of these biobehavioral patterns, even those with demonstrated heritability. Indeed, it appears that genetic and early experiential factors can and do interact to shape individual developmental trajectories. In particular, good mothering appears to somehow protect offspring at genetic risk for developing problems in behavioral and biological functioning when they are reared in less socially supportive settings (see Figure 4.4). My colleagues and I believe that the implications of these most recent findings are of considerable importance in a variety of domains. Beyond demonstrating that whether or not a particular genetic polymorphism has specific biobehavioral consequences may depend on certain early experiences, the present findings readily suggest several potentially promising avenues for future studies of impulsive aggressiveness in monkeys. One approach would be to become increasingly molecular in scope, focusing on demonstrations of specific gene expression, as well as delineating possible mechanisms by which specific early rearing experiences might trigger and/or otherwise influence gene expression. Indeed, this approach is currently being followed in an elegant program of research with rodents by Meaney and his colleagues (cf. Francis, Champagne, Liv, & Meanen, 1999). A second approach might focus on determining the generality of this and other types of gene–environment interaction with respect to other genes associated with particular human psychopathologies, as an increasing number of candidate genetic polymorphisms become identified and functionally characterized. Recently, Caspi et al. (2002) reported a specific gene–environment interaction involving a polymorphism in one monoamine oxidase A (MAOA) receptor gene and adverse early social experiences across a large cohort of adolescents and young adults in New Zealand. Individuals who possessed one form of the polymorphism were disproportionately likely to have been seriously involved in the juvenile justice system, but only if they had been abused

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FIGURE 4.4. Rhesus monkey mothers, each holding an infant.

as children. We have basically replicated the overall pattern of these findings in our Poolesville rhesus monkey colony in a very recent study focusing on a functionally similar MAOA polymorphism (Newman et al., in press), and we are currently examining potential gene–environment interactions, as well as possible gene–gene interactions, in several other candidate genes. A third possible avenue for study involves identifying potentially optimal rearing environments that might serve to minimize the risk for developing psychopathology, or actually turn that risk into a potentially adaptive advantage. For example, we are currently in the middle of a cross-fostering experiment, in which infants selectively bred to have low versus high CSF 5HIAA concentrations are being foster-reared by mothers who differ systematically in their own CSF 5-HIAA concentrations. We are also studying the maternal behavior of females with chronically high versus low CSF 5HIAA concentrations at the Morgan Island field site, with the goal of determining the long-term adaptive consequence for offspring of differing genotypes. It is truly unfortunate that Markku Linnoila is no longer with us to help advance these endeavors. I think he would have been pleased with what has been found to date, and I’m certain he would be eager to press onward in the effort he urged us to begin so many years ago—using research with rhesus monkeys to better understand the basis for the relationship between serotonergic functioning and the expression of impulsive aggression in humans throughout development.

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REFERENCES Alexander, B. K., & Harlow, H. F. (1966). Social behavior of juvenile rhesus monkeys subjected to different rearing conditions during the first 6 months of life. Zoologia Jahrb Physiologia, 60, 167–174. Barr, C. S., Newman, T. K., Becker, M. L., Parker, C. C., Champoux, M., Lesch, K. P., Goldman, D. A., Suomi, S. J, & Higley, J. D. (2003). The utility of the non-human primate model for studying gene by environment interactions in behavioral research. Genes, Brain, and Behavior, 2, 336–340. Barr, C. S., Newman, T. K., Lindell, S. G., Champoux, M., Lesch, K. P., Suomi, S. J., Goldman, D. A., & Higley, J. D. (2004). Interaction between serotonin transporter gene variation and rearing condition in alcohol preference and consumption in female primates. Archives of General Psychiatry, 61, 1146–1152. Bennett, A. J., Lesch, K. P., Heils, A., &., Linnoila, M. (1998). Serotonin transporter gene variation, CSF 5–HIAA concentrations, and alcohol-related aggression in rhesus monkeys (Macaca mulatta). American Journal of Primatology, 45, 168–169. Bennett, A. J., Lesch, K. P., Heils, A., Long, J., Lorenz, J., Shoaf, S. E., Champoux, M., Suomi, S. J., Linnoila, M. V., & Higley, J. D. (2002). Early experience and serotonin transporter gene variation interact to influence primate CNS function. Molecular Psychiatry, 7, 118–122. Berard, J. (1989). Male life histories. Puerto Rican Health Sciences Journal, 8, 47–58. Bernstein, I. S., Williams, L., & Ramsay, M. (1983). The expression of aggression in Old World monkeys. International Journal of Primatology, 4, 113–125. Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Marin, J., Craig, I. W., Taylor, A., & Poulton, R. (2002). Role of genotype in the cycle of violence in maltreated children. Science, 297, 851–854. Champoux, M., Bennett, A. J., Shannonm C., Higley, J. D., Lesch, K. P., & Suomi, S. J. (2002). Serotonin transporter gene polymorphism, differential early rearing, and behavior in rhesus monkey neonates. Molecular Psychiatry, 7, 1158–1163. Champoux, M., Higley, J. D., & Suomi, S. J. (1997). Behavioral and physiological characteristics of Indian and Chinese-Indian hybrid rhesus macaque infants. Developmental Psychobiology, 31, 49–63. Champoux, M., Suomi, S. J., & Schneider, M. L. (1994). Temperamental differences between captive Indian and Chinese-Indian hybrid rhesus macaque infants. Laboratory Animal Science, 44, 351–357. Coccaro, E. M., & Murphy, D. L. (1990) Serotonin in major psychiatric disorders. Washington, DC: American Psychiatric Press. Francis, D. D., Champagne, F. A., Liu, D., & Meaney, M. J. (1999). Maternal care, gene expression, and the development of individual differences in stress reactivity. Annals of the New York Academy of Science, 896, 66–84. Harlow, H. F., & Harlow, M. K. (1969). Effects of various mother–infants relationships on rhesus monkey behaviors. In B. M. Foss (Ed)., Determinants of infant behaviour (Vol. 4, pp. 15–36). London: Metheun. Harlow, H. F., & Lauersdorf, H. E. (1974). Sex differences in passions and play. Perspectives in Biology and Medicine, 17, 348–360. Heils, A. Teufel, A., Petri, S., Stober, G., Riederer, P. Bengel, B., & Lesch, K. P. (1996). Allelic variation of human serotonin transporter gene expression. Journal of Neurochemistry, 6, 2621–2624. Heinz, A., Higley, J. D., Gorey, J. G., Saunders, R. C., Jones, D. W., Hommer, D., Zajicek,

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Lahey, B. B., Moffitt, T. E., & Caspi, A. (2003). Causes of conduct disorder and juvenile delinquency. New York: Guilford Press. Lesch, K. P., Bengel, D., Heils, A., Sabol, S. Z., Greenberg, B. D., Petri, S., Benjamin, J., Muller, C. R., Hamer, D. H., & Murphy, D. L. (1996). Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science, 274, 1527–1531. Lesch, L. P., Meyer, J., Glatz, K., Flugge, G., Hinney, A., Hebebrand, J., Klauck, S. M., Poustka, A., Poustka, F., Bengel, D., Mossner, R., Riederer, P., & Heils, A. (1997). The 5–HT transporter gene-linked polymorphic region (5–HTTLPR) in evolutionary perspective: Alternative biallelic variation in rhesus monkeys. Journal of Neural Transmission, 104, 1259–1266. Lindburg, D. G. (1971). The rhesus monkey in north India: An ecological and behavioral study. In L. A. Rosenblum (Ed.), Primate behavior: Developments in field and laboratory research (Vol. 2, pp. 1–106). New York: Academic Press. Linnoila, M. (1988). Monoamines and impulse control. In J. A. Swinkels & W. Blijeven (Eds.), Depression, anxiety, and aggression (pp. 167–172). Houten, The Netherlands: Medidact. Linnoila, M., DeJong, J., & Virkkunen, M. (1989). Monoamines, glucose metabolism, and impulse control. Psychopharmacy Bulletin, 25, 404–406. Linnoila, M., Virkkunen, M., Scheinin, M., Nuutila, A., Rimon, R., & Goodwin, F. K. (1983). Low cebrospinal fluid 5–hydroxyindoleacetic acid concentration differentiates impulsive from nonimpulsive violent behavior. Life Sciences, 33, 2609–2614. Mehlman, P. T., Higley, J. D., Faucher, T., Lilly, A. A., Taub, D. M., Vickers, J., Suomi, S. J., & Linnoila, M. (1994). Low cerebrospinal fluid 5–hydroxyindoleacetic acid concentrations are correlated with severe aggression and reduced impulse control in free-ranging nonhuman primates (Macaca mulatta). American Journal of Psychiatry, 151, 1485–1491. Mehlman, P. T., Higley, J. D., Faucher, I., Lilly, A. A., Taub, D. M., Vickers, J. M., Suomi, S. J., & Linnoila, M. (1995). CSF 5–HIAA concentrations are correlated with sociality and the timing of emigration in free-ranging primates. American Journal of Psychiatry, 152, 907–913. Mehlman, P. T., Higley, J. D., Fernald, B. J., Sallee, F. R., Suomi, S. J., & Linnoila, M. (1997). CSF 5–HIAA, testosterone, and sociosexual behaviors in free-ranging male macaques during the breeding season. Psychiatric Research, 72, 89–102. Newman, T. K., Syagailo, Y., Barr, C. S., Wendland, J., Champoux, M., Graessle, M., Suomi, S. J., Highley, J. D., & Lesch, K. P. (in press). Monoamine oxidase: A gene promoter polymorphism and infant rearing experience interact to influence aggression and injuries in rhesus monkeys. Biological Psychiatry. Ruppenthal, G. C., Harlow, M. K., Eisele, C. D., Harlow, H. F., & Suomi, S. J. (1974). Development of peer interactions of monkeys reared in a nuclear family environment. Child Development, 45, 670–682. Steklis, H. D., Brammen, G. L., Raleigh, M. J., & McGuire, M. T. (1985). Serum testosterone, male dominance, and aggression in captive groups of vervet monkeys (Cercopithecus aethiops sabacus). Hormones and Behavior, 19, 156–165. Suomi, S. J. (1995). Influence of Bowlby’s attachment theory on research on nonhuman primate biobehavioral development. In S. Goldberg, R. Muir, & J. Kerr (Eds.), Attachment theory: Social, developmental, and clinical perspectives (pp. 185–201). Hillsdale, NJ: Analytic Press. Suomi, S. J. (1999). Attachment in rhesus monkeys. In J. Cassidy & P. R. Shaver (Eds.),

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Handbook of attachment: Theory, research, and clinical applications (pp. 181– 197). New York: Guilford Press. Suomi, S. J., & Harlow, H. F. (1975). The role and reason of peer friendships. In M. Lewis & L. A. Rosenblum (Eds.) Friendships and peer relations (pp. 310–334). New York: Basic Books. Suomi, S. J., & Levine, S. (1998). Psychobiology of intergenerational effects of trauma: Evidence from animal studies. In Y. Daniele (Ed.), International handbook of multigenerational legacies of trauma (pp. 623–637.) New York: Plenum Press. Symonds, D. (1978). Play and aggression: A study of rhesus monkeys. New York: Columbia University Press. Westergaard, C. G., Suomi, S. J., Chavanne, T. J., Houser, L., Hurlye, A. C., Cleveland, A., Snoy, P., & Higley, J. D. (2003). Physiological correlates of aggression and impulsivity in free-ranging female primates. Neuropsychopharmacology, 28, 1045– 1055.

THE DEVELOPMENT Physical Aggression in Humans OF AGGRESSION

5 The Developmental Origins of Physical Aggression in Humans R ICHARD E. T REMBLAY and D ANIEL S. N AGIN

We here saw the native Fuegan; an untamed savage is I really think one of the most extraordinary spectacles in the world.—the difference between a domesticated & wild animal is far more strikingly marked in man . . . with difficulty we see a fellowcreature. —DARWIN (1832/1985, pp. 302–303)

The aim of this chapter is to summarize our present knowledge on the development of physical aggression from early childhood to adulthood, and to discuss the mechanisms that could explain this development. We define physical aggression as the use of physical force against another person with an object (e.g., stick, rock, bullet) or without (e.g., slap, push, punch, kick, bite). The verbs fight, assault, attack, and bully are often used to summarize the actions during a physical aggression. Antecedents and consequences can be used to subdivide this subcategory of aggressions (see Gendreau & Archer, Chapter 2, this volume). However, inasmuch as most developmental studies of physical aggression have not made these distinctions, we will generally refer to an overall category of physical aggression.

THE SOCIAL–HISTORICAL–PHILOSOPHICAL–MORAL CONTEXT OF RESEARCH ON THE DEVELOPMENT OF PHYSICAL AGGRESSION Physical aggression is a socially “hot” topic. An act of physical aggression can make the difference between life and death. Physical violence is omnipresent daily in the mass media of modern societies (Bushman & Anderson, 2001) in 83

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the same way that it is a constant preoccupation for animals living in the wild. Physical aggression is of concern as much to the health professionals (World Health Organization, 2002) as to the social–psychological well-being professionals (U.S. Human Capital Initiative, 1997). Concerted efforts to suppress physical aggression in human interactions is one of the major historical social transformations observed in countries of the Western world in the later part of the 20th century. A half-century ago, it was generally considered normal for elementary school teachers to physically punish students for spelling errors. Elementary school principals used leather straps to discipline disruptive students. Caning was still in use in English public and state schools. In other words, some forms of physical force against others were considered morally acceptable, and were even recommended. Note that in all of these examples an adult uses physical force against a child. Two learning specialists who spent their careers studying nonhuman primates conclude that physical punishment is the natural pedagogical tool (Premack & Premack, 2003). There is now a strong movement to make these practices criminal acts. Some go as far as to argue that parents should not take their children in their arms without asking the children for their permission. Zero tolerance has become the rule concerning physical aggression on the school playground, in the neighborhood, and at home, between spouses and between parents and children. Not using physical force against another human has become the hallmark of a civilized human. The difference in attitudes between 1950 and 2000 is certainly striking. But the difference is still more impressive when we compare late-20th-century attitudes to those of past centuries. Consider the educational practices in one of the great eras of the English public schools. When the 24-year-old Charles Darwin described to his sister the marked difference between “an untamed savage” and his civilized compatriots, the famous educationist and scholar Thomas Arnold had been appointed headmaster of Rugby for less than 4 years. Harold Nicolson (1955) writes that Arnold was convinced that the boys should be whipped to learn their moral responsibilities. To enforce his “muscular Christianity,” he organized a disciplinary system in which older boys ruled by fagging and by beating the younger boys. All accounts of 19thcentury English public schools indicate that bullying was not the exception but the rule. Nicolson cites the following description from Thackeray: “There are at this present writing 500 boys at Eton, kicked and licked and bullied by another 100” (1955, p. 263). Previous centuries were not less violent. Consider the general use of torture and homicide by kings and priests during the most civilized times of Erasmus, Luther, Galileo, Mozart, and Voltaire. Indeed, Eisner (2003) documents that homicide rates in western Europe declined 50- to 100-fold over the past 5 centuries. And what did the civilized Romans enjoy most on a nice leisurely afternoon? A bloody battle among gladiators and starved lions! From an evolutionary perspective, aggression is a solution to a problem (Archer, 1988). From a social, historical, and moral perspective, humans de-

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cide at different places and times which solutions are acceptable. Concerning the use of the word aggress, the American Heritage Dictionary (1985) says: “Though the verb aggress has a long and honorable history, it has lately come to be associated primarily with the jargon of psychology and is often objected to.” Indeed, there seems to have been much change in our attitudes toward the use of physical force by humans. But how deeply rooted is this change? The two world wars of the 20th century killed close to 30 million soldiers, Hitler managed to exterminate approximately 6 million Jews, and nearly 200,000 Japanese civilians were killed by two atomic bombs on Hiroshima and Nagasaki. The United States saw a huge increase in homicides and other violent crimes during the 1990s, mainly among adolescents and young adults (Blumstein & Wallman, 2000; McCord, Widom, & Crowell, 2001). On December 31, 2002, the number of persons in U.S. prisons was equivalent to approximately half the population of Norway (2 million), and a year earlier the richest country in the history of humanity had close to 70 prisoners waiting to be executed for crimes they committed before they were 18 years of age (Bureau of Justice Statistics, 2003; Steinberg & Scott, 2003). Planes are hijacked to destroy skyscrapers filled with thousands of people. We are still killing tens of thousands of people to gain control of a country, and in some European cities conflicts force children to go to school under the protection of the army. The physical violence described here victimizes millions of humans, but only a very small minority of the inhabitants of the wealthy countries will be among these victims. Paradoxically, this fortunate minority, who are less and less at risk of being physically aggressed by a parent, a teacher, a spouse, a neighbor, a stranger, or a soldier, are using a large part of their financial resources and leisure time to consume fictive depictions of physical violence on television, in movies, and in electronic games. This behavior of the most civilized humans in the history of humanity is certainly quite a puzzlement. But still more puzzling is the contrast between this strange addiction to fictive violence by humans who have been educated not to use physical violence, and the results of research published in the top scientific journals, which conclude that the more individuals look at physical violence, the more they become physically aggressive (Anderson & Bushman, 2002; Johnson, Cohen, Smailes, Kasen, & Brook, 2002). Thanks to modern technology, citizens of present-day industrialized nations have, during their lives, seen more physical aggressions causing death than any Roman who had a lifelong Coliseum season ticket. By what peculiar process are these hungryfor-physical-violence modern humans passing laws to eradicate physical violence from their daily lives?

THE AGE–VIOLENT CRIME CURVE Two important scientific committees published reports in the 1990s on the causes and prevention of violence. The U.S. National Research Council panel

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(Reiss & Roth, 1993) concluded that “modern psychological perspectives emphasize that aggressive and violent behaviors are learned responses to frustration, that they can also be learned as instruments for achieving goals, and that the learning occurs by observing models of such behaviors. Such models may be observed in the family, among peers, elsewhere in the neighborhood, through the mass media, or in violent pornography, for example” (p. 7, emphasis in original). Four years later the report of the U.S. Human Capital Initiative (1997) coordinating committee on reducing violence concluded: In short, watching violent movies and television shows year after year and listening to brutal lyrics set to throbbing music can change one’s attitudes about antisocial, aggressive behavior. In children it can lead to more aggressive behavior and also can evoke unwarranted fears and defensive actions. Whatever the violent content, movies and television exert powerful influences through visual imagery and dramatic characterizations; video games may have similar effects. (p. 12)

Figure 5.1 is a representation of the age-specific rate (per 100,000) of individuals arrested (United States) and accused (Canada) for violent offenses (physical aggressions) in 2001. It can be seen that violent offenses appear in preadolescence, increase sharply during adolescence, and then decrease slowly. If young humans learn to physically aggress by imitation of aggressions observed in the home, in the neighborhood, and in the media, the increase in physical violence during adolescence makes sense. The older they are, the more they have observed acts of physical aggression, and the more likely they are to do what they have seen. The beauty of these data is not only that they confirm the prevalent psychological theory, but they replicate the data that Adolphe Quetelet (1833), the Belgian astronomer/statistician, started collecting in the late 1820s. This was at the time Thomas Arnold was becoming headmaster of Rugby and Charles Darwin was a student at Cambridge. While Darwin was traveling around the world to catch beetles and observe volcanoes, the Belgian astronomer/statistician decided to quantify the physical, cognitive, and moral development of humans. The age–crime curve is probably the most robust criminological observation (see Sampson & Laub, 2003). However, if social learning explains the increase in physical violence during adolescence, it does not explain the decrease during adulthood. Quetelet, who was interested in moral development, but also in cognitive and physical development (he invented the Body Mass Index), used a biological explanation (intensity of physical strength and passions), which is close to the modern biological explanation that challenges the social learning hypothesis. The modern explanation is testosterone (see Ellis & Coontz, 1990; Harris, Rushton, Hampson, & Jackson, 1996; Tremblay et al., 1997; and Van Goozen, Chapter 14, this volume). T, as it is known by endocrinologists, has been shown to correlate with physical violence and not only increases substantially from early to late adolescence, but also decreases

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FIGURE 5.1. Age–crime curve in 2001 in the United States and Canada.

during adulthood, hence following the age–violent-crime curve. Testosterone has the added power to explain the sex difference in physical aggression. Indeed, T is the male hormone. Although the adrenal glands and ovaries of women produce T and this production increases during adolescence, the levels of T at the end of adolescence are 20 times higher in males than in females. From this perspective, in his explanation of the causes of antisocial behavior, Quetelet would have been closer to the truth than Jean-Jacques Rousseau, the most famous advocate of the theory of social learning as an explanation of bad behavior (Rousseau, 1762/1979). T feeds muscles and thus increases strength: the fuel for Quetelet’s strength and passion hypothesis.

AGGRESSION BEFORE PUBERTY The main problem with the age–violent-crime curve studies is that they focus on adolescents and adults. Criminologists have tended to neglect humans before the start of adolescence because they cannot be considered legally delinquent. Since Quetelet, at least, criminologists have fed on data produced by the legal system. Only very recently have they started to study precursors of criminal behavior before adolescence. Do humans physically aggress each other before the start of adolescence? The age–violent-crime curve figures give the impression that physical aggressions appear with the legal age for criminal

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responsibility as if lawmakers had chosen the age for criminal responsibility after detailed studies of child development. Those who decided to study elementary school children to understand the precursors of adolescent delinquency discovered that elementary school children use physical aggression before puberty increases their production of T, and before they have accumulated 12 or 13 years of social learning. The Columbia County Study, initiated in the state of New York in 1960, was one of the rare longitudinal studies of elementary school children specifically focused on aggression. More than 800 third-grade schoolchildren rated each other on different behavioral dimensions, including aggression, to test the social learning hypothesis. Following the analysis of the first wave of data when the children were 8 years old, the investigators gave the following summary of their findings: “It is fair to say that all the major findings of that analysis were consistent with the hypothesis that aggression may be learned by a child from his interactions with his environment” (Lefkowitz, Eron, Walder, & Huesmann, 1977, p. 37). Note that this was a conclusion drawn from cross-sectional data. Later analyses of data collected at ages 8, 19, and 30 revealed relatively high correlations between aggression assessments at these different points in time (Huesmann, Eron, Lefkowitz, & Walder, 1984). These results led Eron (1990), in his presidential address to the International Society for Research on Aggression in 1990, to conclude that aggression crystallizes at 8 years of age. Thus, the social learning of aggression would occur much earlier than the start of the age–violent-crime curve. But there were two important limitations with the Columbia County Study. First, the aggression scale used at age 8 should have been labeled a “disruptive behavior” scale (e.g., who does not obey the teacher, who gives dirty looks, who does things that bother others, who is always getting in trouble). Only 2 of the 10 items referred specifically to physical aggressions (who starts a fight over nothing; who pushes and shoves children). The second limitation is that the data collection points had 10-year gaps, making it impossible to study developmental trajectories. Fortunately, a similar U.S. study was initiated 20 years later and collected annual data on physical aggression. The Carolina Longitudinal Study followed 220 boys and girls from 4th to 12th grade and obtained assessments of physical aggression from the students and the teachers (Cairns & Cairns, 1994). Analyses of these data painted an unexpected picture in regard to the “social learning” and “testosterone” hypotheses. The information from teachers, as well as from students, showed a clear mean decrease in the frequency of physical aggression from 10 to 18 years of age, and this was true for males as well as for females (Cairns, Cairns, Neckerman, Ferguson, & Gariépy, 1989). How could longitudinal data from a population sample of American adolescents, living in a southern state, show a physical aggression curve exactly the reverse of the age–violent-crime curve? One explanation could be that although the majority of youth reduce the frequency of physical aggressions as they grow older, a minority are increasing

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their frequency of physical violence and are being processed through the legal system that generates the statistics for the age-crime curve. To test this hypothesis, we needed to go beyond a description of the mean developmental trajectories of a given sample and identify the different types of developmental trajectories that children were following. Nagin and Tremblay (1999) used a semiparametric mixture model with a longitudinal sample of more than 1,000 kindergarten boys in schools from low socioeconomic areas of Montreal to describe these different trajectories. Why use males from low socioeconomic areas to study the development of physical aggression? The answer can be found in the report “Reducing Violence” from the U.S. Human Capital Initiative (1997) coordinating committee: “Certain environmental conditions not only trigger violence, they can also seem to teach aggressive or violent behavior patterns. For example, poverty is associated with both sudden violent outbursts and long-term, habitual aggression” (p. 11). Results (Figure 5.2) from teacher ratings confirmed the North Carolina data. The large majority of boys from the poorest inner city areas of Canada were using physical aggression less frequently as they grew older. Only a very small group of boys (4%) did not show the declining trend; these were the boys who had the highest levels of physical aggression in kindergarten, which remained at the highest level until adolescence. When interviewed at ages 15 and 17, they were the boys who reported the highest frequency of physical violence and those the ones most frequently found guilty of infractions before

FIGURE 5.2. Physical aggression trajectories. From Nagin and Tremblay (1999). Copyright 1999 by the Society for Research in Child Development. Reprinted by permission.

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18 years of age. Thus, the increase in the age-crime curve during adolescence for physical aggressions would be produced by the fact that, during this period, the police and judicial system start arresting and convicting individuals who have been physically aggressing others at least since kindergarten. An international team of investigators replicated these finding using five other longitudinal studies in Canada, New Zealand, and the United States (Broidy et al. 2003).

AGGRESSION BEFORE SCHOOL ENTRY Figure 5.2 clearly shows that all the boys tended to be at their peak level in frequency of physical aggression at 6 years of age, when they were at the end of their kindergarten year. If this is the case, when do such children start to use physical aggression? Is the social learning of physical aggression occurring during the kindergarten year? Studies of preschool children suggest that if humans need to learn to physically aggress, the learning occurs before school entry. There is a long history of case studies of physical aggression in young children. One of the first publications of a “developmental origins of aggression” study appeared during the reign of the Roman Emperor Arcadius (A.D. 395–408). The 46-year-old Augustine of Thagaste (397/1960, p. 49), later known as St. Augustine, when writing his Confessions, realized that he could not remember his first sins. Instead of concluding, like Sigmund Freud, that he needed to “psycho-analyze” himself, he decided to observe babies, reasoning, in all humility, that they must be doing what he did at their age. Following these observations he writes: “Were these things good . . . [when] my parents, and many other prudent people who would not indulge in my whims, when I struck at them and tried to hurt them as far as I could because they did not obey orders that would be obeyed only to my harm?” One millenium and a half later, in the “Rage” section of the The Expression of the Emotions in Man and Animals, Darwin (1872, p. 243) wrote: “Every one who has had much to do with young children must have seen how naturally they take to biting, when in a passion. It seems as instinctive in them as in young crocodiles, who snap their little jaws as soon as they emerge from the egg.” Fifty-nine years after this other jewel by Darwin, two books were published by two women who pioneered 20th-century quantitative studies of early human social-emotional development. The two books used different methodologies. Katharine M. Bantham Bridges was a professor of psychology in the McGill department of psychology and a psychologist in the university’s nursery school. Her book (Bridges, 1931) presented social development and emotional development scales created by daily observations of 2–5-year-old children in the nursery school. One of her conclusions was that children, more than adults, were susceptible to anger expressed by physical aggression. Interestingly, 2 years later, she introduced a paper on the observation of 62 chil-

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dren, between 3 weeks and 2 years of age, by writing that “the trends of development” between 2 and 5 years of age described in her previous book “must have had their beginnings in early infancy” (Bridges, 1933, p. 36). Her 3month cross-sectional observation of infant interactions led her to the conclusion that by 1 year of age children start “to struggle slightly for possession” of objects, and by 15 months “aggressive attacks are indulged in at this stage for their own sake and are not out-grown till well after two years of age” (p. 48). At exactly the same time, Florence Goodenough (1931), a professor at the University of Minnesota Institute of Child Welfare, was studying anger in young children by asking “intelligent parents,” mostly college graduates, to keep records of their children’s anger outbursts during a 1-month period. Two children were not yet 1 year old (7 and 11 months), 9 were between 17 and 23 months, 13 were between 26 and 35 months, 10 were between 36 and 46 months, and the 11 others ranged from 53 to 94 months. One thousand eight hundred and seventy-eight anger outbursts were recorded, for a mean of approximately 1 outburst per 10 hours of observation. As shown in Figure 5.3a, the 17- to 23-month-olds had the highest mean, with 1.3 outbursts per 10 hours. Interestingly, data from a longitudinal study of temper tantrums reported by the mothers of a sample of 126 Belgian children at the end of the 1950s led to very similar results (Sand, 1966; Figure 5.3b). Goodenough and Sand specifically studied the frequency of physical and verbal aggressions during the angry outbursts. They both concluded that as they grow older, children use fewer physical aggressions. Goodenough specifically concluded that with age they attempt more often to hurt the feelings of others (see Vaillancourt, Chapter 8, this volume). An observational study of French children’s social interactions in daycare during the 1970s reported on the frequency of physical aggressions, as compared with other forms of social interactions, for children of different age groups (Restoin et al., 1985). A total of 30 hours of filmed interactions were coded. Results represented in Figure 5.3c show a trend that is very similar to those in parent reports in Figures 5.3a and 3b. The relative frequency of physical aggression increases from the first year after birth to the second, and then decreases. Holmberg (1977) also found that physical attacks increased from 12 to 30 months, and then decreased from 30 to 42 months, when she observed 16 boys and girls interacting with peers in the United States. Recently, similar results were obtained with parent reports in two large Canadian-based longitudinal and cross-sectional studies. From 9 months to 30 months of age the proportion of children who are reported to use physical aggressions increases substantially (Tremblay, 2004); in addition, the frequency of use appears to increase up to nearly the end of the third year after birth (Tremblay et al., 2004). This remarkable increase is then followed by a continuous decline in frequency (Côté Vaillancourt, LeBlanc, Nagin, & Tremblay, 2004; Tremblay et al., 1996). Clearly, the same general developmental picture is drawn whether we use data from different times (1920s, 1970s, or 1990s), data from different countries (Belgium, Canada, France or the United States), data from different re-

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FIGURE 5.3a. Frequency of anger outbursts for 10 hours of observation. Data from Goodenough (1931).

porting sources (filmed interactions in day care, parents’ detailed records, or parents’ recall of behavior in the past months), or data from different methodologies (cross-sectional or longitudinal, calculated as an absolute frequency over a given period of time, a relative percentage of social behaviors, a percentage of individuals using the behavior, or a general estimate of the frequency of the behavior). Frequency of anger outbursts and physical aggression increase rapidly from the first year after birth to approximately the third, and then the frequency decreases. Unfortunately, none of the longitudinal studies that started in early childhood have yet reported on physical aggression up to the end of adolescence. From the Restoin et al. (1985) data it appears that at the peak frequency of physical aggression in a day care environment, physical aggression represents one in four social interactions. This is certainly a high frequency of ag-

FIGURE 5.3b. Percentage of children reported to have a temper tantrum at least every day. Data from Sand (1966).

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FIGURE 5.3c. Relative frequency of aggressive behavior between peers from age 6 to 36 months in day care centers. Data from Restoin et al. (1985).

gressions, but even at the worst of times, there are more prosocial or neutral social interactions than there are physically aggressive ones. This can probably be said for any social group, whether it is composed of nonhuman primates (see de Waal, 2000; also see Suomi, Chapter 4, this volume) or Hell’s Angels. Social life would probably be impossible within a group where physical aggression is the most frequent form of social interaction. However, it does appear clear that most humans have used physical aggression before they reach 36 months of age, that humans use physical aggression most often between 18 and 42 months after birth, and that if humans are learning to physically aggress through imitation, this learning is happening in the first 2 years after birth, not by watching television and playing video games in middle childhood or adolescence. After many decades of training chimpanzees to use “language,” David and Ann Premack (2003, p. 72) wrote: “Biting, hitting, kicking, scratching, pushing are natural reactions to the offensive behavior of another individual. These require no training.”

CAUSES OF PHYSICAL AGGRESSION DURING EARLY CHILDHOOD The causes of physical aggression during early childhood can be considered from many different perspectives, both with reference to the sequence of events (e.g., proximal and distal causes) and with reference to the level of analysis (e.g., behavioral, psychological, physiological, genetic). For example, from the proximal perspective we can investigate the time, the place, and the events that appear to trigger physical aggression by an infant. We can also focus on the emotional characteristics of the child prior to, during, and after an agonistic interaction. Such investigations could target the external expression (e.g., facial expression) or the physiological expression (e.g., heart rate, cortisol levels).

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Most observers of proximal causes of physical aggressions by infants and toddlers have concluded that anger is the main “emotional” antecedent, and that this anger is provoked either by something that prevents the child from getting what he or she wants, or by a request for the child to do something he or she does not want to do (e.g., Bridges, 1933; Goodenough, 1931; Hay, Chapter 6, this volume). The most frequent situational “cause” of physical aggressions among young children is competition for desirable objects or space. Note that these motivations appear not very different from those that lead adult humans to war between countries, inasmuch as these tend to be instigated by competition over desirable resources (e.g., oil) or territories (e.g., for access to the sea). Thus, in humans, as in other species, from the beginning of life onward, the function of many instances of physical aggressions is competition for resources (see Archer, 1988). The developmental trajectories described earlier in this chapter do not help much in identifying proximal causes of physical aggressions, but they do help in understanding distal causes. The distal perspective tends to look for the mechanisms that are put in place over a long period of time and explains at least two different mechanisms: (1) how an individual acquires the ability to physically aggress and (2) why he or she tends to use this ability. For example, the social learning hypothesis appears to argue that a human who has never witnessed a physical aggression in his life could not use physical aggression, even when extremely angry, because he or she would not have “learned” to physically aggress. It is a very different argument from the one stating that infants do not need to learn to physically aggress, but the more they witness physical aggressions the more they are likely to use them when they become angry. The first part of the prior sentence refers to mechanism (1), and the second part refers to mechanism (2). The developmental data we have presented in this chapter appear to indicate that children do not need to have seen models of physical aggression in order to start using physical aggression (onset), unless this learning through models occurs for almost every child during the first 9–15 months after birth. Indeed, by 17 months of age most children are reported by their parents to have used some form of physical force to get what they want or to express their anger (Tremblay et al., 1999a). The developmental trajectories of physical aggression also indicate that having frequently observed models of physical aggression generally does not lead to an increase in the frequency of physical aggression. This can be concluded from the fact that, as they grow older, the majority of children have seen more and more instances of physical aggression, and their frequency of physical aggression decreases. If models of physical aggression have an impact, it is probably by reducing the speed at which children learn not to use physical aggression. Indeed, the declining frequency of physical aggressions with age indicates that the vast majority of children are learning not to use physical aggression as they grow older. It could be argued that the reason for the decline is the reduction of occasions for conflict as children grow older.

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However, the increase in verbal and indirect aggressions with age (see Vaillancourt, Chapter 8, this volume) suggests that reasons for physical aggressions remain, but that children are learning other ways to deal with them. The developmental trajectories described in this chapter indicate that living with others, even in violent environments, forces individuals to learn, as they grow older, to gain some control over their social behavior. Thus, there seems to be much more pressure to learn not to physically aggress than to learn to physically aggress. Even children in “high-risk” families are likely to observe a greater proportion of nonphysically aggressive interactions in their environment, because there is a high probability that no social group could survive for long if the majority of their interactions were physically aggressive. There has been much research over the past 2 decades on the “onset” of children’s disruptive behaviors, such as physical aggressions, property “offenses” (e.g., stealing), and hyperactivity. Most of that work has focused on school-age children (e.g., Lahey et al., 1999; Loeber, Green, Keenan, & Lahey, 1995; Tremblay, Pihl, Vitaro, & Dobkin, 1994). The longitudinal data we have examined from infancy onward leads us to think that physical aggression is not a behavior children learn, like reading or writing, nor an illness children “catch,” like poliomyelitis or smallpox. It is rather a behavior like crying, eating, sleeping, grasping, throwing, and running, which young humans exhibit when the physiological structure is in place, but then learn to control with experience. The learning-to-control process implies regulating one’s needs to accommodate those of others, and this process can be labeled “socialization” (see Paus, Chapter 12, as well as Séguin & Zelazo, Chapter 15, this volume). It is not hard to understand why the evolutionary process would give humans a genetic program that codes for all the basic mechanisms to react to hunger and to threat. Young children’s muscles are activated to run, push, kick, grab, hit, throw, and yell with extreme force when hungry, when angry, or when they are strongly attracted by something. In his Expression of the Emotions, Darwin (1872) anticipates present-day brain imaging techniques when he describes the reddening of the skin during a state of rage and gives this example: “With one of my own infants, under four months old, I repeatedly observed that the first symptom of an approaching passion was the rushing of the blood into his bare scalp” (p. 240). Stating that humans are genetically programmed to be able to physically aggress when needed, is different from stating that the frequency of the physical aggression they use is genetically programmed. Thus, although all 18-month-olds who have developed normally can, and possibly do, physically aggress, not all do so at the same frequency and with the same vigor. The trajectories shown in Figure 5.2 clearly indicate that these individual differences exist at any given point, but also over time. The gene–environment mechanisms are probably very similar to the developmental trajectories of growth in height. Genes code for the growth mechanisms, but there are individual differences in this coding, as well as environmental differences (e.g., access to food) that lead to individual differences in growth in height. Thus,

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these individual differences in the frequency of physical aggressions can be due to a large number of causes—for example, individual differences in the genetic coding for serotonin (see Pihl & Benkelfat, Chapter 13, this volume), testosterone (Van Goozen, Chapter 14, this volume), or language development (see Dionne, Chapter 16, this volume), or cognitive development (see Séguin & Zelazo, Chapter 15, this volume), or to environmental differences such as tobacco use during pregnancy (see Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002), birth complications (see Arseneault, Tremblay, Boulerice, & Saucier, 2002), parental care (see Gatti & Tremblay, Chapter 19, this volume; Raine, Brennan, & Mednick, 1997; Zoccolillo et al., Chapter 17, this volume), and peer characteristics (see Boivin, Vitaro, & Poulin, Chapter 18, this volume). However, the individual differences that we observe are very likely to be due to interactions between many of these mechanisms, and hence to epigenetic mechanisms (Francis, Diorio, Plotsky, & Meaney, 2002; Francis, Szegda, Campbell, Martin, & Insel, 2003; Raine, 2002; Tremblay, 2003; Weaver et al., 2004). Dionne, Tremblay, Boivin, Laplante, and Pérusse (2003) showed, with a large sample of 19-month-old female and male twins, that variance in mothers’ reports of physical aggression was explained about equally by genetic and environmental factors. Similar results were observed with an older sample of twins for assessments of antisocial behavior (e.g., Arseneault et al., 2003; Slutske et al., 1997), but the Dionne et al. study shows that both the genetic and environmental distal causes of physical aggression are in place by 19 months of age, long before the violent video games and the delinquent peers. A similar story is being told by the molecular genetic studies of physical violence. With a longitudinal study of a New Zealand male birth cohort, Caspi et al. (2002) observed that children of abusive and neglectful parents who had a genotype leading to high levels of monoamine oxidase A (MAOA) expression were at much less risk of having a disposition toward violence as young adults and being convicted for violent crimes. We need molecular genetic and twin studies to identify which environmental factors interact with which genetic factors to explain the individual differences in developmental trajectories of physical aggression from early childhood to adulthood. The following is an example of the first few steps in a program of longitudinal studies that pursues this aim. A large population sample of newborns (singletons and twins) are assessed annually from 5 months onward, with physical aggression assessed annually from 17 months (Dionne et al., 2003; Tremblay et al., 2004). Semiparametric statistical analyses of physical aggression data at 17, 30, and 42 months with the singletons indicated that there were three different developmental trajectories (Figure 5.4). Variables measuring parental characteristics before birth were used as predictors of the probability that a child would be on the high-level physical aggression trajectory. Controlling for all other measured variables, the best predictors were presence of a sibling (odds ratio [OR] = 4.00), mother’s history of antisocial behavior before the end of high school (OR = 3.1), mother’s age

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FIGURE 5.4. Trajectories of physical aggression from 17 to 42 months of age. From Tremblay et al. (2004).

when her first child was born (OR= 3.1), low family income (OR= 2.6), and a mother who smoked (OR= 2.2). Two variables measured at 5 months of age also contributed to the prediction: mother’s coercive parenting (OR = 2.3) and family dysfunction (OR = 2.2). This list of predictors for high levels of physical aggression from infancy to toddlerhood is amazingly similar to the variables that have traditionally been shown to predict physical aggression during the school years and delinquency during adolescence (Bovet, 1951; Brennan, Grekin, & Mednick., 1999; Loeber & Dishion, 1983; Nagin & Tremblay, 2001; Tremblay & LeMarquand, 2001). This would be expected if those who have high levels of physical aggression during childhood and adolescence were frequent users of physical aggression during early childhood. Some of the predictors point to causal mechanisms, and others are markers of unclear mechanisms. For example, the sibling variable appears to indicate that young children who have a target are much more likely to use physical aggression (Dunn & Munn, 1985). The smoking variable replicates the increasing number of longitudinal studies suggesting that nicotine has a negative effect on fetal brain development (Brennan, 2003; Fergusson, Woodward, & Horwood, 1998; Wakschlag et al., 2002). Antisocial behavior of the mother during her adolescence could be a marker for many causal mechanisms (see Keenan & Shaw, 1994). First, it could be a marker for some form of genetic transmission of a propensity to impulsive and aggressive behavior (see Caspi et al., 2002; Suomi, Chapter 4,

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this volume; and Pihl & Benkelfat, Chapter 13, this volume). It could also be a marker for the quality of the environment the mother is creating for the child both during the prenatal (e.g., quality of nutrition, stress) and postnatal (e.g., maternal care) periods (Francis et al., 2003). Finally, it could be a marker for both the genetic and environmental contribution of the father, inasmuch as there is much assortative mating (e.g., Rowe & Farrington, 1997). Similarly, family income is probably a marker for many different causal mechanisms, some of which could be quality of nutrition during the prenatal and postnatal periods The two predictors measured at 5 months of age (maternal coercive behavior toward the child and family dysfunction) suggest that children who use physical aggression more frequently than others during infancy are the victims and witnesses of a disproportionately large amount of physical aggressions during their first year after birth. We need more detailed observational and physiological studies of parent–child interactions in these families during the first 12–18 months to understand the mechanisms by which the adult behaviors have an impact on the child’s propensity to use physical aggression. Cross-fostering experiments like those done by Francis et al. (2003), Weaver et al. (2004), and Suomi and his colleagues (see Chapter 4, this volume) would give better insights into causal mechanisms than studies that are limited to observations. Obviously, it would be hard to do such studies with humans. However, prevention experiments that aim to help high-risk families to give better care to their children during early childhood (e.g., Campbell & Ramey, 1994; Olds et al. 1998) could be used to understand the mechanisms that prevent children from behaving as if physical aggression were the best option for adjusting to their environments.

CONCLUSIONS I can say in my own favour that I was as a boy humane, but I owed this entirely to the instruction and example of my sisters. I doubt indeed whether humanity is a natural or innate quality. —DARWIN (1876, p. 11)

The first aim of this chapter was to summarize our present knowledge of the development of physical aggression from early childhood to adulthood. Unfortunately, none of the large longitudinal studies of humans followed from early childhood to adulthood seem to have collected repeated measures of physical aggression throughout the study. Thus, to describe the lifespan intraindividual changes in the physical aggression of humans, we had to put together a patchwork of longitudinal studies that covered different age periods with samples from different populations. Figure 5.5 is a rough representation of this patchwork. The physical aggression trajectories from adolescence to adulthood are modeled on the data from White, Bates, and Buyske (2001); those from childhood to adolescence are inspired by data from Broidy et al.

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FIGURE 5.5. Age–physical aggression curves (hypothesized). From Tremblay (2003). Copyright 2003 by The Guilford Press. Reprinted by permission.

(2003) and Lacourse et al. (2002); and the preschool to elementary school trajectories are adapted from Côté et al. (2004), and Tremblay et al. (2004). The patchwork shows that the peak in frequency of physical aggressions for the large majority of humans is most probably between the end of the 2nd and 4th year after birth. This representation of physical aggression development has a shape similar to the traditional age–violent-crime curve. There is a sharp increase in frequency, a peak that does not last very long, and a slow decline. Note that even those who can be considered on a chronic physical aggression trajectory are slowly declining in physical aggression, with a possible brief increase during adolescence. By adulthood the individual differences in frequency are possibly the smallest. Although the shapes of the curves are similar, moving the peak in frequency of physical aggression from 18 months to 3 years of age should qualitatively change the way we think about the second aim of this chapter, defining the mechanisms involved in the development of physical aggression. St. Augustine (397/1960) can be paraphrased to express one of the obvious differences: Thank God (or nature!) that humans have weak limbs at the age when they most often use physical aggression. We believe that the observed developmental trajectories seriously question the social learning hypothesis as it continues to be expressed, especially with reference to media violence (e.g., Johnson et al., 2002). There is also no evidence that aggression is like an appetite that needs to be satisfied (Archer, 1988; Lorenz, 1966), but it appears very unlikely that humans need to observe physical aggression to initiate its use. If they do, the learning must be occurring in the first 15 months after birth, and that learning would be universal. What appears more certain, from the observed developmental trajectories, is that humans learn not to use physical ag-

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gression by learning alternatives. Some children learn more quickly than others, and girls are overrepresented in this group (see Archer & Côté, Chapter 20, this volume). However, if humans learn more or less rapidly to use alternatives to physical aggression, it is important to note that this behavior remains in the behavioral repertoire and can be used when the need arises. Because we tend to forget this, there is always much surprise when a quiet, law-abiding citizen suddenly physically aggresses a neighbor, a spouse, or a work mate. Most investigators, and indeed, most humans, forget that physical aggression is not in itself a “bad,” “destructive” behavior. It is a solution for securing resources and surviving in a given environment (Archer, 1988). Humans have inherited the ability to use that solution, but they have also inherited the ability to use many other strategies, including cooperation and conflict resolution, that are not based on physical force (see Peterson & Flanders, Chapter 7, this volume, and de Waal, 2000). We are slowly creating a social environment in which the physical aggression solution generally becomes a much less adaptive strategy than its alternatives. Young children will spontaneously cooperate and fight, but they need to learn which of the alternatives is the most effective in which situation. Some, because of their genetic makeup, will more easily learn some solutions than others. Similarly, some environments will tend to facilitate some solutions more than others. The gene–environment interactions will favor different developmental trajectories. The simple law that Darwin put forward was that those who will thrive are those who will be most able to learn to use the solutions that are most appropriate for the problems they face. In a social group that does not tolerate physical aggression, it is better to use a form of aggression that is less sanctioned. This does not mean that a punch in the nose is more harmful than an indirect aggression to a person’s reputation. It simply means that a group of humans have decided that conflicts should not be solved by physical force. There was a time, not long ago, when conflicts between men of honor were solved by a duel using pistols, swords, or fists; in our 21st-century civilization there is an increasing trend to settle conflicts with words. The fact that physical aggression peaks in early childhood when limbs are weak, and when the brain is at its peak flexibility for learning, leads us to two important conclusions concerning research and education during early childhood. First, it is clear that we need to better understand the mechanisms that underlie the rapid increase in frequency of physical aggression in infancy, as well as the mechanisms that lead to the large differences among infants. It must be noted that a similar conclusion was reached 30 years ago. Hartup and De Wit (1974, p. 607) highlighted the fact that “the role of tantrums in the development of aggression can be inferred from existing studies only by piecing together bits and pieces of data. The origins of aggression in human children could be elucidated by several types of longitudinal studies (which might cover no more than 12 or 18 months).” In the same book, Hamburg and van Lawick-Goodall (1974, p. 72) also concluded: “There is a great need for direct studies, utilizing systematic observational techniques of aggressive behav-

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ior and its precursors in human infancy and early childhood.” Unfortunately, not much progress has been made on that front during the 30 years since. Our second conclusion is that because early childhood appears to be the optimal period to learn alternatives to the use of physical aggression, it could be the optimal time to link education and research. Over the past 4 decades there has been an important movement to enrich the educational experience during the preschool years. A number of randomized control experiments tested the effects of different types of preventive programs for children at risk of learning and behavior problems (Olds et al., 1999; Tremblay, LeMarquand, & Vitaro, 1999b). To our knowledge, none of these experiments included a specific component for learning to regulate physical aggression. We believe that such experiments would not only help us learn to what extent we can change the developmental course of physical aggression, but would also help test hypotheses concerning the developmental origins of aggression. We end this chapter with a brief allegoric answer to a question we asked at its beginning when we referred to the huge appetite for media violence in modern societies. The question was: “By what peculiar process are these hungry-for-physical-violence modern humans passing laws to eradicate physical violence from their daily lives?” In the book of Genesis we learn that humans were created to dominate planet Earth, and that soon after Adam and Eve were chased from Paradise there was a homicide: Cain killed Abel. Whether we believe that story or its revision by Darwin, we are told that humans have inherited a biological machine that has the capacity to physically aggress. As humans, we dream of the Paradise where we will not fear being physically aggressed; however, Paradise will be a boring place if the aggression machinery (perceptions, cognitive–emotional processing, and action) is left to rust. Hence, the invention of the horror story, the violent video games, and contact sports. The transformation of real physical violence into fiction or game should help keep Paradise a safe place to live in, as long as we understand what we are doing and why we are doing it.

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THEBeginnings The DEVELOPMENT of Aggression OF AGGRESSION in Infancy

6 The Beginnings of Aggression in Infancy D ALE F. H AY

Aggression is a ubiquitous feature of human social life, which makes it all the more surprising that its developmental course is not more clearly known (see Tremblay, 2000). The aim of this chapter is to trace the earliest beginnings of the human capacity for aggression, as manifested in the first 3 years of life. Two general questions are considered, reflecting the fact that any developmental analysis requires attention to both change and continuity over time (see Appelbaum & McCall, 1983). First, when do infants in general reveal the ability to direct aggression against their companions? Second, do some infants show stable and coherent tendencies to be more aggressive than their peers? To address either question means getting to grips with the thorniest problem in studying aggression, namely, the question of intent. Determining the intent of any action becomes particularly difficult when observing preverbal infants, who cannot be questioned about their intentions and whose motives are usually given the benefit of the doubt. I suggest that the intentionality of social action is itself a developmental phenomenon, and therefore the intentional nature of early aggression becomes an empirical question. I return to this issue later in the chapter. First, I consider some definitional issues, propose operational definitions of the use of force against one’s companions, and note when behaviors meeting these criteria can first be identified and how they change over time. 107

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DEFINITIONAL ISSUES Defining Aggression Hardly any construct in psychology is more difficult to define than aggression (see Cairns, 1979). Broadly speaking, the term aggression implies harm done with malevolent intent; physical harm designed to do good (e.g., surgical procedures) and unintentional assault (e.g., elbowing someone in the face by accident) do not qualify. Even when assaults are intentional, they may be deemed more or less serious on the basis of whether they are reactive rather than proactive and decided upon in the heat of the moment or in a cool, premeditated fashion—hence the legal distinctions among self-defense, manslaughter, and murder. The concept of harm is itself open to varying interpretations: Aggression is often synonymous with physical assault, though it need not be. Intentionally delivered malicious comments about another person’s appearance, actions, or character could so qualify; yet, with notable exceptions (e.g., Muste & Sharpe, 1947), there have been few attempts to explore the early development of verbal aggression. It can also be argued that the failure to act in a friendly, sociable manner can, in some cases, qualify as intentional harm, as in the phenomenon of “relational aggression” in childhood (e.g., Crick, 1995). Thus, in general, definitions of aggression are multidimensional, requiring information about the specific intent of an action, its form and intensity, its provocation, and the interpersonal history of aggressor and victim. It is hardly surprising that such a quicksilver construct is hard to study. How, then, can one proceed to study the developmental origins of something so hard to define? Although human infants may not usually be described as aggressive, some are thought to be “difficult.” Infants show anger (Bridges, 1932; Goodenough, 1931; Lewis, Alessandri, & Sullivan, 1990; Stenberg, Campos, & Emde, 1983). Older toddlers may be “jealous” and “rivalrous” with their younger siblings (Levy, 1939). All of these constructs suggest a potentially fraught relationship between some infants and their companions; infants’ worlds are clearly not free of conflict. I propose that to seek the origins of aggression, we need to look within infants’ conflicts with adults and with other children. Social conflict can be operationally defined as a social interaction in which there is opposition, with one person’s action being protested, resisted, or retaliated against by another person (Hay & Ross, 1982). This definition is at a sufficient level of abstraction that it can be applied across ages and across different sorts of personal relationships. By using conflict as a basic framework, one can identify and chart the developmental course of various phenomena of relevance to aggression throughout the life course. These include (1) emotional expressions of anger and their control, (2) resistance to the actions of others, in terms of gaze avoidance or withdrawal from interaction, (3) vocal and, eventually, verbal protest of the actions of others, (4) use of physical force against another person, (5) defen-

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sive reactions, and (6) name calling and other forms of verbal insult. One can also chart infants’ use of prosocial actions to resolve their disputes, and study the development of related phenomena such as moral condemnation of another’s actions and justification of one’s own behavior. By using conflict as the basic framework for investigating the origins of aggression, infants’ expressions of anger and use of force can be examined in social context, and the growing intentionality of forceful actions can be studied as a developmental phenomenon in its own right. Furthermore, some additional distinctions can be made.

Personally Directed versus Instrumental Use of Force Two characteristic means of directing physical force against one’s companions can be distinguished in early life. The first can be described as personally directed force (e.g., hitting, kicking, pushing, batting at, or otherwise directing one’s body against another’s in a forceful manner). The second is instrumental force (e.g., snatching, grabbing, or otherwise wresting an object away from another person into one’s own possession). These categories roughly correspond to Hartup’s (1974) classic distinction between hostile and instrumental aggression. This basic distinction between force used as an end in itself versus a means to gain access to an object, position, or territory is present in most observational coding systems that have been applied to young children’s social interactions (e.g., Bridges, 1933; Eckerman, Whatley, & Kutz, 1975; Hay & Ross, 1982; Rubin, Hastings, Chen, Stewart, & McNichol, 1998; Strayer & Strayer, 1976). Although these two classes of behavior are often combined into a single category, they appear to have somewhat different developmental courses and sets of correlates, and so I consider them separately in this chapter.

Proactive versus Reactive Use of Force Several investigators have distinguished between aggression used proactively and reactively, and, as we have seen, the extent to which aggression is premeditated or used in self-defense is also an important legal distinction. Longitudinal research has suggested that proactive aggression in early childhood is a serious predictor of later violence and delinquency (Vitaro, Gendreau, Tremblay, & Oligny, 1998). It should be noted, however, that many aggressive individuals use both (Vitaro, Brendgen, & Tremblay, 2002). Furthermore, angry, reactive aggression is linked to social–cognitive problems (Schwartz et al., 1998) and is responded to negatively by peers, which fosters further aggression (Price & Dodge, 1989). It is important to assess the extent to which very young children use force proactively and reactively and whether there are consistent individual differences in this regard.

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The Recipients of the Young Child’s Acts of Force Different investigators tend to study infants’ interactions with parents, siblings, peers, and other adults, and so it is rare to find studies that compare the use of force with different types of companions (for exceptions to this general trend, see Smetana, 1984, 1989). Although we may assume that infants direct force against their caregivers when in the midst of a temper tantrum, or disciplinary encounter, such events seem rarely to have been recorded and are not usually defined as instances of aggression. Rather, most accounts of the early origins of aggression, and its developmental course, focus on children’s use of force in conflicts with other children, that is, their siblings, friends, acquaintances, and newly met peers. However, the initial steps in the development of aggression are probably taken in the context of interactions with adults, in particular with primary caregivers. I thus include these early features of parent–infant relations in a proposed model of the normative development of aggression.

THE NORMATIVE COURSE OF CONFLICT AND AGGRESSION A review of the existing literature on infants’ interactions with adults, siblings, and peers suggests the following model of the normative development of aggression over the first 3 years of life.

The Capacity for Anger A developmental account of the origins of aggression begins with the study of anger (Goodenough, 1931). Recognizable signs of specific emotions emerge in the 1st year of life. Frustrating experiences, such as an adult’s yanking a cookie away from the baby (Stenberg et al., 1983), or extinction of a previously rewarded behavior (Lewis et al., 1990), provoke these expressions. It is, of course, not completely clear whether the facial expressions recorded in these studies are mirrored by the phenomenological experience of anger as felt by adults. Rather little is known about the manifestations of anger in nonexperimental situations and still less about its rate of occurrence in ordinary interactions with parents and other people. Measures of infant temperament do not rate anger per se, although Rothbart’s (1981) Infant Behaviour Questionnaire measures “distress to limitations,” which predicts ratings of “anger proneness” in the toddler years (Goldsmith, 1996). Furthermore, Goldsmith (1996, pp. 225–226) argued that “anger expression appears to be the emotional core of difficulty” as rated by other temperament instruments. In Goldsmith’s (1996) analysis of 11 samples of toddlers, anger-proneness is stable and coherent, but somewhat bound up with activity level. Much work is needed to chart the normative development of anger and its regulation in the early years.

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Resistance and Protest I have defined social conflict as an encounter in which one person’s action meets with an objection from another person, which takes the form of protest, resistance, or retaliation (Hay & Ross, 1982). Early signs of resistance and protest predate the use of retaliation in development. A simple form of conflict occurs when infants avert their gaze in response to unduly intense or prolonged overtures from adults. Young infants also show objections to the actions of other people by wriggling, leaning away, pushing away a caregiver’s hands or face, and, eventually, moving away from the other person. Distress that is contingent upon another person’s actions is similar to an early form of protest that defines a conflict. In the early months of life infants seem remarkably forbearing vis-à-vis their companions. For example, 6-month-old infants touch each other and touch toys they each are holding; these events, which provoke conflict between older infants (e.g., Caplan, Vespo, Pedersen, & Hay, 1991), do not lead to visible signs of protest or resistance (Hay, Nash, & Pedersen, 1983). However, gaze avoidance, distress, and withdrawal from interaction are likely to occur in response to intrusive or very withdrawn maternal behavior, such as that shown by women suffering from postnatal depression (e.g., Field et al., 1988) or mothers who are merely simulating depressed affect in a laboratory paradigm (Cohn & Tronick, 1983). This form of resistance to intrusive or inconsistent caregiving may be the genesis of insecure attachment relationships (Ainsworth, Blehar, Waters, & Wall, 1978; De Wolff & van IJenzdoorn, 1997). Less is known about the normative use of resistance in infants’ social relationships with adults and other children.

Autonomy, Initiative, and Active Defense Studies of infants’ more positive social interaction—their engagement in conventional social games—have demonstrated that infants become increasingly active and creative in the second half of the first year of life (Gustafson, Green, & West, 1979; Ross & Kay, 1980). For example, in the well-studied game of “peek-a-boo,” the infant’s role is first simply to express affect—to laugh when its face is covered with a cloth. Next, at a slightly older age, the infant begins actively to pull off the cloth; then to put the cloth over his or her own face; and finally to cover up the adult’s face with the cloth. I propose that an analogous progression from passive resistance to active defense and the intentional use of force takes place in the context of infants’ conflicts with other people. This development is likely to take place between 9 and 12 months of age, when infants begin to move about the world autonomously. Relationships between infants and their parents become more problematic when the infants learn to walk, particularly when boys walk early (Biringen, Emde, Campos & Appelbaum, 1995). An early scholar suggested that infants’ actions in conflict indeed become

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more active around 11 or 12 months of age. It is fitting that the conference paper on which this chapter is based was presented in Montreal, where, in the 1920s, one of the earliest and most systematic studies of infants’ peer relations was conducted (Bridges, 1932, 1933, 1936). Bridges observed several groups of physically healthy infants and toddlers residing at two foundling hospitals in Montreal. (She noted that the prospects for cognitive and emotional development might be restricted, because of the institutional upbringing of these children, but also suggested that in view of the amount of time they spent playing with peers, their social development might be precocious.) Bridges wrote that the 10-month-old infant seemed “rather indifferent when another child in the [playpen] grasps his toy. He takes hold of some other object or sits and rocks. He scarcely struggles at all for the possession of anything.” In contrast, a month later, “If another child takes it from him he cries. In a few weeks’ time he makes some attempt to hold on to his possessions; he struggles and squeaks. He also squeals if another baby takes hold of some object he coveted.” The 1-year-old’s more active engagement in conflict is also facilitated by improvements in cognitive abilities. Particular strides are made in infants’ understanding of means–end relationships, with consequences for their appreciation of the intentionality of action (e.g., Frye, 1993). Furthermore, in this last quarter of the first year of life infants’ reactions to potentially disturbing events become conditional. They interpret ambiguous events in terms of caregivers’ expressed emotion (Feinman, 1982) and their own degree of control over the situation (Rheingold & Eckerman, 1970; Gunnar, 1980). It is in this context of increased capacities for interpretation and understanding of the things that happen to them that infants can be said to show focused protest and self-defense, not just undifferentiated distress. Unlike younger infants (Hay et al., 1983), 12-month-old infants do notice when their hair is pulled or their toys are taken away by their peers, and react accordingly (Caplan et al., 1991).

The Intentional and Strategic Use of Force Force against Family Members We know relatively little about infants’ use of force against their parents. For example, in one study of small boys in Pennsylvania, the boys’ defiance was subsumed into general measures of “family trouble” and the developmental course of the boys’ aggression against parents was not charted in its own right (Belsky, Woodworth, & Crnic, 1996). The means suggest, however, that defiant behavior on the part of the boys (which might include the use of force) was shown in approximately one-fifth of the conflicts recorded between parents and children. In an observational study of 2-year-olds with their mothers and elder siblings in a laboratory apartment, family conflict was common but the use of

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force was not (Hay, Vespo, & Zahn-Waxler, 1998). However, disputes that entail aggression were observed in home settings when toddlers interacted with mothers as well as with familiar peers (Smetana, 1989).

Force against Peers Bridges (1933) suggested, based on her observations of children in foundling hospitals, that the active use of personal force, in the form of biting or hitting, was in place by 14 or 15 months of age. Despite her belief that institutionalized children might be socially precocious, this is probably a conservative estimate of the age of onset. Both striking others and taking of toys have been recorded, at low levels, in infants between 10 and 12 months (Eckerman et al., 1975).

Does the Use of Force Decline with Age? Given that the use of force emerges around the time of the first birthday, is there then a steady decline in its use thereafter? When force begins to be used in infants’ conflicts with peers, it occurs at quite low rates. Thereafter, the use of force over the next 2 years appears to ebb and flow, rather than showing a clear decline. For example, in our experimental study of previously unacquainted children, observed in a laboratory playroom with their mothers, in groups of three mother–infant pairs, both personally directed and instrumental force occurred at 12 months of age (Caplan et al., 1991). There was no significant difference in the mean rate of force between the 12- and 24-monthold children observed in that study, nor did the rate of conflict with peers differ between the two age groups. It is somewhat difficult to weigh the evidence for a general decline in aggression, as different investigators have used slightly different definitions, different units of analysis, time- versus event-sampling strategies, and specific experimental procedures. However, our own program of work suggests that, rather than showing a monotonic decline in the use of force from the 1st to the third birthdays, there appear to be peaks around 1½ and 2½–3 years of age. For this chapter, I examined cross-sectional data from several studies my colleagues and I conducted in Canada, the United States, and the United Kingdom, in which the occurrence of instrumental and personally directed force against peers was recorded, using equivalent operational definitions (Caplan et al., 1991; Ross & Hay, 1977; Ishikawa, 2003; Pedersen, 1985). In these experiments children were tested in dyads or triads for varying periods of time. To adjust for differences in experimental procedures, I calculated the rate of forceful acts per hour, divided by the number of individuals observed (see Ishikawa, 2003, for an extended justification of this way of adjusting for group size). The results are presented in Figure 6.1. For clarity of presentation, the data are presented as a line graph, although the different data points represent separate studies. These studies show an initial peak in

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FIGURE 6.1. Cross-sectional data from a series of laboratory studies of interaction between unfamiliar peers showed a peak in both instrumental and personal use of force at 21 months.

both personal and instrumental aggression around 18 months of age, and then another around the 3rd birthday. We sought further evidence of change in the rate of force by undertaking longitudinal observations of British children at home with familiar peers (Hay, Castle, & Davies, 2000). The toddlers were observed initially at 18, 24, or 36 months of life and then again 6 months later. Thus, two samples were observed at 24 and 30 months of life, but only one sample each at 18 and 36 months. Instrumental force was reliably more common than hitting, kicking, or biting; many toddlers in the sample never hit their peers. When the pairs of children were observed again 6 months later, the rate of grabbing toys had declined and was now significantly less frequent than spontaneous sharing of toys and other objects. In contrast, personally directed force remained at stable, low rates, shown by a minority of the children (see Figure 6.2). The patterns of change revealed in the figure are broadly comparable to those found in the cross-sectional observations, with peaks in the use of force at 18 and 30 months of life. It is of interest to note that a cross-sectional study of infants and toddlers attending day care centers similarly found peak levels of “assertive interchanges” (combining instrumental force, personal force, and negative commands) at 18 and 30 months of age (Holmberg, 1980); on average, the toddlers made 11 such initiations per hour at 18 months and 7.6 per hour at 30 months. Both the cross-sectional and the longitudinal comparisons show that force is not the “default” strategy that toddlers use in interacting with their peers. Rather, force against peers is used selectively and strategically. For example, laboratory observations of Canadian 21-month-olds showed that toddlers hardly ever began their conflicts with the use of force; the tendency to use force increased the longer a conflict remained unresolved (Hay & Ross,

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FIGURE 6.2. Longitudinal analyses of a sample of British toddlers observed with familiar peers showed peaks in both instrumental and personal use of force at 18 and 30 months.

1982). Two decades later, a new generation of Canadian toddlers showed a similar reluctance to use force, the majority doing so only once, if at all (Rubin, Burgess, Dwyer, & Hastings, 2003). Most conflict initiations are not explicitly aggressive (Green, 1933; Rubin et al., 1998). Furthermore, toddlers demonstrate an implicit awareness of “social rules” governing the use of force; they are less likely to resist instrumental force if the child trying to grab a toy had possessed it previously (Bakeman & Brownlee, 1982). Thus, rather than being a very common state of engagement between young peers, force appears to be used on selected occasions.

Attributions about Companions’ Desires and Intentions In the 2nd and 3rd years of life, toddlers become increasingly aware of other people’s feelings and possible actions. In later childhood, aggression and conduct problems have been linked to social–cognitive deficits and biases (e.g., Dodge & Coie, 1987; Hughes, White, Sharpen, & Dunn, 2000; for an alternative view, see Sutton, Smith, & Swettenham, 1999). The normative understanding of other people’s desires and intentions is thought to develop over the course of the preschool years, with performance in early primary school approaching adult norms (Schult, 2002; Wellman, Phillips, & Rodriguez, 2000). However, our observational studies of children’s conflicts with peers indicate that a rudimentary understanding of intent is present by the 2nd year of life. In our longitudinal study of toddlers observed at home with familiar peers, when one child gestured toward a toy, the peer attempted to defend the object on more than one-third (38%) of the occasions (Hay et al., 2000). In contrast, sharing in response to peers’ gestures occurred on 8% of occasions (Hay, Castle, Davies, Demetriou, & Stimson, 1999a). In both cases, the toddlers were demonstrating their awareness of the peer’s de-

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sire for the object. This growing understanding of other people’s desires and intentions is likely to affect the circumstances in which toddlers choose to use force.

Conflict Avoidance and Resolution Toddlers also develop ways of avoiding conflict or terminating it, once begun. Clearly children do not always protest the actions of their companions. Pedersen (1985) recorded a variety of possible “provocations” in the behavior of 2-year-olds, tested in dyads with familiar peers from a nursery school classroom. Although a great variety of possible provocations were recorded, only a minority of these possibly provoking actions led to conflict and overt aggression was very rare indeed. Similar findings emerged in a study of 2-year-olds with unfamiliar peers, where behaviors that might initiate conflict often failed to do so (Rubin et al., 1998). Furthermore, even when one child protests the action of a sibling or peer, the first actor may simply let it go, and the conflict does not proceed beyond two initial moves (Hay & Ross, 1982; Hay et al., 1998). Even in longer conflicts, one of the antagonists may simply walk away. For example, after a sustained conflict between two 21-month-olds, which involved the use of force, one child ended the dispute by wriggling out from under his antagonist, going over to a mirror and trying on a hat (Hay & Ross, 1982). Toddlers sometimes use explicit prosocial actions to end their conflicts with peers (Caplan et al., 1991; Sackin & Thelen, 1984), but yielding to the antagonist and leaving the situation are rather more common ways of ending disputes. The extent to which a toddler will yield to a peer depends on the identity of that peer. In an experimental study of the effects of acquaintance on peer interaction, pairs of toddlers met on 3 consecutive days; on the 4th day, half the pairs were rearranged so that toddlers met unfamiliar peers (Hay & Ross, 1982). The probability of initiating conflict on the 4th day was predictable from the toddlers’ prior behavior for both groups, but the probability of yielding to the peer’s demands was predictable only if the toddlers remained with their former partners. Such patterns of yielding to particular peers consolidate into structured dominance relationships in peer groups (Bakeman & Brownlee, 1982; Strayer & Strayer, 1976). Very young children’s avoidance or termination of conflicts with their parents has traditionally been studied in a different intellectual framework, namely, the study of compliance, self-regulation and conscience (e.g., Kochanska, 1993; Kochanska, Akson, & Koenig, 1995a; Kopp, 1982; Kuczynski & Kochanska, 1990). Prompt and cheerful compliance to a parent’s command or prohibition would constitute conflict avoidance (e.g., Kochanska et al., 1995a; Rheingold, Cook, & Kolowitz, 1987); in contrast, resistance, prolonged protest, or defiance would produce conflict, which would then have to be resolved by either the parent or the child. Conflicts between parents and toddlers, which are variously described as “child behavior management

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events” (Belsky et al., 1996) or “testings of will” (Biringen et al., 1995), increase in frequency between 9 and 12 months of age (Biringen et al., 1995). During the first 3 years, mothers are increasingly likely to characterize their children in negative terms (Stimson, Castle, & Hay, 1997). A substantial number of “moral encounters” between mothers and children do involve the child’s use of aggression (Smetana, 1989). Within the family circle there are rather distinct features of sibling conflicts as opposed to parent–child conflicts. Positive sibling relationships sometimes follow from fraught relations between the mother and the firstborn (Dunn, 1993). If elder children’s actions are often objected to by their mothers, they are less likely than other children to make objections to behavior shown by their younger siblings, and thus avoid sibling conflict (Hay et al., 1998). Much more attention needs to be paid to the emergence of conflict avoidance and resolution strategies, and the control of aggression, across the child’s different relationships.

Emergence of a Moral Vision By the end of the preschool years, children have firm opinions about aggression and talk about aggression in a moral context. Five-year-olds condemn aggression, especially if it is proactive and involves personal assault (Ferguson & Rule, 1988; Hay, Zahn-Waxler, Cummings, & Iannotti, 1992). This capacity for moral judgment is fostered in the context of children’s conflicts with parents, siblings, and peers (Dunn, 1988; Ross, Tesla, Kenyon, & Lollis, 1990; Smetana, 1989). Particularly in dealing with their siblings, 2- and 3-year-old children begin to justify their own actions and cast aspersions on other people’s motives (Dunn, 1988). Parents’ moral teachings take place under these emotionally fraught circumstances (Ross et al., 1990), and parental intervention in their children’s quarrels reduces the use of physical aggression (Perlman & Ross, 1997). Direct moral education takes place against a background of toddlers’ own increasing concerns with order and social arrangements. Over the course of the 2nd year of life, children begin to show an awareness of “standards” in social and aesthetic life (Kagan, 1981). For example, they express distaste for mess and broken objects (Kochanska, Casey, & Fukomoto, 1995b) and become distressed when they create mess or break things (Cole, Barrett, & Zahn-Waxler, 1992; Kochanska et al., 1995b). In the early years children also become increasingly aware of the concept of personal property. In the context of sibling quarrels, children show an understanding of principles of entitlement that come to govern their designs on other people’s possessions (Ross, 1996). Rudimentary understanding of the rights of possessors can be discerned in 1-year-olds’ interactions with peers (Bakeman & Brownlee, 1982). The capacity for moral evaluation also emerges in the toddler years. Our longitudinal observations of children with familiar peers indicated that even 2-year-olds condemn each other’s actions as “naughty” or “bad” (Hay et al.,

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2000). In the context of this general concern for order, a child’s own aggressive actions require justification, and the aggressive actions of others may provoke fear and dislike (Denham, McKinley, Couchoud, & Holt, 1990).

Summary of the Developmental Trends The foregoing section set out a developmental progression from unfocused activity, reactivity and interactivity through the development of the capacity for anger, focused protest and conflict, with the deployment of instrumental and personal force, to an eventual weighing of the justifications for aggression and the use of alternative strategies to avoid or resolve conflict. The infant’s general approach to conflict moves from general irritation and passive resistance to a capacity for focused protest and explicit use of force. However, aggression never seems to occur at very high rates, even among notoriously “terrible” 2-year-olds. I have proposed that this general developmental model will hold across all the different interpersonal relationships in which infants and toddlers engage. However, to my knowledge, there are no available longitudinal data on which to test that assumption.

EVIDENCE FOR INDIVIDUAL DIFFERENCES IN TODDLERS’ USE OF FORCE Individual differences presumably will manifest themselves at each step in the developmental progression I have described. Of primary interest, however, are individual differences in the use of force. I now examine the evidence for stable and coherent individual differences in young children’s use of force and briefly speculate about possible factors that might underlie these differences, placing particular infants at risk for stable violent careers. First, however, one must briefly consider the vexing question of gender differences. Most studies of infants and toddlers reveal few gender differences in aggression or externalizing problems (for reviews, see Keenan & Shaw, 1997; Loeber & Hay, 1997). In the observational literature there are few striking differences in the use of force by girls and boys. In some studies aggression occurs so infrequently that tests for sex differences are impossible (e.g., BrooksGunn & Lewis, 1979; Castell, 1970; Vespo, Pedersen, & Hay, 1995); in other cases, no significant sex differences are observed (e.g., Bakeman & Brownlee, 1982). The absence of significant sex differences in much observational research may partly be due to lack of statistical power. In a somewhat larger study of 104 2-year-olds (Rubin et al., 1998), girls had lower scores on a composite measure of observed aggression. However, the girls and boys did not differ significantly on “angry aggression,” which comprised physical aggression (hitting, pushing, punching, and kicking), verbal threats and insults, and angry affect. Nor were there gender differences in adult-rated externalizing problems. Where gender appears to make the most difference is not in the absolute

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rate of force, but in qualitative as well as quantitative patterns of individual differences. Thus, with respect to the following evidence for stable and coherent individual differences in the early development of aggression, a number of findings are qualified by gender.

A Forceful Minority? It is generally thought that the use of force is so common in toddlers’ interactions with other children that individual differences would be difficult to discern. This is not true. Although the capacity for forceful action is present in the second year of life, not all toddlers display the use of force during observation sessions. Indeed, most toddlers are observed to use personal force seldom if at all, and in many cases it occurs too infrequently to be analyzed (e.g., Brooks-Gunn & Lewis, 1979; Castell, 1970; Rubin et al., 1998; Vespo et al., 1995). In our experimental studies the use of force is less common than other peer-directed behaviors. For example, over the course of four days in a laboratory playroom, only 35% of the sample engaged in conflicts where force was used (Hay & Ross, 1982). Similar findings emerged over a year of observations of experimental play groups, where, on average across trimesters, 40% of the toddlers used force instrumentally and 20% showed “belligerent assaults” (Bronson, 1981). A higher number of British toddlers used force at home with familiar peers (Hay et al., 2000). Most of those toddlers grabbed objects held by peers (80% at the first visit and 77% six months later). However, the majority refrained from the use of personally directed force, which was shown by 48% at the first visit and 44% 6 months later. Thus, it appears that fewer children use personal than instrumental force. Particular forms of force are even less common. For example, only a minority of boys who hit their peers used “hard hits” (Brownlee & Bakeman, 1981). The proactive use of physical force is relatively uncommon. In our longitudinal study, only a minority of children began an interaction by proactively striking the peer (27% at each visit).

Consistency across Different Measures of Aggression There appears to be moderate consistency across different measures of aggression in very early childhood, to the extent that composite measures show acceptable levels of internal consistency (e.g., Fagot & Leve, 1998; NICHD Early Childcare Research Network, 2001; Rubin et al., 1998, 2003). Toddlers’ observed use of force correlates significantly though modestly with more general measures of externalizing problems (e.g., Rubin et al., 1998). In our longitudinal study of toddlers observed at home with familiar peers, the association between instrumental and personally directed acts of force was positive, but only approached statistical significance. Further analyses showed that the association between the two types of forceful actions was

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significant for girls, but not for boys (Hay et al., 2000). Indeed, at the first visit, boys’ uses of instrumental and personal force were completely uncorrelated. Mothers’ ratings of aggressiveness were associated with girls’ use of personal force at both visits, and with boys’ instrumental force at the time of the second visit. Thus, girls’ aggressive tendencies were more consistent across types of behaviors and types of measurement.

Continuity of Individual Differences in the Use of Force over Time To the extent that early aggression is seen as random, or trivial, or due merely to situational factors, we would not expect any degree of stability of individual differences over time. However, a number of studies have documented statistically significant continuities over time in phenomena related to aggression. For example, toddlers’ tendencies to initiate conflict are stable over days and across peer partners, r’s = .57–.66 (Hay & Ross, 1982). “Agonistic” interactions between toddlers are stable from the first to the third trimester of the second year of life, r = .44 (Bronson, 1981). Aggressive ratings during an experimental paradigm where adults simulated anger were found to be stable over one month, r = .48 (Cummings, Iannotti, & Zahn-Waxler, 1985). Toddlers’ “negative interactions” with peers predicted teachers’ ratings of externalizing problems at 5 years of age, r = .31; the observed measure of aggression was a stronger predictor of teacher-rated externalizing problems than measures of temperament, security of attachment, or parent-rated behavioral problems (Fagot & Leve, 1998). There is considerable debate as to whether such continuities are more evident for boys or for girls. Two-year-old children’s “dysregulated aggression” with familiar peers, measured in a laboratory situation, predicted aggression with peers for boys but not for girls three years later (Cummings, Iannotti, & Zahn-Waxler, 1989). This finding is in line with other longitudinal research suggesting continuities over the lifespan in male aggression (e.g., Olweus, 1979). However, in a study of toddlers in lower-income families, continuities over time were observed for girls as well as boys, r’s = .35 and .23, respectively (Keenan & Shaw, 1994). In some samples, continuity in aggressive tendencies is more evident for girls than for boys. For example, in our longitudinal study of toddlers with familiar peers (Hay et al., 2000), both mothers’ ratings of aggressiveness and observed measures of personally directed force showed significant levels of stability over a 6-month period for girls (r’s = .61 and .47, respectively), but not for boys. Similar patterns are also seen in sibling interaction, where the firstborn child’s hostility to the younger sibling is persistent over a 6-month period for girls (r = .66), but not for boys (Kendrick & Dunn, 1983). Twoyear-olds’ observed initiation of conflict and aggression predicted ratings of externalizing problems two years later for girls, but not for boys (Rubin et al., 2003). Thus, just as female toddlers’ aggressiveness seems more consistent across

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measures and informants, so their forceful and aggressive behavior shows continuities over the years of early childhood. It thus becomes of considerable interest to inquire why there appears to be a discontinuity thereafter. Girls’ antisocial behavior is often linked to a wide range of problems in later childhood and adolescence (Loeber & Hay, 1994; Rutter, Giller, & Hagell, 1998). It is possible that girls who are overtly aggressive in early childhood desist from the overt use of force but continue to manifest other types of adjustment problems thereafter (Rubin et al., 2003); it is certainly possible that they turn to relational aggression (Crick, 1995).

Links with Attributions of Intent Highly aggressive children often make misattributions about their companions’ intentions, and come to be rejected by their peers through a series of misunderstandings (Coie & Dodge, 1998). Children who are rejected by their peers in childhood are at risk for later conduct problems and delinquency, even if by that time they have formed close ties with other deviant teenagers (Cairns & Cairns, 1994). Analogous links between attributions about peers’ intentions and aggression can be discerned in the first years of life. We have seen that a rudimentary anticipation of peers’ intentions can be discerned in the course of toddlers’ conflicts over objects, when one child withdraws or defends an object that is being gestured to by the peer. In our longitudinal study of British toddlers, those children who often responded to peers’ possible designs on their possessions in this way were significantly more aggressive than other toddlers. They were more likely to use personal force against the peer, and, especially, to use it proactively, r’s = .60 to .64. Indeed, defensive reactions to peers’ gestures during the first home visit significantly predicted proactive force 6 months later, r’s = .35 to .45 (Hay et al., 2000). The association between defensive reactions to peers’ possible intentions and the use of force was especially striking for boys. Thus, individual differences in toddler boys’ aggression may be linked to this dimension of social understanding.

RISK FACTORS AND THE EARLY DEVELOPMENT OF AGGRESSION We have seen that behavioral precursors to aggression appear around the time of the first birthday and that stable and coherent individual differences emerge in the 2nd and 3rd years of life. We know that a variety of biological and social risk factors are associated with aggression at later points in the lifespan. Are there any links between the early forms of aggression discussed in this chapter and known sources of risk? In this final section of the chapter, I speculate about some possible risk factors that might operate in early life and therefore influence toddlers’ use of force against their companions.

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Inheritance Behavioral genetics studies have provided only modest evidence for the heritability of overt aggression, as opposed to broader categories of conduct problems and behavioral dysregulation; aggression has been observed directly in only a few such studies, which have shown little evidence for heritability (DiLalla, 2002). One exception is a study of 19-month-olds’ physical aggression (Dionne, Tremblay, Boivin, Laplante, & Pérusse, 2003), which suggests that the striking individual differences in early aggression reported in the studies just reviewed are partly due to genetic factors. Studies that have focused attention on parents’ reports of externalizing problems have shown higher levels of heritability, though also considerable evidence for environmental effects (DiLalla, 2002). It should be noted that measures of externalizing and internalizing problems are highly correlated in the preschool years (e.g., Hay et al., 1999b) and that externalizing scores included items relevant to attention-deficit/hyperactivity disorder (ADHD), which has been shown to be influenced by genetic factors (Thapar, Holmes, Poulton, & Harrington, 1999). Thus, findings regarding the heritability of externalizing problems do not provide direct evidence concerning the genetics of aggression. One possibility for future research is to examine links between psychometric and physiological measures of temperament and children’s overt aggression. Infant temperament has been demonstrated to be heritable (Arcus & Kagan, 1995; Goldsmith, 1996). Individual differences in temperament are under intense scrutiny, particularly in terms of their correlations with patterns of frontal lobe activation (Fox et al., 1995; Calkins, Fox, & Marshall, 1996), production of cortisol (Lewis & Ramsay, 1995; Hertsgaard, Gunnar, Erickson, & Nachmias, 1995; Nachmias, Gunnar, Mangelsdorf, Parritz, & Buss, 1996), and vagal tone (Eisenberg et al., 1995). This literature is complex. Studies of older individuals suggest that both extremes of underreactivity and overreactivity may be associated with aggression. For example, antisocial behavior is sometimes predicted by low heart rate (Raine, 2002) and hyposecretion of cortisol (McBurnett, Lahey, Rathouz, & Loeber, 2000). However, externalizing problems in early childhood are sometimes associated with hypersecretion of cortisol (Gunnar, Tout, de Haan, & Pierce, 1997). This suggests that there may be two distinct pathways to serious aggression; early temperamental features may predict an aggressive career that is characterized by reactive versus proactive aggression (Vitaro et al., 2002). Less is known about the contribution of these temperamental features to very early aggression. It has been noted that aggressive toddlers do not show the same patterns of vagal suppression in response to experimental challenges shown by their agemates (Calkins & Fox, 2002). This was seen both with respect to parental ratings of externalizing problems and overt aggressive behavior with unfamiliar peers.

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Prenatal Insults Prospective longitudinal studies have demonstrated links between prenatal insults and later antisocial behavior (for a review, see Raine, 2002). For example, analyses of large British cohort studies have demonstrated links between maternal smoking and early-onset conduct disorder (Maughan, Taylor, Taylor, Butler, & Bynner, 2001). Similar links between smoking in pregnancy and conduct symptoms have been observed across a range of studies (Wakschlag & Hans, 2002). Mothers’ mental health problems during pregnancy also put infants at risk. In a large British cohort study, maternal anxiety during pregnancy predicted the child’s later externalizing problems (O’Connor, Heron, Golding, Beveridge, & Glover, 2002). Analyses of our own longitudinal data set, the South London Child Development Study, have shown that children whose mothers are depressed during pregnancy are seven times as likely to be diagnosed with conduct disorder at age 11, even when the mother’s later history of depression is taken into account.

The Caregiving Environment Whatever the heritable risk for aggression, it is clear that factors in the caregiving environment potentiate risk. For example, insecure attachment relationships are associated with externalizing problems in the preschool years, especially for boys (Turner, 1991); secure attachment seems especially important for the optimal development of irritable infants (van den Boom, 1995). Avoidant attachment patterns are associated with aggressive behavior in highrisk samples; however, across a wide range of samples, the link between disorganized patterns of attachment and aggression is evident (for a review, see Lyons-Ruth, 1996). The effects of disorganized attachment relationships may be bound up with multiple risk factors, including biological ones. Molecular genetic studies have demonstrated associations between disorganized attachment and the DRD4-7 allele of the dopamine receptor gene (e.g., Lakatos et al., 2003). Structural features of the caregiving environment, such as the mother’s marital status, are also associated with young children’s externalizing problems (e.g., Fagot & Leve, 1998). The impact of family arrangements is often mediated by parental psychopathology and parental behavior (for a review, see Hay & Nash, 2002). For example, analyses of a large British community sample have shown that links between family structure and children’s externalizing problems are mediated by parental depression (Dunn, Deater-Deckard, Pickering, O’Connor, & Golding, 1998). The timing of episodes of depression is important. In our longitudinal study in South London, violent behavior at age 11 was predicted by the mother’s depression during the child’s first months of life, even when family structure and economic status, and the

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mother’s subsequent mental health problems, were taken into account (Hay, Pawlby, Angold, Harold, & Sharp, 2003). There has been relatively little attention paid to the impact of parental psychopathology on aggression in the first years of life. However, two correlates of maternal depression—lowered responsiveness and irritability—clearly influence early aggression. Maternal responsiveness to sibling conflicts decreases the chance of aggression being used (Perlman & Ross, 1997). Maternal negativity increases toddlers’ aggression with peers (Rubin et al., 1998). In a large multisite analysis of the impact of infant day care on peer relationships, toddlers’ aggression against peers was predicted by maternal sensitivity, as well as by the day caregiver’s behavior (NICHD Early Childcare Research Network, 2001). The amount of time spent being cared for by someone other than the mother appears to have a modest but significant effect on children’s subsequent externalizing problems, even when factors such as maternal smoking and depression are taken into account (NICHD Early Childcare Research Network, 2003). It is not clear, however, what dimensions of the child care experience foster aggression. Several possibilities deserve testing. For example, to the extent that adult intervention in children’s quarrels reduces aggression (Perlman & Ross, 1997), it is important to know whether child care workers are inclined to intervene, or whether they instead believe it is important for children to work out their own problems. Second, and more controversial, although harsh discipline is generally associated with children’s externalizing problems, some evidence suggests that there may be positive effects of punishment in the toddler years (Baumrind, Larzelere, & Cowan, 2002). To the extent that toddlers’ aggression is not punished or otherwise dealt with by child care workers, it may stay within the children’s repertoires. Finally, peer influences foster aggression when children are aggregated into groups. There is considerable evidence for the ill effects of group-based interventions for aggressive children in middle childhood and adolescence (e.g., Dishion, Bullock, & Granic, 2002). It is time to investigate whether similar effects of spending the day with peers who are at the peak age for aggression (i.e., between 2 and 3) similarly encourages externalizing problems in toddlers. However, it should be noted that physical aggression is shown more often if children are cared for by their mothers in high-risk homes than if children from low-risk homes attend day care (Borge, Rutter, Côté, & Tremblay, 2004).

CONCLUSIONS The behavioral precursors to aggression in early life are neither random nor trivial. Yet these behaviors, for the most part, occur at low rates. In several samples, personal aggression occurs too seldom to be included in statistical analyses. Instrumental aggression is rather more common, but shows a clear decline over time. Some toddlers, however, use force at higher rates than their

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peers and do so proactively and with greater intensity. These individual differences in the rate at which force is used do not derive solely from situational factors. There is consistency across different measures, and stability over time. Individual differences in early forms of aggression are associated with biological and social risk factors. This has important implications for theory and practice. With respect to developmental theory, additional research on the early origins of aggression would help resolve current debates. For example, classic social learning accounts of aggression (e.g., Bandura & Walters, 1963), which long held sway in developmental theory, have been challenged; children do not need to learn how to be aggressive. At the same time, the search for biological underpinnings of aggression has been hampered by problems of measurement, with only a few genetic studies attempting to assess aggression directly. This is partly because it is neither convenient nor safe for psychologists to be lurking about when serious violence is taking place; they rely on selfreports, informants’ testimony, projective tests, and laboratory simulations. However, as we have seen, toddlers are not loath to use direct force against their companions. Their use of force can be easily and reliably measured within genetically informative designs (e.g., Dionne et al., 2003). There is accumulating evidence that aggression is influenced by both biological and environmental factors. Gene–environment correlations and gene– environment interactions are both likely to be important. This point has been underscored by the recent molecular genetic evidence concerning the risk for antisocial behavior in genetically vulnerable individuals who have been mistreated (Caspi et al., 2002). Normative biological processes underpin the development of aggression, but individual differences are affected by social as well as biological factors. Thus, I argue that the early development of aggression entails the gradual attainment of an “aggressive competence,” that is, the ability to deploy physical and verbal aggression effectively in conflict situations in a species-characteristic manner, using the advantages of our fists, our opposable thumbs—so good for pinching and pulling hair—and our powers of hurtful speech. The appearance of distinctive forms of human aggression is then followed by the flowering of individual differences in “aggressive performance,” influenced by an interaction between the child’s own temperament and social input. Personal aggression soon becomes even more of a minority phenomenon, and the development of other, more socially acceptable ways of pursuing one’s selfinterest leads to a decline in the boorish seizing of other people’s things. Girls as well as boys develop the basic “aggressive competence,” but they are likely to desist sooner. Indeed, what happens to girls may qualify as one of the most effective social intervention strategies ever attempted. With respect to social policy and clinical practice, it is vitally important to take on board the fact that some toddlers are already showing serious aggressive tendencies. The belief that early aggression is normative, and perhaps even desirable, may blind us to important individual differences. Some 2-year-

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olds use force against their companions at rates considerably higher than the norm. This bodes poorly for adjustment to preschool groups and for later social life. We know that some preschool children are already showing oppositional behavior and conduct problems of clinical concern (Keenan & Wakschlag, 2002). It is important to support infants’ and toddlers’ early development and thus prevent the consolidation of early individual differences into entrenched aggressive careers.

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7 Play and the Regulation of Aggression J ORDAN B. P ETERSON and J OSEPH L. F LANDERS

INTRODUCTION: AGGRESSION, EMPATHY, AND SOCIAL BEING ARE ALL INNATE With what simplicity would I have demonstrated that man is naturally good and that it is through these institutions alone that men become bad. —ROUSSEAU, Discourse on the Arts and Sciences (1750/1974) Hereby it is manifest, that during the time men live without a common Power to keep them all in awe, they are in that condition which is called War; and such a war, as is of every man, against every man. —HOBBES, The Leviathan (1651/1909)

Since the 1960s, our culture has leaned powerfully toward the developmental philosophy of Rousseau: Children are naturally self-regulating, creative, positive, and good. Only the arbitrary forces of culture make them bad. Carl Rogers (1989, p. x), a psychologist perhaps more responsible than any other for the modern promotion of Rousseau’s viewpoint, makes the following observation: Man is [a] basically trustworthy member of the human species, whose deepest characteristics tend toward development, differentiation, cooperative relationships . . . whose impulses tend naturally to harmonize into a complex and changing pattern of self-regulation; whose total character is such as to tend to

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THE DEVELOPMENT OF AGGRESSION preserve and enhance himself and his species, and perhaps to move it toward its further evolution.

But is it really true that in our more aggressive moments we are all merely innocent victims of our cultures? Hobbes (1651/1909) believed very much the opposite: In his state of nature, there is no place for industry, because the fruit thereof is uncertain: and consequently no culture of the earth; no navigation, nor use of the commodities that may be imported by sea; no commodious building; no instruments of moving and removing such things as require much force; . . . no account of time; no arts; no letters; no society; and which is worst of all, continual fear, and danger of violent death; and the life of man, solitary, poor, nasty, brutish, and short.

Many cultures tilt strongly toward Hobbes: The child is a force of nature, willful, destructive, capable of self-harm, in dire need of careful, cautious, and intense socialization, and damned in the absence of social order (Fischer, 1989). What might a modern psychologist say about this debate, given the progress in the behavioral sciences over the last century? Is the human being a noble savage, corrupted by the stresses of civilized social being, or a beast of prey, selfish and cruel? To answer this question properly, it is necessary to consider evidence derived from a diverse sampling of the behavioral sciences and to reframe the argument: What tendencies to aggression, if any, characterize the human species, and what mechanisms, individual and social, regulate and constrain those tendencies? It should first be noted that the psychoanalytic viewpoint is not a simple derivative of the Hobbesian perspective, in the same way that the humanistic view is of Rousseau’s. Freud proposed that aggression was innate, part of the id, noting that aggression emerged as a consequence of socially induced frustration in the form of conflict between the pleasure and reality principles. In the psychoanalytic world, the id (nature), the ego (the individual and his or her subjectivity) and the superego (culture) are all good and bad, simultaneously. In keeping with this conceptualization, it appears that aggression is a natural component of our behavioral repertoire, emerging far back in the sequence of development, and not something added secondarily to an essentially peaceful temperament. Young children appear fundamentally egocentric (Piaget, 1932). They hold their own intrinsic desires paramount and exist in a world where those desires are bounded only by their immediate consequences. They reliably begin to manifest aggressive behaviors such as pushing, hitting, kicking, and throwing about 18 months of age, although there is wide individual variability in the frequency with which these behaviors are manifested (Nagin & Tremblay, 1999). Such aggression, manifested in defensive or instrumental form (Vitiello & Stoff, 1997), appears dependent on the operation of very low

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level, early-maturing brain structures, such as the hypothalamus or periaqueductal grey (reviewed in Peterson & Shane, 2004). The incidence of aggressive behavior peaks, surprisingly, in kindergarten, and then declines over time (Nagin & Tremblay, 1999). By age 4, most children have become social. The small number who have not (Nagin & Tremblay, 1999) tend to be aggressive for the rest of their lives (Coie & Dodge, 1998). Chronically aggressive children, then adults, lack empathy, are suspicious, narcissistic, and self-centered (Coie & Dodge, 1998), and are characterized by inappropriate and brittle high self-esteem (Olweus, 1994; Bushman & Baumeister, 1998). Few interventions appear helpful. Chimpanzees, our surprisingly close cousins (Sibley & Ahlquist, 1984), appear primally aggressive within their social groups, in the same manner as children. Most of their within-group aggression appears related to dominancehierarchy maneuvering, as it does in the human case (Wilson & Daly, 1997). Such maneuvering appears to initially manifest itself in the innocuous and easily overlooked form of teasing. De Waal (1996, p. 114) states: [Chimp youngsters] throw handfuls of dirt or pebbles at their elders, hit them with sticks, splash them with water, jump on their heads when they are dozing, and so on. Much of the time, the individual thus bothered takes it remarkably well, tickles the youngster, or makes a mock chase that turns the whole incident into a game.

Teasing techniques transform with age, becoming less frequent, but more severe. The infant engages in little pushes from behind, jumping away when the adult turns around. The adolescent male, in contrast, manifests full-fledged charging displays, seeking to dominate his peers, the adult females that surround him and, eventually, higher-ranking adult males. As adults, chimps form sophisticated coalitions, jockeying for position and, upon occasion, physically engage and dominate or subordinate themselves to other individuals in conflicts that can become violent (De Waal, 1996). Dominance-hierarchy position appears to be a vital determinant of survival and reproductive success. In consequence, little is more important to a social animal than accurate representation of who rules and who is subordinate under what circumstances (Abbott et al., 2003; Virgin & Sapolsky, 1997). The establishment and maintenance of a predictable dominance hierarchy allows for the emergence of orderly access to desirable resources, so that every attempt at consummation within the social environment does not immediately escalate into an aggressive encounter. Tracking dominance and other social information is so important that group size appears as an important correlate of neocortical size in primates, particularly in regard to brain systems devoted to analysis of complex relationships (Joffe & Dunbar, 1997). This all means, of course, that advancement is frequently worth fighting for. The fact of innate dominance striving, buttressed by the mechanisms of aggression, does not mean that chimps or humans lack social feeling and sim-

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ply learn to inhibit their aggression through fear or through cognitively mediated calculation of the potential consequences of aggressive behavior. Primates are as gregarious as they are aggressive—even in the immediate aftermath of intense agonistic encounters (De Waal, 1989b). It appears, therefore, that agonistic and cooperative behaviors are not necessarily opposed to one another, at least not in any simple manner. First, more innately aggressive social creatures may also have to be more innately affiliative (De Waal, 1989b), in order to find and maintain social support, which is even more important to them than the objective safety of their environment (Abbott et al., 2003). Second, at any given time or place, individual action and social interaction can be characterized by cooperation at one level, and competition at another. Among intensely social animals, the social group, the dominance hierarchy, the superordinate level, clearly constitutes a form of extended cooperation. Within that group, however—that cooperative space, the subordinate level— dominance striving takes place. It appears, therefore, that the essentially aggressive instincts appear complexly counterbalanced by the interplay of two equally powerful domains of regulation, one internal and innate; the other, social and emergent. The internal process that regulates aggression (in addition to simple fear) seems to be empathy or, perhaps, identification—the ability to feel the experiences or to adopt the viewpoint of another, respectively. Whether such ability emerges as a consequence of conditioning, emotional contagion, or cognitively mediated understanding, the evidence for its existence is strong (Preston & De Waal, 2002). The circuitry that governs empathy—or its close variants, love, affiliation, and nurturance—is arguably as archaic and deeply rooted as that motivating aggression (Preston & De Waal, 2002; Panksepp, 1998a) and appears to play a modulatory role, regulating the intensity of response to those deemed kin. A wide range of animals exhibit sophisticated reactions to the distress or actions of their conspecifics: Rats appear visibly upset by the sight of another rat receiving electric shocks (Rice & Gainer, 1962; Rice, 1964); hyenas can be primed to eat and drink by the sight of their group mates doing the same, even when they are not visibly attending (Yoerg, 1991); and rhesus monkeys will starve themselves if they learn that their food gathering efforts culminate in the shock of a conspecific (Masserman, Wechkin, & Terris, 1964). Human infants, in turn, respond with crying to the crying of other infants (Zahn-Waxler, Radke-Yarrow, & King, 1979) and, after the first year, imitate the distress behaviors of others and spontaneously manifest helping behaviors (Zahn-Waxler, Radke-Yarrow, & Brady-Smith, 1977). Furthermore, Miller, Eisenberg, Fabes, and Shell (1996) have noted that older children who manifest facial expressions of concern when exposed to the suffering of others are characterized by higher levels of moral reasoning and increased prosocial behavior. The social process that regulates aggression appears more integrally associated, as mentioned earlier, with dominance-hierarchy structure. Chimps are perfectly capable of killing while hunting and during raiding parties con-

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ducted on foreign conspecifics (Wrangham & Peterson, 1996), so there is clearly no necessary internal limit on their aggressive behavior. It appears, as well, that the tendency toward dominance striving among chimps can at least temporarily override any innate tendency toward empathy during intense agonistic within-troupe disputes. De Waal (1989a) has suggested that under such conditions it is the whole chimp troupe that constrains the “ambition” of the individual, becoming agitated en masse and interfering, actively, with any dominance battle that goes too far. Preston and De Waal (2002) have taken pains to outline the nature of those factors that modulate the expression of empathy: Familiarity and perceived similarity, as well as factors such as learning, past experience with the cause of suffering, and the salience of the observed suffering all affect empathic responding. What this means is that social forces can alter the probability that empathy will inhibit aggression by altering the nature of the factors that modulate both. The consequences of extended social being, however, are more indirectly associated with aggression regulation and appear related to the function of neural circuits that mature later in a predictable, regulated, and orderly social environment. If human children are socialized within such an environment, they learn socially acceptable but more complex alternatives to violence. They begin to integrate their own proximate desires with distal wishes and to consider and allow for the wants and needs of others. The human child appears to face the world with a basic set of functional motivational states, mediated by low-level but sophisticated brain circuits governing action, setting the frame for perception, emotion, and cognition (Gregg & Siegel, 2001; Peterson & Flanders, 2002; Swanson, 2000). The operation of these circuits enables the child to identify and pursue valuable goals such as food, water, warmth, social affiliation, self-protection, and the exploring of new territory (Swanson, 2000; Gregg & Siegel, 2001). Each primary motivational circuit sets a unidimensional goal for behavior (Swanson, 2000), so that the child’s first developmental requirement is to learn how to attain that goal. Second, however, he or she must learn how to balance all those primary goals and to determine how they might find their fulfillment within a complex interpersonal environment. The emergence of the emotional circuits, one stage above those governing motivation, helps fulfill this second set of requirements, as does the development of prefrontal circuitry, designed to modulate motivation and emotion and to extend comprehension of the consequences of action across broad spans of time and place (Oatley & JohnsonLaird, 1987; Oatley, 1999; Peterson, 1999). Initially, the child’s mother provides what is needed, with minimal demands for reciprocation. However, as the child grows, expectations for reciprocity grow. He or she enters a world characterized by long-term considerations and by the presence of other people who have goals and feelings of their own. These goals and feelings have to be taken into account, as they manifest themselves in the same environment that provides opportunity for the developing child. This means that the child must solve not only the prob-

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lem of his or her own instincts and their interactions, but also the problem of the instincts of others, in combination with his or her own. The movement toward such solution appears to be mediated, at least in part, by empathy, and then by play. The child appears intrinsically able to experience the motivations and emotions of others. He or she is capable of affiliative instincts and is prepared to be a social animal, cooperative and supportive, as well as competitive and agonistic. The development of social understanding appears to take place from the bottom up, in a kind of bootstrapping process. Rough-and-tumble (R&T) play, mediating and regulating direct physical contact, allows the child to attune his or her body to the embodied presence of others. More abstract forms of play allow for the attuning of motivational states, emotional reactions, and the contents of consciousness over increasingly large spans of space and time. Role play and fantasy mediate abstract forms of identification and the consequent extension of empathy to those beyond the immediately familiar. Finally, the adoption of a role, part fiction and part genuine being, constitutes the establishment of a functional position within a real-world hierarchy of cooperation and dominance. Numerous researchers have sketched the developmental effects of childhood play. Such effects include enhanced physical fitness and improved cognitive, emotional, and social function (Pellegrini & Smith, 1998). Less attention has been paid to the manner in which play cultivates self-regulation. Play, however, might well be regarded as early social cognition: If I can play with you, I can adapt my actions and reactions to yours. I can allow your motivational and emotional states, your reference frame, to modulate mine. I can start to act out your frame, to understand and to embody it. Eventually, perhaps, we can share the same perspective and use the fact of that sharing to work cooperatively toward a common goal. This means that we can start to share identity, predicated on voluntary compliance with the same set of values, and benefit mutually from the consequent control of aggression—not so much because of inhibition, but because of the alignment of mutual desire. This ability unfolds, over time, in a lengthy developmental process—one that appears to start not so much with the mind, as might be initially predicted, but with the body, in direct, physical contact with the bodies of others.

ROUGH-AND-TUMBLE PLAY AND THE EMBODIED NEGOTIATION OF DOMINANCE AND COOPERATION Pellis and Iwaniuk (2000, p. 136) state that “species with a greater proportion of their growth occurring postnatally play more and have more complex play than do species with more of their growth occurring prenatally,” in keeping with Bruner’s (1976) suggestion that the prolonged infancy of humans provides more time for play and more time to develop sophisticated cognitive abilities. Panksepp (1998a) has argued, specifically, that the mammalian brain

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is hard-wired for play—at least for rough-and-tumble (R&T) play. Juvenile rats, for example, exhibit R&T play beginning at 17 days of age, even when prevented from engaging in any prior play experiences, and will play more vigorously if intermittently deprived of the opportunity to do so. However, these early play impulses appear to manifest themselves only under the appropriate conditions. Fear and hunger and associated states of deprivation quickly eliminate play. Young rats must also have a secure home environment, with abundant parental involvement, to play. R&T play is different from exploratory activity and from aggression—two forms of behavior with which it can easily be confused. R&T play and exploratory activity share the fact that both are enjoyable. Habitual R&T play winners and losers will engage in effortful instrumental tasks to gain an opportunity to play, for example, indicating that play episodes are reinforcing, and both will run toward the play arena at equal speeds. (The winners enter confidently, however, while the losers move in more timidly and slowly.) Such enjoyment appears mediated in part by the same dopaminergic incentive reward circuits that underly exploratory behavior, although play also activates widespread release of opiates, particularly in those areas characterized by circuits for sexual, maternal, and other affiliative behaviors (Panksepp, 1998a). However, dopamine (DA) agonists such as amphetamines invigorate exploratory activity, but markedly reduce play. Finally, formal behavioral analysis clearly discriminates R&T play from genuine aggression. A playful rat chases his or her partner around in a “flurry of dynamic, carefree rambunctiousness” (Panksepp, 1998a, p. 284), pouncing on the partner, pinning him or her, in the consummatory stage of each play episode. Such pinning is clearly a gesture of dominance, but not one that breaks the rules of play. In a real fight, rats box, and prance sideways, postures and gestures accompanied by piloerection. Furthermore, in genuine dominance bouts, the resident animal consistently wins if the activity occurs in the animal’s home territory. This is not the case in play fighting (Panksepp, 1998a). Finally, pins during a real battle are more sustained and menacing than they are in playful contexts. Play fighting and genuine aggression appear as distinguishable within the context of human behavior as they are among rats. Blurton Jones (1972), for example—taking a cue from Harlow and Harlow’s (1965) observations of play fighting in young rhesus monkeys—clearly differentiated R&T play from physical aggression among preschool children. Children involved in a play fight wrestle, grapple, jump, tumble, and run, while laughing and exhibiting facial expressions of enjoyment. In addition, in play fighting contexts, children spend most of their time in close proximity, whereas they come together briefly for a genuinely aggressive act and then pull away rapidly. Positive emotional expressions are also markedly absent on such an occasion. Despite these relatively subtle differences, children are highly adept at distinguishing playful from aggressive fighting (Smith & Boulton, 1990; Boulton & Smith, 1992), regardless of their culture (Costabile et al., 1991), and play fighting gestures

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exchanged between experienced children seldomly elicit a hostile response (Boulton, 1991). Children who become skilled at R&T play learn directly what forms of agonistic interaction will be tolerated by others, and carefully and judiciously limit the social expression of their aggression. Mothers are the first to initiate R&T play cycles with their infants, through tickling bouts and mocked acts of aggression. As motor coordination develops and children become more active, fathers, who play more robustly, become the play partners of choice (Roopnarine, Hooper, Ahmeduzzaman, & Pollack, 1993). Maternal depression and paternal absence are therefore associated with childhood externalizing behavior problems (Bates, Bayles, Bennett, Ridge, & Brown, 1991; Pagani, Boulerice, Tremblay, & Vitaro, 1997; Patterson, Reid, & Dishion, 1992). Depressed mothers are less likely to tickle and play peek-a-boo with their infants (Field, 1998). Older children of single mothers have fewer opportunities to learn to regulate aggressive behavior, inasmuch as fathers tend to engage in play fighting after the end of the first year. Such children appear awkward when invited to engage in R&T play. Accidentally, or motivated by frustration, they more frequently hurt their play partners. The victims respond with rejection. Aggression emerges in response to this rejection (Asher & Coie, 1990; Smith, Hunter, Carvalho, & Costabile, 1992), and a detrimental positive feedback cycle establishes itself. The broader nature and significance of R&T play, as well as its role as a scaffold for more sophisticated social cognition, may best be revealed within a broader conceptual framework, including both Piagetian and neuropsychological components. As the child develops, he or she experiments, stage by stage, with the construction of small-scale motor patterns, designed to attain small-scale, motivated ends. Piaget (1932, pp. 16–18) points out, for example, that in the initial, primary stages of play, a child handles objects at the dictates of his or her “desires and motor habits.” Because “play is purely individual” at this stage, “ritualized schemas” develop—skilled play habits—but no collective patterns, much less rules. The child first plays by him- or herself, constructing a repertoire of functional actions, then conceptions, from the bottom up. Swanson (2000, p. 115–116) describes the physiology underlying the construction of such a functional hierarchy: The lowest or first level of the locomotor system is formed . . . by a subset of motoneuron pools in the spinal cord ventral horn that innervates the limb muscles responsible for locomotor behavior. The second major level is referred to as the locomotor pattern generator, which lies entirely within the spinal cord, near the motoneuron pools that it regulates. In fact, it is itself a hierarchy of increasingly complex motor pattern generators that coordinate and time muscle contractions across individual joints, then across multiple joints within a particular limb, and finally amongst all four limbs. . . . A third major level is represented, at least in part, by an ill-defined region of the dorsal tegmentum known as the mesencephalic locomotor region, and rostroventral to this is a fourth major level in an ill-defined region of the caudal hypothalamus/rostral midbrain—the so called subthalamic or hypothalamic locomotor region.

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This hypothalamic locomotor region, a locomotor pattern controller, generates downward outputs to the spinal locomotor pattern generator, and is the next control system to develop, as the individual constructs increasingly complex hierarchies of motor behavior. It is of interest to note, in this regard, (1) that tactile stimulation during infancy—an important aspect of R&T play, and one linked to it through the specialized skin receptors involved in such play (Panksepp, 1998a)—has an important organizing and stabilizing effect on different brain structures, including the hypothalamic–pituitary–adrenal (HPA) axis (Lande, Scarr, & Gunzenhauser, 1989; Meaney, Aitken, Van Berkel, Bhatnager, & Sapolsky, 1988), and (2) that children with chronic aggression problems are frequently characterized by dysregulated HPA activity (McBurnett, Lahey, Rathouz, & Loeber, 2000; Van Goozen, Matthys, CohenKettenis, Thijssen, & Van Engeland, 1998). Traumatic experience during infancy is one of the factors that can cause permanent alterations to the HPA axis by detrimentally affecting steroid receptor function in the hippocampus and the prefrontal cortex. Piaget’s emphasis on embodiment and procedural knowledge (given physiological grounding by Swanson) is particularly clear in his description of the earliest play stages. Before stateable rules emerge, there are behavioral patterns. These arise first under the control of internal motivation, and then as a consequence of social interaction. As the child progresses toward Piaget’s second stage—the first point at which the social world has any major impact— more complex understanding emerges. First, the child starts to copy him- or herself, using procedure to map procedure, at the initial but still embodied stage of genuine representation. The child experiments, initially, using trial and error to attain his or her goals. Any successful action is immediately imitated and practiced. In this manner, the child builds a repertoire of voluntarily accessible, practiced, and automatized motor schema (Piaget, 1932). The imitative process then extends itself to interpersonal action, and the child becomes capable of imitating others. It should be noted, however, that even at this second, imitative stage, the child is still not genuinely playing with others. He or she engages in socially constructed and possibly sanctioned means of playing, but is neither trying to win nor attempting to unify the various modes of playing individually developed or imitated. Nonetheless, at this stage, patterned social interactions can arise spontaneously as a consequence of the interaction of motivated and emotionally driven participants, who are constantly exchanging information about which actions and reactions are acceptable and mutually shaping shared behavior. Although such primary social interaction may look “rule governed” to an observer, because of its regularity, it is still instantiated at a purely procedural, implicit level. It is possible, nonetheless, to see the emergence of a procedural morality at this level. Panksepp (1998a) describes the manner in which rats learn to govern their pinning behavior: Stable patterns of play dominance, corresponding to the establishment of complex, socially modified motor behaviors, rapidly emerge during R&T play. One rat ends up on top more often

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during pinning, in repeatedly matched play pairs. However, if the dominant rat pins its playmate more than 70% of the time, the subordinate, who typically initiates the play sequence, begins to ignore the victor, and playful activity gradually diminishes (Panksepp, 1998a). This means that the dominant rat must learn to respond carefully to the behavioral cues of the subordinate. If the subordinate breaks the shared play frame by escaping or biting, as a consequence of undue frustration or anxiety, then its value as a playmate rapidly decreases. Whether this is morality, or merely conditioning, is beside the point. Such modulation still constitutes the beginning of social behavior, laying the basis for the development of the higher-order morality that keeps aggression properly regulated. The child is alone, at the first stage of play, constructing the basic elements of motor competence—grasping, letting go, extending and contracting limbs—adapting him- or herself to his or her own motivations and their interactions in an increasingly complex world of objects. Then the child starts to combine those actions, sequencing multiple motivated patterns of action, under the guidance of higher-order control systems. The child’s isolated manner of being takes on a social aspect with the onset of R&T play, and he or she begins to establish socially modulated behavioral patterns. R&T play, in turn, shades into dramatic play, laid down in its most fundamental aspects over the sensorimotor substructure constructed first by the individual and then modified by R&T play. As play becomes increasingly dramatic, increasingly abstract, the substructure for the highest stages of social cognition begins to establish itself.

ABSTRACT PLAY AND THE COOPERATIVE ESTABLISHMENT OF JOINT FICTIONAL WORLDS During R&T play children use their bodies in playful dominance interactions, modifying and constructing motor schemas that take the other’s qualities into account, learning to control anxiety, frustration, and the thrill of victory. Some of this control is best understood as inhibition. Whalen & Henker (1991) reported, for example, that theories of impaired behavioral control appeared more relevant to understanding the interpersonal problems of young children with attention-deficit/hyperactivity disorder than theories of impaired social cognition. Hughes, White, Sharpen, and Dunn (2000) noted, likewise, that conduct disorder in 4-year-olds was associated with problems in executive function (associated with inhibitory control), but not with problems in performance on higher-order theory of mind tasks. Séguin, Zelazo, and Tremblay (1999) associated physical aggression among preschoolers with deficits in self-regulatory cognitive skills, and Séguin, Pihl, Harden, Tremblay, and Boulerice (1995) associated aggression among older children with impaired executive or prefrontal function.

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However, theories of inhibition appear insufficient to account for more complex forms of aggression regulation, because they do not take into account the emergence of cooperative behaviors and conceptions, designed to maximize the utility of social being. These are better understood, perhaps, as sophisticated alternatives to aggression, instead of mechanisms that inhibit, govern, or regulate aggression. To cooperate means to establish a mode of occupying the same space as other individuals in a manner that makes aggression positively counterproductive. The groundwork for this ability appears to be scaffolded at the sensorimotor level—mediated, perhaps, by R&T play— but the ability itself is something different: something more akin to the understanding of narrative, drama, and fiction; something more like the development of explicit theory of mind. Higher-order, more explicit, cooperative morality appears to emerge around Piaget’s (1932) third developmental stage, appearing at about age 7. At this stage, each child playing a given game starts to try to win—tries to dominate the narrow hierarchy of achievement specified and constrained by the rules of the game. At first glance, this appears as something essentially competitive. However, for individual victory to occur, the modes of playing between children have to be unified so that all players share the same goal. This means that any disagreements about the game have to be resolved, and that aggression emerging as a consequence of those disagreements must be rendered unnecessary, before any attempt to play, let alone win, can even begin. Piaget notes that this more complex form of play appears to emerge procedurally as well, rather than explicitly. Within the confines of a given group game, where each child can check him- or herself against the behavior of the others, conflict-free, stable, patterned playing quickly emerges. However, if the playing children are separated and interviewed individually, they give disparate or even contradictory accounts of the emergent game’s formal “rules.” At this third stage, children are just beginning to map the contours of their structured social behavior into truly representational linguistic patterns. They still need the information provided by the presence of the others to maintain adherence to the predictable pattern of the game. Once a joint social ritual or game is firmly established, however, its nature can be explicitly described and codified. As a consequence of emerging cognitive ability, and because the child can test his or her explicit verbalizable hypotheses against those of others, the patterns that actually constitute the game and the explicit description of the game come into alignment. At this point, the child has successfully “mapped” his or her own socially modified sensorimotor output, as well as that of the play partners, and becomes a conscious player (Piaget, 1932). Such convergence means that children playing the same game come to inhabit the same fantasy-predicated fictional or dramatic world. It appears to be the ability to establish such joint fictional habitation— more than alignment of motor patterning, more than inhibition of aggressive responding—that constitutes cooperation, and that allows for the modulation

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of motivation and emotion toward some shared end. In a good game, everyone has fun. There is no need to be defensive. There are many opportunities for joint gain. In consequence, there is little need for violence. To understand the organization characterizing complex social play, it is important to note that innate motivational systems are not simple deterministic systems of drive. Nor do these systems merely set goals, although they do that as well (Swanson, 2000). Instead, states of motivation serve as axioms or predicates of experience, providing a delimited, bounded, but flexible, frame for perception, emotion, cognition, and action (Barsalou, 1983; Peterson & Flanders, 2002). With the establishment of such a frame, the more sophisticated goal-oriented individual can strive toward necessary goals in multiple nonreflexive manners, instead of mindlessly heading in a single, familiar, but potentially counterproductive, direction. Such frames appear to be governed by low-level brain circuitry, primarily within the hypothalamus, but also depend on the extended processing resources of the limbic system and cortex. Motivationally bounded states or frames are manifold in number, as there are qualitatively different states of motivation (Rolls, 1999; Swanson, 2000), and they manifest themselves singly and sequentially, as processes of perception, emotion, cognition, and action must be directed toward specified, limited and sequential targets (Miller, 1956; Cowan, 2001). Each frame appears to contain particularized conceptualizations of the current state of affairs, as well as the desired end (Peterson, 1999; Peterson & Flanders, 2002). The individual or individuals operating within the confines of a given story move from present to future in a linear track. Two points define such a track, or line. A present position cannot be defined without a point of future contrast. Likewise, a potential future cannot be evaluated—judged affectively as better— except in terms of a present position. A verbal description of such a conceptualization can be regarded as the most basic form of fiction—drama, narrative, and, not infrequently, game (Peterson, 1999). The construction of a fiction-like frame, simplified by the momentary domination of a single motivational state, helps specify what ends action should pursue and what phenomena might be considered as objects in that pursuit (Hacking, 1999; Lakoff, 1987; Tranel, Logan, Frank, & Damasio, 1997; Wittgenstein, 1968). The immature individual or child, pursuing his or her purely individual goals, acts and perceives in a solipsistic world, established in accordance with those goals. As the developing individual becomes more complex, however, control over the contents of the goal-framework starts to become more differentiated, so that although fundamental underlying motivational states still have access to it (in cases of mounting hunger or thirst, etc.), so do emergent systems of even more complex control. The hippocampus, for example, allows for determination by context or situation (LeDoux, 1996), while the orbitofrontal–prefrontal cortex allows previously unvalued but learned goals to attain the status of true value (Krawczyk, 2002). The dorsolateral–prefrontal cortex, finally, allows complex, abstracted frameworks to govern behavior, removing the developing individual from the

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incessant short-term demands of basic motivational states (Pochon et al., 2002). This sequentially emergent access by higher-order systems to motivational framing appears to allow the individual to formulate goals that take multiple states of motivation and the vagaries of external context into account. “External context” also constitutes social being: the fact of motivated others, singly and in groups, who are also rank ordering their values hierarchically, and implementing their motivational worlds, while constantly exchanging motivational and emotional information with one another. The individual construction of a motivationally predicated frame or story allows an individual to specify starting place, goal, objects of perception, and implication for emotion, and to therefore deal with those bits of the world relevant to a particular need or desire. The joint construction of such a frame, such a story, integrates perception across individuals, placing them in the same world of objects at the same time it aligns their emotions. Such construction allows more than one individual to inhabit the same experiential goal-directed space and to thereby cooperate, voluntarily, to reach the goal and to maintain the integrity of the space. This is the process by which fundamental agreements, nullifying the very necessity of aggression (rather than merely inhibiting its expression), come into being. The specific circuitry mediating the establishment of such agreement has been recently outlined, provisionally, at the prefrontal–cortical level. Rizzolatti, Fogassi, and Gallese (2001) describe a localized class of visuomotor neurons constituting the “mirror neuron system.” First described in monkeys, mirror neurons are located in area F5 of the ventral premotor cortex. This area contains neurons that code “goal-related” motor acts, such as grasping by hand and by mouth. Rizzolatti et al. (2001) state, in regard to these neurons: “Some of these cells are motor neurons, others also respond to visual stimuli. Some of them are activated by the presentation of three dimensional objects, whereas others—mirror neurons—require action observation for their activation” (p. 661). Mirror neurons, part of the system that uses motor output patterning as part of what occurs during an act of “perception,” have a number of remarkable properties. First, they do not respond to the presence of a motivationally significant object (say, an apple) in isolation. Nor do they respond to the sight of a conspecific engaged in a context-independent action (making a grasping action). But they do respond to the sight of a conspecific making a grasping action in the presence of a motivationally significant object. More to the point, their pattern of action when observing such a motivated sequence precisely matches their pattern of action when that sequence is undertaken by the observer. Rizzolatti et al. (2001, p. 662) note that this neural “congruence is sometimes extremely strict. In such cases, the effective motor action and the effective observed action coincide both in terms of goal (for example, grasping) and in terms of how the goal is achieved (for example, precision grip).” In other cases, however, the congruence is broader, matched more to the broad goal of the action. The action of these less specific neurons is of even greater

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interest, because their broader response pattern is not a sign of inaccuracy, but of increased sophistication: They are capable of “imitating” more approximate patterns of motor output—those that generalize the goal of the observed action across many instances of it. . . . [T]he novelty of these findings is the fact that, for the first time, a neural mechanism that allows a direct matching between the visual description of an action and its execution has been identified. Such a matching system constitutes a parsimonious solution to the problem of translating the results of the visual analysis of an observed action… into an account that the individual is able to understand. (p. 662)

Such understanding appears complete and comprehensive, stretching from the abstract, through the emotional, to the physical. The motor system underlying mirroring accepts neural inputs from systems governing sensation, cognition, and circadian state and has three primary divisions of output: somatic, endocrine, and neuroendocrine (Swanson, 2000). Descending control systems from higher-order, “limbic” structures such as the amygdala governing affective response have also been well described (LeDoux, 1996). Furthermore, area F5, which contains the mirror neurons, shares connectivity to inferior parietal lobe with area “a” of the superior temporal sulcus—a brain area that is part of a circuit including the amygdala and orbitofrontal cortex (Amaral, Price, Pitkanen, & Carmichael, 1992). This combination of facts implies that the matching described by Rizzolatti extends past action patterns to the associated emotional, motivational, cognitive, and neuroendocrine consequences and concomitants of those action patterns. To understand someone therefore begins to appear more and more like walking a mile in his or her skin, rather than in his or her shoes. This a hypothesis appears even more compelling once careful attention is paid to the additional neuroanatomical and functional significance of area F5, the monkey homologue of Broca’s area in humans—the prefrontal area governing voluntary speech. This anatomical equivalence suggests that the primary purpose of verbal communication could well be the exchange of motivated patterns of action, instead of the description of the objective world (Peterson, 1999). Furthermore, it appears to be the association between the mirror neuron system and speech that allows verbal communication to take on its embodied, imitation-provoking meaning. These ideas appear critically important in regard to understanding and considering the importance of dramatic social play and associated forms of narrative. Imagine that the developmental elaboration of the mirror neuron system allows the maturing child to embody the action and motivational states of those he or she observes first, directly, with more or less faithful and precise mimicry. Then imagine that the interrelationship between the linguistic abilities of Broca’s area and the mirror neuron circuitry allow communicating children to verbally instantiate shared motivated or goal-oriented states, not at the level of precise imitation, but at a

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higher, generalized state. This means that cooperating and communicating children, engaging in pretend play, can jointly establish fictional worlds and then coordinate their motivations, their actions, their emotions—their very object-perceptions—within those worlds. Finally, imagine that this process of coordination within the confines of a fictional world constitutes the process of scaffolding that underlies (1) the understanding of narrative and fiction, in their verbal forms, (2) the capacity to engage in large-scale, cooperative social enterprises (which have a pronounced fiction-like aspect prior to their manifestation as “completed projects” within the world), and (3) the ability to engage in understanding abstract and even more disembodied semantic thought. A plan, after all—including a shared plan—is nothing but the projection of a compelling fiction onto extant and agreed-upon objects and contexts. The joint establishment of such a plan, motivationally significant to all, emotionally gripping, eliminates the very necessity for conflict. Sophisticated mother–child conversations about emotions appear to lay the groundwork both for children’s discussions of affective states and the emergence of the ability to adopt the perspective of another (reviewed briefly in Oppenheim, Nir, Warren, & Emde, 1997). Oppenheim et al. (1997) have demonstrated, as well, that preschool children able to engage in less emotionally disrupted and more coherent pretend play representations of a hypothetical parent–child separation event with their mothers were also able to produce sentence-stem completion narratives that were more prosocial, less aggressive, and more coherent, and were rated by their mothers as characterized by fewer behavior problems concurrently and 1 year later. Wolf (1990) has suggested, likewise, that the development of narrative ability increases children’s ability to view interpersonal situations from multiple perspectives, including those of their potential selves (their individual selves, in a different motivational state) and those of others. Hughes and Dunn (1997) provide direct support for the notion of social collaboration in pretend play by (1) noting a strong positive relationship between mental state talk and turn-taking and (2) noting that the relationship between mental state talk on the part of one child is as strongly affected by mental state talk on the part of his or her partner as it is by individual variability in verbal ability. Seja and Russ (1999) have demonstrated, similarly, that fantasy play ability is significantly related to emotional understanding, over and above individual variation in verbal ability, and Taylor and Carlson (1997) have demonstrated that children whose fantasy and pretend play abilities was more sophisticated also did better on theory of mind tasks, independently of their verbal intelligence. Finally, Hughes and Dunn (1997) note that theory of mind task performance is positively associated with references to mental state, independently of age. Brown, Donelan-McCall, and Dunn (1996, p. 847) note, in this regard, that the maintenance of interactive games and the construction of fantasy worlds “must surely provide multiple opportunities for the fledgling theorist to appreciate the workings of the mind” (from Hughes & Dunn, 1997). Eckler and Weininger (1989) have paid particular attention to the elaboration

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of such pretense worlds, pointing out that younger children tend toward “preepisodic” and older children toward “episodic play,” which is very dramatic and story-like. Furthermore, these authors also clearly distinguish two aspects of pretense, “setting-up” and “play”—processes that appear to correspond very much to the establishment of a shared frame and action within that frame, respectively. Children setting up a pretend play episode appear to be constructing a joint fictional frame, a delimited subsection of the “real world,” too complex to fully model. This delimited subsection has a consummatory element, which is the complex goal of the fictional world (Rumelhart, 1977) and also contains shared objects of perception—objects which, in the case of pretense, may not even be there (as a child is perfectly capable of acting as if something is there, and as if an object that is there is in fact something else). Children who are “setting up” a play episode therefore appear not only to be negotiating the nature of the actions that will occur in that space, but mutually regulating each other’s perception (as suggested previously). Pretend play thus logically appears associated with talk about subjective mental state at rates much higher than chance (Hughes & Dunn, 1997) and, more specifically, with talk directed at another’s inferred mental state, desired or actual. Children with autism, characterized by fundamental deficits in the substructural elements of social cognition, also fail to use social gaze, which typically serves to specify the target of joint motivation and perception during empathy and joint attention tasks (Charman et al., 1997). This observation adds to the knowledge base already established demonstrating similar impairments among autistic children in empathy, pretend play, and joint attention (reviewed briefly in Charman et al., 1997; Baron-Cohen, Allen, & Gillberg, 1992). The gaze dysfunction is particularly interesting, given that gaze monitoring constitutes a procedural technique for determining intent, or goal-orientation, on the part of another, and is clearly part of the social–cognitive system that enables human beings to establish shared goal-oriented conceptual frames and associated behaviors and emotions (Adolphs, 2001; Hobson, 1990). Autistic children also appear delayed, if not fundamentally impaired, in imitation (Charman et al., 1997). The fact that individuals who have sustained left or right prefrontal damage in adulthood appear impaired on theory of mind tasks, even when their deficits on classic executive–cognitive tests have been controlled statistically, may also be relevant to understanding the emergent neuropsychological control over shared motivation (Rowe, Bullock, Polkey, & Morris, 2001), and helps to elucidate, physiologically, the distinction between voluntary cooperation and pure inhibition of aggression. Similar patterns of deficits also appear to characterize non-Alzheimer’s frontal variant frontotemporal dementia, frequently characterized by emergent suspiciousness, dysregulation of formerly socialized behavior, and antisociality (Lough & Hodges, 2002; Lough, Gregory, & Hodges, 2001). In the case of fronto-temporal dementia, emergent antisociality also appears associated specifically with a breakdown of social cognition, but not classic executive function (Lough et al., 2001) (perhaps as a

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consequence of deterioration in orbitofrontal–ventromedial circuitry, which appears specifically activated during social cooperation [McCabe, Houser, Ryan, Smith, & Trouard, 2001; Rilling et al., 2002]). Dunn and Hughes (2001) demonstrated a clear distinction between hardto-manage children and normal children in regard to violent fantasy play, with a clearly higher proportion of the former group, both boys and girls, consistently engaging in pretend games that involved killing, fighting, or beating (despite the fact that no overall difference in frequency of pretend play as such was observed). Such interest in violent fantasy was itself related to poor executive control and language ability, impaired theory of mind (related as well to language ability), frequent antisocial behavior, displays of anger and refusal to help a friend, poor communication and coordination of play, more conflict within friendships, and decreases in empathic moral sensibility 2 years later. Hughes, Cutting, and Dunn (2001) then attempted to determine whether conduct-disordered children were more likely to respond negatively to the threat of losing a game because (1) they were more preoccupied with aggression, in general, as indexed by violent themes in their pretend play, (2) they were delayed or deviant in regard to reading the intentions of others (potentially manifesting a hostile attribution bias), or (3) they were characterized by a problem with executive function, resulting in difficulties in inhibiting inappropriate behaviors. At age 4, violent pretend play theme frequency, theory of mind performance, and executive function all appeared significantly associated with negative behavior in response to threat of loss at age 5 at the zeroorder correlation level of analysis, and all appeared to be of significant or near-significant statistical import when entered simultaneously in a regression analysis. The picture of multidimensional causality portrayed by this study was marred somewhat in its clarity by the results of longer-term follow-up: By age 7, only the age-4 violent pretend play theme measure remained as a significant predictor (accounting for 25% of the variance). Nonetheless, there is suggestive evidence that many different forms of regulation of aggression exist, at very different levels of neurological instantiation. Perhaps the effects of various pathologies, heightening the probability of aggression, may be additive or even interactive: Aggressive children may lack basic inhibition (first instantiated under normal conditions, as a consequence of R&T play, governing motor output in the presence of others). They may also be impaired in regard to theory of mind and capacity to cooperate. Finally, as Crick and Dodge (1996) and Happe and Frith (1996) have suggested, such children may actively infer hostile intent on the part of others, and plot revenge (thus making even their limited capacity for social understanding into something positively counterproductive). Jenkins and Greenbaum (1999) have argued, in this regard, that disruptive children develop an overt “adversarial goal structure” that leads to frequent anger and aggression. Such a structure could be a generalized hypothesis such as “cooperation is impossible” (a theme that makes antisociality more or less logically inevitable), or “individual victory trumps cooperative action” (a theme logically associ-

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ated with narcissism, characterized by high levels of extraversion and low levels of agreeableness). Rose and Asher (1999) have noted, in keeping with this general hypothesis, that children who pursue the explicit goal of revenge toward a friend after conflict within a friendship were (1) more likely to use aggressive strategies, such as assertion of self-interest and hostility, (2) less likely to use prosocial strategies, such as relationship maintenance and accommodation or compromise, (3) more likely to lack friends, and (4) more likely to have poor-quality friendships. It is interesting to note more broadly in this regard, first, that social strategies or algorithms such as strike back once, then forgive and forget, are the most likely to win iterative repetitive tit-for-tat cooperative exchange games such as Prisoner’s Dilemma (Wedekind & Milinski, 2000) and, second, that the combination of yoked goal-and-strategy implementation sounds very much like a social game (not least because of the emergence of constant reciprocity). It is also very relevant in regard to the potential developmental origins of an essentially adversarial game that maltreated children are more likely than their nonmaltreated peers to develop more negative, constricted, and less coherent narrative or story-like representations of their caregivers. These more negative representations, although potentially accurate in the circumstances in which they emerged, generalize poorly and are associated with emotional dysregulation, aggression, and peer rejection. Positive and coherent representations of caregivers, by contrast, are related both to prosocial behavior and to preference by peers (Shields, Ryan, & Cicchetti, 2001). Maltreated children appear to see the social surround as “angry, malevolent, punitive, exploitative, and conflictual” (reviewed briefly in Shields et al., 2001). It is particularly interesting, therefore, to note that R&T play initiated with popular, prosocial young school-age children generally turns into play with rules or more advanced pretend play, whereas such play initiated with aggressive children degenerates rapidly into violence (Pellegrini & Smith, 1998). Given the aggressive child’s vengeful and mistrustful view of the world, it is not unreasonable to suppose that exploratory R&T play forays on the part of one child with regard to another allow that child to assess the basic social strategies employed by that other—to investigate, very rapidly and directly, whether the other has established a basic capacity for inhibition, and can therefore be trusted not to harm, or if he or she is hostile and aggressive, and unfit for continued interaction. Finally it is useful to note that violent video game play—a form of scaffolded pretend play that highlights themes of revenge and destruction—does in fact appear causally associated with aggressive behavior, thoughts and feelings, and with a decrease in prosociality (Bushman & Anderson, 2002). Kochanska and colleagues (Murray & Kochanska, 2002) have recently developed a statistically coherent and longitudinally stable battery of “effortful control tasks,” which measure the capacity to delay gratification and to voluntarily suppress or initiate actions (performance on which can be assessed

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as early as 2.5 years). Lesser performance on this task battery was associated with some elements of conduct-disordered behavior, such as impaired attentional control. Forman and Kochanska (2001) have also demonstrated that children who were more imitative and responsive during pretend-play sequences modeled by mothers were also more positively responsive to maternal control, and less likely to manifest noncompliance in a typical discipline context. This appears to mean that children who are more capable of adopting a shared frame of reference in a play-like context are also those who are more willing to “play the right game” when attention is called to their transgressions or rule-breaking behaviors. Stipek, Recchia, and McClintic (1992) note, in this regard, that young children do not really distinguish between teaching and disciplinary contexts, reacting with pride to doing well and with shame to doing badly in both contexts. Kochanska, Aksan, and Koenig (1995) and Kochanska, Tjebkes, and Forman (1998) have therefore proposed the concept of committed compliance, something opposite to that of “the adversarial goal structure,” distinguished from externally imposed obedience by its “enthusiastic and self-sustaining quality, unmediated by ongoing parental control” (Forman & Kochanska, 2001, p. 199), and described further as “visible embracing of the parent’s agenda” and as “a behavioral tendency consistent across situations shown by the child’s continued restraint when the [parent] is no longer present.” This sounds very much like the adoption of a shared motivational frame of reference, constructed on the basis of true social cooperation, and not merely the inhibition of aggression.

CONCLUSION First, it is clear that both Hobbes and Rousseau were correct. The individual brings to the world a set of inborn motivations, including those that underlie aggression, and these motivations are brought under control—or not—as a consequence of socialization. This control appears at least twofold. The direct inhibition and regulation of aggression appears established as a consequence of R&T play and also appears associated, in principle, with the development of some forms of executive control. The formal adoption of a prosocial stance toward the world, by contrast, mediated by emergent trust in the trustworthiness of self and other, culminates not so much in the capacity to obey rules and to stay on track (associated perhaps with inhibitory and executive control), but in the willingness to voluntarily enter into complex, cooperative social games with others, mediated by shared, goal-directed frames of reference (Peterson, 1999; Peterson & Flanders, 2002). These tendencies toward the social good seem as predicated on innate capability, interest, and inborn empathy as do the tendencies toward aggression. There is no shortage of evidence for innate human good, and much suggestion that it might even reasonably be considered the norm. Furthermore, it is clear that pathological socialization experiences, first in the context of the family and second in the context of

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early peer experiences (variants of the institutional sickness described by Rousseau) can produce and then reinforce in a child the conviction that the world is a cruel and sadistic place, fit only for interpretation through lenses colored by the desire for revenge. Finally, it is clear that complex processes of play, beginning with R&T play and culminating in the production of sophisticated, abstract socially shared frames of reference, play an important role in the modulation of aggression, both in regard to its inhibition and in regard to its integration into fully functional individual and social identities. The first problem that life presents, so to speak, is the necessity of satisfying basic motivational states. The next emergent problem is the necessity to construct and integrate techniques designed to satisfy these motivational states across different states, across different time frames and in a wide variety of contexts. Given the intensely social nature of the natural human environment, this problem of integration must eventually expand to include the other, the motivated other.

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THE DEVELOPMENT Indirect Aggression among OFHumans AGGRESSION

8 Indirect Aggression among Humans Social Construct or Evolutionary Adaptation? T RACY V AILLANCOURT

During the course of the 20th century, a considerable growth in knowledge took place concerning the functions, correlates, and developmental patterns of aggression among humans. The bulk of these studies focused on physical aggression, which was found to be used more by males than females (e.g., Loeber & Hay, 1997; Maccoby & Jacklin, 1974, 1980; Hyde, 1984) and to decrease with age (e.g., Broidy et al., 2003; Cote et al., 2004; Kingston & Prior, 1995; Loeber & Stouthamer-Loeber, 1998; Tremblay et al., 1999). As the turn of the century approached, scientists demonstrated that aggression in humans extended beyond its physical form and beyond the Y chromosome. Indeed, a wave of new studies appeared, showing that females were also capable of aggressing against another, but that they expressed aggression in a more covert manner (i.e., indirect aggression), taking the form of rumor spreading, peer group exclusion, and silent treatments, to name a few strategies (e.g., Björkqvist, Lagerspetz, & Kaukiainen, 1992a; Björkqvist, Osterman, & Kaukiainen, 1992b; Cairns, Cairns, Neckerman, Ferguson, & Gariepy, 1989; Crick, 1995, 1996; Crick & Grotpeter, 1995; Lagerspetz, Björkqvist, & Peltonen, 1988; Galen & Underwood, 1997). These studies also revealed that indirect aggression, in contrast to physical aggression, increased with age (e.g., Vaillancourt et al., 2004; Vaillancourt, Brendgen, Boivin, & Tremblay, 2003b) and was associated with its own unique set of correlates/predictors (see Underwood, 2003, for review). Although our knowledge relating to indirect aggression is growing, the greater part of this knowledge is informed by an ontogenetic perspective, with little attention paid to its possible evolutionary significance. Twenty-five years 158

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ago, Robert Cairns (1979) noted that “the phenomena of evolutionary adaptations can no longer be ignored in developmental analyses, even if they do not readily fit existing ideas” (p. 370). This argument stemmed from the idea that social patterns can be “seen as developing in an individual’s life time (over years) or they may be viewed as evolving over a species ‘lifetime’ (over thousands or millions of years)” (p. 370). Through the integration of research from a variety of different fields such as psychology, sociology, anthropology, ethology, and biology, the purpose of this chapter is to put forth a phylogenetic argument concerning the function of indirect aggression among human females. Toward this end, indirect aggression is first defined, followed by a review of the correlates of indirect aggression, with particular focus on age- and sex-related differences associated with its use. Next, early theories of aggression are presented to place in context the current hypotheses concerning females’ use of indirect aggression. Finally, an evolutionary hypothesis is proposed on why females use indirect aggression.

WHAT IS INDIRECT AGGRESSION? To understand what we have learned and what we need to learn, we first need to agree on the topic. —TREMBLAY (2000, p. 130)

Naming the behavior that entails the use of socially conniving acts such as getting others to dislike a person, becoming friends with another as a form of revenge, telling a person’s secrets to another, saying bad things about a person behind his or her back, telling others to avoid a person, using derisive body language, and the like, should, in theory, be relatively straightforward. The problem, however, is rooted in that fact that there are currently three terms being employed to describe this phenomenon: social aggression is used by Underwood and colleagues (e.g., Galen & Underwood, 1997) to describe behavior that is “directed toward damaging another’s self-esteem, social status, or both” (p. 589; see also Cairns et al., 1989; Xie, Cairns, & Cairns, 2002a); relational aggression is used by Crick and colleagues (Crick, 1995, 1996; Crick & Grotpeter, 1995) to describe behavior that harms others “through purposeful manipulation and damage of their peer relationships” (Crick & Grotpeter, 1995, p. 711); and indirect aggression is used by Björkqvist and colleagues to describe a set of behaviors that are socially manipulative and circuitous in nature, such as spreading invidious rumors about another person (e.g., Björkqvist et al., 1992a; Björkqvist et al., 1992b; Lagerspetz et al., 1988). Although these three “types” of aggression seem to overlap considerably (Björkqvist, 2001), it has nevertheless been argued that they are in fact conceptually different from one another (Underwood, 2003; Underwood, Galen, & Paquette, 2001). For instance, Underwood and colleagues (Underwood,

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2003; Underwood et al., 2001) argue that social aggression is different from relational aggression in that social aggression involves damaging a person’s self-esteem and/or social status, whereas relational aggression involves damaging a person’s peer relations. Indirect aggression is similar to relational aggression in that it involves the manipulation of peers and damage to these liaisons, but differs in that it includes only behaviors that are covert. Both social aggression and relational aggression include a mélange of covert and overt behaviors. These nuances aside, what these so-called distinct types of aggression have in common is that they involve hurtful behaviors that are socially scheming. Using different terms to describe a certain phenomenon is problematic (Björkqvist, 2001; Vaillancourt & Hymel, 2003) in that it impedes progress in the area by confusing, among others, new scholars coming to the field. According to Walter Mischel, researchers should create and go beyond theories that have already been developed rather than renaming them (Rabasca, 2000). In an attempt to circumvent another “renaming of the term” indirect aggression is used throughout this chapter in recognition of the pioneer work by Feshbach (1969, 1971) and Björkqvist and colleagues (Björkqvist et al., 1992a, 1992b; Lagerspetz et al., 1988) in this area of study. Once a study has been conducted demonstrating that social, relational, and indirect aggression are distinct forms of aggression, this position can be reevaluated. However, it is likely that this stance will remain, in that this future study will not only need to demonstrate the statistical uniqueness of these “different” types of aggression, but will also have to demonstrate that social, relational, and indirect aggression are differentially associated with outcomes.

WHO USES INDIRECT AGGRESSION? Age Differences It has been suggested that as children age their mode of aggressing against another changes and that the use of indirect aggression is the more sophisticated form of hurtful behavior (Björkqvist, 1994; Björkqvist et al., 1992a, 1992b; Lagespetz et al., 1988). Specifically, Björkqvist and colleagues hypothesize that children switch from being physically aggressive to being verbally aggressive as their language skills develop, and, in turn, they change from being verbally aggressive to being indirectly aggressive as their social-cognitive skills advance. Cross-sectional and longitudinal studies of aggression appear to support this claim. For example, in contrast to the use of physical aggression in humans, which has been shown to peak at around the age of 30 months and decline steadily thereafter (e.g., Broidy et al., 2003; Cote et al., 2004; Kingston & Prior, 1995; Loeber & Stouthamer-Loeber, 1998; Tremblay et al., 1999), the use of indirect aggression has been shown to increase with age (Björkqvist et al., 1992a; Björkqvist et al., 1992b; Cairns et al., 1989; Osterman et al., 1998; Tremblay et al., 1996; Vaillancourt et al., 2004). Some have suggested that indirect aggression peaks during early adolescence (Björkqvist et al., 1992a;

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Björkqvist et al., 1992b), and others have argued that it continues to rise well into late adolescence (e.g., Owens, 1996). To date, precious few studies have examined, longitudinally, the development of indirect aggression, and the few studies that have, focused primarily on children and preadolescents (Cairns et al., 1989; Vaillancourt et al., 2003b; Vaillancourt et al., 2004). Thus, at this point in time, a complete picture of the developmental sequence of indirect aggression is not available. Nevertheless, based on these few longitudinal studies, as well as on cross-sectional results, it appears that as children age, their use of indirect aggression increases (Björkqvist et al., 1992a; Björkqvist et al., 1992b; Osterman et al., 1998; Tremblay et al., 1996; Vaillancourt et al., 2003b; Vaillancourt et al., 2004). However, it is still unclear as to when indirect aggression is at its highest or lowest across the lifespan. Currently, what is known is that humans as young as preschoolers (e.g., Crick, Casas, & Mosher, 1997; McNeilly-Choque, Hart, Robinson, Nelson, & Olsen, 1996; Vaillancourt et al., 2003b) and as old as seniors (Walker, Richardson, & Green, 2000) use indirect aggression.

Sex Differences Although at present there is little information concerning developmental changes associated with the use of indirect aggression, there is a considerable amount of information regarding sex differences in the expression of aggression. These studies have consistently demonstrated that females are typically more indirectly aggressive than males, whereas males are invariably more physically aggressive than females (Craig, Peters & Willms, 2002; Crick, 1995, 1996; Crick et al., 1997; Crick & Grotpeter, 1995; Björkqvist et al., 1992a; Björkqvist et al., 1992b; Feshbach, 1969, 1971; French, Jansen, Pidada, 2002; Hines & Fry, 1994; McNeilly-Choque et al., 1996; Lagerspetz et al., 1988; Osterman et al., 1998; Prinstein & Cillessen, 2003; Tremblay et al., 1996; Vaillancourt et al. 2003b). Although this sex difference in the expression of indirect aggression has been reported often, it is important to note that in some studies no sex differences in the use of indirect aggression have been found (Hart, Nelson, Robinson, Olsen, & McNeilly-Choque, 1998; Rys & Bear, 1997; Willoughby, Kupersmidt, & Bryant, 2001), and in others, males have been shown to be more indirectly aggressive than females (David & Kistner, 2000; Hennington, Hughes, Cavell, & Thompson, 1998; Tomada & Schneider, 1997). It is worthwhile to clarify these discrepancies concerning who uses indirect aggression more—females or males—and what these findings mean. The fact that a few studies have shown males to be more indirectly aggressive than females does not detract from the overarching finding, which is that females’ preferred mode of aggressing is indirect. Further, the fact that several studies have demonstrated that females use indirect aggression more than males does not mean that females are globally more aggressive than, or equally aggressive as, males. Indeed, the literature to date points in a definitive direction, suggesting that males use aggression more than females. However,

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these findings highlight two important points that have historically been overlooked in the aggression literature: (1) females’ use of aggression is not a rare phenomenon, and (2) when females do aggress, they tend to do so in a circuitous manner. The evolutionary significance of these differences is considered shortly.

WHAT ARE OTHER CORRELATES OF INDIRECT AGGRESSION? Although physical aggression has been linked to an extensive list of individual (e.g., Lahey, McBurnett, & Loeber, 2000; Moore, Scarpa, & Raine, 2002; Plomin, 1983; Raine, 1993; Schaal, Tremblay, Soussignan, & Susman, 1996; Tremblay & LeMarquand, 2001), early environmental (e.g., Arseneault, Tremblay, Boulerice, & Saucier, 2002; Fergusson, Woodward, & Horwood, 1998; Raine, 2002), familial (e.g., Keenan & Shaw, 1994; Lykken, 2001; Tremblay, 1999), and parent–child factors (see Coie & Dodge, 1998 and Patterson, 1995, for reviews), the study of indirect aggression is still in its infancy. Accordingly, there have been only a small number of studies that have examined its correlates and even fewer that have examined its predictors. Further, the majority of studies that have examined the correlates of indirect aggression have tended to focus on the same few variables—social status (e.g., Crick, 1997; Crick et al., 1997; Crick & Grotpeter, 1995; Hennington et al., 1998; McNeilly-Choque et al., 1996; Rys & Bear, 1997; Salmivalli, Kaukiainen, & Lagespetz, 2000; Vaillancourt & Hymel, 2004; Werner & Crick, 1999) and psychological maladjustment (e.g., Crick, 1997; Crick & Grotpeter, 1995; Owens, Slee, & Shute, 2000b; Richardson & Green, 1997; see Crick et al., 1999 for a review). These studies have demonstrated that indirect aggression is associated with increased peer rejection and psychological impairment, such as greater loneliness and depression for both females and males, although girls seem to be more adversely affected than boys (e.g., Crick & Grotpeter, 1995; Hennington et al., 1998; Rys & Bear, 1997). It is also important to note that the direction of these relations has yet to be established. For example, it is not clear as to whether peer rejection precedes the use of indirect aggression or whether peer rejection is a consequence associated with its use. Accordingly, more longitudinal work in this area is needed. Moreover, it is also not clear as to whether the association between indirect aggression and psychosocial maladjustment is curvilinear. That is, for some, using indirect aggression may not be problematic because it is used sparingly and in a goaldirected way. However, for others, diminished returns are likely to ensue in that indirect aggression is used often and impulsively. Studies that have investigated the link between indirect aggression and other markers of social status emphasize the idea that for some, indirect aggression may be related to competency. For example, several researchers have recently noted a positive relation between the use of indirect aggression and

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peer perceptions of popularity (i.e., high visibility and influence among peers) (e.g., Cillessen & Mayeux, 2002; Prinstein & Cillessen, 2003; Vaillancourt & Hymel, 2004) and peer group centrality (e.g., Xie et al., 2002a; Xie, Swift, Cairns, & Cairns, 2002b). Ethnographic work by Merten (1997) and Adler and Adler (1998) elucidate this seemingly contradictory link by describing how girls use indirect aggression to achieve and maintain hegemony. In their aggressive strive for popularity, girls are often disliked by their lower-status and victimized peers. Thus, girls can be perceived as popular and powerful while simultaneously being rejected by the larger peer network (Vaillancourt & Hymel, 2004). Beyond sex, age, social status, and psychological maladjustment, the list of variables examined in relation to indirect aggression is rather short (see Underwood, 2003, for a more comprehensive review). For example, Kaukiainen et al. (1999) found that among adolescent males and females, high levels of social intelligence were associated with the use of indirect aggression, whereas the relation between physical aggression and social intelligence was virtually orthogonal. Vaillancourt and Hymel (2004) reported that adolescents’ use of indirect aggression was positively associated with the possession of peer-valued characteristics such as attractiveness and stylish clothing. Walker et al. (2000) noted that adults who used indirect aggression were more masculine than nonaggressive adults. These few studies certainly do not depict a clear profile regarding who typically uses indirect aggression but, rather, highlight how much there is to be done in this area of study.

WHY DO FEMALES USE INDIRECT AGGRESSION? Women are naturally less prone to react aggressively than are men . . . such variations . . . are largely socially determined. Physically smaller and weaker and periodically incapacitated during an important period of their lives by pregnancy and, to a less extent, by menstruation, women are taught to accept a protected albeit subservient position within the group. —DOLLARD, DOOB, MILLER, MOWRER, & SEARS (1939, p. 130)

Early Theories of Aggression In conjecturing about why humans use aggression, many early theorists inadvertently wrote about physically aggressive males and thus incorrectly assumed that females were less likely to respond aggressively (e.g., Bandura, 1973; Dollard, Doob, Miller, Mowrer, & Sears, 1939; Freud, 1915; Lorenz, 1966). These early (male) scholars of aggression failed to recognize (or perhaps consider) that females did aggress and did so in a circuitous manner. This oversight may be due to the fact that there were not a lot of data on female ag-

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gression to attend to. More likely, however, the omission was due to the fact that they held the assumption that the typical female was characteristically docile and nurturing, not aggressive. The failure of early aggression theorists to notice or contemplate females’ use of aggression was not overlooked by Maccoby and Jacklin (1974), who in their review of the literature did address the “different modes hypothesis” (i.e., females and males aggress in dissimilar ways), only to dismiss it in favor of a biological argument, which again concentrated on physical aggression. More recently, Campbell (1993) appeared to be aware that females and males expressed aggression differently, with males using physical aggression and females using indirect aggression. As a matter of fact, she stated that “boys are not simply more aggressive than girls; they are aggressive in a different way” (p. 19), suggesting a recognition of the different modes hypothesis. In actuality, however, what Campbell meant by “in a different way” was that males express their aggression directly whereas females suppress their aggressive feelings entirely. “Girls do not learn the right way to express aggression; they simply learn not to express it” (p. 20). Naturally, since the initial writings of scholars such as Freud (1915), Dollard et al. (1939), Lorenz (1966), Bandura (1973) and Maccoby and Jacklin (1974), our understanding of aggression in humans has developed considerably, with many of these progressions evolving in terms of our understanding of how females aggress. For example, researchers have shown that sex differences in the mode of aggressing are robust (see the preceding section) and several researchers have put forth hypotheses of why this may be.

Current Hypotheses Concerning Indirect Aggression Although Feshbach (1969, 1971) was the first to empirically examine different modes of aggression in relation to sex, she did not comment on why it was that girls directed more indirect aggression against newcomers than did boys. In fact, it took another 2 decades for researchers to validate these findings and to hypothesize why this pattern of results existed. The first researchers to articulate a hypothesis concerning sex differences in the mode of aggressing were Lagerspetz et al. (1988), who postulated that the organization of children’s peer groups, in particular the closeness of girls’ friendships, facilitates the use of indirect aggression by females by creating more “opportunities” to aggress in this manner. Lagerspetz et al. also argued that the social sanctions placed against the use of physical aggression by females contribute to these sex differences. Like Lagespetz et al. (1988), Crick and Grotpeter (1995) argued that sex differences in the mode of aggressing exist because children aggress in ways that are most salient and valued by their respective genders and peer groups (see also Campbell, 1999). For boys, dominance and submission are important themes in their social lives, but for girls, inclusion and exclusion are important themes (see Block, 1983, for a review). Consequently,

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boys use physical aggression to harm their peers, and girls rely on indirect aggression. Whereas Lagerspetz et al. (1988) and Crick and Grotpeter (1995) attempt to explain sex differences in the ways children aggress in relation to peer group structures, Björkqvist (1994) proposed that such sex differences are the result of a cognitive assessment strategy he termed the “effect/danger ratio” in which the aggressor considers the situation and makes a decision as to the type of aggressive tactic to employ. This determination is based on the judgment of its effectiveness and on the potential danger involved. Because females are usually involved in conflict with other females, targeting social relationships would be the most successful way of inflicting harm (see also Crick & Grotpeter, 1995). Further, because indirect aggression is circuitous, it also represents the least dangerous strategy inasmuch as the aggressor is often not identified as the perpetrator. The use of indirect aggression by females thus represents an aggressive strategy that yields the maximum effect with the minimum amount of hazard (see Björkqvist, 1994). As mentioned previously, ethnographers such as Merten (1997) postulate that girls, in particular adolescent females, use indirect aggression as a way of achieving and maintaining popularity within their social reference group (see also Adler & Adler, 1998; Vaillancourt, 2001). Being popular is an important goal for many adolescents (see Gavin & Furman, 1989). Studies that have examined the link between indirect aggression and peer perceived popularity provide support for this hypothesis by demonstrating its strong association with peer recognized power and visibility (e.g., Vaillancourt & Hymel, 2004; Vaillancourt & McDougall, 2003). What is striking about the aforementioned hypotheses concerning sex differences in the expression of aggression is that they almost invariably fail to explain the function of indirect aggression (with the exception of Adler & Adler, 1998; Merten, 1997; Vaillancourt, 2001). In other words, why aggress indirectly in the first place? More than 30 years ago, Bandura (1973) stated that “a complete theory of aggression, whatever its orientation, must explain how aggressive patterns of behavior are developed, what provokes people to behave aggressively, and what maintains their aggressive actions” (p. 43). Within the study of indirect aggression, it can be said that we have succeeded only somewhat in explaining how it develops. Perhaps, then, it is time to consider alterative hypotheses regarding why females use indirect aggression. One such hypothesis, which to date has not been fully considered, is that there may be an evolutionary history associated with its use. That is, indirect aggression may be an inherent strategy that is employed by females to secure access to desirable mates and resources.

Evolutionary Theory of Direct Aggression From an evolutionary perspective, males and females share similar reproductive goals—the passing of their genes to subsequent generations. However, de-

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spite similarities in their ultimate reproductive objectives, males and females approach this endeavor differently. This sex difference in procreative strategies had been attributed to differential parental investment, whereby (typically) females across mammalian species, including humans, invest more resources in their offspring than do males (Trivers, 1972). The result of this imbalance is that females are choosy when selecting a reproductive partner, and males compete for access to these selective females. The idea that females select whereas males contend is one of the central tenets of Daly and Wilson’s (1988) evolutionary theory of violence. Specifically, they argue that aggression is an evolved adaptation. This position is supported by numerous examples of aggression being initiated in circumstances where increases to fitness (i.e., reproductive success) are to be reaped, as well as by data demonstrating that aggression comes to pass in situations in which resources (i.e., territory, food, etc.) are limited or unavailable, or threats to self and/or family are perceived (Daly & Wilson, 1988; see also Archer, 1988). These contexts, in which aggression is regularly displayed, illustrates well the two processes believed to be involved in adaptation—natural selection, which arises from competition for survival (i.e., access to food), and sexual selection, which arises from competition for reproduction (Darwin, 1859, 1871).

Toward an Evolutionary Theory of Indirect Aggression among Females Although Daly and Wilson’s (1988) evolutionary theory of aggression is appealing insofar as it addresses the functions aggression might serve (i.e., increased fitness and increased survival), one complication is the centered attention on direct forms of aggression and what it means to the lives of males. Such a concentration on male antagonism has a long tradition among evolutionary thinkers, including Darwin, who hardly referenced female–female competition but rather focused on the “struggle between individuals of one sex, generally males, for the possession of the other sex” (1859, p.88). It is curious that well over a hundred years after Darwin (1859, 1871) wrote his seminal books on the evolution of species, few scientists have considered the possibility that there may be an intrinsic function associated with females’ use of indirect aggression (Campbell, 1999). This is especially intriguing given that human females are not randomly choosing mates but rather, are often actively selecting partners (Fisher, 1930; Zahavi, 1975; see Kokko, Brooks, Jennions, & Morley, 2003, for review) whom they perceive to be of superior quality— typically meaning higher in occupational and/or economic status (e.g., Bereczkei, Voros, Gal, & Bernath, 1997; Buss, 1989; Feingold, 1992). These high-status males can presumably provide females with greater resources, which in turn translates into greater reproductive advantage such as an increased number of surviving offspring (Daly & Wilson, 1983). Studies from preindustrial (Voland & Engel, 1990) and industrial (Bereczkei & Csanaky,

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1996) societies support this idea, showing that females married to high-status males produced more surviving offspring than other females. Considering that a female’s overall fitness may be positively augmented by choosing a male with viability characteristics, and considering that not all males will enjoy such positive qualities, intrasexual competition among females should be expected (Paul & Baenninger, 1991). Such competition could take the form of attracting mates (Darwin, 1871), for example, by making oneself more appealing through the use of tactics like manipulating appearance (Buss, 1988) or by intimidating competitors (Darwin, 1871) by making the adversary seem less attractive through, for example, the use of derogation strategies (Buss & Dedden, 1990). Fittingly, then, it may be that females use indirect aggression because it represents an effective and less dangerous (Björkqvist, 1994) intrasexual strategy that ameliorates access to quality mates and their resources (Campbell, 1995, 1999). Circumlocutory evidence supporting this idea follows. First, several researchers have shown that indirect aggression is especially damaging to female victims (e.g., Crick, 1996; Crick, Bigbee, & Howes, 1996; Galen & Underwood, 1997; Paquette & Underwood, 1999), who experience difficulties such as decreased self-esteem, increased anxiety and depression, school departure, and even suicide (e.g., Munro, 2000; Owens et al., 2000b). The plight of these victims highlights the efficacy of such agonistic tactics. In fact, when undergraduates were asked to rate the usefulness of derogation tactics in the context of intrasexual competition (Buss & Dedden, 1990), females selected items that were markedly consistent with those cited by developmental psychologists (e.g., Crick & Grotpeter, 1995; Galen & Underwood, 1997; Lagerspetz et al., 1988) when describing the acts of indirect aggression. For instance, females rated spreading rumors (i.e., calling a competitor promiscuous or a “tease”) and peer group exclusion as effective ways to disparage a female rival. In considering these findings, it seems likely that female victims of indirect aggression would be less willing or able to vie for a male’s affection if they were suffering psychologically or if they had removed themselves entirely from the competition (i.e., suicide). In the nonhuman primate literature, it has been remarked that high-status females harass low-status females indirectly. This pestering has been linked to estrus suppression and miscarriages among the victims. The reproductive success of the victim is thus obviously reduced and, accordingly, the resources available to the aggressor and her offspring increased (Hrdy, 1981, 1999; see Campbell, 1999). Among humans, several studies have demonstrated that prominent and powerful females use indirect aggression more than lowerstatus females (e.g., Vaillancourt & Hymel, 2004). Like their primate sisters (Wildman, Uddin, Liu, Grossman, & Goodman, 2003), high-status females are more likely to succeed in reducing a rival, given their social standing among peers (see Merten, 1997). It is perhaps not so peculiar that girls use indirect aggression to achieve and maintain hegemony, and do so at an early

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age, for this jostling for elevated status may be fundamentally linked to fitness. Second, the notion that the use of indirect aggression by females may represent an effective means for securing access to mates (direct benefit) and hence increase reproductive success (ultimate benefit) is supported by the ethnographic work of Artz (1998a, 1998b), Campbell (1982, 1995), and Marsh and Paton (1986). In these studies, adolescent females, without fail, accused other females of being “sluts.” This tactic of exaggerating another’s sexual history is consistent with the evolutionary idea that a female’s success in obtaining a desirable partner, who is committed, is largely determined by his appraisal of her fidelity (Buss, 1988; Wilson & Daly, 1992). The adolescent females in these studies also reported that they would defame and even beat another female if she slandered the aggressor’s reputation or showed an interest in her current or desired partner. In 1997, a 14-year-old Canadian girl was savagely beaten and than drowned by a gang of females (and one male). The reason for this murderous assault—supposedly, the victim had spread rumors about one of her attackers and was perceived to have shown an interest in the boyfriend of one of her assailants (Pemberton, 1997). It appears from these accounts that indirect aggression and physical aggression are used by females to secure access to mates, although the use of indirect aggression is far more common among females than the use of physical aggression. The evolutionary significance of this sex difference in aggressing likely has to do with the risk of injury involved to self and/or offspring when physical methods are used (see Björkqvist, 1994; Campbell, 1999, regarding humans; see Hrdy, 1981, 1999, regarding nonhuman primates). Indeed, physically aggressive encounters may result in injury or death, which in turn may reduce a female’s offspring’s ability to survive, thus decreasing her fitness. Historically, among humans, and currently among most other species, offspring survival was/is inextricably linked to maternal survival (see Hrdy, 1999) Third, the idea that indirect aggression may be an evolved adaptation is further supported by cross-culture studies that have reliably demonstrated a bias for females with respect to the use of indirect aggression. Specifically, females from such diverse cultural backgrounds such as Indonesia (French et al., 2002), Finland (Lagerspetz et al., 1988), Poland (Osterman et al., 1994, 1998), Italy (Osterman et al., 1994, 1998), North America (Crick & Grotpeter, 1995; Vaillancourt, 2001), Israel (Osterman et al., 1994, 1998), Australia (Owens, Shute, & Slee, 2000a), and Argentina (Hines & Fry, 1994) were found to express their aggression in a similarly covert and socially manipulative fashion. These consistent findings challenge theories of socialization in that “culture” is no longer a fixed variable. It will be interesting to see whether this pattern of results remains robust when indirect aggression is studied more diversely (i.e., in more varied ethnic and religious cultures). Fourth, according to Campbell (1999), females are more likely to use intrasexual strategies (i.e., indirect aggression) when their reproductive value is at its peak (i.e., around puberty; ages 11–15) (Tanner, 1989), because this

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represents a time in their lives in which they have a “competitive advantage over younger and older women” (p. 109). This evolutionary hypothesis is consistent with several cross-sectional reports of indirect aggression that have shown that early- and middle-adolescent females use indirect aggression more than preadolescent and late-adolescent females (e.g., Björkqvist et al., 1992a, 1992b; Osterman et al., 1998; Xie et al., 2002a, 2002b). This hypothesis is also consistent with results from a recent nationally representative study of 2,123 adolescent girls aged 10 to 16 in which early-maturing girls reported using significantly more indirect aggression than average- and late-maturing girls (Vaillancourt, Balshine, & Clark, 2003a). Maturation status was assessed by having participants indicate the age at which they began to menstruate, and the three groups were created based on a ±1 standard deviation split. Fifth, coherent with the hypothesis that indirect aggression represents an effective strategy to access and secure romantic partners, Vaillancourt et al. (2003a) also found that self-reported use of indirect aggression was positively associated with number of romantic partners and negatively related to the age at which participants had their first boyfriends. One limitation to this study was that in these analyses, maturation status was not controlled for statistically. However, similar results were also reported by Pellegrini and Long (2003), who found in their longitudinal study of adolescent males and females (grades 6–8) that the use of indirect aggression was positively related to dating at all four assessment point for girls only. For boys, “dating popularity” was related to dominance-related strategies. Informed by sexual selection theory, Pellegrini and Long concluded that males and females use different “agonistic strategies in the service of dating popularity,” with females using indirect aggression and males using dominance (p. 271). Perhaps young females’ use of indirect aggression is akin to Wilson and Daly’s (1985) “young male syndrome,” albeit less extreme and risky. “Young male syndrome” refers to the intense intrasexual competition (violence) that occurs more often among young, poor males who, presumably, experience the most “intense reproductive competition (fitness variance) during the species’ evolutionary history, and in those individuals whose present circumstances are predictive of reproductive failure” (p. 59). Using 1972 homicidal data from Detroit, Wilson and Daly (1985) found that most murders were committed over status disputes by young, socially disadvantaged, unwed males. The adaptive function of engaging in these high-risk tactics is that they impart to females information about their resource-holding capability and their “good genes” (see Kokko et al., 2002, 2003). With respect to the use of indirect aggression, studies have shown that adolescents (ages 10 and 11) report using indirect aggression more when they come from families of lower socioeconomic status (SES) that are headed by single mothers (Craig et al., 2002; see also Tremblay, 1999). Interestingly, increased reported use of indirect aggression was also found to be inversely related to the age of the participant’s mothers at the time of his or her birth. Unfortunately, in these analyses, possible interactions between sex, SES, and indirect aggression were not reported,

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so it is not clear whether these relations are stronger for females than for males. Nevertheless, these findings highlight important future areas of inquiry that are informed by a phylogentic perspective. For instance, Campbell (1995) argues that “the degree of female economic and social dependence on men is related to the intensity with which women are prepared to fight to secure high status males” (p. 116). Accordingly, then, less economically advantaged females should engage in more intrasexual competition than their more resourced peers, because their “fitness” is rather dependent on securing and retaining a partner with resources (Bereczkei & Csanaky, 1996; Voland & Engel, 1990). The strength of these associations should be greater in nonindustrialized countries, where dependency on males for economic and social security is still very much a reality. In considering the aforementioned studies, there is some evidence to support the idea that use of indirect aggression by females represents an effective (and less dangerous) means of intimidating potential rivals, hence increasing access to desirable partners and ultimately increasing fitness. From an evolutionary perspective, females and males have similar reproductive goals. However, the ways in which they achieve their goals are different, with males relying on overtly aggressive tactics and females relying on covertly aggressive tactics (see Pellegrini & Long, 2003). It has been argued that for females, the risks involved in engaging in physical aggression outweigh the benefits accrued, and thus females use indirect aggression to secure their goals (Björkqvist, 1994; Campbell, 1995, 1999). It has also been argued that indirect aggression is less appealing to males than females because it does not promote their social goals of achieving dominance within the peer group (Campbell, 1999; Pellegrini & Long, 2003). To do this, males should use visible tactics that signal to others their strength and bravado (see also Wilson & Daly, 1985). It certainly appears that males and females are using different strategies to access romantic partners. The question that remains, however, is “whether the two sexes have evolved distinctive modes of adaptation or, more likely, whether there has been a single adaptation with sex-specific threshold settings” (Campbell, 1999, p. 120).

CONCLUSION Aggression is an organized, goal-directed activity, not the kind of event that could come from a random malfunction. —PINKER (2002, p. 316)

Because the concentrated focus of research on aggression has been on physical aggression, the terms male and aggression have effectively become synonymous with one another. The review of the indirect aggression literature challenges this assumption by demonstrating that females are capable of aggressing, but do so in a more covert manner. The review also highlights that, with

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few exceptions, the bulk of our research efforts to date have been on explaining indirect aggressing from an ontogenetic perspective, with little consideration of the fact that ontogeny is inextricably linked to phylogenetic selection (Cairns, 1979; Gaulin & McBurney, 2001). Accordingly, then, there still remains a need to consider the function of indirect aggression, as there should be a reason for its consistent use by females across the planet. One such explanation is that, for females, indirect aggression may pay off in evolutionary terms by increasing access and retention of high-quality males and their resources, and thus increasing their reproductive fitness.

ACKNOWLEDGMENTS I wish to thank Amanda Krygsman, Brynn Winegard, and Sigal Balshine for their helpful comments regarding this chapter. I also wish to thank Richard Tremblay, Bill Hartup, and John Archer for their careful review of, and suggestions for, this chapter.

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THE DEVELOPMENT Proactive and Reactive Aggression OF AGGRESSION

9 Proactive and Reactive Aggression A Developmental Perspective F RANK V ITARO and M ARA B RENDGEN

TERMINOLOGIES AND DEFINITIONS Different subtypes of aggressive behaviors may be defined on the basis of their form. For example, based on form, several authors have suggested distinctions between physical and nonphysical aggression (Tremblay, 2000) or between direct and indirect/relational aggression (Björkqvist, Lagerspetz, & Kaukiainen, 1992; Crick & Grotpeter, 1995). Others proposed subtyping of aggressive behaviors on the basis of the underlying goal (i.e., function, motivation). One such subtyping with respect to the underlying goal that has received increasing attention is the distinction between reactive and proactive aggression (Dodge, 1991; Dodge & Coie, 1987). The concept of reactive aggression has its roots in the frustration–anger theory of aggression (e.g., Berkowitz, 1963, 1993; Dollard, Doob, Miller, Mowrer, & Sears, 1939). According to this perspective, aggression is a response triggered by goal blocking and is accompanied by high autonomic arousal (i.e., anger). Reactive aggression thus occurs as a consequence of antecedent conditions of real or perceived provocation, frustration, or threat and is usually accompanied by the expression of anger. Its main goal is to react to the anger–frustration stimulus and hurt the perpetrator of the provocation or the threat. Finally, it is rather immediate and impulsive in response to the source of provocation or threat. As such, reactive aggression can be linked conceptually to behavior displayed by Type A personalities, who are easily irritable and angered by provocation, competition, or denigration (Holmes & Will, 1985). In line with the frustration—aggression 178

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model, reactively aggressive behaviors and anger can be viewed as unconditioned temperamentally based reactions or conditioned emotional responses to external events (Berkowitz, 1989). This view, however, does not imply that external contingencies cannot influence the use of reactively aggressive acts or moderate their links to anger feelings. Conceptually, reactive aggression can be used as a synonym for “defensive,” “angry,” “hot blooded,” “impulsive,” “emotional,” or “retaliatory” aggression (Berkowitz, 1993; Buss, 1961; Feshback, 1964). Conversely, the concept of proactive aggression is more in line with the social learning model of aggression (Bandura, 1973, 1983), which postulates that aggression is an acquired behavior governed by reinforcement contingencies. According to this notion, proactive aggression is thought to be driven by the anticipated rewards that follow the perpetration of aggressive acts. For example, proactive aggression can be used as an instrumental means to secure goods from others or to dominate others. Synonyms for proactive aggression are “offensive,” “predatory,” and “instrumental” aggression. Following these two theoretical concepts of aggression, a substantial number of researchers have differentiated between reactive acts of aggression, committed out of anger or fear, and goal-directed proactive aggression (Berkowitz, 1989, 1993; Buss, 1961; Dodge, 1991; Feshback, 1964; Parke & Slaby, 1983; Pulkkinen, 1987; Zillman, 1979). Others, however, have challenged the view that the distinction between reactive and proactive aggression in humans is reliable, valid, and useful (Bushman & Anderson, 2001). The question is thus whether reactive and proactive aggression are indeed two distinct types of aggressive behaviors, that is, whether they can be distinguished not only theoretically but also empirically. If the answer is yes, then important implications follow. At the theoretical level, two distinct etiological models may be necessary to account for the origins and the developmental course of each type of aggressive behavior. At the practical level, it will be necessary to measure the two types of aggressive behaviors separately. At the clinical level, evidence for a distinction between reactive and proactive aggression might necessitate specific treatments and prevention programs for each type of aggressive behavior. The purpose of this chapter is to more closely examine the empirical evidence in support of, or against, this distinction. Because the main focus of this book is the investigation of the developmental origins of aggressive behavior, we review studies of proactive and reactive aggression that are based on child and adolescent samples; adult data are also discussed in some cases. The first part of the chapter is devoted to measurement and construct validity issues regarding proactive and reactive aggression. The second part reviews evidence supporting or contesting the distinction between the two types of aggressive behaviors by examining the personal, social, behavioral, and physiological correlates of proactive and reactive aggression. In the third part, we attempt to integrate the existing findings into a tentative developmental model of

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proactive and reactive aggression and point out specific areas that merit further research.

MEASUREMENT AND VALIDITY ISSUES Measurement With some notable exceptions (i.e., Chaux, Arboleda, & Rincón, 2003; Coie, Dodge, Terry, & Wright, 1991; Little, Jones, Henrich, & Hawley, 2003b; Pulkkinen, 1996), the majority of studies on proactive and reactive aggression in human children used questionnaire-based measures that are usually evaluated by teachers, or in some instances, by parents or peers. With the exception of the aforementioned investigations, the studies have used six items originally developed by Dodge and Coie (1987) to operationalize the two different types of aggression. The proactive items are, “This child uses physical force, or threatens to use force, to dominate other children,” “This child threatens or bullies others in order to get his/her way,” “This child gets other children to gang up on a peer he/she does not like.” The reactive items are, “When this child has been teased or threatened, he/she gets angry easily and strikes back,” “When a peer accidentally hurts this child, this child assumes that the peer meant to do it and then overreacts with anger and fighting,” This child claims that other children are to blame for a fight and feels like they started the trouble.” On the basis of these items, some authors then analyzed the continuous total scores of reactive and proactive aggression, respectively. Others created groups of individuals who scored high (e.g., one standard deviation above the mean or more) or low (e.g., less than one standard deviation above the mean) on one or both types of aggressive behaviors to identify proactive-only, reactive-only, proactive–reactive, and nonaggressive individuals. For example, in one study, about 53% of children were found to be both proactively and reactively aggressive, about 32% were only reactively but not proactively aggressive, and about 15% were only proactively but not reactively aggressive (Dodge, Lochman, Harnish, Bates, & Pettit, 1997). Despite slight variations due to different cutoff criteria, these percentages are very similar across different studies (e.g., Pulkkinen, 1996; Vitaro, Gendreau, Tremblay, & Oligny, 1998). The first strategy is called the “variable-centered approach,” and the second is known as the “person-centered or grouping approach.” The variable-centered approach is mostly used (1) to test the factor structure of proactive and reactive aggression or (2) to examine the unique relations of the continuous reactive and proactive aggression scores (i.e., controlling for the respective other type of aggression) with some other continuous variable such as, for example, self-esteem. In contrast, the person-centered approach is used to examine differences between the aggression groups (i.e., proactive-only, reactive-only, proactive–reactive, and nonaggressive individuals) in regard to a given set of variables. The use of continuous scores of proactive and reactive

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aggression has the obvious advantage of using of the full variability of these behaviors. However, given that aggression scores are often non-normally distributed, with most individuals receiving low scores and a few individuals receiving high scores, the person-centered approach is also reasonable and does not necessarily diminish statistical power (Farrington & Loeber, 2000). Nevertheless, the use of arbitrary cutoffs to create groups of reactively and/or proactively individuals remains an important and difficult-to-solve problem for the person-centered approach, which might affect the interpretability and comparability of findings across studies. Despite their methodological differences, however, the two approaches basically yield the same information in regard to the question of whether the distinction between proactive and reactive aggression is valid. Therefore, we include both studies using a variable-centered approach and studies using a person-centered approach in this chapter.

Factor Structure The first question that needs to be answered in regard to the proactive–reactive dichotomy is whether the two can be at all distinguished on a measurement level. Individuals obviously can exhibit both reactive and proactive aggression (Berkowitz, 1993; Dodge, 1991), and continuous proactive and reactive aggression scores indeed correlate on average at r = .70 (± .15) in variable-centered studies. Similarly, a majority of participants identified as aggressive in personcentered studies score above the cutoffs on both reactive and proactive aggression, whereas only a minority are only reactive and even fewer are only proactive (Dodge, Lochman, Harnish, Bates, & Pettit, 1997; Pulkkinen, 1996; Vitaro et al., 1998). These results seem to speak against a clear distinction between reactive and proactive aggression at the empirical level and are in line with arguments by Bushman and Anderson (2001) that it is often not possible to conclude whether an aggressive act is reactively or proactively motivated. Despite the high overlap between the two types of aggression, exploratory and confirmatory factor analyses nevertheless yield two distinct factors in line with the reactive–proactive dichotomy (Brown, Atkins, Osborne, & Milmanow, 1996; Crick & Dodge, 1996; Day, Bream, & Paul, 1992; Dodge & Coie, 1987; Pellegrini, Bartini, & Brooks, 1999; Poulin & Boivin, 2000a; Salmivalli & Nieminen, 2002). For example, Poulin and Boivin (2000a) used confirmatory factor analysis to test whether a one- or two-factor solution would best fit the data. They found that a two-factor model showed better fit indices than a single-factor model, based on teacher and parent ratings of children’s proactive and reactive aggression, but were unable to distinguish between reactive and proactive aggression when using peer data. However, other authors did find a two-factor structure based on peer-rated reactive and proactive aggression using exploratory factor analysis (e.g., Salmivalli & Nieminen, 2002). Even stronger evidence for the factorial distinctiveness of proactive and

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reactive aggression comes from a recent study by Little et al. (2003b). Previous studies on proactive and reactive aggression have focused exclusively on direct, especially physical, forms of aggression. Little and colleagues, however, distinguished not only between the different functions of aggression (i.e., between proactivity and reactivity, labeled instrumental and reactive in their study), but also between the different forms that aggressive behavior can take (i.e., overt/direct versus relational/indirect). Based on self-reports of aggressive behavior from children in grades 5–10, confirmatory factor analysis revealed a clear four-factor structure. Specifically, two distinct constructs referring to the function of aggression were identified—proactive and reactive aggression—as well as two distinct constructs referring to the form of aggression—overt and relational aggression. Notably, by taking into account any confounds between proactive and reactive aggression that might be due to a similar form of aggression, Little et al. (2003b) showed that proactive and reactive aggression were basically uncorrelated (r = –.10). This obvious distinctiveness of proactive and reactive aggression was the same across age (grades 5–7 vs. grades 8–10), gender, and ethnic groups (i.e., in German and Turkish children).

Construct Validity of the Proactive–Reactive Distinction As we have seen, it seems possible to reliably measure two distinct factors of proactive aggression and reactive aggression in children and in adolescents. The question emerges, however, as to whether these measures indeed capture the proactive–reactive distinction on a conceptual level. Dodge & Coie (1987) were the first to examine the convergent validity of their teacher-rated measure of reactive and aggressive aggression by comparing it with direct observations of proactive and reactive aggression during children’s interactions in small play groups. These authors found that teacher ratings and direct observations of the same type of aggressive behavior were moderately correlated (i.e., r = .27 for both types of aggressive behavior), indicating that questionnaire-based measures of proactive and reactive aggression are indeed rooted in real-life behavior. A similar conclusion can be drawn from research linking psychopathy and proactive versus reactive aggressive tendencies in adult offenders. For example, in two ethnically different samples of incarcerated adults, proactive but not reactive aggression was significantly correlated with Factor 1 of the Psychopathy Checklist (PCL; Harpur, Hakstian, & Hare, 1989) (Joseph P. Newman, personal communication). Factor 1 of the PCL covers personality traits such as callousness, a lack of affect, guilt, remorse, and empathy, habitual lying and manipulation, and superficiality, which closely resemble the definition of proactive aggression as instrumental and “cold-blooded.” Similar findings were obtained in a person-centered study showing that incarcerated proactive–reactive adult offenders are more psychopathic than either reactive-only violent offenders or nonviolent offenders (Cornell et al., 1996).

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Other Validity Issues: The Underlying Social Cognitions of Proactive and Reactive Aggression The view of reactive aggression as an angry response to real or perceived provocation, and of proactive aggression as an instrumental means driven by the anticipated rewards, implies that the underlying social–cognitive processes of these two types of aggression should be very different. In line with this notion, several studies have shown that reactive but not proactive aggression is related to hostile attributional biases in response to ambiguous provocation (Dodge & Coie, 1987; Crick & Dodge, 1996; Dodge et al., 1997; Hubbard, Dodge, Cillesen, Coie, & Schwatz, 2001; Schippell, Vasey, Cravens-Brown, & Bretveld, 2003). Reactive but not proactive aggression is also related to biased attention for rejection, ridicule, and failure cues (Schippell et al., 2003). Moreover, as compared with nonaggressive children, only reactively aggressive children manifest problem solving deficits in difficult social situations (Dodge, 1991; Kolko & Brown, 1997; Price & Dodge, 1989). In contrast, proactively aggressive children value aggression as an effective means to achieve desired goals more than other children (Crick & Dodge, 1996; Dodge et al., 1997). Similarly, proactive but not reactive aggression was related to positive outcome expectancies for aggressive behavior in a sample of incarcerated male adolescents (Smithmyer, Hubbard, & Simons, 2000). Although these findings do not reveal the directionality of effects between social cognitions and proactive or reactive aggression, they nevertheless support the notion of two forms of aggressive behavior that are used in different contexts and for different purposes.

Validity of Proactive and Reactive Aggression: A Word of Caution The empirical evidence reviewed here indicates that the distinction between proactive and reactive aggression is internally valid. However, it is important not to equate the proactive and reactive distinction with other terminologies. For example, a distinction between instrumental and hostile aggression might be used as a synonym for the proactive–reactive aggression distinction (e.g., Bushman & Anderson, 2001), but this equation may not necessarily be appropriate. Thus, in some studies, instrumental aggression has been operationalized by the rate at which a child pressed a button, which created an obstacle to victory for a (fictitious) opponent during a competitive game. Hostile aggression was defined by the rate at which the child pressed a different button, which caused the opponent to hear an aversive noise (Atkins & Stoff, 1993; Atkins, Stoff, Osborne, & Brown, 1993b; Hoving, Wallace, & La Forme, 1979). This type of aggressive behavior was termed “hostile” because it gave no apparent advantage to the child with respect to the game. It is obvious from this description that not only instrumental but also hostile aggression can be proactive (i.e., initiated by the aggressor without a triggering provocation from the opponent). In addition, hostile aggression does not necessarily

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include the emotional features (i.e., anger) that characterize reactive aggression. Empirical evidence for the notion that the proactive–reactive distinction may not be synonymous with instrumental and hostile aggression, respectively, comes from a study examining the links between teacher-rated proactive– reactive aggression and instrumental–hostile aggression using the competitive paradigm described earlier (Atkins et al., 1993a). The results indicated that boys who engaged in high rates of instrumental aggression were likely to be rated by teachers as high in proactive aggression, but this was true only for boys who were rejected by their peers. In contrast, boys who engaged in high rates of hostile aggression were rated by teachers as high in both proactive and reactive aggression. Again, this result applied only to rejected boys. Obviously, although there is a parallel between instrumental and proactive aggression, reactive aggression cannot be equated with hostile aggression. These subtle but important differences between different terminologies need to be kept in mind when interpreting empirical findings from different studies.

CORRELATES OF PROACTIVE AND REACTIVE AGGRESSION So far, we have seen that the distinction between proactive and reactive aggression seems to be sufficiently reliable and also shows reasonable construct and convergent validity. Another way to examine whether proactive and reactive aggression are two distinct constructs is to test whether reactive and proactive aggression have different concurrent or longitudinal correlates (Campbell & Fiske, 1959). As discussed in the following paragraphs, empirical findings indeed support the notion that the two types of aggression are differently related to various personal, social–environmental, behavioral, and physiological factors.

Temperament So far, only one study has examined whether proactive and reactive aggression are differentially related to temperament (Vitaro, Brendgen, & Tremblay, 2002). The findings are in line with the view of reactive—but not proactive— aggression as an intense temperament-based response to an aversive stimulus. By age 6, reactively aggressive preadolescents (whether also proactively aggressive or not) already seem to be temperamentally more reactive and more inattentive than proactive-only or nonaggressive children, who actually do not differ from each other in this respect. Notably, reactively aggressive preadolescents in the Vitaro et al. (2002) study also showed increased reactivity to unconditioned stimuli such as light or pain by age 6, suggesting that these youngsters might be prone to react to any disturbance from a social or a nonsocial source. These findings concur with the image of reactively aggressive children as more excitable than proactively aggressive or nonaggressive children, because of a lower response threshold in regard to disturbing stimuli.

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However, because temperament was assessed at age 6, temperament measures may reflect socialization influences as well personal dispositions at that age. As shown next, empirical evidence indeed suggests that proactive and reactive aggression are related to very different socialization experiences within the family and with peers.

Family History Dodge hypothesized that a history of social–environmental hostility and maltreatment is implicated in reactive aggression, whereas a history of exposure to successful aggressive models and a positively reinforced experience with coercive behavior are implicated in proactive aggression (Dodge, 1991; Dodge & Coie, 1987). Existing studies seem to confirm this hypothesis. Thus, parents of reactively aggressive schoolchildren have been found to be more controlling and punitive during the preschool years than parents of proactively aggressive or nonaggressive children (Bowen & Vitaro, 1998). Similarly, in a sample of young adolescent males treated for severe behavior problems, the reactively aggressive youngsters demonstrated histories of physical abuse, whereas proactively-only and proactively–reactively aggressive individuals did not (Dodge et al., 1997). In contrast, proactively aggressive adolescents seem to enjoy rather positive family relations as compared with their proactively– reactively aggressive or reactively aggressive counterparts (Poulin & Dishion, 2000). At the same time, proactively aggressive youth report less parental monitoring and fewer household rules than the reactively aggressive group and the nonaggressive group (Poulin & Dishion, 2000). Although suggestive of a unidirectional causal influence of different parenting practices on proactive and reactive aggression, these results may be interpreted in more than one way. For example, if indeed reactive aggression has its roots in a highly reactive, difficult temperament, parents may soon become exasperated by their reactively aggressive child’s behavior and develop a negative attitude toward him or her as a consequence. What may seem like a cause may thus well be a consequence of the child’s reactive behavior. Once again, only the study of a birth cohort of children and their parents may help solve this chicken-and-egg problem and possibly reveal a transactional instead of a unidirectional process between children’s and parents’ behaviors.

Peer Relations In addition to different family experiences, proactive and reactive aggression also seem to entail different experiences with peers, both in terms of children’s level of acceptance in the peer group and in terms of their dyadic friendships. Overall, existing data indicate that reactive aggression seems to be less tolerated by other children than proactive aggression. For example, reactive but not proactive aggression has been linked to low social preference during the preschool years as well as in late childhood and adolescence, both when using

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continuous measures of aggression (Alvarez & Olson, 1999; Price & Dodge, 1989; Prinstein & Cillessen, 2003) and when employing a person-centered approach (Dodge et al., 1997; Poulin & Boivin, 2000a). Further evidence that reactive but not proactive aggression is related to peer difficulties comes from research showing that reactive children are also more victimized than proactive children (Poulin & Boivin, 2000a). It is clear from these results that reactively aggressive children are at high risk for maltreatment by peers, in addition to maltreatment by adults (Dodge et al., 1997). In turn, maltreatment by peers may aggravate their reactive tendencies and their propensity for hostile attributions. This hypothesis is supported by recent data showing that peer rejection during the early elementary years predicted later reactive aggression more than later proactive aggression (Dodge et al., 2003). Proactive aggression also seems to be more tolerated and even reinforced by peers at the dyadic level. Thus, proactively aggressive children not only have more friends than reactively aggressive children, but the former also have a greater tendency to have similarly aggressive friends than the latter (Poulin & Boivin, 2000b). Moreover, friends’ proactive aggressiveness has been shown to increase children’s own proactive aggressiveness over the course of a school year, whereas friends’ reactive aggressiveness has no influence on children’s own aggressiveness profile (Poulin & Boivin, 2000b). Once more, these results concur with the view that proactive aggression is supported by positive socialization experiences whereas reactive aggression is related to or results from aversive experiences. However, the greater acceptability of proactive aggression among peers seems to depend on the context in which proactively aggressive behavior is used. Although object-oriented proactive aggression is indeed unrelated to peer acceptance, person-oriented proactive aggression (i.e., bullying) has been found to be negatively related to popularity among peers (Price & Dodge, 1989). These latter findings suggest that the link between each type of aggressive behavior and peer status may be conditioned by contextual and dispositional factors, such as local norms regarding use of aggression, children’s age, and possibly other methodological elements such as the type of specific measures or instruments used.

Other Related Adjustment Problems In light of the negative experiences in the family and peer contexts associated with reactive aggression, it is perhaps not surprising that reactive aggression has also been linked with other concurrent behavioral, emotional, and cognitive adjustment problems to a greater extent than proactive aggression. For example, reactive aggression, but not proactive aggression, is significantly correlated with disruptive classroom behaviors (Waschbusch, Willoughby, & Pelham, 1998). Reactive-only boys and proactive–reactive (but not proactiveonly) boys are also less skilled than nonaggressive children at responding to teasing, sharing, negotiating, handling failure, compromising, and displaying sportsmanship, and perform more poorly in school (Day et al., 1992). More-

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over, reactive but not proactive aggression has been linked to internalizing problems such as withdrawal, anxiety, depression, and psychosomatic symptoms, as well as ADHD diagnosis and personality disorder (Day et al., 1992; Dodge et al., 1997; Vitaro et al., 2002). In contrast, proactive aggression has sometimes even been associated with reduced anxiety (Scarpa, Hurley, & Hirai, 2002). An extensive test of the notion that reactive aggression but not proactive aggression is linked with a host of concurrent adjustment difficulties has been performed in a recent study of primary and secondary school children (Little et al., 2003a). In addition to the three usual groups of highly reactiveonly, highly proactive-only, and highly reactive–proactive individuals, these authors distinguished between two groups of nonaggressive participants, namely, children with a typical/average level of proactive and/or reactive aggression and children with very low levels of both proactive and reactive aggression. Interestingly, the proactive-only group resembled the typical/average group in many ways. Proactive-only youth did well in school, had positive self-concepts, did not harbor hostile feelings toward others, and were able to regulate feelings of frustration. In contrast, the reactive-only group and the reactive–proactive group showed considerable frustration, intolerance, and elevated levels of hostility, as well as low levels of school performance and intellectual skills, as compared with nonaggressive children. In light of these findings, one might be tempted to conclude that reactively aggressive children experience considerably more adjustment difficulties than proactively aggressive children in a variety of domains. Empirical evidence suggests, however, that not only reactive but also proactive aggression carries substantive risks for developmental adjustment problems. Specifically, proactively aggressive children seem more at risk than reactively aggressive children for some forms of externalizing problems. Thus, teacher-rated proactive but not reactive aggression during childhood has been found to predict later delinquency and conduct disorders during adolescence in low SES boys (Vitaro et al., 1998). These results were replicated in another study with a representative sample of children that also included girls (Vitaro et al., 2002). Proactive-only children were mostly at risk for later overt delinquency (e.g., violent bullying and gang fights), whereas reactive-only children were not more involved in overt or covert delinquent behaviors than nonaggressive children. Other researchers also found that proactive aggression but not reactive aggression predicts later criminal behavior (Pulkkinen, 1996). Finally, there is evidence with adult criminals (Cornell et al., 1996), as well as with adolescent offenders (Connor, Steingard, Anderson, & Melloni, 2003) and normal adolescent samples (Poulin & Dishion, 2000), that proactive but not reactive aggression is concurrently related to criminal behaviors and substance use. Part of the explanation of why proactively aggressive children are more at risk of later delinquency-related problems involving other co-offenders may lie in the fact that proactively aggressive children often have friends who are similarly proactively aggressive, whereas reactively aggressive children are often

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friendless (Poulin and Boivin, 2000b). This tentative explanation is further supported by recent findings by Poulin, Dishion, and Boivin (2002) indicating that proactive but not reactive aggression predicts involvement with a deviant peer group from grade 6 to grade 7 even when controlling for gender, current deviant peers, parental monitoring, and peer rejection. Finally, the high anxiety of reactively aggressive children may also help explain why they are not at a similar risk for delinquency-related acts as proactively aggressive children. Anxiety might reflect high harm avoidance, according to Cloninger’s personality model (Cloninger, 1986), or a high inhibition system, according to Gray’s model (Gray, 1982). This disposition to inhibition has been shown to operate as a protective factor against delinquency for aggressive boys (Kerr, Tremblay, Pagani & Vitaro, 1997). Recent evidence suggests, however, that it is not only the proactively aggressive individuals who are at risk for violence and criminal behavior (Brendgen, Vitaro, Tremblay, & Lavoie, 2001). Although confirming that proactive aggression uniquely predicted delinquency-related violence (e.g., gang fights), these authors showed that reactive aggression uniquely predicted dating violence during late adolescence, after controlling for proactive aggression. Findings from Cornell et al. (1996) and Cornell, Benedek, and Benedek (1987) also support the notion that reactively aggressive individuals are more prone to violence in intimate relationships, whereas proactively aggressive counterparts are more inclined to violence in delinquency-related situations such as robbery, gang fights, or drug dealing. The fact that violence against intimate partners often occurs as a defense against feelings of frustration or vulnerability in situations of conflict with the partner (Prince & Arias, 1994) may explain why reactive aggression is specifically related to this type of behavior.

Emotions and Biological Correlates Virtually all the studies reported until now support the validity of the distinction between reactive and proactive aggression by showing different links with social–cognitive, temperamental, behavioral, school-related, peer-related, and family-related correlates. In comparison, only a few studies used biological or affective/emotional correlates to establish the validity of the reactive–proactive dichotomy, and the few existing studies show equivocal findings. For example, the link between reactive and proactive aggression to physiological and observational indicators of anger was examined in a sample of second-grade children (Hubbard et al., 2002). As mentioned previously, anger is, by definition, considered a concomitant (and possibly a cause) of reactive but not proactive aggression and should thus be strongly related to the former but unrelated to the latter. In order to test this notion, angry feelings were induced by exposing the children to a confederate who cheated during a competitive game. Physiological, behavioral, and subjective indicators of anger (i.e., skin conductance and heart rate, angry facial expressions, and angry nonverbal behaviors) were collected during the game and self-reports of anger collected during the subse-

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quent viewing of the game on videotape. Two aspects of each measure were considered: an aggregate score throughout the game and an increased score over the course of the game. Two of the five measures (i.e., angry nonverbal behaviors and skin conductance) were positively related to teacher-rated reactive aggression while controlling for proactive aggression. Moreover, angry nonverbal behaviors were negatively related to proactive aggression. The rate of increase of these behaviors over the course of the game was also positively related to reactive aggression but unrelated to proactive aggression. An aggregate score of skin conductance throughout the game was also uniquely and positively related to reactive aggression. Furthermore, the skin conductance levels of children who were high in reactive aggression increased continuously throughout the game, whereas it did not for children who were low in reactive aggression. Although these results support the distinction between reactive and proactive aggression by suggesting a unique link between reactive aggression and anger, other results from the same study did not support this distinction. Thus, the total number of angry expressions and their evolution during the game were not related to reactive (nor to proactive) aggression. Moreover, self-reports of anger were not related to reactive aggression when averaged across the game, but, unexpectedly, they were related to proactive aggression when examined over the course of the game. Finally, the pattern of results for heart rate reactivity did not support an exclusive link with reactive aggression. When averaged across the game, heart rate reactivity was negatively related to reactive aggression but not to proactive aggression. The authors explain these results by stating the possibility that the game may have elicited as much (if not more) interest as anger in the participants. The fact that heart rate is driven upward by emotional arousal, but downward by interest or orientation to a triggering event, may explain the results with respect to the links between heart rate and proactive and reactive aggression. Other results indicating that teacher-rated reactively aggressive children are not viewed by their classmates as more angry than proactively–reactively and proactively-only aggressive children also cast doubt on the exclusive link between reactive aggression and anger (Dodge & Coie, 1987). Another physiological correlate that may differ for proactive and reactive aggression is cortisol. Cortisol is a marker of the activity of the hypothalamic– pituitary–adrenal (HPA) axis, which is sensitive to physical and psychological stress. Most researchers have reported an inverse relationship between cortisol level and antisociality at all ages (King, Jones, Scheurer, Curtis, & Zarcone, 1990; Woodman, Hinton, & O’Neill, 1978). One study, however, reported high levels of cortisol in conduct-disordered children, provided that they also manifested anxiety problems (McBurnett et al., 1991). Based on behavioral correlates of reactive aggression, these children may well resemble reactively aggressive children. A direct test of this hypothesis was performed recently by van Bokhoven et al. (2003). These authors found that, when controlling for proactive aggression, boys who were high in teacher-rated reactive aggression

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manifested significantly higher levels of cortisol than boys low or average in reactive aggression. Like the majority of studies on cortisol, this study was based on measurements of resting cortisol concentrations. The few other studies that tested for the link between aggression and cortisol in children or adolescents during stress or anger-provoking situations unfortunately did not distinguish between reactive and proactive aggression (Klimes-Dougan, Hastings, Granger, Usher, & Zahn-Waxler, 2001; Susman, Dorn, Inoff-Germain, Nottelmann, & Chrousos, 1997; Van Goozen, Matthys, Cohen-Kettenis, Buitelaar, & Van Engeland, 2000).

CONNECTING THE PIECES: A DEVELOPMENTAL MODEL OF PROACTIVE AND REACTIVE AGGRESSION In light of the studies reviewed in this chapter, can we conclude that the distinction between reactive and proactive aggression is reliable, valid, and useful? Despite a high correlation between the two types of aggressive behaviors and their co-occurrence in a majority of aggressive individuals, reactive and proactive aggression can be distinguished at the factorial level, which speaks to the reliability of the proactive–reactive distinction. In addition, despite some equivocal findings, most existing evidence suggests that reactive and proactive aggression do not seem to share the same correlates at the personal, social, academic, behavioral, and physiological levels. This speaks to the validity of the proactive–reactive distinction. Perhaps most important, personcentered studies consistently show that, in addition to individuals who display both types of aggressive behavior, individuals can be identified who show mostly reactive but not proactive aggression, even though proactively-only aggressive individuals seem to be rare. In light of the different correlates of proactive and reactive aggression, this person-centered distinction may eventually be important in identifying at-risk children for prevention purposes aimed at specific maladjustment outcomes. As such, the existing evidence suggests that the distinction between reactive and proactive aggression can be useful for both theoretical and practical purposes. Obviously, much still remains to be learned about the developmental origins and outcomes of proactive and reactive aggression. For one thing, most of the existing research is based on concurrent data. This makes it impossible to disentangle the directionality of effects between proactive and reactive aggression and their respective associated correlates. Moreover, studies usually focus on only a limited number of correlates, which makes it difficult to assess the relative contribution of a given risk factor to the development of proactive versus reactive aggression. Despite these shortcomings, we believe that the existing data already allow the formulation of a tentative model of the developmental pathways associated with reactive and proactive aggression. In this section we attempt to integrate the current knowledge into such a theoretical

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framework. The starting point is the theoretical model proposed by Dodge (1991), in which reactive and proactive aggression originate from different experiences and develop independently. According to this model, reactive aggression develops in reaction to a harsh, threatening, and unpredictable environment or abusive and cold parenting. Conversely, proactive aggression thrives in supportive environments that foster the use of aggression as a means to achieve one’s goals. Individuals who are high in both types of aggressive behaviors likely experience both types of environment. Many empirical studies reviewed in this chapter support these different etiological pathways for reactive and proactive aggression. This first theoretical model may be termed the parallel development model, because it views reactive and proactive aggression as originating from different etiological factors and as developing in a parallel, almost independent manner. There is, however, another possible model in which temperamental factors operate as main (i.e., initial) effects and in which different psychosocial factors serve as moderators. We call this second model the sequential development model. It is based on the findings, discussed previously, that temperamental and neurophysiological elements seem to play a role in reactive aggression but not in proactive aggression. Conversely, environmental factors seem to play a role mostly in proactive aggression. According to this alternative model, children with certain temperamental or neurophysiological characteristics are initially disposed to display aggressive behavior as a means of interacting with their environment. Initially, this tendency might be expressed mainly in a reactive manner, such as in high irritability and a difficult temperament in early infancy. If early outbursts of anger (screaming, kicking) lead to the desired outcome (food, toys, etc.), these children may learn that such behavior is a successful means not only of alleviating a stressful situation but also of obtaining a desired goal in a nonstressful situation. Gradually, aggression may also be used in a “purely” proactive manner to achieve goals, particularly in a permissive familial or peer environment, which may not only fail to inhibit but even foster this type of behavior. These personal and environmental contingencies related to proactive aggression may eventually open the way to other externalizing behavior problems, in particular delinquency. Such oversimplifications do not imply that proactive aggression has no neurophysiological or genetic correlates or that reactive aggression is not partly dependent on environmental contingencies and learning experiences. Nevertheless, the idea that reactive aggression might precede and open the way to proactive aggression is supported by data showing that elements of reactive aggression such as anger and irritability seem to appear already in early infancy. In contrast, dominating and instrumental proactive aggression directed toward peers does not emerge until about 12 months of age, when conflicts become extremely frequent, characterizing as much as half of peer exchanges between 12 and 18 months (Caplan, Vespo, Peterson, & Hay, 1991). Also in support of this notion, longitudinal data from Lansford, Dodge, Pettit, and Bates (2002)

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showed that reactive aggression in one year is predictive of proactive aggression in the next over a period of several years (i.e., from kindergarten through grade 7), whereas proactive aggression does not predict subsequent reactive aggression. Why do not all children with an initial disposition for aggressive behavior display both reactive and proactive aggression later on? More specifically, why are some individuals mainly reactively but not proactively aggressive and why are there so few who seem to use aggression in a proactive but not in a reactive manner? Some aggressive children may be less successful than others in controlling resources and dominating through aggression, perhaps because they are more frequently and severely punished for aggressive acts or because they are more anxious and sensitive to punishment. To avoid negative consequences, these aggressive children may stop using or never start using (physically) aggressive behavior in a proactive fashion and may adopt alternative strategies for goal achievement. Nevertheless, because of their high sensitivity to stressful stimuli and their lack of impulse control, these children may remain reactively aggressive and use aggression when provoked or threatened and would therefore be called the “reactive-only” group. Because of their high reactivity to stress, these children may eventually also develop internalizing problems, which may be exacerbated by other problems associated with reactive aggression, such as peer rejection, victimization, or low school achievement. The question then remains as to how some children come to be proactiveonly if aggressive behavior is indeed initially used mainly in a reactive manner. One possible explanation is that these children may experience very few provocations from others, perhaps because of their greater physical strength or because they possess other personal characteristics that make them an unlikely target of attacks from others. In their case, there may not be much need to use aggression in a reactive manner. As a consequence, outside observers such as teachers, parents, or peers, who are often used to evaluate children’s aggression, may hardly ever observe reactive aggression in these children. The use of proactive aggression in these children is shaped through reinforcement contingencies and maintained through beliefs in its power and deference of its effects on the victims. This is not to say that these children would not use aggression in a reactive manner if they were provoked. In fact, given that their proactive aggression is a very successful strategy of goal achievement, it is highly likely that these children will avert a provocation or threat from another child through aggressive means with equal success. Thus, there may in fact not really be a group of “proactive-only” children, a notion that is fostered by the extremely small number of children identified as such in empirical studies (e.g., Dodge et al., 1997; Pulkkinen, 1996; Vitaro et al., 1998). Of course, the described developmental processes of reactive and proactive aggression remain highly speculative at this point. However, this (temporary, it is hoped) situation should not weaken the conclusion that subtypes of aggressive behav-

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iors based on their function can and should be distinguished in future research and that pertinent instruments should be developed in that direction. In the rest of this chapter, we identify areas in need of investigation and offer possible directions for future research.

OPEN QUESTIONS AND ADDITIONAL ISSUES Developmental Trajectories As mentioned earlier, many open questions remain that preclude a full understanding of the etiology of proactive and reactive aggression. An obvious issue in need of clarification is the question of whether the “age of onset” and the developmental course of proactive and reactive aggression differ. In our tentative model, we have speculated that reactive aggression precedes proactive aggression, but no study (to our knowledge) has examined the developmental trajectories of reactive and proactive aggression from birth onward to examine the developmental course of the two types of aggressive behavior. Some support of the notion that reactive aggression seems to start at an earlier age than proactive aggression is provided by findings that, according to mothers’ reports, clinically referred reactively aggressive boys were 4.4. years old when their behavior problems began, whereas proactively aggressive boys were 6.8 years old when their behavior problems began (Dodge et al., 1997). Given the retrospective nature of the assessments, the characteristics of the sample, and the possibility that reactive aggression was reported earlier because it was more salient than proactive aggression, these results are difficult to interpret. There is only one study, to our knowledge, that has directly tested the mean level development of proactive and reactive aggression over an extended period of time, that is, from kindergarten through grade 7, through growth curve analysis (Lansford et al., 2002). In this study, children displayed higher levels of reactive aggression than of proactive aggression during kindergarten. On one hand, this finding might indicate that proactive aggression develops at a later age than reactive aggression. On the other hand, because both types of aggression decreased with age, it is also possible that both types of aggression emerge at the same time but that socialization experiences succeed more quickly in teaching children to abandon the use of aggression for instrumental purposes. This may be more difficult to achieve with the highly emotiondriven reactive aggression. Obviously, more longitudinal research is needed to clarify the developmental course of proactive and reactive aggression. In this context, the use of new clustering techniques for longitudinal data, such as Nagin’s (1999) trajectories procedure would be especially useful to identify groups of children with different longitudinal profiles of proactive and/ or reactive aggression and to examine the longitudinal course of these children’s aggressive behaviors.

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In Search of Causality: Experimental Manipulation of Reactive and Proactive Aggression Apart from mapping the longitudinal developmental course of behaviors such as proactive and reactive aggression, the big challenge in developmental research is to detect the causal links between these behaviors and associated variables. As mentioned earlier, most of the discussed studies on proactive and reactive aggression are based on concurrent data, although some used longitudinal designs either (1) to investigate potential antecedents of proactive and reactive aggression while controlling for previous levels of the two types of aggression or (2) to assess the putative outcomes of proactive and reactive aggression while controlling for previous levels of the outcome measures. Even in longitudinal studies, however, effects may be difficult to interpret. For example, the contribution of a putative environmental factor such as parental behavior on the etiology of proactive and reactive aggression is difficult to interpret because the effect may also be due, for example, to the genetic transmission of aggressive behaviors. The use of twin samples provides a better control of this problem because it allows testing additive models of variance decomposition, which distinguish between heritable or genetic influences, shared environmental influences, and nonshared environmental influences on the phenotypic (i.e., behavioral) similarity between twins (Neale & Cardon, 1992). Although, to our knowledge, no studies to date have used a twin design to examine the antecendents (or outcomes) of proactive and reactive aggression, this approach represents a promising avenue for future research. Although superior to studies producing cross-sectional or simple longitudinal data, even a twin design does not provide clear information about the causality of effects between proactive and reactive aggression, on the one hand, and associated variables, on the other hand. A test of causality can be achieved only through experimental manipulation. One such way to test, for example, the specific causal link between reactive or proactive aggression, and their putative antecedents, would be to reduce the hypothesized antecedent risk factor through intervention and see whether proactive or reactive aggression is decreased subsequently. For example, the notion that a lack of anger management skills represents a risk factor for reactive but not for proactive aggression could be tested by improving anger management skills in aggressive children and testing whether reactive—but not proactive—aggression is reduced as a consequence. Similarly, potential outcomes of proactive and reactive aggression could be examined by reducing either proactive or reactive aggression through intervention and investigating whether the outcomes that are considered specific to one type of aggression or the other (e.g., delinquent behavior or depression) are reduced subsequently. To date, only one study (to our knowledge) has attempted a manipulation of putative specific antecedents of proactive and reactive aggression through intervention (Phillips & Lochman, 2003). A normative sample of 10–12-yearold boys from low SES families was divided into a reactive-anger manipula-

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tion group and a proactive-instrumental manipulation group. The children in the reactive-anger manipulation group were trained to recognize angry feelings, to control impulsive responses, and to relax and refocus attention when angry. Children in the proactive-instrumental manipulation condition learned to recognize domineering behavior and to think about the positive consequences of using nonaggressive acts. Results indicated that the reactive manipulation was indeed successful in specifically reducing reactive aggression and anger in a competition game. Contrary to what would be expected, however, the proactive manipulation resulted in lowered levels of both reactive and proactive aggression. Lochman and collaborators used a similar approach to test outcomes specific to proactive and reactive aggression. The first study used a childcentered small-group-format program aimed at teaching aggressive boys with anger management problems to regulate their angry feelings and improve their social problem-solving strategies (Lochman, 1992). Although reactive and proactive aggression were not measured specifically, it is reasonable to assume that the program impacted mostly on reactive aggression, given its aim and the participants’ characteristics. Interestingly, later delinquency was not reduced despite a proximal positive effect of the program on reactive aggression and social-problem–solving skills. This finding is thus in line with the previously discussed correlational studies showing that reactive aggression does not predict subsequent delinquency (e.g., Pulkkinen, 1996; Vitaro et al., 2002). In a more recent prevention program called the Power Coping Program, a significant proximal effect of the child-centered program on angry feelings and hostile attributions in the aggressive participants was found (Lochman & Wells, 2002; Lochman & Wells, 2004). Again, no effect was found on delinquency and substance use one year after the end of the program. Interestingly, however, the data show that the combination of the Coping Power Program with a Parent Training Component and a universal prevention program was successful in improving parent disciplinary strategies and in reducing children’s positive outcome expectancies regarding aggression. Parent-rated and teacher-rated proactive aggression also decreased. Moreover, the combined program successfully reduced substance use and delinquency one year later. These results suggest that reducing proactive aggression and associated positive expectations regarding the use of violence has an impact on later delinquency and later substance use. In contrast, reducing anger-driven reactive aggression seems less effective in this regard. It should be noted, however, that no analysis was performed in these studies to directly test this mediational assumption. These studies provide excellent examples of how experimental manipulation in an intervention can be used for testing causal linkages between proactive and reactive aggression, respectively, and putative antecedents or outcomes. To be sure, intervention studies would be a costly strategy if the sole purpose were the testing of theories. However, the potential benefits for the developmental adjustment of proactively and/or reactively aggressive chil-

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dren makes the intervention approach an attractive option and more, similar studies are needed.

Gender, Ethnicity, and Culture A final issue in need of further research is the question of potential differences between boys and girls, and between ethnic or cultural groups, with respect to the prevalence or etiology of proactive and reactive aggression. As mentioned, many of the previously discussed studies on proactive and reactive aggression have been conducted with boys only, and the few studies that did examine gender differences reported equivocal results. For example, in a sample of German and Turkish participants in grades 5–10, boys were found to display more proactive aggression than girls, whereas girls were more reactively aggressive than boys (Little et al., 2003b). In a sample of American adolescents in grades 6–8, however, boys reported only higher levels of reactive aggression, but not of proactive aggression, than girls at the first time of measurement (Little, 2002). However, reactive aggression in that study decreased in boys over an 18-month interval, whereas it increased in girls, so that boys and girls did not differ any more in regard to reactive aggression at the final point of measurement. In yet another study with a clinically referred adolescent sample, no gender differences were found in regard to both proactive and reactive aggression (Connor et al., 2003). An even greater lack of knowledge exists with respect to a potential difference in proactive and reactive aggression between different ethnic groups and cultures. So far, only one study—to our knowledge—has examined potential differences between different ethnic groups with respect to proactive and reactive aggression (Little et al., 2003b). These authors not only examined potential gender differences but also compared Turkish and German children with respect to the prevalence of proactive and reactive aggression. The Turkish children reported more reactive but not more proactive aggression than the German children. To be sure, the detection of differences between genders or cultural groups in regard to proactive and reactive aggression has limited value unless we try to understand the underlying mechanisms that may explain these differences. For example, the dissimilarity between Turkish and German children with respect to reactive aggression may hint at possible differences in temperamental and potentially heritable characteristics between ethnic groups, or might reflect different cultural norms concerning the expression of reactive aggression. Only through a comprehensive comparison of the interplay between behavioral, cognitive, environmental, and biological factors in boys and girls or between ethnic groups can we hope to gain a better understanding of the cultural or gender differences in proactive and reactive aggression. At the same time, such research might provide valuable insights into the etiology of proactive and reactive aggression, especially when based on longitudinal data or combined with powerful methodological approaches such as twin designs or experimental manipulations.

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In this chapter, we have attempted to summarize and integrate the existing knowledge regarding the reliability, the validity, and the theoretical and practical usefulness of the distinction between proactive and reactive aggression. Although limited and not always consistent, the available evidence supports this distinction. Nevertheless, we are still a long way from a full understanding of the developmental origins and course of proactive versus reactive aggression. With new longitudinal research and innovative measurement and analytical tools, the next decade promises to open the door to a greater insight into these different aspects of aggressive behavior.

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THE DEVELOPMENT Homicide, Violence, andOF Developmental AGGRESSION Trajectories

10 Homicide, Violence, and Developmental Trajectories R OLF L OEBER , E RIC L ACOURSE , and D. L YNN H OMISH

The title of this book, Developmental Origins of Aggression, necessarily focuses on childhood as the period in which many children display aggression and outgrow aggression (Tremblay et al., 2004). More contentious is whether persistent aggression can first emerge after the first few years of life and how important it is to study escalation in the severity of aggression from childhood onward. In this chapter we do not deal with the onset of aggression in the preschool period. Instead, we focus on two aspects of violence processes: late onset and escalation processes, especially processes leading to violence and homicide. Typically, the onset of violence (such as rape, robbery, and aggravated assault) and homicide takes place in late adolescence and early adulthood (Snyder & Sickmund, 1999). It is vastly different in form as compared with typical forms of aggression during childhood, involving more force, more trauma to the victim’s body, and often the use of a lethal weapon such as a gun. Homicide is the most serious forms of aggression. We are particularly interested in tracing the developmental origins of homicide between childhood and early adulthood. An important assumption about individuals who commit homicide is that they have shown violent behaviors consistently earlier in life. However, this assumption has been challenged (Heide, 2003), and we reexamined it with prospectively collected data rather than using retrospective data, which are typical of almost all homicide studies. In this chapter we address three key questions: 1. Are there developmental precursors to homicide? 2. Which developmental trajectories in violence are particularly relevant 202

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to homicide, and are most homicide offenders positioned on the highest and most stable trajectory of violent individuals? 3. What is the relevance of the findings for interventions and the prevention of aggression, violence, and homicide? We address these questions in the context of two theoretical conceptualizations of the explanation of delinquency: population heterogeneity and state dependency.

VIOLENCE AND HOMICIDE In the United States alone, during 1999 there were 46 homicides, 1,050 sexual assaults and 2,220 robberies committed each day. Homicide is known to be the second leading cause of death for persons ages 15–24 (Federal Bureau of Investigation, 2001). During the past two decades the overall rate of homicide and violence has varied. From the early 1980s through the early 1990s, the juvenile homicide rate increased substantially to reach a peak of 14 homicides per 100,000 persons in 1993. The increase in violence during the 1990s was so spectacular that it was described by many scholars as an unprecedented epidemic (Cook & Laub, 1998; Cook & Laub, 2002; Blumstein, 2002). This epidemic was mostly characterized by an increase in gun-related homicides. Subsequently, the homicide rate dropped dramatically to around 6 per 100,000 in the United States and 1.9 per 100,000 in Canada in the early 2000s. Although this apparent decline in overall homicide offending is encouraging, the homicide rate today is at approximately the same rate as it was in the early 1980s. Strikingly, this increase and drop in violence affected specific age segments of the population, teenagers and young adults. Although this apparent decline in overall homicide offending in youth is encouraging, it remains a very important issue inasmuch as the youth homicide and violence rate today remains high. More research is needed to better understand the developmental heterogeneity of violence in the population and the environmental and proximal factors that can increase the escalation and lethality of violence in individuals.

HETEROGENEITY OF HOMICIDE OFFENSES AND HOMICIDE OFFENDERS? The field of homicide studies is torn by opposites. On one hand, each homicide is unique in the circumstance in which the act is committed and the characteristics, motivations, and setting in which the homicide offender meets his or her victim. Sometimes, the difference between who will be the homicide offender rather than the homicide victim will be decided at the last moment and depends on strength, the weapon used, accuracy, and other circumstances. On other hand, criminologists are seeking principles and classifications behind multiple instances of murder (Heide, 2003). For example, homicides have typ-

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ically been classified on the basis of the victim characteristics, such as infanticide and parricide, or on the basis of frequency of homicides committed (single vs. serial homicide offenders). Other classification schemes concern the motives for homicide, such as gang-related homicide, homicide in retaliation to prior homicide, and family–intimate partners homicide. Other typologies have focused on the circumstances of the offense, including psychotic episodes, conflict, and crime circumstances leading to homicide (Heide, 2003). What these classifications have in common is the reliance on the basis of a single event (leaving aside multiple or serial murderers, who are usually very uncommon). We argue that a classification based on a single incident at one point in time is hazardous because it contains too little information to reveal the following key aspects: (1) the individual’s propensity for violence and (2) the etiology of violence and homicide. To concentrate on the first point, the key forensic question is whether juvenile homicide offenders from inner cities with high levels of community violence have higher levels of propensity for violence other than homicide. To answer this question, it is necessary to obtain information about the offender’s history of violence and aggression (such as bullying, physical fighting without causing wounds) as a child or adolescent. Several possibilities exist. First, one might suppose that most homicide offenders have been highly aggressive and violent for years, and that committing a homicide results from a process of gradual escalation in violence, in which early forms of aggression (such as bullying) set the stage for physical fighting, which in turn set the stage for violence. Another train of thought is that some homicide offenders are not known for a highly violent career, but even at an intermittent or moderate level of violence they still are at risk of killing someone. A third possibility is that even among those juveniles without a history of violence, there are some who may “lose it” on a rare occasion and murder somebody. Heide (2003) concluded in her review of homicide offenders that all three possibilities might apply and that “findings regarding whether young killers have had a lengthy history of fighting and other acts of violence have been mixed” (p. 13). This conclusion, however, is mostly based on case studies and chart reviews rather than prospective follow-up studies. Developmental approaches to the classification of violent offenders that take individuals’ past history of aggression and violence into account have addressed two aspects: developmental pathways leading to violence and serious property crime, and developmental trajectories of violence and property offenders throughout the life course.

Developmental Pathways A developmental pathway is defined as the behavioral development of a group of individuals that is different from the behavioral development of other group(s) of individuals (Loeber, DeLamatre, Keenan, & Zhang, 1998a). The first question is what dimensions should be used to plot individuals’ progres-

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sion to serious property crime and violence. The second question is whether the development toward violence occurs in an orderly way or randomly. And the third question pertains to the particular stages in the development of violence and serious property crime. We addressed these issues in our research on developmental pathways to violence and serious property offenses. We aimed at creating a model that would specify heterotypic continuity of disruptive behaviors (Loeber et al., 1993), particularly from minor to serious forms of delinquency. There has been considerable debate about whether all juvenile problem behaviors should be considered sufficiently similar to be covered by a single construct. Some have advocated a general deviance or problem construct (e.g., Jessor, Donovan, & Costa, 1991; Robins, 1966), whereas others have advocated a more differentiated approach (e.g., Loeber, 1988; McCord, 1990; Osgood, Johnston, O’Malley, & Bachman, 1988). The latter position is supported by accumulating empirical evidence for a distinction between overt (e.g., aggression and violence) and covert (e.g., theft and fraud) behavior problems (e.g., Frick et al., 1993; Loeber & Schmaling, 1985; Loeber et al., 1993). We found that antisocial behavior was best represented by a model of three pathways (Figure 10.1). The steps in each pathway are developmentally arranged by average age of onset. The pathways are as follows: (1) an authority conflict pathway prior to the age of 12, which started with stubborn behavior, had defiance/disobedience at a second stage, and authority avoidance (e.g., truancy) at a third stage, (2) a covert pathway emerging before age 15,

FIGURE 10.1. Developmental pathways to serious and violent offending.

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which started with minor covert acts, had property damage at a second stage, and moderate to serious delinquency at a third stage, and (3) an overt pathway, which started with minor aggression, had physical fighting at a second stage, and more severe violence at a third stage. Typically, individuals who escalated to the most serious delinquent acts progressed along the steps specified in the model. The results of these studies showed that with age, a proportion of boys progressed on two or three pathways, indicating an increasing variety of problem behavior over time (Kelley, Loeber, Keenan, & DeLamatre, 1997; Loeber et al., 1993; Loeber, Keenan, & Zhang, 1997). We found some evidence that development in more than one pathway was asymmetric; that is, boys who were escalating in the overt pathway were at risk of also escalating in the covert pathway, but not vice versa. Further, escalation in either the overt or covert pathway was often preceded by boys’ escalation in the authority conflict pathway (Loeber et al., 1993). In other words, conflict with authority figures was either a precursor or a concomitant of boys’ escalation in overt or covert acts. Moreover, an early age of onset of problem behavior or delinquency, as compared with onset at a later age, was associated with boys’ escalation to more serious behaviors (Tolan, GormanSmith, & Loeber, 2000). The pathway findings have been replicated in samples of Caucasian, African American, and Hispanic males in several cities (Loeber et al., 1998a; Loeber, Wei, Stouthamer-Loeber, Huizanga, & Thornberry, 1999; Loeber et al., 1993; Tolan et al., 2000). In summary, the pathway model allows several conceptualizations of development toward increasingly serious disruptive and delinquent behavior, such as escalation within a single or multiple pathway(s), heterotypic continuity, and age of onset of problem behaviors.

Developmental Trajectories Major work has been undertaken in the past decade to document individuals’ trajectories of crime and delinquency (Nagin & Land, 1993; Osgood & Rowe, 1994; Horney, Osgood, & Marshall, 1995). For example, aggression and violence have been studied from early childhood to adulthood (Brame, Nagin, & Tremblay, 2001; Broidy et al., 2003; Lacourse et al., 2002; Laub & Sampson, 2003; Nagin & Tremblay, 1999; Tremblay et al., 2004). Trajectories approach developmental aspects of violence from a different angle. There have been two major trends in the study of developmental trajectories. One trend, random effect growth modeling, is related to important advances in structural equation and multilevel modeling during the past decades (Bryk & Raudenbush, 1987; Meredith & Tisak, 1990; Rogosa & Willet, 1985). Random effect growth modeling has been a very popular analytical technique in developmental psychology and criminology since it provides analytical tools that favor more dynamic explanations of repeated measures data as compared with more traditional approaches such as analysis of variance or simplex regression. A shortcoming of these methods is that they are not well

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suited for testing theories that postulate qualitatively different developmental trajectories of antisocial behaviors resulting from possibly distinct causal processes (Moffitt, 1993; Patterson & Yoerger, 1993, 1997). In recent years statistical analyses have been developed to identify developmental trajectories of unobserved subgroups in the population, described as latent trajectory classes (Jones, Nagin, & Roeder, 2001; Muthen, 1989, 2001; Nagin, 1999; Nagin & Land, 1993). Typically, group-based trajectory analyses assume that a population of individuals “is composed of a mixture of groups with distinct developmental trajectories” (Nagin & Tremblay, 2001, p. 21). Trajectory analyses of aggressive and violent behaviors have usually been based on few repeatedly measured indicators of disruptive behavior and on the frequency of behavior (thus, different than the diversity of behaviors considered in the pathways model). They have also been less focused on qualitative changes over time. The analyses, primarily done with data on the period between childhood and adolescence, usually led to the identification of four more easily interpretable trajectories: individuals whose aggressive and violent behavior remains high over time, individuals who remain nonaggressive, and individuals whose violent behavior increases or decreases with development (e.g., Brame et al., 2001; Broidy et al., 2003; Fergusson & Horwood, 1995; Lacourse et al., 2002; Nagin & Tremblay, 1999). The key advantage of group-based trajectory analyses is that a statistical estimation procedure using mixture modeling identifies the shape of the trajectory for each group, and the prevalence in the population that constitutes each group (Nagin, 1999). However, few studies using trajectory analyses have shed light on heterotypic continuity of different problem behaviors as they unfold over time (see Brame et al., 2001; Nagin & Tremblay, 2001, for examples of heterotypic continuity models). Furthermore, homicidal behavior is not often measured in surveys using self-reported delinquency questionnaires (e.g., Elliott, Huizinga, & Ageton, 1985; Loeber et al., in press). For these reasons, there are no studies yet that have shown the location of homicide offenders on developmental trajectories of violence that vary in terms of severity.

DEVELOPMENTAL ASPECTS OF HOMICIDE The notion that delinquency and violence develop gradually in individuals has gained widespread acceptance (e.g., Blumstein, Cohen, Roth, & Visher, 1986; Loeber & Le Blanc, 1990; Loeber & Farrington, 1998). There is also a consensus that individual differences in offending are quite stable and that initial individual differences persist over time (e.g., Moffitt, 1993). Although we have described how manifestations of aggression change during adolescence, it is also important to understand how manifestations of aggression are related to each other during different age periods. It could be important to distinguish between different types of violence trajectories that have different beginnings and differently unfold over time. It appears clear from the research

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in psychology and criminology that there is a moderate-to-strong positive correlation between past and future aggressive or violent behaviors (Olweus, 1979). Although this correlation has been acknowledged by researchers, they differ as to its meaning. Drawing from the work of Heckman (1981), Nagin and Paternoster (1991, 2000) concluded that criminal behaviors that include violent offends could be related to two processes, population heterogeneity and state dependence.

Population Heterogeneity Theories Theories of population heterogeneity suggest that there is an initial proneness to commit violent offenses and that this early difference in the development of an individual remains quite stable over time (Gottfredson & Hirschi, 1990; Moffitt, 1993; Caspi, Lynam, Moffitt, & Silva, 1994). An individual with numerous risk factors before birth, in toddlerhood, or in childhood would be more likely to act with violence during adolescence and adulthood. This is not the place to review the variety of risk factors that appear associated with violence (see, for example, Loeber & Farrington, 1998; Raine, 2002; Thornberry, Freeman-Gallant, Lizotte, Krohn, & Smith, 2003). Yet, it is important to know that research on population heterogeneity for explanations of crime and violence is broad, focusing on topics such as early biological differences, neurological deficits, temperament, personality, parenting, and early child care. A commonality in population heterogeneity models of violence is that “any observed correlation between past and future criminal offending is due to enduring differences between individuals in an initial proneness of propensity to commit crime” (Nagin & Paternoster, 2000, p. 124).

State Dependence and Escalation Theories The state dependence position suggests that actions and events that occur in a person’s life affect the probability of subsequent actions or events. State dependence is a dynamic process that evolves in two ways: (1) aggressive behavior can open opportunities for more aggressive behavior while closing opportunities for other kinds of behaviors and (2) nonaggressive behaviors could open up possibilities for other nonaggressive behaviors and close opportunities for aggressive behaviors. The state dependence position suggests that life events that occur later in the development of an individual have a direct causal effect on violence while controlling for prior proneness to commit violent acts. There are many classical and modern theories in criminology and psychology that use state dependence as a primary explanation for crime and violence. Labeling and symbolic interaction theories (Lemert, 1951; Becker, 1963; Matsueda & Heimer, 1997), social learning theory (Akers, 1985; Bandura, Ross, & Ross, 1961; Coie & Dodge; 1988), general strain theory (Agnew, 1992) and social interactional theory (Thornberry, 1987) are all examples of theories that focus on state dependence. For example, labeling theo-

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rists argue that the likelihood of future criminal or violent behavior is closely related to the reaction of social control agencies to the first aggressive or violent behavior of the individual. If an individual is labeled as aggressive, he or she will define himself as aggressive and will act accordingly. Social learning and interactional theories focus their research on the reinforcement contingencies in the environment that will maintain or extinguish the aggressive or violent behavior. Family and peer interactions are of primary importance in these theories. Coercive family interactions and deviancy training by peers are thought to be important state-dependent factors that explain stability and change in violent behavior over time. Preventive intervention with high-risk children can also be thought of as a state dependence process that can modify a person’s developmental trajectory (see Lacourse et al., 2002, for an example).

Mixed Theories Although population heterogeneity and state dependence appear as incompatible processes, some theories have tried to explain violence using a mixture of these two processes. The blending of developmental psychology and criminology during the past 10 years and the strong interest in the age–crime curve have helped to set aside the more traditional focus on interindividual differences to put more focus on intra-individual development and the life course of offending. The confrontation between ontogenetic and sociogenetic theories or, in other words, between population heterogeneity and state dependence theories fostered the integration of theories that could be considered mixed. In criminology the blend of these two perspectives was pioneered by Le Blanc and Fréchette (1989), Loeber and Le Blanc (1990), and Sampson and Laub (1993), whereby the link between childhood and adolescent experiences and adulthood life circumstances were combined into one theoretical framework. For example, Sampson and Laub (1993), in their age-graded theory, showed that the self-selection thesis, or early individual difference model, was supported, but that important life events in late adolescence such as military enrollment, a good marriage, employment, parenthood, and an advantaged neighborhood (low crime, high employment opportunities) were also thought to reduce crime and violence. Recent studies using the semiparametric trajectory models have confirmed the tenability of mixed theories of crime and violence (Lacourse et al., 2002; Lacourse, Nagin, Tremblay, Vitaro, & Claes, 2003; Laub, Nagin, & Sampson, 1998; Laub & Sampson, 2003; Nagin, Pagani, Tremblay, & Vitaro, 2003). The mixed model appears to apply as well to homicide.

PREDICTORS OF HOMICIDE Using data from the Pittsburgh Youth Study (Loeber, Farrington, StouthamerLoeber, & Van Kammen, 1998b), we briefly present a mixed model predicting

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violence and homicide among young urban males. Virtually all the studies that have tried to understand causes or factors that could explain homicide offending in youth during the past 50 years have relied on case studies and studies using a retrospective design (Cornell, 1989; Ewing, 1990; Heide, 2003). Most of the case studies were done with male youth who were referred to psychiatric facilities for evaluation and treatment following their perpetration of homicide (Heide, 2003). Given the professional background of the clinician/researchers, it is clear that most descriptive explanations of homicidal behavior were related to population heterogeneity factors such as mental illness, neurological deficits, intelligence, and childhood trauma and abuse. In this section we briefly describe recent findings from the Pittsburgh Youth Study, a longitudinal empirical study in which three samples of schoolboys were followed up from childhood to early adulthood. The study sheds light on population heterogeneity and state dependence factors that could explain differences between violent offenders, homicide offenders, and nonviolent delinquent youth (Loeber et al., in press). By the middle of 2003, 129 participants had been convicted of violence, and another 306 self-reported violence. Thirty-three participants had been convicted in court of homicide (2.2%). Normally, it is impossible to predict low-base-rate events such as homicide, because almost all individuals do not commit homicide, and the best prediction would be that 97.8% would not commit homicide. A way to overcome the low-base-rate problem, however, is to use knowledge of state dependency to improve the prediction. We first looked at which delinquent behavior was shared by most of the homicide offenders. The results showed that almost all (93.9%) of the homicide offenders had been violent prior to the homicide (a probable indication of state dependence). Based on this finding, we decided that the best strategy would be to first predict who would become violent and then predict who would become a homicide offender among the violent offenders. The results of the prediction of violence showed support for the population heterogeneity hypothesis, in that predictors of violence were observed in the domains of the individual child, child attitudes, family, school, and demographics. The following factors predicted violence in univariate analyses: Factors evident early in life (such as the mother’s cigarette or alcohol use during pregnancy), onset of delinquency prior to age 10, and acting out problem behavior, including serious markers such as physical aggression, cruelty, and callous/unemotional behavior. In addition, cognitive factors (such as low school motivation) predicted violence. Poor and unstable child rearing factors also contributed to the prediction of violence, including two or more caretaker changes prior to age 10, physical punishment, poor supervision and communication, and several other family factors. Undesirable or delinquent peer behavior, according to either parent report or self-report, predicted violence. Poor school performance and truancy were also among the predictors of violence. Finally, demographic factors indicative of family disadvantage (low family SES, welfare, teenage motherhood) and residence

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in a disadvantaged neighborhood also predicted violence. Among the proximal factors associated with violence were weapon carrying, weapon use, gang membership, drug selling, and persistent drug use. Those who scored positively for three or more risk factors out of a total violence risk score of 12 were six times more likely to later commit violence as compared with those with fewer risk factors (odds ratio = 6.30). The next step was to predict those who would commit homicide among the violent offenders. Homicide offenders, as compared with violent offenders, were more likely to carry a weapon, to qualify for a diagnosis of conduct disorder, and to sell hard drugs. In addition, homicide offenders were more likely to have a positive attitude to substance use, to have delinquent peers, and to be held back in school. Homicide offenders were more likely to have a high risk score at the beginning of the study (i.e., at ages 7, 10, or 13), have at least one disruptive behavior diagnosis, and to be African American. The homicide risk index was based on the presence or absence of nine significant risk factors for homicide offenders (screening risk score, positive attitude to substance use, conduct disorder, carrying a weapon, gang fight, selling hard drugs, peer delinquency, being held back in school, and having a family on welfare). A homicide risk score based on these factors (excluding race) showed that those with 4 or more of the risk factors were 14 times (odds ratio = 14.33) more likely to be convicted for homicide than violent offenders with a lower risk index. The results underscore the applicability of the state dependency model to the prediction of both violence and homicide. However, the population heterogeneity model applied better to the prediction of violence than to the prediction of homicide among the violent offenders. In the latter instance, more individual factors, rather than family and neighborhood factors, contributed to the prediction of homicide as compared with violence. Less distinctive were peer factors, which predicted both homicide and violence.1

HOMICIDE OFFENDERS AND VIOLENCE TRAJECTORIES The observation that almost all of the homicide offenders had been violent earlier in life does not tell us whether most homicide offenders derive from those who were characterized by a consistently high level of violence over time. Recall that Heide’s (2003) review of homicide offenders spoke of mixed evidence that all homicide offenders were characterized by a lengthy history of fighting and other violent behavior. To test this important issue, we used a violence seriousness scale to first model the number and the shape of developmental trajectories. Rating on this scale had three levels: (0) no violence; (2) moderate violence: gang fighting or carrying a weapon; (3) serious violence: attack to seriously hurt or kill. Rating was based on information provided by the teacher, the parents, and the youth himself. Each individual’s score on this scale represents the most serious vio-

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lent offense committed during a given time interval (thus, giving less weight to presence of less serious offenses). The best model was chosen using the BIC statistic, which identifies the optimal number of groups in mixture models of developmental trajectories (D’Unger, Land, McCall, & Nagin, 1998). As shown in Figure 10.2, a four-group model was selected as the best-fitting model to explain the relationships between violence scores over the 12 assessment waves. A main finding is that violence seriousness trajectories strongly decline and become close to zero between the ages of 20 and 24. Another important finding is that the mixture model did not identify any adolescent- or adulthood-onset trajectories and there were more trajectories than the number generally theoretically speculated (Moffitt, 1993; Patterson & Yoerger, 1993, 1997). One group representing 4.7% of the sample appears to increase its level of violence from ages 14–20 and to slowly decline until age 24, slightly below the initial level at age 14 (called the chronic group). A second group, 22.4%, starts off at the same level but shows a steep decline that reaches zero by age 24 (called the late desister group). A third group, 21.9%, starts off at a lower level and shows a slow decline that also reaches zero by age 24 (called the early desister group). A last group displays, on average, no violence during the whole time period (the low group). This specific group represents 51.0% of the overall sample. These results are in line with previous research that shows a strong decline in trajectories of violent crimes during the transition between late adolescence and adulthood (Laub & Sampson, 2003). How do these data look at the individual level? Figure 10.3 presents the trajectories of four randomly selected homicide offenders. The trajectories

FIGURE 10.2. Trajectories of violence between ages 14 and 24.

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show that these homicide offenders have experienced violence during adolescence. Most of these trajectories show some decline during adulthood, which follows the general trend found in other samples (Laub & Sampson, 2003). As expected, 81.8% of the homicide offenders and 61.7% of the violent index offenders (with a court conviction of rape, robbery, or aggravated assault) followed the two highest trajectories of violence seriousness (the chronic group and the late desister group; see Table 10.1). Most court-identified homicide offenders (63.6%) and violent index offenders (53.2%) followed a trajectory that shows declining levels of violence over time (the late desister group). We first thought that these results were due to the impact of incarceration, but preliminary results suggest that incarceration did not have a large impact on the level of violence of individuals in this representative sample. Similar results were found by Laub and Sampson (2003). What the study clearly demonstrates is that most homicide and index violent offenders are individuals on developmental trajectories that are already present in early adolescence. There is substantive agreement among studies that the majority of serious and violent offenders experience an early onset of offending of any type (Loeber & Farrington, 1998, 2001). Analyses of pathways to serious delinquency suggest that onset patterns of predelinquent problems often take place during the elementary school age period, if not earlier (Loeber et al., 1993; Loeber et al., 1998a; Moffitt, 1993). The study has several limitations. Only 11 convicted homicide offenders were available for the analyses. Moreover, the unavailability of data prior to age 13 and after age 25, means that the analyses of trajectories were limited by left- and right-censored data. It is possible that membership in certain tra-

FIGURE 10.3. Trajectories of violence for four homicide offenders.

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TABLE 10.1. Percentage of Court-Reported Homicide and Violence Index Offenders per Violent Offending Trajectories Violence seriousness trajectories 1 Low

Homicide offenders (%) (n = 11)

Violence index offenders (%) (n = 47)

0.0

23.4

2 Early desister

18.2

14.9

3 Late desister

63.6

53.2

4 Chronic

18.2

8.5

jectories, based on the currently available data, would have been different if earlier or later assessments had been undertaken (Laub & Sampson, 2003; Eggelston, Laub, & Sampson, 2004). The study did not attempt to determine which risk factors were associated with which trajectory group. Neither did the study attempt to explain different ages of desistance for those trajectories that decreased with age. Trajectory analyses, although very valuable, are postdictive rather than predictive in that individuals’ assignment to a trajectory group is dependent on knowledge of their offending over a full period of time. Instead, we need to move to predictive assignment of individuals to trajectories in a probabilistic manner before they reach the most serious offense levels. This is particularly relevant for the prevention of homicide and violence in a proactive manner.

PREVENTION We think that the findings are relevant for prevention. First, there is evidence for state dependency and escalation, as evident from developmental pathways from less serious forms of aggression to violence and, eventually, homicide. Second, almost all homicide offenders had been violent earlier in life, which further supports the state dependency hypothesis. At the same time, however, we think that there is strong support for the notion of escalation within the state dependency paradigm, in that it takes years for aggression processes to culminate in homicide for a minority of the population. Models of escalation can be best conceptualized as funnels (Figure 10.1) in that most individuals with the lower-level forms of aggression do not escalate to homicide or even violence. However, those who took the next one or two steps in the developmental sequence (such as physical fighting and violence) were at much greater risk of committing homicide later. We also propose that as individuals escalate from minor aggression to violence and homicide, population heterogeneity and diversity of risk factors/ domains diminishes. Specifically, population heterogeneity is highest at the lowest level of developmental pathways (i.e., at the base of the pyramid

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shown in Figure 10.1), but decreases as certain individuals progress and escalate to the more serious behaviors. Thus, population heterogeneity is inversely related to escalation, or, stated otherwise, population homogeneity increases as some individuals desist from lesser forms of antisocial and delinquent behavior, whereas others rise to become serious offenders. In conjunction with these processes, we also postulate a narrowing of the domains of risk factors that play a role in antisocial and delinquent behavior as individuals escalate to violence and homicide. We saw that individual, family, peer, school, and neighborhood factors all contribute to the prediction of violence. In contrast, however, individual factors especially account for the prediction of homicide (leaving aside peer factors, which probably are, to some extent, confounded with individual factors). What are the implications for prevention? First, the process of escalation usually takes years to be completed, which therefore provides ample opportunity for preventing individuals to commit more serious antisocial and delinquent acts (Loeber & Farrington, 2001). Second, intervention research (Loeber & Farrington, 1998) shows that the best interventions address at least two risk domains (and are less effective if aimed at a single risk domain). This reinforces the notion that interventions should take place early in the delinquency careers rather than later, when it is probable that other individual risk factors prevail. However, because the transition of individuals’ aggression to violence often involves increasingly more lethal weapons and increasingly more dangerous activities (such as gang membership and drug dealing), other important avenues for the prevention of violence (and homicide) should consist of the restriction of weapons, especially guns, for those who are known to be highly aggressive, and the encouragement of alternatives to gang membership and drug dealing.

ACKNOWLEDGMENTS This chapter was prepared with financial assistance of Grant Nos. 86-JN-CX0009 and 96-JN-CX-0003 from the Office of Juvenile Justice and Delinquency Prevention (OJJDP), and of Grant Nos. MH48890 and MH50778 from the National Institute of Mental Health (NIMH). Points of view or opinions in this chapter are those of the authors and do not necessarily represent the official position of OJJDP, the Department of Justice, or NIMH.

NOTE 1. However, we are not certain that this is valid, because peer factors may have reflected cooffending rather than independent effects. This seems probable because information about peer delinquency and peer substance use was based on the reports of the participants in the study.

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Nagin, D. S., Pagani, L., Tremblay, R. E., & Vitaro, F. (2003). Life course turning points: The effect of grade retention on physical aggression. Development and Psychopathology, 15, 343–361. Nagin, D., & Paternoster, R. (1991). On the relationship of past and future participation in delinquency. Criminology, 29, 163–190. Nagin, D., & Paternoster, R. (2000). Population heterogeneity and state dependence: State of the evidence and directions for future research. Journal of Quantitative Criminology, 16, 117–144. Nagin, D. S., & Tremblay, R. E. (1999). Trajectories of boys’ physical aggression, opposition, and hyperactivity on the path to physically violent and non-violent delinquency. Child Development, 70, 1181–1196. Nagin, D. S., & Tremblay, R. E. (2001). Analyzing developmental trajectories of distinct but related behaviors: A group-based method. Psychological Methods, 6, 18–34. Olweus, D. (1979). Stability of aggressive reaction patterns in males: A review. Psychological Bulletin, 86, 852–875. Osgood, D. W., Johnston, L. D., O’Malley, P. M., & Bachman, J. G. (1988). The generality of deviance in late adolescence and early adulthood. American Sociological Review, 53, 81–93. Osgood, D. W., & Rowe, D. C. (1994). Bridging criminal careers, theory, and policy through latent variable models of individual offending. Criminology, 32, 517– 554. Patterson, G. R., & Yoerger, K. (1993). Developmental models for delinquent behavior. In S. Hodgins (Ed.), Mental disorder and crime (pp. 140–172). Newbury Park, CA: Sage. Patterson, G. R., & Yoerger, K. (1997) A developmental model for late-onset delinquency. In D. W. Osgood (Ed.), Motivation and delinquency (Vol. 44, pp. 119–177). Lincoln: Nebraska Symposium on Motivation. Raine, A., (2002). Biosocial studies of antisocial and violent behavior in children and adults: A review. Journal of Abnormal Child Psychology, 30, 311–326. Robins, L. (1966). Deviant children grown up. Baltimore: Williams & Wilkins. Rogosa, D. R., & Willett, J. B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrika, 50, 203–228. Sampson, R. J., & Laub, J. H. (1993). Crime in the making: Pathways and turning points through life. Cambridge, MA: Harvard University Press. Snyder, H. N., & Sickmund, M. (1999). Juvenile offenders and victims: 1999 national report. Washington, DC: U.S. Department of Justice, Office of Juvenile Justice and Delinquency Prevention. Thornberry, T. P. (1987). Toward an interactional theory of delinquency. Criminology, 25, 863–891. Thornberry, T. P., Freeman-Gallant, A., Lizotte, A. J., Krohn, M. D., & Smith, C. A. (2003). Linked lives: The intergenerational transmission of antisocial behavior. Journal of Abnormal Child Psychology, 31, 171–184. Tolan, P. H., Gorman-Smith, D., & Loeber, R. (2000) Developmental timing of onsets of disruptive behaviors and later delinquency of inner-city youth. Journal of Child and Family Studies, 9, 203–220. Tremblay, R. E., Nagin, D. S., Séguin, J. R., Zoccolillo, M., Zelazo, P., Boivin, M., Pérusse, D., & Japel, C. (2004). Physical aggression during early childhood: Trajectories and predictors. Pediatrics, 114, 43–50.

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Part III DETERMINANTS OF AGGRESSION

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DETERMINANTS Genetics and the Development OF AGGRESSION of Aggression

11 Genetics and the Development of Aggression D ANIEL P ÉRUSSE and P AUL L. G ENDREAU

The overall goal of this chapter is to assess the evidence for genetic influences on the developmental origins of aggression. Unlike simple qualitative Mendelian traits, which are generally mediated by a single gene and are relatively insensitive to environmental influences, quantitative traits, such as aggressiveness, vary continuously across a population and derive from a large number of additive and/or interactive genetic and environmental influences. As this is a vast and complex issue, we focus on the major findings and their limitations. We first describe the most significant approaches to investigate the genetic basis of aggression in animals. Then we review evidence from quantitative genetics concerning the genetic–environmental etiology of aggression in humans. Finally, we examine the relatively recent and still scarce evidence from molecular genetic studies of aggressive behavior. Both animal and human models of aggression have contributed considerably to progress in understanding the complex interaction of genetic and environmental factors in the emergence of aggressiveness. Different approaches can be used to investigate the genetic basis of complex traits. Some are termed genotype driven, as the initial step is to alter the genome in animal models by knocking out or “knocking in” specific genes. Once the desired developmental stage has been reached, the phenotypic outcome is observed. With this “reverse genetics” (Picciotto & Wickman, 1998), an infinite number of genetically altered animal strains (primarily mouse strains) characterized by distinct neurobehavioral phenotypes can be produced. This approach is particularly useful to dissect the function of specific genes and proteins on brain and behavior, as well as the compensatory mechanisms by which neurobehavioral adjustment occurs (for reviews, see Phillips et al., 2002; Picciotto & Wick223

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man, 1998). Despite their considerable scientific interest, however, gene knockouts have little value in explaining naturally occurring variations in behavioral phenotypes such as aggression. In addition, gene-targeted approaches may induce gross morphological and neurophysiological anomalies that may mask more subtle behavioral effects (Lathe, 1996; Nelson & Young, 1998). Some approaches are more applicable to normal—and human—development, as the first step is to characterize the neurobehavioral phenotype; then an attempt is made to trace back the genes associated with the expression of this phenotype. These approaches are termed phenotype driven. In animals, crossing/ backcrossing of two strains—each with its own genetic makeup but with little or no intrastrain genetic variability (inbred)—and selective breeding of individuals with high genetic variability (outbred) have been the traditional phenotype-driven methods. These methods, however, tell us only that a phenotype of interest is heritable and that genes contribute in a dominant or recessive fashion. To circumvent these limitations and to identify genes or DNA regions potentially associated with a phenotype, quantitative trait locus (QTL) mapping can be employed. This method is extremely valuable to examine complex gene–environment interactions and the development of specific neurobehavioral phenotypes in both animals and humans. However, despite the fact that a particular locus (chromosomal region that encloses a definite gene) can be associated to a phenotype, QTLs typically yield only small genetic effects and do not provide a fine resolution for detecting relevant gene units (Darvasi, 1998). Therefore, once a region of interest has been determined, the task to identify the putative influential DNA sequences among the larger region still remains.

GENETIC–DEVELOPMENTAL MODELS OF AGGRESSION IN ANIMALS Mus musculus (mouse) has been the species of choice for genetic studies of aggressive behavior. Mouse models provide many advantages over human studies for examining the relative influences of genes and environment on the development of complex behavioral traits, such as aggressiveness. One such advantage is that the genotypes of several strains have been well characterized, therefore facilitating the analysis of gene–environment interactions. In addition, the mouse genome has about 30,000 protein-coding genes, a number broadly similar to that in the human genome. Approximately 80% of the two genomes are organized similarly (orthologue), and only 1% of the human genome does not have a homologue mouse gene (Mouse Genome Sequencing Consortium, 2002).

Inbred Mouse Strains The use of inbred mouse strains has been a popular methodological choice to examine the genetic basis of biobehavioral phenotypes. This approach stems

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from a long history in mammalian genetics, dating from the beginning of the century. Scott (1942) and Ginsburg and Allee (1942) were among the first to examine differences in aggressiveness among inbred mouse strains. Inbred mouse strains are produced using brother–sister mating over several generations (20 generations are sufficient to produce very low levels of heterozygosity at all loci; see Taylor et al., 1999). Inbred strains such as Balb/c and ABG have been shown to be extremely aggressive under a variety of testing conditions, whereas other strains such as A/J, CBA/ca, and AB//Halle rarely exhibit aggressive behavior, even under experimental conditions, known to induce high levels of aggression (e.g., prolonged social isolation, resident–intruder paradigm; see Gendreau, Petitto, Petrova, Gariépy, & Lewis, 2000; Kessler, Elliott, Orenberg, & Barchas, 1977; Southwick & Clark, 1968). Two strains that differ both genetically and behaviorally (but with low within strain variability) provide an excellent starting point for the genetic analysis of complex traits, particularly those that have low heritability (Taylor, 1989). The crossing of two inbred strains results in genetically identical pups, the so-called F1 animals, which receive one allele at every locus from each parent. These animals are not of much interest in respect to genetic analysis, but their offspring, the F2 generation individuals, are, because each animal of this second generation has a unique combination of alleles. With this genetic diversity, it becomes possible to correlate genetic markers with the differential expression of aggressiveness. Typically, the genetic analysis is limited to the animals that are at the two extremes of the continuum—that is, animals that show no aggression and those that display the highest levels. The effects of reciprocal backcrosses of the F2 offspring with one or both of the parental strains can also be informative. Kessler et al. (1977) performed crossing and backcrossing of the aggressive Balb/c strain with the nonaggressive A/J strain. Their results suggested the presence of a single autosomal recessive trait for the transmission of high aggressiveness. Others have argued that aggressiveness may be transmitted through the Y chromosome (Maxson, 1996). But as Carlier, Roubertoux, Kottler, and Degrelle (1990) claimed, “the Y correlates probably are nothing more than possible genetic variants being expressed at different levels of physiological functions and acting on aggression” (p. 151).

Selective Breeding of Aggressive Behavior Selective breeding, also known as artificial selection or psychogenetic selection (Broadhurst, 1958), is clearly the most ancient method used to produce varieties or subspecies of animals that exhibit a particular phenotypic characteristic. Selective breeding is a relatively simple method that allows the gradual segregation of genes contributing to the phenotype of interest. Numerous behavioral characteristics, from locomotor activity to emotionality and aggression, have been investigated through selective breeding (Fuller & Thompson, 1978). Since the 1960s there have been three major selective breeding programs

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of aggressive behavior in male mice. All three programs were based on the animal’s propensity to exhibit either high or low levels of aggression against a male opponent. The earliest program was initiated by Kirsti Lagerspetz in Finland (Lagerspetz, 1961, 1964; Lagerspetz, Tirri, & Lagerspetz, 1968; see also Nyberg, Vekovischeva, & Sandnabba, 2003). Two lines of mice, the Turku Aggressive (TA) and the Turku Nonaggressive (TNA) were produced in just a few generations. Aggression was measured following a period of social isolation. Then Van Oortmerssen set in motion another breeding program in the Netherlands, producing two lines of mice that differed in their latency to attack another male conspecific, but without using social isolation prior to testing (Van Oortmerssen & Bakker, 1981; see also Sluyter, Korte, Bohus, & Van Oortmerssen, 1996). At about the same time in North America, Cairns initiated his own program of selective breeding for isolation-induced aggression in Institute for Cancer Research (ICR) mice (Cairns, MacCombie, & Hood 1983). For inducing intermale aggression, mice were singly caged from 21 days of age to approximately 45–50 days, as this specific period of ontogeny and this particular length of isolation (sensitive period) were shown to produce the highest levels of aggression (Cairns, Hood, & Midlam, 1985). Hence, by altering the social environment during a restricted window of time, two lines of mice that differed markedly in behavioral reactivity were produced: one line of animals that promptly attacked and a second line that exhibited high levels of “freezing” (for a review see Cairns, Gariépy, & Hood, 1990). Selection effects appeared promptly, with statistically significant line differences in isolation-induced aggression obtained as early as the fourth (S4) generation of selection. In this breeding program, no brother–sister mating was allowed. Perhaps as a result, aggressive behavior continued to appear, albeit extremely rarely, in the low-aggressive line even after the 30th generation (Gariépy, Rodriguiz, & Jones, 2002; Gariépy, Gendreau, Mailman, Tancer, & Lewis, 1995). In addition, although the breeding program had targeted intermale aggression, females of the highly aggressive line were also found to be more aggressive than females of the low-aggressive line when assessed under postpartum conditions (Hood & Cairns, 1988). One breeding program specifically targeted interfemale aggression (Ebert & Hyde, 1976). As in the other breeding programs, the effects of selection appeared quickly (S2). These effects were not paralleled by aggression in males, however (Hyde & Ebert, 1976). Sandnabba, Lagerspetz, and Jensen (1994) showed that females of the Turku Aggressive line also exhibited more aggression after repeated exposure to testosterone than those of the Turku Nonaggressive line. During female–female dyadic interactions, however, no such difference was observed (Van Oortmerssen & Baker, 1981). In their selective breeding program based on attack latency in males, Van Oortmerssen and Baker (1981) estimated a heritability of 30% for intermale aggression. In the selective breeding program performed by Lagerspetz and colleagues, heritability was estimated at 36% (McClearn &

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DeFries, 1973, in Van Oortmerssen and Baker, 1981). Ebert and Hyde (1976) estimated the heritability of female aggression to be between 43 and 55%. A significant contribution of these selective breeding programs was to point out the importance of developmental timing for the expression of aggressive behavior and the specificity of the context for eliciting specific forms of aggression. In Cairns’s program, for instance, line differences in aggression were dependent on the developmental stage in which comparisons were made; line differences in aggression were not observed earlier in ontogeny and were not as pronounced later in development (Cairns et al., 1985, 1990), which suggests that the influence of genes on aggression varies throughout the lifespan. What do animal models tell us about the genetic basis of human aggression? QTL mapping in conjunction with selective breeding would provide an interesting approach to examining the genetic basis of aggression. For instance, once an association with a genetic locus and a specific form of aggression has been reported, selective breeding on this phenotype can be conducted. If QTL analysis shows that the frequency of this fragment of DNA changes as selection is progressing, support can be acquired for the establishment of a genotype–phenotype link (Phillips et al., 2002). However, QTL analyses of aggressive behavior in mammals or even in insects—for instance, defensive stinging behavior in honeybees (Hunt, Guzman-Novoa, Fondrk, & Page, 1998)—do not contribute much to understanding the neurobiological and behavioral processes by which aggression develops in humans. In addition, despite obvious genetic and neurobiological similarities, the phylogenetic gap between rodents and humans is important, therefore making phenotypic and etiologic comparisons rather precarious. Nevertheless, developmental models of mouse aggression such as those using selective breeding provided a significant contribution by pointing out the importance of developmental timing for genetic influences on aggressive behavior. These selective breeding programs have also stressed the key input of environmental–experimental factors in the expression of aggression. For instance, rearing animals in groups rather than isolating them prevented the expression of aggressive behavior (Gariépy et al., 1995; Gendreau, Gariépy, Petitto, & Lewis, 1997). Comparable gene–environment interaction for the expression of aggression in monkeys was found recently by Suomi and colleagues (Suomi, Chapter 4, this volume). These authors showed that the genetic predisposition to exhibit aggressiveness, which was linked to a polymorphism of the gene coding for the serotonin transporter, was conditional to being maternally deprived. Genetically predisposed animals that were reared with their mothers early in life did not show aggressiveness, as compared with those that were reared only with same-age conspecifics. These findings constitute the beginning of a promising era of research for determining the complex developmental interaction of specific environmental–experiential factors with specific genes and gene products.

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GENETIC STUDIES OF HUMAN AGGRESSION The genetic–developmental theory behind a complex trait like aggression is based on the multifactorial polygenic threshold model of heredity. This model holds that individual differences in a continuous phenotype such as aggression result from the action of a large number of genes, each exerting a small effect, acting in conjunction with nongenetic (environmental) factors. Above a certain threshold of genetic liability and environmental risk, an extreme, often pathological manifestation of the trait (e.g., violent crime) develops. In humans, the study of the genetic and environmental causes of phenotypic variation depends on genetically informative designs, that is, twin and adoption studies. The magnitude of genetic influence is inferred from comparing the phenotypic resemblance between groups of individuals that vary in their degree of genetic relatedness (e.g., monozygotic [MZ] twins sharing all their genes vs. dizygotic [DZ] twins sharing on average half of their genes), everything else being assumed equal. Similarly, the magnitude of environmental influence is estimated by comparing groups of individuals differing, or not, in their exposure to common environmental factors (e.g., biological siblings vs. adoptive siblings). One should not be concerned merely with quantifying the genetic–environmental contribution to aggression, however, but also with identifying specific genes and specific environmental factors that make up these contributions. On the genetic side, this has recently been explored using molecular genetic techniques. On the environmental side, twin and adoption studies offer the opportunity of “controlling” for genetic factors in order to identify unambiguously environmental influences on aggression.

Quantitative Genetics of Human Aggression More than 100 twin and adoption studies have been conducted in the past three decades to examine the genetic basis of aggressive behavior and related constructs (e.g., externalizing behavior problems, conduct disorder, antisocial personality disorder (ASPD), delinquency, criminality). Not surprisingly, several reviews have concluded that both genetic and environmental factors were important in the etiology of these heterogeneous operationalizations of aggression assessed throughout the lifespan (e.g., Gottesman & Goldsmith, 1994; Carey, 1994). Four meta-analyses have gone further by providing quantitative estimates of the genetic and environmental contributions to individual differences in aggression-related constructs across studies. Walters (1992) reviewed 11 family, 14 twin, and 13 adoption studies of criminality and concluded that genetic influences on criminality were low to moderate. Mason and Frick (1994) reviewed 12 twin and 3 adoption studies of antisocial behavior and concluded that approximately half of the variance in various measures of antisocial behavior could be attributed to genetic influences. Miles and Carey (1997) reviewed 20 twin and 4 adoption studies of behavioral aggression and also con-

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cluded that genetic influences accounted for approximately 50% of the variance. A more recent and more exhaustive meta-analysis of various constructs of antisocial behavior was conducted by Rhee and Waldman (2002). A total of 51 twin and adoption studies comprising 87,152 individuals were reviewed, bearing on antisocial behavior operationalized in four ways: (1) psychiatric diagnoses such as conduct disorder and ASPD, (2) delinquency and criminality, (3) antisocial behavior combining delinquency and aggression, and (4) behavioral aggression per se. Across these four operationalizations, broad heritability, that is, the sum of additive (termed “A” in the genetic literature) and nonadditive (“D”) genetic effects reached 41%. Common environmental influence (“C,” i.e., environmental effects that are shared between twins and siblings) was 16%, and unique environmental influence (“E,” i.e., environmental effects that are not shared between twins and siblings) reached 43%. According to this latest meta-analysis, genetic variation thus appears to cause approximately 40% of individual differences across various constructs of aggressiveness, whereas about 60% of the variance is explained by environmental factors. Interestingly, Rhee and Waldman (2002) examined whether these results varied according to the different assessment methods used to measure the constructs of aggression (i.e., official records, behavioral reaction to stimuli, objective assessment, self-report, and report by others). In the case of official records, assessment method and operationalization were completely confounded, as the assessment by records was used only in studies of criminality, and the potential moderating effect of this method could therefore not be examined as such. In the case of criminality, however, a distinction needs to be made between violent crimes involving physical aggression toward others and nonviolent crimes such as theft. This suboperationalization was not performed by Rhee and Waldman (2002), but Mednick, Gabrielli, and Hutchings (1984), as well as Bohman, Cloninger, Sigvardsson, and von Knorring (1982), found evidence that genetic influences were significant for property crimes, but not for violent crimes. Most studies reviewed by Rhee and Waldman (2002) used self-report and/or report by others for assessing aggressiveness. Interestingly, significant differences in the magnitude of genetic and environmental effects were found between these two methods, with heritability reaching 39% and 53%, respectively. Behavioral reactivity to stimuli and objective assessment were used in only three studies. The moderating effects of these methods could therefore not be estimated. The single study using direct observation ratings of laboratory behavior reviewed by Rhee and Waldman (2002) was that of Plomin, Foch, and Rowe (1981), who examined aggression in young twins using an objective test validated against peer ratings and teacher ratings. No heritability was found for this measure. Only three published studies have actually measured children’s and adolescents’ aggressive behaviors in the laboratory (Owen & Sines, 1970; Plomin et al., 1981; O’Connor, Deater-Deckard,

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Fulker, Rutter, & Plomin, 1998). None of these studies found evidence for significant genetic influence on aggression. What to make of these conflicting results? Depending on how aggression is measured, genetic influences appear to range from 0% (objective assessment) to more than 50% (report by others). We grouped twin studies of overt aggression reviewed in Rhee and Waldman (2002), DiLalla (2002), Miles and Carey (1997) as well as two recently published studies (Dionne, Tremblay, Boivin, Laplante, & Pérusse, 2003; Arseneault et al., 2003) in three categories according to the degree of twin-wise dependency in information resulting from the assessment method used: (1) complete dependency (i.e., report by other: The same informant (parent or teacher) provides information for both members of a twin pair), (2) partial dependency (i.e., self-report: Each twin reports on him- or herself, but knows the other twin, and (3) no dependency (i.e., different raters for each twin, official records). As shown in Figure 11.1, the heritability is found to decrease linearly with information dependency, from 45% for complete dependency to 29% for partial dependency to 5% for no dependency. Rhee and Waldman (2002) also found that twin studies yielded higher heritability estimates than adoption studies across the four operationalizations of aggressiveness. This may be due to overestimates of heritability resulting from methodological shortcomings specific to the twin design, such as the informant-dependency bias suggested earlier and possible violations of the equal environment assumption of twin studies. To our knowledge, the requirement that MZ twins are not exposed to more similar environmental influences

FIGURE 11.1. Heritability estimates of aggression in relation to twin-wise dependency in the source of information for the assessment of aggression.

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than DZ twins has never been tested in the case of aggression, although it has been found to be supported in a number of studies of other phenotypes. Adoption studies also have a number of methodological problems that limit their interpretation. One problem is that it has been shown in several countries that children given away for adoption have a higher rate of antisocial behavior as compared with the general population (e.g., New Zealand (Fergusson, Lynskey, & Horwood, 1995), the Netherlands (Verhulst, Versluisden-Bieman, Van der Ende, Berden, & Sanders-Woudstra, 1990), the United States (Sharma, McGue, & Benson, 1998)). It is likely that the parents who give their children away for adoption also exhibit higher levels of antisocial behavior than parents in the general population, and certainly as compared with adoptive parents. The resulting correlation between adoptees and their biological parents in antisocial behavior can then hypothetically be generated by two different processes: (1) the transmission of antisocial genes from biological parents to their adopted-away children or (2) a purely environmental causal process, progressing from parental antisociality to giving away children for adoption to adoptive child antisociality due to abandonment. These two competing hypotheses appear confounded by the very design that is supposed to enable their disentangling. A more adequate adoptive design, corresponding to the animal cross-fostering method, would involve comparing adoptedaway children (AAC) with children who would have been given away by the AAC’s adoptive parents, and with children who would have been adopted by the AAC’s biological parents—a “natural experiment” that, perhaps fortunately, does not occur in reality. Stoolmiller (1999) has shown that genetic influences may be overestimated and shared environmental influences underestimated in adoption studies if the sample’s range of environments is restricted—for instance, in terms of socioeconomic status, which is generally the case in adoptive families. ClergetDarpoux, Goldin, and Gershon (1986) demonstrated how a genetic effect is simulated in adoption studies when a positive correlation exists between the adoptive and biological parents for an etiologic environmental variable, which is likely the case for selective placement (i.e., where environmental features of the biological and adoptive parents’ households tend to be matched by placement agencies). In addition, prenatal and early postnatal environments are evidently shared to a greater extent by adopted-away children and their biological siblings than by adopted-away children and their adoptive siblings. This would be an important control, as there is mounting evidence from animal and human studies that both prenatal and perinatal risk factors are associated with the development of later aggressive and antisocial behavior (e.g., Raine, 2002). Such unmeasured correlation in environmental risk between adoptees and their biological siblings, if any, will artificially inflate heritability estimates. Finally, both twin and adoption designs use analytical models that assume the independence, and therefore additivity, of genetic and environmental influences. If the two types of influences are not perfectly independent, the ap-

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plication of an additive model may result in systematic overestimation of heritability and underestimation of environmentality. In the case of aggression and antisocial behavior, evidence precisely points to the dependence between genetic and environmental influences (e.g., Cadoret, Cain, & Crowe, 1983; Ge et al., 1996; O’Connor et al., 1998; Caspi et al., 2004; Jaffee, Caspi, Moffitt, & Taylor, 2004). As discussed in the next section, genotype-by-environment interaction for aggressive and antisocial behavior has now recently been traced at the molecular level (Caspi et al., 2002).

Molecular Genetics of Aggression In recent years a number of molecular genetic studies have targeted different neurobehavioral correlates of aggression. Researchers have generally used a candidate gene approach, that is, attempting to locate genes that influence neurophysiological and hormonal systems (i.e., endophenotypes) thought to be involved in aggressiveness. Most studies have examined various polymorphisms of serotonin receptors, dopamine receptors, and the neurotransmittermetabolizing enzyme monoamine oxidase A (MAOA). The serotonergic abnormalities related to aggressiveness in humans have motivated linkage and association studies of serotonin-related genes and impulsive aggression. Knockout of the HTR1B (formerly 5-HT1B) serotonin receptor gene in mice results in increased aggression, as well as alcohol and cocaine consumption. Relationships between various measures of aggressiveness and HTR1B, which regulates the synthesis and release of serotonin from presynaptic neuron terminals, have thus been tested in a number of samples. In a study of Finnish alcoholic criminal offenders and a large multigenerational family of southwestern American Indians with a high rate of alcoholism, Lappalainen et al. (1998) investigated whether the HTR1B gene was linked with the psychiatric diagnoses of antisocial personality disorder and intermittent explosive disorder comorbid with alcoholism. Significant linkages were found for one of the two polymorphisms studied in the Finnish sample, and for both polymorphisms in the American Indian tribe. However, the functional significance of the polymorphism found to be linked in both populations has not yet been established. Given the comorbidity of aggression, suicide, alcoholism, and substance abuse, Huang, Grailhe, Arango, Hen, and Mann (1999) studied the relationship of these psychopathological problems to the human HTR1B receptor gene. Contrary to the findings of Lappalainen et al. (1998), no relationship was found between two polymorphisms of the HTR1B gene and suicide, major depression, alcoholism, or pathological aggression. Similarly, in a sample of 89 Caucasian patients with personality disorder, no association between the HTR1B genotype and self-reported measures of impulsive aggression was found (New, Goodman, Mitropoulou, & Siever, 2002). Transcription of the serotonin transporter gene (SLC6A4) is modulated by a common polymorphism in its promoter region, with demonstrated func-

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tional significance in coding for high and low transporter production. In a much-publicized study, association analyses in two independent samples revealed that the S allele was associated with increased anxiety-related personality scores, including impulsivity and harm avoidance (Lesch et al., 1996). A subsequent study using a different but related personality questionnaire failed to replicate this finding in a normal cohort (Ebstein et al. 1997). In another replication attempt, Gelernter, Kranzler, Coccaro, Siever, and New (1998) investigated the same SLC6A4 promoter polymorphism and an additional polymorphism in intron 2, among a sample of American subjects of European and African ancestry with diagnoses of a personality disorder or substance dependence and normal subjects. Again, they were unable to replicate the association finding. Tryptophan hydoxylase is the rate-limiting enzyme in the synthesis of serotonin from tryptophan and is coded for by the TPH gene (see Pihl & Benkelfat, Chapter 13, this volume). As low turnover rates of serotonin have been associated with impaired impulse control, polymorphisms of the TPH gene were investigated in a sample of Finnish impulsive and nonimpulsive, alcoholic, violent offenders and normal control subjects. The TPH genotype was associated with suicidality, which may involve impaired impulse control, but not with impulsive behavior itself (Nielsen et al., 1994). In a subsequent study, association and linkage analyses were conducted on a polymorphism in intron 7 of the TPH gene with suicidality, alcoholism, and a personality questionnaire among a larger sample of Finnish alcoholic offenders, controls, and their relatives (Nielsen et al., 1998). This polymorphism showed significant evidence of linkage with suicidality and severe suicide attempts. An association between various polymorphisms of the TPH gene and suicide by violent means has been replicated in some studies (e.g., Mann et al., 1997; Abbar et al., 2001), but not in others (e.g., Kunugi et al., 1999; New et al., 1998). These latter authors reported that the LL genotype of the TPH gene was associated with higher scores of impulsive aggression personality traits as compared with the UL or UU genotypes in Caucasian males, whereas Manuck et al. (1999) found exactly the opposite, with aggression and anger-related traits associated with the UL or UU genotype as compared with the LL genotype. It should be noted that, being intronic, these polymorphisms do not code for any gene products. Schmidt, Fox, Rubin, Hu, and Hamer (2002) investigated three candidate polymorphisms (dopamine receptor gene DRD4, serotonin transporter 5-HTT, and serotonin receptor 5-HT2C) in relation to aggression and shyness in a study of 4-year-old children. A significant association was found between the DRD4 genotype and maternal report of problems with aggression. However, there were no significant associations of the DRD4 genotype with observed behavioral measures of aggression. In addition, no significant associations of either of the 5-HTT or 5-HT2C serotonin genotype were found with any of the maternal report and observed behavioral measures. Brunner, Nelen, Breakefield, Ropers, and van Oost (1993) showed that a

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mutation in the MAOA gene could cause a syndrome that includes violence and impulsivity in a large Dutch family. This mutation is extremely rare, however. Furthermore, an association between MAOA and aggressive behavior in the general population has not been established. Using data from a longitudinal study of 500 adult males, Caspi et al. (2002) found higher levels of antisocial behavior in men who had a low-activity MAOA genotype if they had also experienced childhood maltreatment. However, antisocial behavior was not as elevated among men who had the more common high-activity MAOA genotype even if they had experienced maltreatment as children. Although these findings suggest a genotype-by-environment interaction for aggression in humans, a main statistical effect was found for maltreatment but not for the MAOA genotype. Finally, many studies of testosterone activity show a relation between high plasma levels and a tendency toward aggression (see Van Goozen, Chapter 14, this volume). Jonsson et al. (2001) investigated the association between a trinucleotide (CAG) repeat polymorphism in the androgen receptor gene and various personality traits. There were tendencies in some scales indicating possible relationships between the androgen receptor allele length and personality traits related to dominance and aggression. After correction for multiple testing, however, no significant differences were found. To summarize, linkage and association studies of aggression have so far largely resulted in contradictory findings characterized by failed attempts at replication. Most research has focused on aggression assessed as a personality trait, as opposed to a behavior. Studies generally report simple tests of association, with or without correction for multiple testing. Explained phenotypic variance is rarely reported, and potential confounding variables, such as population stratification and environmental risk factors, are seldom taken into account. It is still premature to provide a definite conclusion concerning the molecular-genetic causes of individual differences in aggression. Studies may be generally underpowered to detect polygenes of very small effects, and many candidate genes remain to be investigated. Nevertheless, the inconclusive results observed so far are compatible with the equally disappointing findings obtained for most other complex behavioral phenotypes (Goldman & Mazzanti, 2002). These weak findings appear somehow difficult to reconcile with the otherwise strong heritability estimates found for those phenotypes.

CONCLUSION More than two decades ago, Plomin (1981) noted that parental ratings of any characteristic tend to yield high heritability estimates, suggesting that parents tend to rate identical twins more similarly than fraternal twins on all measures. Concerning the lack of heritability found for objective assessments of aggressive behavior, Miles and Carey concluded at the end of their 1997 review: “Given that almost all substantive conclusions about the genetics of

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personality have been drawn from self or parental reports, this last finding has obvious and important implications for both aggression research in particular and personality research in general.” In her review of the genetics of aggression in children, DiLalla (2002) concluded that “although a large number of studies support the heritability of childhood aggression, it is still inconclusive.” To interpret the mixed findings presented in this chapter, it is important to probe a number of theoretical issues on the genetic and developmental origins of aggression. First, what does the term genetic influence entail concerning the development of a phenotype like aggression? As such, the term does not refer simply to whether genes play a part in the production of aggression, because it is taken for granted that aggression (like all other behavioral phenotypes) is the outcome of a neurobiological machinery that is unquestionably underwritten by genes, as is amply documented by the studies reviewed here. Rather, what behavior geneticists mean when evoking a genetic influence on aggression is that variation in aggression between individuals is partially caused by genetic differences between these individuals. The distinction is important because although we posit a genetic substrate for aggression (along with nongenetic factors), this in no way implies that this substrate varies between individuals. Nor, if it does, that the genetic variation contributes to phenotypic variation in the development of aggressive behavior. It is clear, by analogy, that we posses two arms and two legs because of genetic factors. The phenotype “limb number” is unquestionably specified in our DNA. Differences between individuals in this phenotype, however, are overwhelmingly caused by nongenetic factors (e.g., teratogens, accidents, surgical amputations) and the heritability (i.e., the magnitude of “genetic influence”) of number of arms and legs thus approaches zero. Given this meaning of genetic influences on aggression (i.e., genetic variants causing individual differences in aggression), a fundamental question must be addressed. Theoretically, should we expect genetic variation between individuals for a trait like aggressive behavior? The general answer to this question is, no, we should not. This is because several well-known processes govern the evolution of gene frequencies and variation among living organisms. Genetic variation is fueled by mutations and can be temporarily maintained by certain phenomena such as heterozygote vigour, genetic drift, and evolutionarily stable strategies. However, the overarching process guiding genetic evolution is natural selection. And natural selection, inexorably, stamps out genetic variation. The phenotypic outcome of natural selection is adaptation, the ultimate measure of which being Darwinian fitness. There is a truism among plant and animal geneticists that “one cannot breed for fitness.” The reason is simple: With fitness being the result of natural selection, which weeds out genetic variation, breeding for fitness is impossible, for lack of genetic variation. In natural populations, it has indeed been shown that fitnessrelated traits such as size, longevity, and mating behavior have very low (near the mutational rate) or zero heritability. Thus, the data reviewed here on arti-

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ficial breeding for aggression-related traits in laboratory animals does not truly inform us on the existence of genetic variants that would account for naturally occurring variation in aggression in these species. Is aggressiveness a fitness-related trait? In elephant seals, for instance, intermale aggression and success in the monopolization of ovulating females is directly proportional to reproductive success. Studies covering the lifespan of elephant seals, however, show that individual males do not differ significantly in their lifetime reproductive success (LeBoeuf & Laws, 1994). This is because male aggression is directly proportional to size, which itself depends on age: With time, each male passes through the optimal period in terms of development and exhibits approximately the same level of aggression pertaining to its age and size—thereby achieving roughly the same lifetime reproductive success. In this case, genes affecting the development of aggression seem to have long been “fixed” by natural selection, suboptimal genetic variants having been selected out. It is uncertain whether aggression in humans was a crucial fitness-related trait during our evolutionary past, but there is no reason to believe that we are unique among mammals or, for that matter, among living organisms. The inconclusive results reviewed here concerning the quantitative and molecular quest for genetic variants associated with individual differences in the development of aggression appear, in this light, less than surprising. The recent studies of Suomi (2003) and Caspi and colleagues (2002) point to a new era of behavior genetics in which specific genes and specific environmental risk will be measured in longitudinal designs to assess their dynamic interplay during development. This search should be guided by quantitative genetic assessments of the magnitude of genetic–environmental influences as they unfold during development from birth to adulthood, taking care to document environmental risk directly and prospectively, to test design features such as the equal environment assumption, and to ensure unbiased assessment of aggression phenotypes themselves.

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Gariépy, J.-L., Gendreau, P. L., Mailman, R. B., Tancer, M. E., & Lewis, M. H. (1995). Rearing conditions alter social reactivity and D1 dopamine receptors in high- and low-aggressive mice. Pharmacology, Biochemistry and Behavior, 51, 767–773. Gariépy J.-L., Rodriguiz, R. M., & Jones, B. C. (2002). Handling, genetic and housing effects on the mouse stress system, dopamine function, and behavior. Pharmacology, Biochemistry, and Behavior, 73, 7–17. Ge, X., Conger, R. D., Cadoret, R. J., Neiderhiser, J. M., Yates, W., Troughton, E., & Stewart, M. A. (1996). The developmental interface between nature and nurture: A mutual influence model of child antisocial behavior and parent behaviors. Developmental Psychology, 32, 574–589. Gelernter, J., Kranzler, H., Coccaro, E. F., Siever, L. J., & New, A. F. (1998). Serotonin transporter protein gene polymorphism and personality measures in African American and European American subjects. American Journal of Psychiatry, 155, 1332– 1338. Gendreau, P. L., Gariépy, J. L., Petitto, J. M., & Lewis, M. H. (1997). D1 dopamine receptor mediation of social and nonsocial emotional reactivity in mice: Effects of housing and strain difference in motor activity. Behavioral Neuroscience, 111, 424–434. Gendreau, P. L., Petitto, J. M., Petrova, A., Gariépy, J.-L., & Lewis, M. H. (2000). D3 and D2 dopamine receptor agonists differentially modulate social-emotional reactivity in mice. Behavioural Brain Research, 114,107–117. Ginsburg, B., & Allee, W. C. (1942). Some effects of conditioning on social dominance and subordination in inbred strains of mice. Physiological Zoology, 15, 485–506. Goldman, D., & Mazzanti, C. (2002). From phenotypes to genes and back: A critical appraisal of progress so far. In J. Benjamin, R. P. Epstein, & R. H. Belmaker (Eds.), Molecular genetics and the human personality (pp. 273–291). Washington, DC: American Psychiatric Press. Gottesman, I. I., & Goldsmith, H. H. (1994). Developmental psychopathology of antisocial behavior: Inserting genes into its ontogenesis and epigenesist. In C. A. Nelson (Ed.), Threats to optimal development: Integrating biological, psychological, and social risk factors (pp. 69–104). Hillsdale, NJ: Erlbaum. Hood, K. E., & Cairns, R. B. (1988). A developmental-genetic analysis of aggressive behavior in mice. II. Cross-sex inheritance. Behavior Genetics, 18, 605–619. Huang, Y., Grailhe, R., Arango, V., Hen, R., & Mann, J. J. (1999). Relationship of psychopathology to the human serotonin 1B genotype and receptor binding kinetics in postmortem brain tissue. Neuropsychopharmacology, 21, 238–246. Hunt, G. J., Guzman-Novoa, E., Fondrk, M. K., & Page, R. E., Jr. (1998). Quantitative trait loci for honey bee stinging behavior and body size. Genetics, 148, 1203–1213. Hyde, J. S., & Ebert, P. D. (1976). Correlated response in selection for aggressiveness in female mice. I. Male aggressiveness. Behavior Genetics, 6, 421–427. Jaffee, S. R., Caspi, A., Moffitt, T. E., & Taylor, A. (2004). Physical maltreatment victim to antisocial child: Evidence of an environmentally mediated process. Journal of Abnormal Psychology, 113(1), 44–55. Jonsson, E. G., von Gretten, C., Gustavsson, J. P., Yuan, Q.-P., Lindblad-Toh, K., Forslund, K., Rylander, G., Mattila-Evenden, M., Asberg, M., & Schalling, M. (2001). Androgen receptor trinucleotide repeat polymorphism and personality traits. Psychiatric Genetics, 11, 19–23. Kessler, S., Elliott, G. R., Orenberg, E. K., & Barchas, J. D. (1977). A genetic analysis of aggressive behavior in two strains of mice. Behavior Genetics, 7, 313–321. Kunugi, H., Ishida, S., Kato, T., Sakai, T., Tatsumi, M., Hirose, T., & Nanko, S. (1999).

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No evidence for an association of polymorphisms of the tryptophan hydroxylase gene with affective disorders or attempted suicide among Japanese patients. American Journal of Psychiatry, 156, 774–776. Lagerspetz, K. M. J. (1961). Genetic and social causes of aggressive behavior in mice. Scandinavian Journal of Psychology, 2, 167–173. Lagerspetz, K. M. J. (1964). Studies on the aggressive behavior in mice. Annales Acadamiae Scientiarum Fennicae, Sarja-series B, 1–131. Lagerspetz, K. Y. H., Tirri, R., & Lagerspetz, K. M. J. (1968). Neurochemical and endocrinological studies of mice selectively bred for aggressiveness. Scandinavian Journal of Psychology, 9, 157–160. Lappalainen, J., Long, J. C., Eggert, M., Ozaki, N., Robin, R. W., Brown, G. L., et al. (1998). Linkage of antisocial alcoholism to the serotonin 5-HT1B receptor gene in 2 populations. Archives of General Psychiatry, 55, 989–994. Lathe, R. (1996). Mice, gene targeting and behaviour: More than just genetic background. Trends in Neurosciences, 19, 183–186. LeBoeuf, B. J., & Laws, R. M. (Eds.). (1994). Elephant seals: Population ecology, behavior and physiology. Berkeley: University of California Press. Lesch, K., Bengel, D., Heils, A., Sabol, S. Z., Greenberg, B. D., Petri, S., et al. (1996). Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science, 274, 1527–1531. Mann, J. J., Malone, K. M., Nielsen, D. A., Goldman, D., Erdos, J., & Gelernter, J. (1997). Possible association of a polymorphism of the tryptophan hydroxylase gene with suicidal behavior in depressed patients. American Journal of Psychiatry, 154, 1451–1453. Manuck, S. B., Flory, J. D., Ferrell, R. E., Dent, K. M., Peters, D. G., & Muldoon, M. F. (1999). Aggression and anger-related traits associated with a polymorphism of the tryptophan hydroxylase gene. Biological Psychiatry, 45, 603–614. Mason, D. A., & Frick, P. J. (1994). The heritability of antisocial behavior: A meta-analysis of twin and adoption studies. Journal of Psychopathology and Behavioral Assessment, 16, 301–323. Maxson, S. C. (1996). Searching for candidate genes with effects on an agonistic behavior, offense, in mice. Behavior Genetics, 26, 471–476. Mednick, S. A., Gabrielli, W. F., & Hutchings, B. (1984). Genetic influences in criminal convictions: Evidence from an adoption cohort. Science, 224, 891–894. Miles, D. R., & Carey, G. (1997). Genetic and environmental architecture of human aggression. Journal of Personality and Social Psychology, 72, 207–217. Mouse Genome Sequencing Consortium. (2002). Initial sequencing and comparative analysis of the mouse genome. Nature, 410, 520–562. Nelson, R. J, & Young, K. A. (1998). Behavior in mice with targeted disruption of single genes. Neuroscience and Biobehavioral Reviews, 22, 453–462. New, A. S., Gelernter, J., Yovell, Y., Trestman, R. L., Nielsen, D. A., Silverman, J., et al. (1998). Increases in irritable aggression associated with “LL” genotype at the tryptophan hydroxylase locus. American Journal of Medical Genetics, 81, 13–17. New, A. S., Goodman, M., Mitropoulou, V., & Siever, L. (2002). Genetic polymorphisms and aggression. In J. Benjamin, R. P. Epstein, & R. H. Belmaker (Eds.), Molecular genetics and the human personality (pp. 231–244). Washington, DC: American Psychiatric Press. Nielsen, D. A., Goldman, D., Virkkunen, M., Tokola, R., Rawlings, R., & Linnoila, M.

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(1994). Suicidality and 5–hydroxyindolacetic acid concentration associated with a tryptophan hydroxylase polymorphism. Archives of General Psychiatry, 51, 34–38. Nielsen, D. A., Virkkunen, M., Lappalainen, J., Eggert, M., Brown, G. L., Long, J. C., et al. (1998). A tryptophan hydroxylase gene marker for suicidality and alcoholism. Archives of General Psychiatry, 55, 593–602. Nyberg, J. M., Vekovischeva, O., & Sandnabba, N. K. (2003). Anxiety profiles of mice selectively bred for intermale aggression. Behavior Genetics, 33, 503–511. O’Connor, T. G., Deater-Deckard, K., Fulkner, D., Rutter, M., & Plomin, R. (1998). Genotype-environment correlations in late childhood and early adolescence: Antisocial behavioral problems and coercive parenting. Developmental Psychology, 34, 970–981. Owen, D., & Sines, J. O. (1970). Heritability of personality in children. Behavior Genetics, 1, 235–248. Phillips, T. J., Belknap, J. K., Hitzemann, R. J., Buck, K. J., Cunningham, C. L., & Crabbe, J. C. (2002). Harnessing the mouse to unravel the genetics of human disease. Genes, Brain and Behavior, 1, 14–26. Picciotto, M. R, & Wickman, K. (1998). Using knockout and transgenic mice to study neurophysiology and behavior. Physiological Review, 78, 1131–1163. Plomin, R. (1981). Heredity and temperament: A comparison of twin data for self-report questionnaires, parental ratings, and objectively assessed behavior. In L. Gedda, P. Parisi, & W. E. Nance (Eds.), Twin research: Vol. 3. Intelligence, personality, and development (pp. 269–278). New York: Alan R. Liss. Plomin, R., Foch, T. T., & Rowe, D. C. (1981). Bobo clown aggression in childhood: Environment, not genes. Journal of Research in Personality, 15, 331–342. Raine, A. (2002). Annotation: The role of prefrontal deficits, low autonomic arousal, and early health factors in the development of antisocial and aggressive behavior in children. Journal of Child Psychology and Psychiatry, 43, 417–434. Rhee, S. H., & Waldman, I. D. (2002). Genetic and environmental influences on antisocial behavior: A meta-analysis of twin and adoption studies. Psychological Bulletin, 128, 490–529. Sandnabba, N. K., Lagerspetz, K. M., & Jensen, E. (1994). Effects of testosterone exposure and fighting experience on the aggressive behavior of female and male mice selectively bred for intermale aggression. Hormones and Behavior, 28, 219–231. Schmidt, L. A., Fox, N. A., Rubin, K. H., Hu, S., & Hamer, D. H. (2002). Molecular genetics of shyness and aggression in preschoolers. Personality and Individual Differences, 33, 227–238. Scott, J. P. (1942). Genetic differences in the social behavior of inbred strains of mice. Journal of Heredity, 33, 11–15. Sharma, A. R., McGue, M. K., & Benson, P. L. (1998). The psychological adjustment of United States adopted adolescents and their nonadopted siblings. Child Development, 69, 791–802. Sluyter, F., Korte, S. M., Bohus, B., & Van Oortmerssen, G. A. (1996). Behavioral stress response of genetically selected aggressive and nonaggressive wild house mice in the shock-probe/defensive burying test. Pharmacology, Biochemistry, and Behavior, 54, 113–116. Southwick, C. H., & Clark, L. H. (1968). Interstrain differences in aggressive behavior and exploratory activity in inbred mice. Communications in Behavioral Biology, 1, 49–59. Stoolmiller, M. (1999). Implications of the restricted range of family environments for es-

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DETERMINANTS Mapping Brain Development OF AGGRESSION and Aggression

12 Mapping Brain Development and Aggression T OMÁŠ P AUS

BRAIN–BEHAVIOR RELATIONSHIPS This chapter provides an overview of the basic principles guiding research on brain–behavior relationships in general, and as applied to studies of aggression during human development in particular. The emphasis is on the use of structural and functional neuroimaging to measure age- and behavior-related variations in brain structure and function. It begins with a brief introduction to the methodology of techniques used to map the developing brain, including magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG). I then review the current knowledge of structural maturation, assessed by MRI, of the human brain during childhood and adolescence; given the importance of structural connectivity for interregional communication, the emphasis of this section is on the maturation of white matter. The next part describes some of the results of neuroimaging studies aimed at identifying neural circuits involved in various aspects of aggression. The chapter concludes by discussing the potential and limitations of the neuroimaging approach in this field. The chief motivation for brain mapping studies is identification—in time and space—of neural circuits associated with particular sensory, motor, and cognitive functions. Although the initial research has focused on the healthy brain of an adult individual, functional neuroimaging is also beginning to make inroads into the research of normal and abnormal brain development; unraveling the details of structural and functional maturation of various neural systems represents a first step toward the understanding of the biological 242

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underpinnings of cognitive development in health and disease. A wide range of brain-mapping techniques are available today, including positron emission tomography (PET), functional MRI (fMRI), EEG, MEG, and transcranial magnetic stimulation (TMS). These methods allow the researcher to measure (PET, fMRI, EEG, MEG) and to manipulate (TMS) neural activity in the human brain; they differ in spatial and temporal resolution, in the nature of the measured signal, as well as in the extent of brain coverage. Given their noninvasive nature, MRI, EEG, and MEG represent the most common techniques employed for developmental studies and are considered in this chapter. The reader interested in the other techniques is referred to other publications (e.g., Paus, 2003; Walsh & Cowey, 2000).

PRINCIPLES OF BRAIN MAPPING (MRI, FMRI, EEG, AND MEG) Several noninvasive techniques are available today to map the structure and function of the human brain during development; those most frequently used are MRI, EEG, and MEG. MRI is the only technique that allows the researcher to measure both the structure and function of the brain. MRI is based on the following principles. Nuclei that have an odd number of nucleons (protons and neutrons) possess both a magnetic moment and an angular momentum (or spin). In the presence of an external magnetic field such nuclei precess (or wobble) around their axis at a rate proportional to the strength of the magnetic field, emitting electromagnetic energy in the process. The hydrogen atom contains only a single proton and therefore precesses when exposed to a magnetic field. In the majority of MR imaging studies, precessing nuclei of hydrogen associated with water and fat are the source of the signal.

Structural MRI Contrast in structural MR images is based on local differences in (1) proton density (i.e., in the number of hydrogen nuclei per unit of tissue volume) or in (2) either of the following two relaxation times: (a) longitudinal relaxation time (T1); and (b) transverse relaxation time (T2). Local differences in relaxation times are reflected in the image contrast because, at a given measurement time, the MR signal has already recovered (T1) or decayed (T2) more in regions with short T1 (or T2), and vice versa. For this reason, tissue with short T1 (white matter) shows a high MR signal and appears bright on T1weighted images, whereas tissue with long T2 (grey matter) shows high signal and is bright in T2-weighted images (see Figure 12.1). Although proton density reflects the amount of signal-emitting nuclei present in the tissue (primarily water), relaxation times and therefore tissue “brightness” on T1- and T2-weighted images depend on a variety of biological and structural properties of the brain tissue, all of which vary as a function

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FIGURE 12.1. MR images acquired in a 15-year-old individual (sagittal sections).

of age. Content of water is one of the most important determinants influencing T1 in the brain; to simplify, the more water there is in a given tissue compartment, the longer the T1 and the lower the signal on a T1-weighted image will be in that compartment. In the adult brain, T1 is the longest in cerebrospinal fluid, intermediate in grey matter, and the shortest in white matter. The content of hydrophobic lipids in white matter may also influence T1 through magnetic interactions with the hydrogen nuclei of the lipids. The content of iron is another important factor, influencing primarily local magnetic inhomogeneities; the higher the content of iron, the shorter the T2. Finally, the anatomic arrangement of axons may influence the amount of interstitial water and, in turn, T1 values; more tightly bundled axons would have shorter T1 and therefore appear brighter on T1-weighted images. Several other MR techniques are used to image specific structural properties of the brain. Thus, the preferred direction of movement of water molecules along the axons is the basis of diffusion tensor imaging (DTI). The chemical composition of the brain is studied with magnetic resonance spectroscopy (MRS).

Computational Analysis of MR Images Structural images are but color-coded representations of MR, the signal measured throughout the brain and localized in individual three-dimensional (3D) elements of the brain image (i.e., voxels). It is therefore relatively straightforward to apply various computational approaches to quantify a variety of morphometric features using fully automatic procedures. In this way, we can measure volumes of grey and white matter in the whole brain and its main subdivisions (e.g., frontal lobe), the size/volume of well-demarcated brain regions (e.g., corpus callosum or caudate nucleus), variations in the shape of large (e.g., frontal pole) or small (e.g., cingulate sulcus) morphological entities

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or those in the cortical thickness. Voxel-wise comparisons of various age (or clinical) groups are used to assess the “density” of grey and white matter (see Figure 12.2).

Functional MRI The chief motivation for functional neuroimaging is identification—in time and space—of neural circuits associated with particular sensory, motor, and cognitive functions and their development, from infancy through adolescence. The high spatial resolution of functional MRI (fMRI) makes this technique ideal for determining where in the brain changes in neural activity occur. In the majority of fMRI studies, task-related changes in local hemodynamics are inferred from changes in the so-called blood-oxygenation–level dependent (BOLD) signal. As its name suggests, the BOLD signal is based on our ability to detect, with MRI, changes in blood concentration of deoxyhemoglobin. Deoxyhemoglobin is paramagnetic and, as such, acts as an endogenous contrast agent that creates microscopic magnetic-field inhomogeneities in the sampled tissue. These local inhomogeneities increase the rate of decay of transverse magnetization, that is, shorten T2 and T2* relaxation times. Upon neural activation, the disproportionate increase in local blood flow “dilutes” the amount of deoxyhemoglobin in the small veins leaving the “activated” tissue and, in turn, reduces the amount of local inhomogeneities; this leads to a positive signal on T2*-weighted images (“red” veins in Figure 12.3).

FIGURE 12.2. Age-related changes in white matter density in the internal capsule (left) and the left arcuate fasciculus (right). The thresholded maps of t-statistic values (t > 4.0) are superimposed on axial (capsule) and sagittal (arcuate) sections through the magnetic resonance image of a single subject. The images depict the exact brain locations that showed statistically significant correlations between white matter density and the subject’s age (n = 111; age: 4–17 years). From Paus et al. (1999). Copyright 1999 by the American Association for the Advancement of Science. Reprinted by permission.

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FIGURE 12.3. Principles of functional MRI (the blood oxygenation-level dependent signal). Courtesy of Dr. Bruce Pike, Montreal Neurological Institute.

EEG and MEG Compared with fMRI, more direct and real-time measurements of electrical and magnetic signals generated by brain tissue are recorded by EEG and MEG (Niedermeyer & Lopes da Silva, 1999). EEG and MEG are the methods of choice for determining when changes in neural activity occur. The main sources of these signals are intra- and extracellular currents, or field potentials, elicited by the activation of excitatory and inhibitory synapses. Spatial and temporal summation is necessary, however, to generate signals strong enough to be detected outside the head. Such a summation occurs most often during simultaneous excitatory inputs onto apical dendrites of pyramidal cells; the apical dendrites are for the most part oriented in parallel with each other and are perpendicular to the cortical surface. EEG detects field potentials regardless of their orientation relative to the skull. In contrast, MEG can measure only magnetic fields perpendicular to the skull. Such fields are generated by tangential current dipoles and, because of the orientation of pyramidal cells and their apical dendrites in the cortex, reflect primarily postsynaptic activity occurring in the cerebral sulci. Analysis of EEG and MEG data for brain mapping purposes focuses typically on two domains: (1) event-related potentials and (2) event-related synchronization or desynchronization of brain activity.

MRI STUDIES OF BRAIN DEVELOPMENT Brain weight reaches adult values (about 1.45 kg) between 10 and 12 years of age. The fastest growth occurs during the first three years of life, so that by the

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age of 5 years the infant’s brain weighs about 90% of the adult value (Dekaban, 1978). Clearly, the changes in brain morphology in childhood and adolescence are more subtle that those in the first four years of life (see Paus et al., 2001, for a review of MR studies carried out during infancy). Qualitative evaluation of MR images is of little value at this point, and the ability to obtain quantitative measurements is of the essence if we are to detect brain maturation during this “late” period of brain development. Several approaches have been used to obtain such measurements, including (1) semiautomatic or automatic classification of brain tissue and the subsequent “count” of image elements classified as a particular tissue type (e.g., white matter), (2) manual outlining of a structure of interest (e.g., the corpus callosum) on an MR image and the subsequent calculation of its volume/area, (3) voxel-wise analysis of local growth using deformation fields, and (4) voxel-wise statistical analysis of white matter “density.” Classification of brain tissue into grey and white matter and cerebrospinal fluid allowed several investigators to calculate the absolute and/or relative brain volume occupied by white matter. In the most extensive study to date, Giedd et al. (1999a) reported age-related changes in 145 children and adolescents (age 4–20 years) in volumes of grey and white matter of the frontal, parietal, temporal, and occipital lobes; the study used a cross-sectional (n = 145) and longitudinal (65/145 subjects) design. Volumes were quantified by combining a technique using an artificial neural network to classify tissues based on voxel intensity, with a technique performing nonlinear registration to a template brain for which the four lobes had been manually defined (Collins, Zijdenbos, Baare, & Evans, 1999). A significant increase in the absolute volume of white matter was found in this study, with the volume increasing steadily across ages 4–22 by about 12%; this increase was similar in the four different lobes but was steeper in boys than in girls. These recent findings are consistent with the previous observations of other authors, including the agerelated increase in the cerebral white matter : grey matter ratio (Jernigan & Tallal, 1990; 8–10 years [n = 9] vs. 25–39 years [n = 15]); the increase in absolute and relative volumes of “cortical” white matter (Pfefferbaum et al., 1994; 3 months–30 years [n = 88]); and increase in the relative volume of cerebral white matter (Reiss, Abrams, Singer, Ross, & Denckla, 1996; 5–17 years [n = 85]). In the Pfefferbaum et al. (1994) cross-sectional study, cortical white matter continued to increase from birth to about 20 years, after which it leveled off. In the majority of the aforementioned studies, age-related increases in white-matter volume are accompanied by decreases in grey-matter volume. This observation is best illustrated in a study by Steen, Ogg, Reddick, and Kingsley (1997; 4–10 years [n = 19], 10–20 years [n = 31], 20–30 years [n = 20]), who measured T1 relaxation times and used these to classify all voxels into those containing either “pure” grey or white matter; the number of white-matter and grey-matter voxels increased and decreased with age, respectively, with the inverse relationship between the number of “white” and

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“grey” voxels (r = .64; p < .0001) (Steen et al., 1997). This finding raises the possibility that a decrease in (cortical) grey-matter volumes may, at least in part, reflect intracortical myelination (and the resulting partial volume effects) rather than loss of grey-matter tissue due to “pruning.” Recent observations by Zilles and collaborators are consistent with this view; using high-resolution MR imaging and post-mortem histological analysis of the (adult) human cerebral cortex, they could explain up to 80% of variance in T1 relaxation times by differences in myeloarchitecture in deep cortical layers (Zilles et al., unpublished observations). These changes in the volume of white matter, calculated using various tissue-classification algorithms, reflect, to a great extent, subtle age-related changes in relaxation times. Steen et al. (1997; see earlier for sample size and age) measured T1 relaxation times in nine regions of interest (ROIs), including the four placed in the white matter: (1) the genu of the corpus callosum, (2) frontal white matter, (3) optic radiation, and (4) occipital white matter. The mean values of T1 decreased from childhood (4–10 years) to adulthood (20– 30 years) in all four white-matter structures. Significant decreases were also observed in comparing children with adolescents (10–20 years) in all whitematter structures except the genu of the corpus callosum, and in comparing adolescents with young adults in all regions except occipital white matter. Transverse relaxation times (T2) were measured by Hassink, Hiltbrunner, Muller, and Lutschg (1992; 8–10 years [n = 9] and 24–25 years [n = 8]) in eight ROIs, including the frontal subcortical white matter, the corpus callosum and the genu of the internal capsule. Although limited by a small sample, significant decreases in T2 values were found from childhood to adulthood in all white-matter regions but the corpus callosum. These two quantitative studies clearly illustrate significant age-related changes in white matter, most likely caused by small but consistent increases in the degree of myelination. The volumetric assessment of age-related changes in white matter is often a global rather than a regional one. This is due to the absence of readily detectable boundaries between different fiber tracts constituting the white matter of the four cerebral lobes. This is not the case for the corpus callosum, the largest fiber tract in the human brain interconnecting the cerebral cortex of the left and right hemispheres. The corpus callosum can be easily delineated on a midsagittal section and, therefore, its area can be measured with great precision. Even though the corpus callosum acquires an “adult” appearance by about the age of 1 year (Barkovich & Kjos, 1988), its growth continues until early adulthood. In one of the first MR-based morphometric studies, Pujol, Vendrell, Junque, Marti-Vilalta, and Capdevila (1993) measured the area of the corpus callosum in adolescents (11–19 years, n = 14), young adults (20–29 years, n = 45) and older adults (30–61 years, n = 31) using a longitudinal design; two scans were acquired in each subject with an average between-scan interval of 2 years. Not surprisingly, the largest growth in the 2-year period was observed in the youngest group (an increase of about 10%). But the area of the corpus callosum increased significantly even in the group of young

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adults (24–25 years, an increase of about 5% over 2 years); no change was observed from the age of 27 years on. In a cross-sectional study, Giedd et al. (1999a; 4–18 years, n = 114) confirmed the significant age-related increase in the total area of the corpus callosum. They were also able to demonstrate that most of this growth occurs in the posterior half of the corpus callosum and, in particular, in the splenium; no growth was observed in the genu. These findings were corroborated by the same authors, who followed up their original sample and rescanned a large number of the subjects (n = 75) at least once 2 years later (Giedd et al., 1999b). Again, the growth of the splenium far outperformed that of any other subdivision of the corpus callosum. This finding is somewhat surprising in light of the caudal-to-rostral time sequence of myelination of this structure after birth and the presumed late development of the prefrontal cortex, a region interconnected through the (rostral) genu of the corpus callosum. Further studies are necessary to establish whether changes in the splenium reflect possible ongoing maturation of the inferior temporal and occipital cortices, the main sources of the callosal fibers in the splenium (Pandya & Seltzer, 1986). The rostro–caudal wave of growth of the corpus callosum was recently demonstrated by a computational analysis of so-called deformation fields (Thompson et al., 2000; 3–15 years, n = 6). The 3-D deformation fields specify, at each voxel, the vector of forces applied to bring the local anatomy of the subject’s brain in alignment with that of the template brain. Thompson et al. (2000) rescanned each subject within 1–4 years and, by subtracting local deformation fields obtained in each subject at Time 1 and Time 2, were able to visualize changes in the local growth of the corpus callosum. Consistent with the previous findings, changes in the genu were observed in the youngest subject (scanned at 3 and 6 years of age), whereas changes in the splenium were most pronounced in rescanning during adolescence (Time 1: 9 years, Time 2: 13 years). In order to detect more subtle variations, however, group analysis of deformation fields and its statistical evaluation will be necessary. Chung et al. (2001) have developed a novel statistical analysis of local growth that will allow investigators to evaluate the statistical significance of age-related changes in deformation fields throughout the brain. Subtle regional variations in white matter can also be evaluated using a voxel-by-voxel analysis of the images. This approach borrows from the concepts developed in the context of functional neuroimaging: It is based on the use of standardized stereotaxic space and voxel-based statistics. In a study of age-related changes in white matter, we (Paus et al., 1999; 4–18 years, n = 111) have observed significant age-related changes in white-matter “density” in the posterior limb of the internal capsule and in the left arcuate fasciculus; the former is likely to contain fibers connecting the motor cortex and spinal cord, and the latter those connecting the anterior (Broca’s) and posterior (Wernicke’s) language areas. The analysis of images obtained in 111 children and adolescents included the following steps: (1) nonlinear transformation of images into standardized stereotaxic space to remove global and local differ-

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ences in the size and shape of the individual brains, (2) classification of brain tissue into white matter, grey matter, and cerebrospinal fluid, (3) blurring of white-matter binary masks to generate 3-D maps of white-matter “density,” and (4) correlation between voxel values of white-matter density and the subject’s age. Such voxel-based analyses of age-related variations in white- and grey-matter (Sowell et al., 1999) densities complement the volumetric approach in allowing for subtle local differences to emerge in regions that may not be delineated as a single volume. However, relatively large numbers of individuals and rather conservative statistical criteria need to be applied to separate signal from noise in a reliable fashion. Overall, there is ample evidence that white matter continues to mature during childhood and adolescence, increasing its volume and becoming more myelinated. Most of the changes are occurring throughout this period of development, with no pronounced differences in the rate of maturation during puberty. The absence of such developmental “spurs” could, however, reflect the lack of high-density longitudinal data for this period of life. Several largescale longitudinal MR studies of brain maturation are under way at the moment; these are likely to provide important insights regarding the structure– function relationship during infancy, childhood, and adolescence in healthy individuals.

BRAIN MAPPING STUDIES OF AGGRESSION Most of the literature on the neural underpinnings of aggressive behavior reflects a theoretical framework that views aggression in the context of antisocial behavior, such as violence and delinquency, rather than as one of the essential (adaptive) motivational states, such as hunger or maternal instinct (for recent criticism, see Tremblay, 2003). It is therefore not surprising that the vast majority of previous studies are based on two methodological approaches: (1) clinical studies of overt aggressive behavior in patients with brain lesions and (2) neuroimaging studies of brain abnormalities in individuals who had committed acts incompatible with societal norms, such as murderers. In the first part of this section, I review this literature and, given its emphasis on the frontal lobes, I also provide a brief synopsis of the structure and function of this part of the primate cerebral cortex. In the second part, I suggest an alternative approach for studying aggression and its elements in healthy subjects; this approach is based on a theoretical framework that views aggression as a social interaction between familiar individuals and, consequently, includes conflict resolution (reconciliation) as an integral part of aggressive behavior (De Waal, 2000). The search for a neural substrate of aggression has a long history that started with clinical observations of patients with brain lesions. In the 19th century, several reports described individuals who had had an injury to the frontal lobes and, subsequently, showed changes in their “personality.” The

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most famous example is Phineas Gage, who suffered a large penetrating injury to the ventromedial and orbitofrontal cortex, after which he became fitful, irreverent, profane, indifferent, inpatient, obstinate, and unable to plan (Harlow, 1868; Damasio, Grabowski, Frank, Galaburda, & Damasio, 1994). In the 20th century, several studies of war veterans confirmed a link between lesions to frontal lobes and an increased risk of aggressive behavior (e.g., Grafman et al., 1996, reviewed in Brower and Price, 2001; Kleist, 1934, cited in Brower & Price, 2001; Lishman, 1968; Virkkunen, Nuutila, & Huusko, 1976). In the majority of these studies, the injury occurred in young male adults, who were studied many years after their injuries. Several case studies also described a high incidence of aggressive behavior in adults who suffered lesions to the frontal cortex early (before the age of 8 years) in their lives (Anderson, Bechara, Damasio, Tranel, & Damasio, 1999; Eslinger, Grattan, Damasio, & Damasio, 1992; Price, Daffner, Stowe, & Mesulam, 1990). Together, these lesion studies suggest that an intact frontal cortex is important for adequate control of aggressive behavior in adulthood; the early-lesion cases suggest that remaining brain structures cannot compensate for the loss of brain tissue in childhood. Which parts of the frontal lobes are critical in this respect? A reconstruction of the skull injury suffered by Phineas Gage led Damasio and colleagues to conclude that “the lesion favored the ventromedial region of both frontal lobes while sparing the dorsolateral” (Damasio et al., 1994). The Vietnam Head Injury Study found a similar association between aggressive behavior and lesions in the orbital and medial aspects of the frontal lobes (Grafman et al., 1996). To understand the significance of this pattern, a brief review of the organization of the primate frontal cortex can be helpful here. The frontal cortex constitutes about 35% of all cerebral cortex in humans and great apes (Semendeferi, Lu, Schenker, & Damasio, 2002). It contains the primary motor cortex, premotor cortex (dorsal and ventral premotor cortex on the lateral convexity; supplementary motor area (SMA) and the cingulate motor areas (CMA) on the medial convexity), and the prefrontal cortex. The prefrontal cortex is further subdivided into the mid-dorsolateral and mid-ventrolateral frontal cortex, the frontopolar cortex, the orbitofrontal cortex, and the mesial frontal cortex; the latter also includes the anterior cingulate cortex surrounding the anterior part of the corpus callosum. Each of these gross morphological subdivisions consists of a number of areas that differ in the exact arrangement of cells in the six cortical layers (cytoarchitecture; see Figure 12.4) and in their connectivity with other cortical and subcortical regions. These anatomical differences determine to a great extend what type of information is being processed in a given region, and which other regions share this information. Such regional specialization is reflected, in turn, in the specific contributions made by a given “node” of a particular neural network in support of a specific behavior. Given the structural heterogeneity of the frontal cortex and the presence of extensive connectivity of frontocortical regions with other parts of the cere-

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FIGURE 12.4. Schematic diagrams of the lateral (left), medial (middle), and inferior (right) surfaces of the human frontal lobe to illustrate its cytoarchitectonic parcellation. From Petrides and Pandya (1994). Copyright 1994 by Elsevier. Reprinted by permission.

bral cortex, most prominently with the temporal and parietal cortex, it is not surprising that the frontal cortex supports a multitude of motor, sensory, and cognitive functions. For example, the premotor areas on the medial convexity may be essential for sequencing behavior (SMA) and willed initiation and suppression of movement (CMA; reviewed in Paus, 2001). The mid-dorsolateral and mid-ventrolateral frontal cortex play an important role in working memory and retrieval, respectively (Petrides, 1996). Maturation of the mid-dorsolateral frontal cortex underlies the emergence of working memory during infancy (e.g., A-not-B test) and a further increase in working memory and planning during childhood. Maturations of the lateral prefrontal and/or cingulate cortices may be critical for the dramatic increase in the child’s ability to suppress external interference observed just before the onset of puberty (e.g., suppression of reflexive eye movements; Munoz, Broughton, Goldring, & Armstrong, 1998; Paus, Babenko, & Radil, 1990). Maturation of the orbitofrontal, mediofrontal, and cingulate cortex may be associated with the development of delayed gratification and other aspects of intentional behavior, including the control of motivation states such as aggression. Underlying the latter control of motivational states are extensive connections between the orbitofrontal/cingulate cortex and the amygdala (Barbas, 1995; Morecraft & Van Hoesen, 1998). The second “classical” approach to studies of the neural underpinnings of aggressive behavior is that of imaging the brains of individuals who show different forms of violent or antisocial behavior; unlike the neurological patients described earlier, these individuals have not suffered any known external damage to their brains. Using structural MR imaging, two recent studies described reductions of the volume of grey matter in different parts of the frontal lobes in aggressive patients with temporal lobe epilepsy (Woermann et al., 2000) and individuals with antisocial personality disorder (Raine, Lencz, Bihrle, LaCasse, & Colletti, 2000); the latter study described a 11% reduction in the volume of the orbitofrontal cortex in 21 community volunteers with an-

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tisocial personality; like changes were not found in two different control groups. Using functional imaging, Raine, Buchsbaum, and LaCasse (1997) described hypometabolism in the prefrontal cortex in 41 individuals charged with murder or manslaughter; in subsequent reanalyses of this sample, Raine and colleagues found that this hypometabolism was present only in those individuals who did not have history of psychosocial deprivation (Raine, Pihl, Stoddard, Bihrle, & Buchsbaum, 1998b) and those who committed impulsive/ emotional rather than purposeful aggression (Raine et al., 1998a). Similar findings were obtained in other clinical populations (reviewed in Brower & Price, 2001). Given the above lesion and imaging findings, we may ask: What is happening in the human brain during early infancy and childhood that “enables” aggressive behavior, which arguably peaks between 2 and 4 years of age (Tremblay, 2003; Tremblay et al., 2004) and then provides adaptive mechanisms, allowing its expression and resolution in a socially acceptable manner? Admittedly, we know too little about structural and functional development of the human brain to answer these questions at this point. It is clear that the most dramatic phase of brain growth takes place during the first 2 years of life: brain weight more than doubles, the overall volume of white matter and the degree of myelination increases sharply, with the overall increases in grey matter being less dramatic (e.g., Matsuzwa et al., 2001; Paus et al., 2001; Utsunomia, Takano, Okazaki, & Mitsudome, 1999). It is important to note that some interesting regional differences are beginning to emerge. For example, the volume of grey matter constituting the hippocampal formation shows a fast increase during the first 2 years of life and continues to increase slowly during childhood and adolescence (Utsunomyia et al., 1999). However, the volume of prefrontal grey matter appears to increase slowly until the age of 8 years, followed by rapid growth between 8 and 14 years (Kanemura, Aihara, Aoki, Araki, & Nakazawa, 2003). Although these patterns are based on cross-sectional studies of a relatively small number of infants and children, they provide a preview of what we may learn from several large-scale MRbased developmental studies that are under way. Returning to our question, it is possible that the development of structures in the mesial temporal lobes, such as the hippocampus and amygdala, underlie the initial development of aggressive behavior, whereas the relatively late development of cortical regions, such as the prefrontal and parietal cortex, enables adaptive regulation of aggression in the social context. Let us now examine some of the processes, and their neural substrates, that may be important for the latter. As suggested in the opening paragraph of this section, most acts of aggression take place in the context of social interactions among familiar individuals, be it at home, daycare, school, or the workplace. As with any other forms of communication, each side of the conflict emits and receives a number of cues, both verbal and nonverbal, that are essential components of the overall dynamics of their (aggressive) interaction. I suggest that the study of the neural substrates of such interactions, and their normal development, will

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benefit from the use of the experimental paradigms utilized over the past decade by cognitive neuroscientists interested in the brain mechanisms of interpersonal communication carried by gaze, face, body, and voice. Over the past several years a number of brain-mapping studies carried out with PET, fMRI, and EEG identified a key set of brain regions involved in the processing of “biological motion” generated by the movements of the eyes, mouth, and body. In such studies the subjects view stimuli such as eye and mouth movements (e.g., Puce, Allison, Bentin, Gore, & McCarthy, 1998), hand movements/ actions (e.g., Beauchamp, Lee, Haxby, & Martin, 2002; Decety et al., 1997; Grezes, Costes, & Decety, 1999), or body movements conveyed by point lights attached to the body (e.g., Bonda, Petrides, Ostry, & Evans, 1996). Among other brain regions, biological motion leads consistently to the increases in neural activity along the superior temporal sulcus, (STS) (Figure 12.5; reviewed in Allison, Puce, & McCarthy, 2000); the exact location may depend on the moving body part (e.g., mouth vs. eyes vs. hands) and the source of movement (tool vs. hand; Beauchamp et al,. 2002). Although most of the previous studies of biological motion used emotionally “neutral” stimuli, several investigators observed changes in brain activity in structures involved in processing emotional salience (amygdala) or reward value (orbitofrontal cortex). As suggested by Allison et al. (2000), feedforward and feedback interactions between the STS and the amygdala may be critical for the discrimination of various facial expressions and for the

FIGURE 12.5. Regions along the left (a) and right (b) superior temporal sulcus of the human brain “activated” by the movement of various parts of the body. From Allison, Puce, and McCarthy (2000). Copyright 2000 by Elsevier. Reprinted by permission.

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attentional enhancement of the neural response to socially salient stimuli. Consistent with such an “amplification” mechanism, Kilts, Egan, Gideon, Ely, and Hoffman (2003) observed significantly stronger neural response to dynamic, as compared with static, facial expressions of anger in both the STS and the amygdala. Developmentally, the basic aspects of face perception are in place shortly after birth (Goren, Sarty, & Wu, 1975), but both the quantity and quality of face processing continues to increase all the way through adolescence (e.g., Carey, 1992; McGivern, Andersen, Byrd, Mutter, & Reilly, 2002; Taylor, McCarthy, Saliba, & Degiovanni, 1999); perhaps one of the structural correlates of such continuing maturation of face processing in an increase in white matter density along the occipitotemporal pathway (Watkins et al., 2002). Seeing and hearing signals of upcoming aggression is often enough to prevent it; in the monkey, this can be achieved by quickly averting the gaze (e.g., Capitanio, 2002). The frontal cortex and its various subregions (see the preceding discussion) are likely involved in evaluating the overall context and significance of the detected visual (eyes, face) and auditory (vocalization) displays of aggression and in generating the appropriate behavioral response. This response could, nonetheless, be an aggressive act. If this is the case, what happens next? In many primate species, aggression is often followed by “reconciliation” or “conflict resolution” (Aureli & De Waal, 1997). Rather than viewing aggression as serving a “spacing” function, De Waal argues that “individuals try to ‘undo’ the social damage inflicted by aggression; hence, they will actively seek contact, specifically with former opponents” (De Waal, 2000). Several studies are beginning to document different forms of reconciliatory behavior in children observed in naturalistic settings (e.g., Ljungberg, Westlund, & Lindqvist Forsberg, 1999). Overall, careful studies of the neural substrate underlying various aggression-relevant elements of social cognition will undoubtedly further our understanding of human aggression, its normal development, and its socially unacceptable expressions.

CONCLUSIONS Structural and functional neuroimaging is making strides in elucidating the structure–function relationships underlying aggression, as well as providing novel information on brain maturation in children and adolescents. Previous research has focused on studies of adult individuals and overt aggressive behavior; lesions to the frontal lobes seem to increase the incidence of certain elements of aggressive behavior, whereas having aggression-relevant behavioral traits appears to correlate with functional or structural abnormalities in this brain region. Very little is known, however, about the relationship between aggression and the individual’s ability to detect and interpret nonverbal cues carried by the gaze, the face, and the body in a social context. I

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suggest that the study of brain–behavior relationships in this domain would be very helpful when combined, for example, with a detailed assessment of the perceptual and cognitive skills of individuals with different developmental histories of aggressive behavior. Finally, it is likely that future research on the role of the frontal lobes in aggression will shift from studying the actual act of aggression to investigating the brain substrate of reconciliation and conflict resolution. Although neuroimaging is a valuable tool in this endeavor, one should not forget about its limitations. For example, although T1-weighted MR images provide an impressive contrast between the (cortical) gray and white matter, we are not sure about the biological source of signal differences between various clinical or age groups; many factors may influence the signal, including the density of neurons, glia, or vascularization, or the degree of (intracortical) myelination. Functional imaging poses different challenges; for example, are age-related differences in the fMRI signal the cause or consequence of age-related changes in a given behavior? In other words, how do we make sure that the “stimulus” is held constant across different populations so that we can evaluate the magnitude of neural response to the same probe, rather than use the fMRI signal as a mere correlate of different behavior? Finally, structure–function correlations observed with structural and functional neuroimaging are just that, correlations. Other experimental approaches must be used to confirm whether a given region is necessary for a given behavior; such an inference can be made only when irreversible (lesion) or reversible (electrical or pharmacological stimulation) manipulations lead to the predicted behavioral consequences. Although some of these techniques can be used in (adult) human subjects, the ultimate tests would require animal models.

ACKNOWLEDGMENTS My research is supported by the Canadian Institutes of Health Research, the Canadian Foundation for Innovation, and the National Science and Engineering Research Council of Canada. I thank Drs. Richard Tremblay and Gabriel Leonard for their comments on the early version of this chapter.

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DETERMINANTSinOF Neuromodulators Aggression AGGRESSION

13 Neuromodulators in the Development and Expression of Inhibition and Aggression R OBERT O. P IHL and C HAWKI B ENKELFAT

Lack of behavioral control/regulation is known to predispose to aggression and substance abuse/dependency (Pihl, Peterson, & Finn, 1990). Conversely, the ability to inhibit/regulate behavior is a basic characteristic of healthy development. It is the assumption of this chapter that much of inhibition represents learned behavior. For example, a lack of inhibition is fundamental in impulsive–reactive aggression, and its frequency and form at various ages is affected by how biology and experience alter particular neuromechanisms involved in behavioral control. Tremblay et al., (1996), among others, have illustrated how aggression typically decreases with age, steadily declining from a peak around age 2. Clearly, the form of this behavior changes with age and sex, with the declining frequency likely representing the incorporation by the individual of societal restrictions and thus behavioral control. To drastically restate Rousseau, we begin not as noble savages but as savages who may or may not be “nobilized.” Thus, how the ability to inhibit develops and what mechanisms are operative is a preeminent developmental question. The purpose of this chapter is to present information about various neuromodulators that fuel brain development and functioning as it pertains to inhibition and aggression. Foremost among these are the neurotransmitters serotonin, dopamine, norepinephrine, and gamma-aminobutyric acid (GABA), as well as their interactions and the myriad of factors that modulate their activity. We first state some important caveats and then review the evidence supporting the involvement of these neurotransmitters and their interactions in 261

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inhibition. Finally, we examine how these systems change with development and specifically affect the development and functioning of the prefrontal cortex and its putative “executive control.”

A FEW ESSENTIAL CAVEATS That neuromodulators affect inhibition and aggression is a given. The specification of which neuromodulators play the key roles, and how, is, however, a different matter. Generalizations and conclusions must be qualified by at least four caveats. First, although we discuss various neurotransmitters and their respective systems as separate entities, nothing in the brain functions independently. The serotonin system, for example, interacts with most other major systems affecting behaviors ranging from aggression to sleep. In fact, the conclusion that the serotonin system’s main role is to modulate the activity of other systems has much support. Further, pharmacological studies, particularly, from which many conclusions regarding how these systems operate are drawn, rarely impact one system, one set of receptors, and so forth. Thus, findings often presented as specific and clear are in fact suspect. Second, although we argue for particular functions of certain neurotransmitters, these functions are neither static nor stable. For example, GABA, well recognized as the major inhibitory neurotransmitter in the brain, has been shown to be a major stimulus for neuronal excitation in the developing brain (McCarthy, Auger, & Perrot-Sinal, 2002). It is only with brain maturation that the more traditional function of neuronal inhibition becomes dominant. Facts like this, of course, raise the general issue of plasticity. Nelson (1999) has analogized neural plasticity as a “subtle but orchestrated dance that occurs between the brain and the environment” (p. 42). The brain shapes how one reacts to the environment, which in turn shapes how the brain affects anatomical, neurochemical, and metabolic change. As Nelson notes, these changes can be both adaptive and maladaptive for the organism, and for our purposes this phenomenon greatly complicates discussion of generic neurochemical systems. Third, consideration of sex differences in the functioning of neurochemicals is rare, but is important. Such differences are especially relevant, as a wealth of studies have reported significant differences between men and women in levels and types of aggression (see Archer & Lloyd, 2002). Further, laboratory studies of alcohol-related aggression typically display a much greater effect for men than women (Hoaken & Pihl, 2000). How hormones may alter gene expression, and thus subsequent brain development, particularly during adolescence, may have direct ramifications for sex differences in mood disorders and aggression, as well as in personality traits like introversion and sensation seeking. The frontal and temporal corticies, as well as the amygdala and hippocampus in particular, reflect significant postpubertal

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development. Walker (2002) has recently pointed out the significance of this time for brain development, which is reflected in the fact that the heritability of some behaviors and disorders increase with age, particularly during adolescence. Fourth, any attempt to delineate the neurochemical precursors of inihibition and aggression implies that we have a clear definition and subsequent measures for these phenomena. We have previously examined the relationship between self-report and behavioral measures of inhibition and have found it to be low to nonexistent (Helmers, Young, & Pihl, 1995). Similarly, definitions of aggression proliferate, as do measures, both lacking, respectively, in operationism and validity.

EVIDENCE FOR THE DIFFERENTIAL INVOLVEMENT OF NEUROTRANSMITTERS IN DISINHIBITION Serotonin The contention that altered serotonergic neurotransmission might play an important role in the pathophysiology of impulse-control disorders/aggressivity is not new. Using measurements in lumbar cerebrospinal fluid (CSF) of the main metabolite of serotonin (5-HT), 5-hydroxyindoleacetic acid (5-HIAA), investigators in the 1970s and 1980s proposed theoretical models implicating low serotonergic neurotransmission as a critical biological substrate for behavioral dyscontrol, often associated with impulsive, suicidal, and/or aggressive behaviors. These observations were fully consistent at the time with the findings that neurochemical lesions of the ascending serotonergic fibers were reported to facilitate aggressive behavior in rodents and with the subsequent discovery that tricyclic antidepressants enhanced serotonergic neurotransmission in rodents. Some researchers were then prompt to close the circle and suggest that these medications were effective in preventing suicide and attenuating aggressivity–impulsivity through their purported ability to correct for a neurochemical imbalance. This model of a deficit in serotonergic neurotransmission being primary in the causation of impulsivity and/or aggressivity, and predictive of therapeutic response to drugs shown to enhance serotonergic neurotransmission, is now obsolete. For example, not all impulsive–aggressive patients show these abnormalities and benefit from drugs enhancing serotonergic neurotransmission. Further, several drugs devoid of major effects on serotonergic neurotransmission are known to be effective in controlling aggressive behavior/impulsivity. The categorical view has gradually been replaced by a dimensional approach, that is, that low 5-HT explains in part the vulnerablity to impulsivity across various disorders. Hence, the thinking about this system has progressively evolved, which is the case for all systems described in this chapter, from an absolute deficit to a high-risk model. In other words, low serotonin neurotransmission is now thought to operate as a biological risk factor, resulting from genetic inheritance and/or early environmen-

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tal insult, neither sufficient nor necessary, yet when combined with other salient genetic factors and/or environmental stressors, may play an important role in the triggering and maintenance of disorders of impulse control and aggressive behavior(s). Most indices suggest that 5-HT metabolism is a relatively stable trait. Over time (months to years), CSF concentrations of 5-HIAA are highly correlated in studies in both human and nonhuman primates. This stability of CSF 5-HIAA concentrations likely reflects genetic contributions. Evidence for the existence of a low 5-HT neurotransmission trait is manifold; 5-HT1B receptor knockout mice are more aggressive (Hen, 1996); aggressive–impulsive primates followed longitudinally in their own ecosystem for years have stable low CSF 5-HIAA over time (Higley et al., 1996), and low CSF 5-HIAA has also been found in patients who reattempted suicide within 5 years as compared with those who did not (Roy, Pickar, De Jong, & Karoum, 1989). Further, it has been reported that newborns from families with antisocial personality disorder show lower CSF 5-HIAA concentrations than those from families devoid of a history of antisocial behavior (Constantino, Morris, & Murphy, 1997), and low central 5-HT neurotransmission in probands has been associated with an increased risk for impulsive aggression in their firstdegree relatives (Coccaro, Kavoussi, Hauger, Cooper, & Ferris, 1998). We have shown that subjects at genetic risk for mood and/or impulse control disorders are more vulnerable to the effects of transient lowering of serotonergic neurotransmission by means of dietary manipulations than age- and sexmatched controls devoid of family history for depression, substance abuse, and/or violent behavior (Benkelfat, Le Marquand, & Pihl, 1994; LeMarquand, Benkelfat, Pihl, Palmour, & Young, 1999). Impulsive aggression, including impulsive suicidal behavior, has been shown to be associated with specific polymorphisms of tryptophan hydroxylase (TPH) (the rate-limiting enzyme for 5-HT synthesis) and the serotonin transporter (5-HTT) (the protein responsible for the neuronal reupake of 5-HT and responsible for the recycling of up to 85% of synaptic 5-HT) (Nielsen et al., 1998). In addition, postmortem brain studies and in vivo imaging studies have demonstrated greater 5-HT1A receptor binding in females as compared with males (Parsey et al., 2002). Accordingly, there are several reports of an inverse relationship between aggression and 5-HT1A receptors (Cleare & Bond, 2000). Although the underlying cause for this sex difference is unclear, sex steroids are known to modulate 5-HT1A binding and it has been suggested that estradiol increases 5-HT1A binding (Biegon & McEwan, 1982). Furthermore, several lines of nonhuman evidence exist that suggest a functional difference in 5-HT1A receptors between males and females. For example, 5-HT transporter knockout mice have lower 5-HT1A receptor binding, which is more extensive in females than in males (Li, Wichems, Heils, Lesch, & Murphy, 2000). Finally, in the hippocamus, 5-HT and/or 5-HIAA concentrations are higher in female rats than in males (Haleem, Kennett, & Curzon, 1990). These serotonergic differ-

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ences may help to explain the higher incidence of mood disorders and depression among females, being twice that of males, and the lower reported overall incidence of overt female aggression. The concept of a low 5-HT trait being a predisposing factor for abnormal behavior has generated considerable interest and lots of supporting indirect evidence. Yet this concept is still much of a working hypothesis. Most of the findings establishing a link between low 5-HT neurotransmission and impulsivity and/or aggressive behavior were obtained in psychiatric patients, collected from nonepidemiological samples, studied as adults typically once, and compared with controls. In general, no information could be inferred from this type of design as to whether the purported abnormalities are trait- or state-related. Moreover, studies of clinical samples, though essential, have limitations of their own: sample heterogeneity, small sample size, not representative, retrospective, confounded by uncontrolled random environmental events (i.e., drugs), and so on. Further, there is no consensus of the operational definition of the corresponding behavioral phenotype for the proposed trait with the clinical syndrome complex, combining symptoms of mood liability/ explosiveness-irritability, increased impulsivity, quarrelsomeness, a predisposition for binge eating and substance abuse, with unclear boundaries, and with character cluster B pathology. More germane is the consideration of involvement and interaction of 5-HT with other neurotransmitters.

Dopamine The relationship between 5-HT and dopamine (DA) is particularly relevant. In a study in which microdialysis probes were used to measure these neurotransmitters in the nucleus accumbens (NAC) and medial prefrontal cortex (MPFC) in rats during intruder-precipitated aggressive behavior, it was found that DA levels increased significantly in the NAC and 5-HT decreased 80% in the prefrontal cortex (PFC; Van Erp & Miczek, 2000). Increased DA levels in the NAC have also been linked to many motivational and motor functions, including drug taking, food-reinforced behavior, sexual behavior, foot shock, social defeat, and attention to novel environmental stimuli. This range of behaviors reflects the fact that DA ascending pathways from this area project to and innervate more than 20 different structures, thus reflecting general rather than specific functions, and, in effect, neuromodulating various areas of incentive motivation (Le Moal & Simon, 1991). In particular, this system responds to cues of incentive reward, including novelty, receiving differential afferents from many sources, including the basolateral amygdala, the extended amygdala, the hippocampus, and the prefrontal medial orbital cortex. DA’s activity is related to its activation of two families of DA receptors: the D1 and D2 subtypes. Both are linked to G-protein activation, thus their signals are generally slow and long lasting rather than fast (Nieoullon, 2002). D1 receptors appear to underlie DA’s tonic activity, whereas D2 receptors underlie

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DA’s phasic activity. A tonic response implies that the neurons fire continuously throughout the duration of a stimulus, which appears to relate to DA’s ability to increase the stability of maintained representations. Stabilization involves increasing the signal-to-noise ratio of background versus evoked activity in the prefrontal cortex (Cohen, Braver, & Brown, 2002) D1 receptors appear to interact with other receptors, especially fast-signaling ones such as glutamate (Nieoullon, 2002), and have been implicated in the working memory functions of the dorsolateral PFC. Conversely, a phasic response implies that the neurons fire briefly at a particular phase of the stimulus (usually the onset) and likely relates to DA’s role as a gating signal. The DA system is responsible for indicating when new inputs should be encoded and maintained, or when currently maintained representations should be updated in response to salient, reward-predicting information. DA’s phasic response appears to involve activation of D2 receptors (Cohen et al., 2002). These receptors have been implicated in the reward circuits of the brain (Blum, Cull, Braverman, & Comings, 1996), as well as in the PFC’s regulation of the subcortical DA system. The subcortical DA system is involved in signaling reward-predicting information and, as such, is involved in motivational aspects of behavior. Thus, increases in DA transmission lead to more information being allowed to enter the “motive circuit” (ventral tegmental area–accumbens–ventral pallidum), so that this information becomes more motivationally relevant (Spear, 2000). In seeking out reward-related information, the DA system helps the organism to adapt to its present situation by facilitating the initiation of new responses and switching between alternate responses (Spoont, 1992). Serotonin and GABA appear to modulate DA’s reward-related activity. Blum et al. (1996) have proposed a “cascade theory” of the reward circuitry of the brain, implicating dopamine, serotonin, and GABA. In particular, they propose that the release of serotonin in the hypothalamus causes a release of enkephalin (an opioid peptide) in the ventral tegmental area, which, in turn, inhibits GABAergic neurons in the substantia nigra. This disinhibits DA neurons in the ventral tegmental area, allowing them to release DA in the nucleus accumbens and hippocampus. The released DA then activates D2 receptors in these regions, producing rewarding effects. Deficits in this reward pathway lead to what Blum et al. (1996) refer to as the “reward deficiency syndrome,” characterized by addictive, impulsive, and compulsive behavior. Thus, hypoactivity of the limbic DA system may be related to reduced levels of 5-HT or increased levels of GABA, whereas hyperactivity of this system should be associated with increased levels of 5-HT and decreased levels of GABA. As stated previously, reduced 5-HT has been associated with disorders of impulsivity, addiction, and aggression. Furthermore, GABA agonists have been suggested as a possible treatment for drug addiction, and aggression (Eichelman, 1990). In particular, GABA appears to dampen DA neurons via inhibitory GABAB receptors. Stimulation of GABAB receptors in the ventral tegmental area has been shown to dampen DA release in the nucleus accumbens produced by abused drugs

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(Cousins, Roberts, & De Wit, 2002), thereby reducing the rewarding effects of these drugs. Sex differences also exist in the regulation of dopaminergic neurotransmission. There is substantial evidence, primarily from nonhumans, that gonadal hormones modulate behavioral and neurochemical indices of activity in the striatum and nucleus accumbens. For example, female rats have higher striatal dopamine and homovanillic acid (HVA) levels than males, and aging reduces DA and HVA in males but not in females. Endogenous ovarian hormones, but not testicular hormones, modulate extracellular striatal DA concentrations in rats (Xiao & Becker, 1994). These differences may be related to the observations that female rats appear to be more sensitive than males to the toxic and reinforcing effects of psychostimulants that increase the DA system, an idea that is supported by research on gender differences in the behavioral response to cocaine, in which males and females do not differ in cocaine metabolism but female rats exhibit greater locomotor activation in response to cocaine than do male rats (Bowman et al., 1999). A contrasting view of serotonin’s interaction with dopamine has also been proposed. Spoont (1992) has suggested that 5-HT constrains DA’s reward-related activity, such that the organism’s behavioral output becomes more controlled. Thus, 5-HT’s role would be to increase the threshold by which exogenous stimuli become motivationally relevant, by decreasing the signal-to-noise ratio. Indeed, 5-HT has been shown to decrease the signal-tonoise ratio by inhibiting spontaneous cell activity to a lesser extent than specific evoked responses (Tassin, 1992). This would suggest that, through 5HT’s activity, a greater evoked response would be required in order for a stimulus to cause the cell to fire. This would ensure that only signals of sufficient strength or of sufficient relevance to the organism are able to interrupt current information flow and would prevent overshoots in the system by constraining the intensity of signals once they gain access to the system (overshoots in the system are associated with an increased magnitude of response and decreased sensitivity to cues of suppression). Supporting evidence for this view is drawn from studies showing decreases in 5-HT associated with increased locomotor activity and increased exploratory behavior signifying a release of normally inihibited operant behavior in diverse contexts, as well as increased food intake, sexual behavior, and aggression. Furthermore, behavioral evidence showing serotonergic modulation of the startle reflex is cited, with 5-HT decreasing the signal-to-noise ratio, thereby protecting the animal from interference from nonsalient environmental cues. Spoont (1992) further argues that DA normally functions to initiate new responses as well as to switch between alternative responses (a role that would appear to be related to DA’s rewardsignaling activity), which 5-HT constrains by making it more difficult for signals to gain access to the system. A similar pathway could be postulated to explain the effects of decreased serotonin on operant behavior, food intake, sexual behavior, and aggression. Furthermore, in considering the evidence that 5-HT normally constrains operant behavior and protects the organism from

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interference from nonsalient environmental cues, as well as evidence that decreasing 5-HT increases the propensity to switch between alternative responses while decreasing the integrity of those responses, one could argue that these are indicators of 5-HT’s effect on PFC function. As the section“Executive Control” discusses further, 5-HT appears to enhance PFC function, although the effect may depend on the particular characteristics of the situation in which behavior is assessed.

Norepinephrine The noradrenergic system serves many different functions, all of which are known to affect behavior profoundly. One comprehensive review argued that noradrenaline (NA) centrally and indirectly affects aggression on three different levels: the hormonal system, the sympathetic nervous system, and the central nervous system, in different, but functionally synergistic ways (Haller, Makara, & Kruk, 1998). All three components react very rapidly to environmental changes, catecholamine hormones being amongst the fastest to react. Behavior, of course, may involve a very rapid response to environmental challenges and engages the whole organism. Behavior, including aggressive behavior, is also energy dependent and therefore requires the rapid mobilization of energy stores. The peripheral catecholamines are important in ensuring the “energy” of behavior, whereas central noradrenaline is activated by offensive and defensive aggression in males (Higley et al., 1992). As such, external stimuli anticipating a demanding behavior or the demanding behavior itself activates the central nervous system noradrenergic system. Thus, even if NA would have no effect on mechanisms directly involved in aggression, it would nonetheless have profound influence on the expression of aggressive behavior through its indirect effects on other mechanisms vital during social challenges such as arousal and attention, pain sensitivity, olfaction, and memory. The NA neurotransmitter system has long been implicated as a modulator of normal arousal, vigilance, and engagement with the environment. It has also been shown that agents that increase brain noradrenaline improve attention in rats (Sirvio et al., 1993). Furthermore, pain sensitivity, beyond opiodergic control, is decreased by medullar descending noradrenergic pathways, and changing pain perception has an obvious function in aggressive behavior. The NAergic system is also involved in memory/recognition processes and in learning, mainly when olfaction is also involved. In summary, various socially relevant stimuli elicit a central release of norepinephine, which in turn promotes arousal and shifts attention toward relevant stimuli, induces analgesia, and enhances olfaction, learning, and memory. Such specific changes may together significantly change an animal’s reaction to social challenges. In general, studies have demonstrated an increase in aggressive behavior when norepinephine (NE) activity surges, and a decrease in aggression when NE activity is decreased. Increased NE function is positively correlated with the number of shock-induced aggressive episodes in rodents (Stolk, Connor,

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Levine, & Barchas, 1974), and pharmacological agents that increase NE function also increase shock-induced fighting in rodents. Mice that have been isolated for prolonged periods of time show increased aggressive behavior when given desipramine (which increases NE), an effect that is not observed when they are pretreated with a selective NE neurotoxin (Matsumoto, Ojima, & Watanabe, 1995). Stimulating postsynaptic noradrenergic receptors in cats’ hypothalami facilitates aggression; in humans, clinical treatment with tricyclic/ monoamine oxidase inhibitor antidepressants (which increase NE function) is associated with agitation and irritability, particularly in patients with borderline personality disorder. Thus, NE seems to increase/facilitate aggression. However, there are also contradictory studies. For example, positive correlations have been reported between the CSF concentration of NE’s major metabolite, 3-methoxy-4-hydroxyphenylglycol (MHPG), and life history of aggressive events in men confined to a military forensic unit (Brown, Goodwin, Ballenger, Goyer, & Major, 1979), and to impulsivity ratings in humans (Roy et al., 1989). Yet Virkkunen, Nuutila, Goodwin, and Linnoila (1987) have found lower CSF MHPG in violent offenders and in impulsive arsonists as compared with healthy volunteers, and a study by Coccaro et al. (1998) reported a negative correlation between plasma MHPG and life history of aggression in personality-disordered patients. The most extensive review on the relationship between norepinephrine and aggression offers an explanation for this discrepancy in results by suggesting that NA’s contradictory effects on aggressive behavior depends on what kind of aggressive paradigm is used (Haller et al., 1998). According to Haller and colleagues (1998), as far as isolation-induced or social (rank associated) aggression is concerned, a reduction in NA is followed by a parallel inhibition of aggressive behavior, but NA depletion appears to increase shock-induced and chemically elicited aggression. In these latter instances, the increase in aggression after NA depletion may be caused by parallel changes in other neurotransmitter systems, such as dopamine and/or serotonin and/or alterations in reactivity to environmental challenges. Haller and colleagues (1998) also conclude that when noradrenaline is in excess (i.e., when release is stimulated or reuptake is blocked), it influences aggression biphasically, such that a slight activation increases aggression whereas a strong activation decreases it.

GABA Similarly elusive is the role of gamma-aminobutyric acid (GABA) in aggression. It is well known that GABA serves as an inhibitory neurotransmitter at many central nervous system synapses. Yet increased GABAA receptor activation by alcohol suggests that GABA transmission can facilitate aggression (Miczek, De Bold, van Erp, & Tomatzky, 1997). In addition, one study surprisingly showed that when GABA was injected into medial hypothalamic defensive rage sites in cats, response thresholds were actually lowered following drug infusion (Nakao, Tashiro, Kono, & Araki, 1979). However, interven-

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tions that increase GABA receptor activation nonselectively do inhibit aggression. For example, microinjections of the GABA agonist muscimol into defensive rage sites within the dorsal periaqueductal gray matter inhibits aggression (Siegel, Roeling, Gregg, & Kruk, 1999). Similarly, aggressive mice have lower brain GABA concentrations as compared with nonaggressive mice, and agents that inhibit GABA metabolism dose-dependently decrease fighting in conjunction with increases in brain GABA (Simler, Puglisi-Allegra, & Mandel, 1982). Furthermore, both clonidine and lithium, which have anti-aggressive behavioral effects in some patients, have reportedly increased peripheral measures of GABA (Kemph, De Vane, Levin, Jarecke, & Miller, 1993). A study by Bjork et al. (2001) found that plasma GABA levels were lower in first-degree relatives of patients with major depressive disorder—who are also shown to have low plasma GABA—as compared with controls, thus indicating that plasma GABA is under genetic control. This study went on to demonstrate that plasma GABA levels and self-reported aggressiveness correlated negatively, but that this was more specific to subjects with a family history of depression.

DEVELOPMENT At each of the developmental stages, from genes to old age, the functioning and density of these neurotransmitters critical to behavioral control are operative. For example, regarding dopamine, a recent review (Di Maio, Grizenko, & Joober, 2003) has detailed the involvement of dopamine genes in attentiondeficit/hyperactivity disorder (ADHD). These authors marshal considerable evidence to support the strong involvement of the dopamine transporter gene (SLC3A6) and the dopamine receptor 4 gene (DRD4) in ADHD. A mouse with the dopamine transporter gene knockout has been developed, with the resultant animals displaying spontaneously increased activity and higher reactions to stress, which are significantly calmed by the administration of stimulants. This review further details how extra repeat copies of this gene have been reported in diagnosed ADHD populations. A similar repeat polymorphism has been reported for the alleles of the DRD4 gene, with particular focus on the 7 repeat allele. In a recent meta-analysis (Faraone, Doyle, Mick, & Biederman, 2001) it was reported that an odds ratio of 1.9 existed between the repeat allele and ADHD for family-based studies, suggesting a small but significantly increased risk. Another study of DA receptor density in 16 mice strains found threefold differences for the nucleus accumbens and a sevenfold difference among strains for the caudate-putamen between strains, demonstrating remarkable genetic variability (Jones, Hou, Cook, & Melloni, 1996). Excess dopamine prenatally, such as occurs when a mother is cocaine dependent, likely results in abnormalities, which studies suggest affect the differentiation of neurotransmitter systems, cell function, migration, and neuronal growth. Cocaine levels in the fetal brains of rats have been found to be greater than the 100% of those in the maternal blood. As shown in longitudinal stud-

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ies, infants born to cocaine-using mothers typically display poor behavior regulation, habituation, and orientation (Chasonoff et al., 1998). At age 6 this is seen in difficulty in managing impulses, frustration, and arousal. Studies of monkeys have shown that this prenatal exposure results in reduced expression of the rate-controlling enzyme in dopamine synthesis, as well as an elevation in dopamine receptors, particularly in frontal brain areas (Ronnekleiv, Fang, Choi, & Chai, 1998). Similar behavioral profiles to that produced by prenatal cocaine insult have been reported for many other drugs, with alcohol predominating. Prenatal alcohol exposure affects the functioning of many neurotransmitters and neuromodulators. Recent work focusing on serotonin has shown that alcohol fed to pregnant mice resulted in a 20–30% reduction in serotonin neurons (Zhou, Sari, Zhang, Goodlett, & Li, 2001) and a decrease in the density of serotonin fibers, particularly in the forebrains of the offspring (Sari, Powrozek, & Zhou, 2001). These effects likely permanently decrease serotonergic functioning in the mature animal, thus affecting behavioral regulation. The effect of prenatal malnutrition on the developing brain is another example of altered neurochemical function that has been extensively reviewed (Galler & Tonkiss, 1998). Depending on the time, type, and severity of malnutrition, the basic cytoarchitectine of the brain can be affected. Protein deficiencies in particular are significant, as proteins are precursors of enzymes, peptide hormones, and neurotransmitters. Morgane et al. (1993) have demonstrated in rats long-term inhibition in certain hippocampal GABA interneuron systems following prenatal protein malnutrition, which affects a myriad of other systems and is possibly responsible for many attentional and learning problems. In terms of neonates, rearing rats in isolation produces a behavioral syndrome that includes hyperactivity and an increased response to reinforcers, response perseveration, decreased pain thresholds, and a heightened response to dopamine agonists. Further, basal levels of dopamine are higher, and a down regulation of D2 receptors in the nucleus accumbens is affected (Hall et al., 1998). In the turbulent years of adolescence there is a concomitant shift in dopaminergic activity from subcortical to cortical areas. As one further ages, so does neurotransmitter functioning. In a PET study of individuals ages 24– 86 correlations were conducted between the density of D2 receptors and neuropsychological test performance. It was found that D2 receptor availability in the caudate and putamen declined with age and was correlated with decreased performance on a motor task, a measure of abstraction, and a response inhibition task (Volkow et al., 1998). As the preceding examples illustrate, throughout childhood, adolescence, and even into old age, changes occur in the circuitry of the brain that likely account for age-related cognitive and behavioral changes. For example, in adolescence there is a massive loss of synapses in the neocortex, with the most intense period of pruning occurring between 7 and 16 years of age. Although this pruning occurs for many different kinds of receptors, the majority of syn-

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apses lost are those that are excitatory in nature. Such pruning occurs throughout the brain, including the PFC and limbic regions. During adolescence there is also an increase in DA fiber density in the PFC, which may be compensated for later in adolescence by a decline in DA synthesis and/or turnover in this region. Developmental changes also occur in the GABAergic system. Studies in rats have shown increased responsiveness of the GABAB system and of the GABA/benzodiazepine receptor complex from adolescence to adulthood, but a decrease in responsiveness of the cortical GABAA system. Based on studies of knockout mice, it has been suggested that dysfunctional GABAA receptors lead to increased emotional reactivity (Mohler, Fritschy, Benke, Benson, & Luscher, 1996). In light of GABAB’s previously mentioned involvement in the reward circuit of the brain (in particular, dampening DA release produced by drugs), it could be inferred that this gradual increase in responsiveness of the GABAB system may reduce one’s susceptibility to the rewarding effects of certain drugs. Thus, it may be postulated that from childhood into adulthood, there is a decrease in the responsiveness to cues of reward. With respect to the serotonergic system, 5-HT binding appears to be lower during adolescence than during childhood or adulthood (Spear, 2000). Considering the myriad studies linking low serotonin levels to disorders of behavioral control and impulsivity, this lowered serotonin binding during adolescence may account for the impulsive behavior often seen at this developmental period. As concerns the relative balance between subcortical and cortical DA systems, there appears to be a shift toward greater predominance of cortical DA during early adolescence. With a peak in cortical DA activity at this time, a concomitant loss in excitatory drive to the cortex may result. Both rat and human studies have found a decrease of one-third to one-half in dopamine receptors in the striatum during adolescence (Seeman, Bzowej, Guan, & Bergeron, 1987). Spear (2000) has postulated that this adolescent-associated loss in excitatory drive to the cortex may create a mini-“reward–deficiency syndrome.” Thus, too little DA stimulation caused by overactivity of the PFC may lead to a state of underarousal. It is further thought that this underarousal may account for the increase in impulsive behavior often seen during adolescence. In addition, these mesocortical DA projections are seen as more sensitive to activation by stressors than are mesolimbic DA systems. Consequently, stress may exacerbate this adolescent-associated mini-reward– deficiency syndrome by increasing the extent to which cortical DA inhibits excitatory drive to the cortex. Adolescence is also a time when there is a shift toward greater efficiency of processing information. MRI studies have shown an inverse relationship between cortical grey matter loss and brain growth in the frontal cortex of adolescents, suggesting that the synaptic losses may be concomitant with increased myelination. Thus, maturation of the frontal cortex seems to involve a shift toward fewer and faster connections, a change that presumably increases the speed and efficiency of processing. These changes involve use-dependent

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patterns of connectivity, implying that experience plays an important role in the development of the PFC.

EXECUTIVE CONTROL Russian neuropsychologist Luria (1980) conceptualized the operation of the PFC more wholistically and realistically than the current focus on specific functions and their localization. Conceptually, he saw working memory, attentional control, verbal organization, and so forth, operating collectively to ascribe meaning to stimuli, in effect creating the context for possible responses. In this view, the frontal lobes are seen as responsible for planning, controlling, and verifying behavior in the presence of goals, working within a context and providing control over the more automatic subcortical systems. As reviewed earlier, the major neurotransmitters are integral to the development and functioning of the PFC. Dopamine is highly concentrated in the prefrontal cortex, in fact, more concentrated than in any other cortical region. One study showed that as infant monkeys improved their performance on a delayed response task requiring inhibition, the level of dopamine in the prefrontal cortex increased, as did the density of dopamine receptors (Brown & Goldman, 1977). Further, lesioning of the dorsolateral prefrontal cortex interferes greatly with performance on delayed response tasks, as does blocking dopamine receptors in these areas. On these tasks delay of responding is critical, which is why this area has been related to sustained attention and working memory. What is also noteworthy is that the pattern of responses in lesioned and pharmacologically manipulated animals is not random. Specifically, what occurs is a perseveration of the previous response. On tasks requiring memory with inhibition, little is known about dopaminergic functioning in children between the ages of 3 and 6. However, Diamond (2000) has been studying children who have been treated early and continuously for phenylketonuria, and who thus have reduced levels of dopamine in the prefrontal cortex, but have otherwise normal brains. These children typically reflect cognitive deficits and score in a similar IQ range to children with prefrontal damage (Diamond, 2000). Treated phenylketonuric children have a reduced level of the dopamine precursor tyrosine in the brain, which is particularly significant for the prefrontal cortex because it has a higher rate of dopamine turnover than any other brain area. The nature of the deficits in these treated children involve deficits in working memory and in inhibitory control. These deficits are seen even when IQ, gender, and other variables are controlled and are evident in all age groups: infants, toddlers, and young children. It is also notable that it is specifically deficits in working memory and inhibitory tasks, rather than other cognitive measures, that reflect the determined deficiencies. Cognitive and behavioral inhibition have long been linked to DA activity in the dorsolateral and ventrolateral PFC. Braver et al. (2001) have sug-

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gested that one of the key components in the ability to exert control over thoughts and actions is context processing, using subsets of representations within working memory that govern how other representations are used. Thus, in order to understand behavioral control and aggression, it is helpful to examine the mechanisms underlying working memory. Within the PFC, DA enhances working memory by modulating excitatory neurotransmission. D1 receptors, being colocalized with glutamate receptors on the spines of pyramidal neurons in the PFC, appear to enhance working memory by inhibiting excitatory input by activating the neuron. Thus, too little DA may lead to cognitive dysfunction through excessive stimulation, whereas too much DA may lead to deficits through insufficient stimulation (GoldmanRakic, 1999). This would be consistent with the theory of schizophrenia, which postulates that hypodopaminergic activity in the frontal cortex (along with hyperdopaminergic activity in the limbic system) leads to overstimulation and disorganized thought. This is also consistent with Arnsten’s (2000) finding that, in the PFC, DA has an inverted U-shaped dose–response curve, whereby either very high or very low levels of D1 stimulation impair cognitive function. The activity of the subcortical DA system appears to be partially under the control of the PFC. Deutch (1992) has proposed that DA tonically inhibits corticostriatal projection neurons, such that glutamate’s release in the striatal complex, in turn, inhibits DA from being released in the subcortical site. This hypothesis implies that diminishing the activity of DA in the PFC results in increased subcortical DA being released. Indeed, levels of DA activity in the PFC appear to be inversely related to DA release in subcortical regions (Spear, 2000). For example, it has been proposed that in children with ADHD, reduced activity in the PFC may lead to low tonic DA activity in limbic regions. This low tonic stimulation of DA autoreceptors may lead to high phasic activity in the nucleus accumbens and other subcortical sites. Thus, reduced PFC activity leads to low tonic DA activity, which leads to hyperresponsiveness of the DA system to reward-related cues. This model would account for the beneficial effects of stimulants in treating ADHD. DA’s inhibitory action may be mediated through direct activation of D2 receptors, or may occur indirectly by facilitating GABA release from interneurons. D2 receptors have been implicated in a number of addictive, impulsive, and compulsive disorders (Blum et al., 1996), and drugs that enhance GABAergic function have been used in clinical settings to control aggressive behavior. GABA and 5-HT have also been implicated in working memory in the PFC. GABAergic interneurons stabilize representations by inhibiting pyramidal neurons with opposite “best directions” (Goldman-Rakic, 1999). Thus, by inhibiting contradictory signals, the GABAergic system provides feedforward inhibition, thereby stabilizing maintained representations and preventing distractors from disturbing the system. In fact, postmortem and other biological studies have supported the suggestion of a defective GABAergic

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system in the frontal cortex of patients with schizophrenia (Blum & Mann, 2002). With respect to the 5-HT system, Williams, Srinivas, & GoldmanRakic, 2002) have found that in rhesus monkeys, 5-HT enhanced PFC function via activation of the 5-HT2A receptor, which facilitates both pyramidal cells and interneurons. In particular, direct facilitation of pyramidal cells, as well as indirect feedforward inhibition of pyramidal cells via GABA interneurons, provides tonic facilitation of the neuronal network (increased signal-to-noise ratio). However, in light of behavioral findings linking 5-HT to deficits in PFC function (Sasaki-Adams & Kelley, 2001), 5-HT’s facilitory effects may apply to only very constrained situations. Thus, 5-HT, by increasing the signal-to-noise ratio, may improve PFC function when the organism is highly motivated and when only task-relevant stimuli are present in the environment. However, in more realistic situations where there are many possible behaviors in response to a wide variety of stimuli, 5-HT’s facilitory effect may impair PFC function by increasing the amount of “noise” entering the system. NE has also been implicated in the functioning of the PFC. It appears to exert its influence through activation of alpha-1, alpha-2, and beta-noradrenergic receptors, all of which have been located in the PFC, and may also act through D4 receptors. Studies with rats, humans, and primates have indicated opposing effects of alpha-1 and alpha-2 receptor stimulation. Activation of alpha-2A subtype appears to enhance PFC functioning, as indexed by improvements in working memory tasks, response inhibition, and planning (Arnsten, 2000). Conversely, activation of alpha-1 receptors appears to impair performance on tasks subserved by the PFC. Furthermore, there appears to be an optimal level of NE, as NE exhibits higher affinity for alpha-2 than for alpha-1 adrenoceptors. Thus, moderate levels of NE (for example, as induced by stress) engage alpha-1 receptors and impair PFC function (Arnsten, 2000). Furthermore, there are NE–DA interactions, for example, cortical alpha-1 adrenergic and D1 receptors may be located on the same cells, and “the message induced by the stimulation of cortical D1 receptors is inhibited by alpha-1 adrenergic receptors” (Tassin, 1992, p. 145). NE’s functioning in the PFC also seems to be consistent with clinical research. Administration of beta-adrenergic receptor antagonists appears to attenuate aggressiveness in organically impaired children and adults, as well as in schizophrenic patients prone to violent outbursts. Moreover, lithium (which describes the functional availability of NE) reduces aggressiveness in personality-disordered adults and conduct-disordered children. Furthermore, one study found a positive correlation between CSF levels of the NE metabolite (MHPG, 3-methoxy-4-hydroxyphenylglycol) and a life history of aggressive behavior (Eichelman, 1990). Thus, in individuals with unusually high levels of NE, PFC function may be impaired by increased activation of alpha-1 adrenoceptors, which may lead to impaired behavioral control. In these populations, decreasing available NE seems to reduce aggressiveness, perhaps by reducing activation of alpha-1 receptors.

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CONCLUSION The development of behavioral regulation is essential to the control of impulsivity and most forms of aggressive behavior. This development requires the normative functioning of a wide range of neurochemical activities that affect and are affected by genetic variation and by pre- and postnatal experience. These interactions shape the brain and its functioning in that orchestrated dance between brain and environment. Although many neuromodulators are active participants, featured performers are serotonin, dopamine, norepinephrine, and GABA. Low serotonergic neurotransmission has been repeatedly linked to impulsive–aggressive behaviors. The mechanisms of the linkage, however, remain at issue, with enhanced vulnerability most likely associated with serotonin’s interaction with dopamine—specifically, hypoactivity at the limbic level, an involvement not unlike that of GABA’s. With reduced serotonin and GABA activity at this level weak, even irrelevant signals produce system activation. The inhibiting potential of the prefrontal cortex can limit this overactivation, again, through neurochemical functioning. Prefrontal serotonin levels, which appear reduced during adolescence, seem germane specifically to situations where highly motivated and task-relevant stimuli are present. Dopamine’s role, which is initiated when limibically active, appears inhibiting when active in the prefrontal cortex. This brain area basic to the control of behavior is a structure that develops through adolescence, is programmed by experience but fueled by the interaction of basic brain neuromodulators. Finally, an unmentioned but most significant caveat is relevant. That is, with the remarkable development of new technologies and daily flurry of scientific study, “all of the above is subject to change.”

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Spoont, M. R. (1992). Modulatory role of serotonin in neural information processing: Implications for human psychopathology. Psychological Bulletin, 112, 330–350. Stolk, J. M., Connor, R. L., Levine, S., & Barchas, J. D. (1974). Brain norepinephrine metabolism and shock-induced fighting behavior in rats. Journal of Pharmacology and Experimental Therapeutics, 190, 193–209. Tassin, J. P. (1992). NE/DA interactions in prefrontal cortex and their possible roles as neuromodulators in schizophrenia. Journal of Neural Transmission, 36, 135–162. Tremblay, R., Boulerice, B., Harden, P., McDuff, P., Pérusse, D., Pihl, R. O., & Zoccolillo, M. (1996). Do children in Canada become more aggressive as they approach adolescence? Growing up in Canada: The National Longitudinal Survey of Children (pp. 127–136). Ottawa: Statistics Canada. Van Erp, A. M. M., & Miczek, K. A. (2000). Aggressive behavior, increased accumbal dopamine, and decreased cortical serotonin in rats. Journal of Neuroscience, 20(24), 9320–9325. Virkkunen, M., Nuutila, A., Goodwin, F. K., & Linnoila, M. (1987). Cerebrospinal fluid monoamine metabolite levels in male arsonists. Archives of General Psychiatry, 44, 241–247. Volkow, N., Gur, R., Wang, G., Fowler, J., Moberg, P., Ding, Y., Hitzemann, R., Smith, G., & Logan, J. (1998). Association between decline in brain dopamine activity with age and cognitive and motor impairment in healthy individuals. American Journal of Psychiatry, 155, 344–349. Walker, E. (2002). Adolescent neurodevelopmental and psychopathology. Current Directions in Psychological Science, 11, 24–28. Williams, G., Srinivas, G., & Goldman-Rakic, P. (2002). The physiological role of 5HT2A receptors in working memory. Journal of Neuroscience, 22, 2843–2854. Xiao, L., & Becker, J. B. (1994). Quantitative microdialysis determination of extracellular striatal dopamine concentration in male and female rats: Effects of estrous cycle and gonadectomy. Neuroscience Letters, 180(2), 155–158. Zhou, F. C., Sari, Y., Zhang, J. K., Goodlett, C. R., & Li, T. K. (2001). Prenatal alcohol exposure retards the migration and development of serotonin neurons in fetal C57BL mice. Brain Research Developmental Brain Research, 126, 147–155.

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14 Hormones and the Developmental Origins of Aggression S TEPHANIE H. M. V AN G OOZEN

In considering biological influences on the development of behavior, in this case aggression, one should (and this cannot be emphasized enough) always see the behavior as the outcome of a complex interplay of individual, developmental, and social factors. Some of these factors might play a more or less important role as a function of the age of a child. For example, with respect to social factors, harsh parental discipline with cruel punishment plays a causal role in the development of antisocial behavior in childhood, whereas the absence of parental supervision is an important factor in antisocial behavior in late childhood or adolescence (Lahey, Waldman, & McBurnett, 1999). To give an example of a more individual factor, the early (perinatal) hormonal environment is assumed to play a role in shaping temperament and its development before the onset of important social influences such as peer interactions; at puberty, when pronounced hormonal changes occur, these individual factors may again become more relevant. When we consider young children, it is most likely that the origin of aggressive behavior lies in a combination of a toddler/child with a difficult temperament and a nonoptimal environment in which ineffective socialization plays a key role: A difficult child elicits harsh, inconsistent, and negative socialization behaviors, as a result of which a difficult temperament ultimately develops into aggressive or disruptive behavior. Although there are factors that contribute to antisocial behavior in childhood becoming chronic, not all antisocial children become antisocial adolescents, and not all antisocial adolescents become antisocial adults. A study of the individual factors in the development of aggression could help explain why these behavioral patterns change over time. 281

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In this chapter the role of two hormones—testosterone and cortisol—in the development and maintenance of aggressive and/or antisocial behavior are discussed, namely the androgen testosterone and the stress hormone cortisol, the primary reason for their selection being that most research on human aggression has focused on these two hormones. Before considering the evidence of hormonal factors in aggression, it is important to keep in mind that aggression can occur in both normal and pathological contexts. In the first case we mean normal individual variations in aggressive behavior, whereas in the second case aggression occurs more frequently and in more serious forms and is usually more persistent. In the latter case we are dealing with evidence from psychopathological studies. Because there have been very few studies addressing the influence of hormones on the normal development of aggression, evidence in support of the influence of hormones on both normal variations in aggression and more serious and persistent aggression are discussed. Another complex issue concerns the behavior of interest, aggression, and, in particular, its multiple causations. Many aggressive, antagonistic, or hostile acts are elicited by events, for instance, frustrating or otherwise aversive events. Yet aggression results from the individual’s disposition to react aggressively to such events. Such a disposition can be conceptualized in various ways, and problems have always existed with the predictive validity of instruments that measure such traits. One reason for such problems may be that much aggressive behavior results from emotional responses and that individuals differ in their proneness to emotional responding of particular kinds. It is not difficult to find examples from everyday life showing that aggression and emotion are intimately connected phenomena. Aggression can result from fear, hate, or even love. Still, the most common emotion related to the occurrence of aggressive behavior is anger. Whether a certain situation leads to anger, and perhaps to aggressive behavior, depends to an important extent on individual differences, such as personality characteristics, and these can be partly influenced by hormonal (organizing or activating) factors. Moreover, such individual differences can be of a short-term (temporary mood changes in irritability and quick-temperedness) or long-term character. It is clear that items in most aggression questionnaires, whether the focus is on adults or children, measure the occurrence of overt aggressive acts without reference to relevant antecedents, such as emotions and situational cues. Although there is important research examining the relationship between aggression and anger (Berkowitz, 1989), little has been done to study possible relationships between aggression and individuals’ proneness to anger, and as far as I know, nobody has studied hormonal influences on anger proneness in young children. A final comment concerns the type of aggression under investigation. An emotional or reactive form of aggression (with high levels of emotional arousal) is commonly distinguished from a more instrumental, proactive, or calculated (low emotional arousal) form (Vitiello & Stoff, 1997). Within these categories aggression can be of a more direct or indirect nature, it can be phys-

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ical or verbal, and other subcategories can also be distinguished. It is beyond the scope of this chapter to discuss these differences, but it should be clear that highly emotional and impulsive aggression and cold-blooded, calculated aggression have different neuropsychological and/or neurobiological underpinnings. For present purposes it is important to keep in mind that studies investigating the relationship between hormones and aggression have rarely addressed this issue, focusing usually on one type of aggressive behavior in particular.

TESTOSTERONE Why Is Testosterone an Interesting Hormone? Studies of aggressive behavior in animals indicate that the exchange of antagonistic and hostile acts is predominately a male attribute, exhibited between males. Criminological studies reveal a similar clear-cut sex difference: Men use far more physical violence and are more often the victims of aggression. Biological explanations have linked these findings to the social dominance of the male and to testosterone, the most important male sex hormone. Whereas many animal studies have demonstrated that the presence of this hormone is a prerequisite for the display of aggressive behavior, results of such studies in primates (Dixson, 1980; Eberhart, Keverne, & Meller, 1980) and humans are less clear-cut and at best suggestive of a positive association (Albert, Walsh, & Jonik, 1993; Archer, 1991; Archer, Graham-Kevan, & Davies, in press; Harris, 1999; Mazur & Booth, 1998). However, the interest in the aggression– testosterone relationship remains a strong one and can most probably be explained by the extensive literature on gender differences in aggressive behavior. If one investigates behaviors that clearly show differences between men and women, it is clear from a biopsychological perspective that the role of gonadal hormones is an important one on which to reflect. Indeed, gonadal hormones have been shown to be a relevant factor in the origin and expression of sex differences in behavior: The so-called “organizing” and “activating” effects have been well established in studies on neuroendocrine functioning, in anatomical studies, and in studies of behavior (Goy & McEwen, 1980). The development of internal and external genitalia, of sex differences in figure and appearance, and of various classes of sex-specific behaviors, such as the occurrence of sexual behavior or aggression (but by no means only these!) are to an important extent related to the presence or absence of testosterone during particular prenatal and postnatal developmental phases (Collaer & Hines, 1995). In adulthood both males and females are exposed to different classes and patterns of gonadal hormone stimulation, which, again, affect brain and behavior. However, understanding the origin of sex differences in behavior is complicated by the fact that such differences are not only manifestations of the organizing and activating effects of hormones; they are also the result of

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interactions between these hormonal influences on behavior, on one hand, and social influences on the individual during various phases of development, on the other.

Organizing and Activating Hormonal Effects The long-term developmental and structural effects of pre- and postnatal exposure to sex hormones on sex-dimorphic behavior have been termed “organizing” effects. These developmental effects are distinguishable from “activating” effects of gonadal hormones in that activating effects are reversible, repeatable, and not limited to a critical phase of development. It is, however, generally assumed that organizing, and activating hormone effects interact, and the distinction is therefore not as easy to make as the definition of the terms suggests. Activating hormone effects presumably act in concert with perinatal hormonal and early developmental experiential factors to perpetuate sex-dependent and individual behavioral characteristics (Van de Poll & Van Goozen, 1992). Organizing effects are usually tested by manipulating the exposure to sex hormones during fetal development, whereas activating effects are investigated at the time of puberty or adulthood. For obvious reasons, experimental research on these effects has focused almost exclusively on animals, rodents in particular. Androgenic gonadal hormones have been shown to be involved in various aspects of fighting behavior, including “intermale” aggression (Moyer, 1976). Studies of female rodents also demonstrate that the female, when exposed to testosterone prenatally or in adulthood, may exhibit high levels of aggressive behavior equal to those of males (Van de Poll, Van Zanten, & DeJonge, 1986). Although animal studies can teach us a great deal about the role of testosterone in behavior, and in aggression in particular, extrapolating the results to humans and implicitly postulating similar mechanisms in humans may present us with an unduly simplified and misleading picture of human functioning. The important issue to be addressed next is whether individual differences in human aggression have anything to do with differences in hormone levels or hormonal functioning.

Organizing Effects: Sex Differences in Aggression Evidence concerning the development of aggression is obviously important for the study of sex differences in aggression. One can assume that socializing processes start early, so that if one wants to research gender differences, these have to be studied at an early age. Boys and girls differ in play styles and toy preference: Boys are more energetic and active and show more aggressive and destructive behavior, involving so-called rough-and-tumble play, a form of play-aggression that has also been observed to be sex-dependent in monkeys (Hines & Green, 1991). Some of these sex differences have been reported in

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children as early as 12 months of age. Recently, Hines et al. (2002), in a large population-based study, found a relationship between testosterone levels, as measured in the blood samples of pregnant women, and gender role behavior in 3.5 year old girls (n = 337), such that as maternal testosterone levels increased, so did masculine-typical gender role behavior. No relationships between hormones and gender role behavior were found in boys (n = 342). The largest gender differences, however, are manifested in the years that follow, and this is a strong argument for the influence of socialization, modeling, and norms and values. A fair amount of evidence also exists for gender differences in aggressive feelings and behaviors during adolescence. Most of these associations involve the androgens and, as expected, larger effect sizes have been reported for boys than for girls. Several studies found evidence of a mediating role for impatience and impulse control in the association between hormonal levels and aggression (Susman et al., 1987; Warren & Brooks-Gunn, 1989). Olweus, Mattson, Schalling, and Low (1988) reported a causal effect of pubertal hormones on aggressive behavior via increased impatience and irritability. Hormonal influences on the development of the human brain and behavior can be investigated in individuals who have been exposed to unusual gonadal hormone environments, pre- or neonatally, due to genetic disorders or because their mothers were prescribed hormones during pregnancy. Reinisch (1981) concluded on the basis of her study that the development of aggressive behavior in humans is partly determined by prenatal androgens. Aggression proneness in children was measured with a response hierarchy test, consisting of a series of drawings picturing daily situations (e.g., a child takes away your toy) together with a number of possible reactions (hitting, shouting, go to parents, or crying); the number of aggressive reactions was the aggression score. Reinisch found a clear sex difference in (physical) aggression between boys and girls. Moreover, the administration of progestins to the mother during pregnancy (i.e., progestin being a synthetic sex hormone with androgenic action, prescribed to avoid the risk of possible miscarriage) had an aggressionenhancing influence on exposed boys and girls. Animal research on mice has demonstrated that sex differences in aggression can be counteracted by exposing female mice to testosterone or by castrating male mice postnatally. Later studies of similar effects in girls with congenital adrenal hyperplasia (CAH: an autosomal recessive disorder associated with an enzyme defect in the pathway of cortisol and aldosterone biosynthesis), who had been exposed prenatally to elevated levels of androgens, have not shown clear effects on aggressive behavior, although different aspects of gender role behavior were affected. These girls were more energetic, played with male peers and with boys’ toys more, and were identified by themselves and others as tomboys (Ehrhardt & MeyerBahlburg, 1981; Berenbaum & Resnick, 1997; Berenbaum, Duck, & Bryk, 2000). These studies of the prenatal effects of androgens on aggression used

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small samples and different research methods. For example, Reinisch (1981) measured aggression proneness as a more or less stable way of reacting to a number of standard situations. In studies in which no effects were found, a more or less standardized interview was often conducted with the children, their parents, and sometimes also their teachers. The differences in findings may be due to the different research methods used. Gender differences in aggression seem to be found most often when the subjects are offered response alternatives, for instance, a choice between verbal versus physical aggression. Reviewing the results of these studies of humans exposed prenatally to excessive androgens, one can conclude that certain aspects of gender-related behavior are influenced by prenatal hormones. The influence of these hormones is primarily on “tomboyism” or over-energetic and playful behavior. In girls, interest in maternity may be affected, but many androgenized women who are able to have children do become mothers. Clear-cut differences in gender identity and sexual orientation have not been found (Ehrhardt & Meyer-Bahlburg, 1981; Ehrhardt et al., 1985; Gooren, Fliers, & Courtney, 1990), although androgenized females sometimes show a delay in exhibiting normative teenage sexual experience and motivation, possibly because these girls look “different” and are less likely than their normal counterparts to develop a typically female body shape and may be masculinized if not treated by estrogens. Thus, whereas clinical studies with humans suggest organizational effects of excessive androgens on gender role behavior (specifically, oppositesex relationships and activity level), they do not appear to have a clear influence on aggression or other gender-typed behavior such as sexual behavior or sexual orientation (Paikoff & Brooks-Gunn, 1990). In sum, there are not many studies that have addressed the issue of whether prenatal androgen levels influence human aggression. The limited support for hormonal effects on aggression comes from studies with good experimental designs, good selection of control groups, and standardized measures of aggression (Berenbaum & Resnick, 1997). The literature reviewed earlier in this section suggests that there is no good evidence of a link between androgens and aggression in children, apart from Reinisch (1981). The recent study by Hines et al. (2002) and the research on girls with CAH were cited as evidence of effects of androgens on energy levels, play activity, and gender role behavior, not aggression.

Activating Effects of Testosterone on Aggression in Adolescents and Adults Correlations in men between androgens and self-reports of aggressive behavior or scores on aggression inventories are generally low (Meyer-Bahlburg, Boon, Sharma, & Edwards, 1974). For example, in one study a correlation of 0.28 was found between total testosterone and scores on a physical aggression subscale; the correlation with free testosterone was even lower, at 0.14 (Gladue, 1991). A study relevant to the issue of whether pubertal increases in

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testosterone levels produce an increase in physical aggression is that by Halpern, Udry, Campbell, and Suchindran (1994). They found no evidence of either an increase in aggression or an association between testosterone and aggression in a 3-year longitudinal study of 100 teenage boys (ages 12–13 at study entry) going through puberty. Recently, in a high-quality multitrait, multimethod, and multisampling study, Granger et al. (2003) also found no relationships between (saliva) testosterone and aggression, delinquency, or symptoms of disruptive behavior disorders in a relatively large sample of adolescent boys (n = 106). However, present or past aggressive behavior has sometimes been found to correlate positively with testosterone concentrations. For instance, Dabbs, Frady, Carr, and Besch (1987) measured saliva testosterone in 89 male prison inmates. They found that testosterone concentration was related to the type of crime: Men convicted for violent crimes (murder, rape, robbery) had higher testosterone concentrations than men convicted for theft or burglary. Most of the studies on activating effects have been correlational in design, thereby limiting the possibility of establishing a causal role for testosterone in eliciting aggression. A more compelling line of research is one that examines the effects of testosterone administration or depletion on aggression. Finkelstein et al. (1997) investigated the effects of testosterone administration on aggression in hormone-deficient (delayed puberty) adolescents. The data demonstrated significant testosterone effects, specifically on physical aggression and aggressive impulses in boys (and similar effects were found after estrogen administration in teenage girls). O’Connor, Archer, Hair, and Wu (2002) studied the effects of exogenous testosterone on aggression and mood in 30 eugonadal and 8 hypogonadal men. No significant increases in a range of aggression measures and no testosterone-related mood effects were observed in the eugonadal men. However, significant positive mood effects were found in the hypogonadal group. Another group of human subjects that is interesting from the standpoint of the study of activating effects of testosterone on aggression are transsexuals. In the process of their sex reassignment procedure, these patients are treated with high doses of so-called opposite sex hormones. In two studies it was found that when female-to-male transsexuals received high doses of androgens, their anger and aggression proneness increased, whereas the reverse happened in male-to-female transsexuals receiving anti-androgens and estrogens (Van Goozen, Frijda, Van de Poll, 1994; Van Goozen, Cohen-Kettenis, Gooren, Frijda, & Van de Poll, 1995). It is nevertheless clear that the evidence of a link between androgens and aggression is much weaker in humans than in animals. The results seem to be clearer when the relation is studied in younger age groups, as shown in studies of adolescents (Olweus et al., 1988; Schaal, Tremblay, Soussignan, & Sussman, 1996). This could be because social restrictions on aggression are still limited at a younger age and behavior has yet to be shaped. One therefore wonders what evidence there is for a relation between testosterone and aggression in prepubertal children.

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Androgens and the Development of Aggression in Young, Prepubertal Children Testosterone Given that there has been little research on testosterone and aggression in older age groups, it does not come as a surprise that there is even less information on young children. Until very recently it was not easy to measure testosterone levels in children. This is because prepubertal plasma levels are very low,1 and if one wants to sample testosterone in saliva, which is the least complicated way, only the unbound fraction of testosterone is available. To my knowledge, only four studies have measured testosterone levels (two in plasma and two in saliva) in preschool or schoolaged children and related these levels to aggression. Constantino et al. (1993) measured testosterone in plasma of 18 highly aggressive boys and 11 controls, all children being between 4 and 10 years old, and found neither a difference in testosterone between the groups nor a relationship between testosterone and the children’s Child Behavior Checklist (CBCL; Achenbach, 1991) aggression scores. The authors concluded that these findings raise questions about inferences from adult studies suggesting that testosterone may play a causal role in the development of aggression. However, an explanation for the negative results may lie in the composition of the groups, because 10 out of 18 aggressive boys had a comorbid diagnosis of psychotic disorder. Psychosis has been considered an exclusion criterion (Kruesi et al., 1990), because aggression as a temporary symptom of a psychotic episode is clearly different from aggression as observed in children with a psychiatric diagnosis of oppositional–defiant disorder (ODD) (American Psychiatric Association, 1994) or conduct disorder (CD) (American Psychiatric Association, 1994), let alone in normal, healthy children. Moreover, the age range in the subgroups was large (between 4 and 10 years), and the investigators had to divide the groups into smaller subgroups (i.e., an adrenarchal subgroup consisting of 6 psychotic–aggressive, 4 nonpsychotic–aggressive, and 6 normal controls; and a preadrenarchal subgroup of 4 psychotic–aggressive, 4 nonpsychotic–aggressive, and 5 normal controls). Van Goozen, Matthys, Cohen-Kettenis, Thijssen, and Van Engeland (1998b) also found no difference in plasma testosterone between boys with CD (n = 15) and normal controls (n = 25; all participants were between 8 and 12 years old), and there were no significant relationships between testosterone and CBCL ratings of aggression and delinquency. A third study focused on normal, healthy 4-year-olds and measured testosterone in saliva (SánchezMartín et al., 2000).2 No difference in testosterone was observed between boys (n = 28) and girls (n = 20), but testosterone in boys was positively correlated with observations of more serious aggression in social interaction. No such relations were observed for more playful aggression, and no relations between testosterone and behavior were observed in girls. Finally, Scerbo and Kolko (1994) measured saliva testosterone in forty 7–14-year-old clinic-

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referred disruptive children and found a significant positive relationship between testosterone and staff-rated aggression, after taking age and physical characteristics into account, but no differences in mean levels for children with or without CD, ODD, or ADHD.

DHEA/DHEAS From about age 6, children exhibit a gradual increase in androgens of adrenal origin, a period called the adrenarche, and it is not until puberty that gonadal androgens, such as testosterone, become more important. Research in prepubertal children should therefore not only focus on testosterone, but should also consider adrenal androgens, such as dehydroepiandrosterone (DHEA), its sulphate (DHEAS), and androstenedione. Of these, DHEA and DHEAS are particularly interesting because they are also endogenously synthesized by the brain and act as neurosteroids (Robel & Baulieu, 1995), they increase neuronal excitability, enhance neuronal plasticity, and have neuroprotective properties (Wolf & Kirschbaum, 1999) and, finally, they appear to have potent antagonistic effects on central gamma-aminobutyric acid (GABAA) mechanisms, which are involved in aggressiveness (Majewska, 1992). One would therefore expect to find elevated DHEA/DHEAS levels in individuals who are aggressive. Until now, very few studies have focused on the role of adrenal androgens in children. Interestingly, a pattern of DHEA hyposecretion has been found in children and adolescents with major depression (Goodyer et al., 1996). So far, three studies have examined DHEAS levels in prepubertal aggressive boys. The previously mentioned study by Constantino et al. (1993) found no relationship with aggression, but, as noted earlier, there are some grounds for treating this null finding with caution. Van Goozen et al. (1998b) found that DHEAS levels were significantly higher in boys with CD than in normal controls and were strongly related to aggression and delinquency scores; differences between the two groups in androstenedione and testosterone were, respectively, marginally significant and not significant. However, no data on developmental status were collected and no psychiatric control group was included. One could speculate that if higher adrenal androgen levels reflect adrenal response to stress, and if chronic stress stimulates adrenal development and secretion (Sapolsky, 1997), it is possible that elevated DHEAS levels would also be found in other psychiatric groups as a result of stress associated with the psychiatric disorders. The aim of a subsequent study (Van Goozen et al., 2000b) was to investigate DHEAS levels in a new group of prepubertal children with ODD and normal and psychiatric controls, including a group of children with attention-deficit/hyperactivity disorder (ADHD). DHEAS levels were examined in relation to developmental status, psychiatric diagnosis, and intensity of aggression and delinquency during the preceding 6 months as rated by parents/care workers. The results again showed that the ODD group

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had significantly higher levels of DHEAS than both the normal and psychiatric control groups. At present it is not clear how best to explain these results. It may be that the DHEAS levels of the children with ODD were higher from early childhood onward; alternatively, it may be that these children had higher levels only since the beginning of adrenarche. However, by measuring the development of the secondary sex characteristics and finding that the different groups of children were similar with respect to physical development, Van Goozen and colleagues could rule out the possibility that the children with ODD were physically more mature than their counterparts in the two control groups. The positive relation observed between ODD and/or CD, on one hand, and plasma levels of DHEAS, on the other, is of interest. As mentioned earlier, higher endogeneous levels of this neuroexcitatory steroid may contribute to more aggression because of its GABAA antagonistic actions (Majewska, 1992). It is also possible that higher DHEAS levels contribute to a larger pool of endogeneous testosterone. However, in our own study measuring different androgenic hormones (i.e., testosterone, DHEAS, and androstenedione) in children with CD, we found that the relation between DHEAS and aggressive behavioral problems is stronger than that between testosterone and such problems, suggesting a more important role of CNS excitatory mechanisms in aggressive behavior of children (Van Goozen et al., 1998b). These results demonstrate that adrenal androgen functioning is an important subject for future research on the developmental origin of aggression in children.

Methodological Considerations A large part of human aggression research has been questionnaire-based, and it is worthwhile to reflect on the potential for measuring the effects of hormones on aggression by means of this methodology. If one accepts the evidence that hormonal effects on aggression are rather subtle, and admits that the assessment of the type of behavior under consideration is complicated, not only because there are many different ways of expression, but also because one is dealing with a sensitive (and rather negatively valued) issue, it follows that asking people to report on their own aggression or asking informants for their observations about other people’s aggression is fraught with difficulties. The evidence shows that the assessment of the frequency and intensity of children’s aggression is, to a large extent, dependent on whether one asks the parents, the teachers, or the children themselves, and that there are considerable cross-informant discrepancies (see, e.g., Loeber, Green, Lahey, & StouthamerLoeber, 1991). If the assessment of the target behavior is so variable, how can one expect to find a reliable relationship with hormonal parameters? It is safe to conclude that questionnaire studies of the relationship between testosterone levels in humans and aggressive disposition have generated a conflicting body of evidence and that, on the whole, directly observational research or studies that treat differences in hormonal condition as an inde-

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pendent variable (e.g., Finkelstein et al., 1997; Reinisch, 1981; SánchezMartín et al., 2000; Van Goozen, Frijda, Wiegant, Endert, & Van de Poll, 1996) have been better able to reveal the rather subtle hormonal effects on overt angry and aggressive behavior.3 Given that there are very few data on children’s aggression, it is our belief that future studies on the development of aggression in children, in focusing on the involvement of hormonal parameters, should rely on such methods to explore this issue further.

CORTISOL A second hormonal factor contributing to individual differences in antisocial behavior is cortisol. Cortisol is related to the experience of stress, and it seems likely, on the basis of observing overt aggressive behavior, that the stress system is involved in displaying aggression. Specifically, one could hypothesize that people who engage in aggression are, relatively speaking, unafraid of the negative consequences of their actions or, stated differently, are less sensitive to punishment (Matthys, Van Goozen, De Vries, CohenKettenis, & Van Engeland, 1998; Van Goozen et al., 2004). One important biological stress system is the hypothalamic–pituitary–adrenal (HPA) axis, which plays an important role in the regulation of both physical and psychological stress. It has been proposed that a reduced activity of the HPA system is part of the biological predisposition to antisocial behavior (Van Goozen, Matthys, Cohen-Kettenis, Buitelaar, & Van Engeland, 2000a). Low activity or arousal has been linked to fearlessness, sensation seeking, and/or risk-taking behavior (Raine, 1996). Specifically, one can predict that individuals who are less sensitive to stress (i.e., stress hyporesponsive) are more likely to engage in aggression because they do not fear the negative consequences of their actions because of a lack of fear conditioning. A lack of fear of punishment would also reduce the effectiveness of social conditioning and could therefore explain why this pattern of behavior, especially when observed in disruptive and antisocial clinical cases, can be so persistent and hard to treat.

The Stress System There are clear indications that stress plays an important role in the explanation of individual differences in antisocial behavior, and in this connection it is useful to draw on concepts such as stress sensitivity, stress regulation, and coping with stress. The activity of the neuroendocrine HPA system is central to stress resistance and can be assessed by using measures of its end products, the glucocorticoids. The primary glucocorticoid in humans is cortisol, and this hormone can be relatively easily assessed in saliva (Dettling, Gunnar, & Donzella, 1999). A well-functioning HPA system is necessary for survival, but hyperactivity of this system may have deleterious effects on immune system

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activity and brain areas involved in memory and attentional processes and may influence the expression of defensive behaviors (Gunnar, Tout, de Haan, Pierce, & Stansbury, 1997). Thus, healthy adaptation involves efficient regulation of HPA system activity. Generally speaking, the expression of an adrenocortical stress response is dependent on (1) whether the situation is perceived as potentially threatening, (2) whether the outcome is important to the individual, and (3) whether the individual expects to have the resources necessary to manage the threat (Gunnar et al., 1997). Factors such as control, sense of success and efficacy, and predictability are therefore very important in the activity of the HPA system. The starting point of research on the relationship between stress and antisocial or aggressive behavior is the hypothesis that aggressive individuals are less fearful or sensitive to stress. This can be deduced from the fact that these individuals are less inhibited and more prone to engage in risky, stressful, or dangerous situations than other people are. If this is true, there are two possible explanations for a relationship between a lower stress sensitivity and aggressive or antisocial behavior. One theory claims that antisocial or aggressive individuals have low levels of fear (Raine, 1996). A relative lack of fear or a less inhibited temperament would lead to aggression or antisocial behavior because the person is less sensitive to the negative consequences of his or her own or other people’s behavior in general, and the receipt of punishment in particular, and because the person overestimates his or her own coping strategies. If this is the case, the implication for the treatment of serious aggression or antisocial behavior is clear. Thus, aggressive individuals, including children, have problems in conditioning, so trying to point out the negative consequences of behavior, or punishing unacceptable behavior, is likely to have little or no effect. A different stress theory focuses on sensation seeking (Zuckerman, 1991). Here it is argued that a certain level of stress is needed in order to feel pleasant and that too little or too much stress is experienced as unpleasant. Aggressive individuals are supposed to have an elevated threshold for stress. They are easily bored and are not put off by situations that most people find too exciting, stressful, or dangerous.

Human Studies on Cortisol and Aggression What evidence is there that a dysfunctional stress system plays a role in aggressive behavior? Several studies have found that antisocial and aggressive adults have lower levels of cortisol. There are also indications of inverse relationships: The more aggressive the behavior, or the more serious the antisocial behavior disorder, the lower the biological stress levels (King, Jones, Scheurer, Curtis, & Zarcone, 1990; Virkkunen, 1985; Woodman, Hinton, & O’Neill, 1978). This type of research has also been conducted on children with antisocial behavior, albeit less frequently. Although the results are less consistent

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than those from the adult studies, the predicted relations have been found. For example, Tennes and Kreye (1985) and Tennes, Kreye, Avitabe, and Wells (1986) found a relationship between lower cortisol levels in urine and the intensity of aggressive behavior as expressed toward peers or a teacher. In other studies researchers have found a negative relation between conduct disorder severity and cortisol (McBurnett, Lahey, Rathouz, & Loeber, 2000; Pajer, Gardner, Rubin, Perel, & Neal, 2001; Van Goozen et al., 1998a; Van Goozen et al., 2000a; Vanyukov et al., 1990). However, the findings for children and adolescents are not as unequivocal as those for antisocial adults, in that positive relationships between cortisol and antisocial behavior have also been found in some studies. In normal, healthy adolescents a positive relationship was found between aggression and cortisol response level during an experimentally induced aggression task (Gerra et al., 1997) and during an emotion-arousing and painful procedure (Susman, Dorn, Inoff-Germain, Nottelmann, & Chrousos, 1997). Moreover, McBurnett et al. (1991) reported high levels of cortisol in conduct-disordered (CD) children, but only when they had a comorbid anxiety disorder. Finally, some studies have found no relationship between cortisol and antisocial or aggressive behavior (Klimes-Dougan, Hastings, Granger, Usher, & Zahn-Waxler, 2001; Kruesi, Schmidt, Donnelly, Hibbs, & Hamburger, 1989; Scerbo & Kolko, 1994; Schulz, Halperin, Newcorn, Sharma, & Gabriel, 1997; Stoff et al., 1992; Susman et al., 1999). Apart from the direct relationship between stress and antisocial or aggressive behavior, cortisol also seems to play a part in the prediction of antisocial behavior in the long term (McBurnett et al., 2000). At present is not known whether a reverse relationship also exists, that is, that aggressive children with an elevated sensitivity to stress are more fearful and therefore have a lower risk of persisting in their antisocial behavior. Such data already exist for autonomic nervous system measures (Brennan et al., 1997). An important future line of research is therefore to establish whether the development of aggression over time is related to young children’s stress sensitivity or level of fearfulness, in the sense that children with elevated HPA axis activity levels are biologically protected against acting aggressively on a frequent and/or more serious basis.

Methodological Considerations The mixed findings in regard to cortisol and aggression in children and adolescents may be due to important methodological differences between these studies. First, the label “aggression” or “antisocial” has been used for behaviors as different as physical aggression, running away from home, stealing, and drug use (Coie & Dodge, 1998; Tremblay, 2000, 2003). Furthermore, studies that specifically assess physical aggression have generally not taken into account whether it is of a reactive or proactive type. Reactive

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and proactive aggression have been observed in children, adolescents, and adults (Brendgen, Vitaro, Tremblay, & Lavoie, 2001; Dodge, Lochman, Harnish, Bates, & Pettit, 1997). Reactive aggression is impulsive, often accompanied by disinhibition and affective instability, but not necessarily by antisocial tendencies; it is characterized by high levels of bodily arousal. Proactive aggression, however, is nonimpulsive and controlled and occurs in the context of persistent antisocial behavior. Proactively aggressive individuals are less likely to have unstable affect, their aggression is goal directed, and the level of arousal is usually low (Vitiello & Stoff, 1997). It seems theoretically plausible that proactive aggression is likely to be associated with low levels of cortisol, whereas reactive aggression is accompanied by elevated levels of cortisol. Differences in assessments of cortisol may also explain the diversity of results. Some studies measured cortisol under resting conditions (Kruesi et al., 1989; McBurnett et al., 2000; Tennes & Kreye, 1985), and other studies measured cortisol before the occurrence of an anticipated stressful event (Dawes et al., 1999; Moss, Vanyukov, & Martin, 1995), during an aggression-provoking task (Gerra et al., 1997), or under highly stressful conditions (Van Goozen et al., 1998a, 2000a). Moreover, most studies on children’s cortisol involved measurements varying over the day, without controlling for the clear circadian rhythm in cortisol secretion or for the kinds of activity in which participants had been engaged before the start of the study (McBurnett et al., 2000); only a few studies measured cortisol at specific time points, having kept the conditions constant for all participants (Susman et al., 1997; Van Goozen et al., 1998a, 2000a). Finally, some studies used only clinical samples (Scerbo & Kolko, 1994; McBurnett et al., 2000), some compared clinical samples with nonclinical samples (Kruesi et al., 1989; Pajer et al., 2001; Stoff et al., 1992; Van Goozen et al., 1998a, 2000a), and others used community samples (Gerra et al., 1997; Klimes-Dougan et al., 2001). To summarize, research on aggressive child psychiatric patients (i.e., children with a psychiatric diagnosis of CD or ODD) demonstrates that these children are characterized by a lower sensitivity to stress, as reflected by a lower secretion of cortisol during experimental conditions involving stress exposure (Van Goozen et al., 2000a). These data support the fearlessness theory of aggression as described by Raine (1996). The situation is less clear with respect to the issue of whether persistently aggressive children also have lower resting levels of cortisol. Furthermore, normal variations in HPA system (re-) activity seem to play a clear role in temperamental differences between children, with higher activity being linked to a shy, inhibited, and anxious temperament and low activity with a more impulsive and aggressive temperament (Gunnar et al., 1997; Kagan, Resnick, & Snidman, 1988; Susman, Schmeelk, Ponirakis, & Gariepy, 2001). However, there has been hardly any research directly studying the relationship between cortisol and the occurrence and development of aggression. This is clearly an important issue for future research.

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The Role of Early Experiences We do not currently know why aggressively acting individuals have lower HPA-axis activity levels, although it is, of course, possible that genetic factors play a role (Bakshi & Kalin, 2000). However, there is also evidence that stressful events—by which is meant serious stressors such as neglect, abuse, and trauma—in the first years of life play an important role in “programming” the HPA axis. The evidence comes mainly from animal studies, but it seems likely that the neurobiological consequences of the severe stress that can be manipulated in animal studies also occur in humans. Interactions between a person’s biological makeup, on one hand, and the environment in which that person is raised, on the other, determine his or her physical and psychological development. Physical and biological problems during important phases in pre- or postnatal development (e.g., birth complications, intense stress or illnesses during the mother’s pregnancy), together with aversive early psychosocial experiences (such as malnutrition, poverty, neglect, and abuse) contribute importantly to the development of personality and psychopathology (Gottlieb & Halpern, 2002). There is increasing evidence that such interactions between biological and environmental factors affect the developing brain both prenatally and postnatally, including the functioning of the HPA axis (Francis, Caldji, Champagne, Plotsky, & Meaney, 1999; Kaufman, Plotsky, Nemeroff, & Charney, 2000; Liu et al., 1997) as well as the serotonergic system (see Suomi, Chapter 4, this volume). Although preclinical studies offer important suggestions regarding the way in which early experiences can influence the development of specific biological systems that are involved in aggressive behavior, the conclusions are based on animal data and it is obvious that such experimental studies cannot be done on humans. There is, however, some preliminary evidence that similar processes can occur in humans. In a study conducted in an orphanage in Romania, Carlson and Earls (1996) measured the cortisol levels of children who had been severely neglected. They found that these children failed to exhibit a normal diurnal cortisol rhythm. In another phase of the study they exposed some of these children to an intervention. In this intervention the children lived in smaller groups, and they were positively stimulated by their caretakers and were given toys. After 13 months their cortisol levels were measured again in order to establish whether they exhibited a normal diurnal pattern. This was not the case. Such a finding is consistent with the view that a long and intense period of neglect had a permanent effect on cortisol functioning, although it is, of course, also possible that the intervention was too short or too weak to allow the children to recover normal functioning. Although there is presently not much solid evidence that processes similar to those observed in animals also occur in humans, it is known that abuse and neglect are serious psychosocial stressors, that such experiences can occur at a

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young age, and that a high proportion of children with aggressive behavioral problems have had such experiences.

FUTURE RESEARCH ON ADRENAL STEROIDS Testosterone has been found, albeit inconsistently, to play a role in aggression, but levels are very low in prepubertal children and it is therefore difficult to assess its role in the development of this behavior from an early age. This chapter reviewed the evidence that children with aggressive or antisocial behavior have increased plasma levels of the adrenal androgen DHEAS and either a decreased basal level of another adrenal steroid, cortisol, or a decreased cortisol reactivity to stress. It is not unusual to observe these steroids changing in opposite directions. Adrenocorticotropic hormone (ACTH) stimulates the secretion of cortisol, DHEA, and DHEAS, but there are many instances of dissociation between the secretion of cortisol and adrenal androgens, indicating that they are governed by separate regulatory mechanisms and that other factors may modulate their biosynthesis. Moreover, although both are secreted by the adrenal cortex, they have different sites of origin. Clarke, Fearon, Cunningham, and McKenna (1996), in their research on the hypothalamic– pituitary–adrenal (HPA) axis, demonstrated that beta-endorphins (the levels of which rise at adrenarche at the same time as the secretion of DHEA/ DHEAS increases) and joining peptide stimulated adrenal androgen production but inhibited ACTH-stimulated cortisol production. One could infer from these results that a dissociation between cortisol and adrenal androgen secretion might be found in people with antisocial behavior, but it is also possible that other regulatory mechanisms will be uncovered in future research. Clearly, adrenal androgens in young children should be studied more extensively, and preferably in combination rather than separately. The observation of an association between increased DHEAS levels, decreased cortisol levels, and a current diagnosis of ODD or CD in children (Van Goozen et al., 1998a, 1998b, 2000a, 2000b) suggests that it would be worthwhile to study the mechanisms underlying adrenal steroids alterations in childhood. If future studies replicate the findings of an aberrant secretion of adrenal steroids (i.e., an excess of DHEAS and a deficit of cortisol reactivity), this would confirm the idea that such a hormonal profile contributes to aggressive or antisocial tendencies. Such a hormonal line of research on the developmental origins of aggression should focus on children as young as possible, preferably in the prenatal period, and should extend from the immediate postnatal period into early and late childhood. The implication is that hormonal samples would be taken frequently and controlled for various internal (e.g., diurnal rhythm) and external (e.g., life events) influencing factors. Not only is such a line of research timeconsuming and expensive, it is also difficult to carry out for practical reasons. Large sample sizes are required, and these have to be followed up over time.

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Moreover, as far as the prenatal part of such a project is concerned, recent evidence from my own research group suggests that it is not steroid levels measured in the umbilical cord or maternal serum (assessed over the three trimesters of pregnancy) that provide the best source of information if one wants to assess androgen exposure during fetal development (Van de Beek, Thijssen, Cohen-Kettenis, Van Goozen, & Buitelaar, 2004). Rather, it is the analysis of the amniotic fluid that provides the most valid assessment of fetal androgen exposure during a very sensitive period of development (about 16–18 weeks into pregnancy). Specifically, it was found that the mother’s own androgen levels were unrelated to the androgen exposure of her child as reflected in the amniotic fluid. If one accepts these results, this poses severe restrictions on conducting this type of research, because it is not easy to collect amniotic fluid simply for scientific purposes. Nevertheless, if one wants to investigate hormonal influences on the very early development of temperament in general, and aggression in particular, this seems to be the way to go about it. The picture is somewhat different for cortisol. An adequate physiological stress response, characterized by a rapid increase and subsequent decrease in stress hormones, is essential in adapting to and coping with stress. As discussed earlier, variations in both basal activity and stress responses have been associated with the existence of problem behavior and the development of psychopathology. Long-term changes in stress hormonal functioning play a key role not only in the pathophysiology of aggressive behavior but also in depression (Goodyer et al., 1996). Adequate physiological stress responses are also important in infants. Neonates (4–7 days old) who were alert during a physical examination and well orientated had relatively higher baseline cortisol values and weaker cortisol responses (Spangler & Scheubeck, 1993). Insecure–avoidant and disorganized 1-year-old children showed a clear increase in cortisol during the Strange Situation Test (SST) as compared with securely attached children, who showed an adequate behavioral response and no increase in cortisol (Spangler & Grossmann, 1993). These examples illustrate the relationship between physiological and behavioral responses to stress. However, the precise relationship between behavioral and physiological stress responses is complex and dependent on age and developmental phase, type of stressor, and the state the child is in. Given that physiological stress responses play an important role in normal and deviant forms of adaptation, it is important to establish what determines individual differences in reactivity. Animal research has shown that prenatal and early postnatal stress results in long-term changes in the regulation of the offspring’s stress hormonal (HPA) axis (Francis, Diorio, Plotsky, & Meaney, 2002; Francis, Szegda, Campbell, Martin, & Insel, 2003). Thus, it can be assumed that individual differences in maternal hormones and emotions can have a significant impact on fetal neural development and, specifically, that the amount of prenatal stress the mother experiences has a programming effect on the reactivity of the child’s HPA axis (Anisman, Zaharia, Meaney, & Merali, 1998). In humans, prospective research examining the in-

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fluence of prenatal stress on the HPA axis of mother and fetus, and later HPA axis functioning and development in the child, is virtually absent (but see Susman et al., 2001). At present it is therefore unclear how prenatal and early postnatal stress in the mother affect the infant’s HPA axis and temperament. Following birth, maternal hormone concentrations and emotions can still contribute to the development of the infant’s temperament as mediated by the quality, quantity, and regularity of maternal interactions. The postpartum period is for many women a time of intense emotions attributable to the dramatic psychological and role-requirement changes that accompany the transition into motherhood. New mothers have to assume responsibility for a helpless infant, often without adequate preparation. If these challenging roles and responsibilities occur in a family context without adequate social or economic support, negative effects on the mothers and their children may well occur. Postpartum maternal emotions are in many women characterized by dysphoria or other depressive symptoms, and the rapid decrease in gonadal and adrenal hormone concentrations in this period is likely to be a contributing factor. It has been found that children of affectively ill mothers have earlier and significantly more depressive and disruptive behavior problems, and it is likely that a suboptimal mother–child relationship plays an important role in this effect (Susman et al., 2001). On the basis of the substantial literature on animals, one can expect maternal stress and alterations in human prenatal hormones to affect fetal development and later infant behavior. For example, one can hypothesize that infants born from pregnancies with elevated levels of prenatal and/or postnatal stress will have a more reactive stress system and problems with coping and adaptation, resulting in behavioral problems such as aggression.

CONCLUSIONS To avoid any misunderstanding, it is worth emphasizing that biological contributions to human behavior should not be regarded as deterministic. Rather, the hormonal environment may affect behavior by biasing the neural system in such a way as to create behavioral dispositions. It is then that environment and culture add their influence by rewarding, punishing, and/or ignoring behaviors, thereby exaggerating, diminishing, distorting, or permitting the expression of biologically based behaviors (Reinisch & Sanders, 1992). Aggression is, of course, an optional behavioral strategy: As humans, we are exquisitely sensitive to our social environment and we are usually capable of inhibiting this form of behavior, although biological factors may play a role in how easy it is for us to do so. Any consideration and reflection of the biological—in this case the hormonal—influence on aggression is controversial. On one hand, it is obvious that individual differences in aggression originate, at least partly, in differences in the biological substrate and the central nervous system. On the other

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hand, we find it hard to accept that these differences, and the way in which they are established, may also involve specific possibilities and restrictions. In light of this debate, it is important to remember that the evidence that hormones play a role in individual differences in aggression, certainly when we focus on normal aggression, is small. Nevertheless, research on the influence of biological factors on the origin and development of behavior in humans is important, not in order to demonstrate or reject the importance of biological factors, but rather because these biological factors are part and parcel of a process of growth and development that can be influenced and disturbed in numerous ways.

NOTES 1. The Constantino et al. (1993) study provides some information about pre-adrenarchal plasma testosterone values: in one study the mean T value for 3- to 5-year-olds was found to be 6.0 ± 2.0 ng/dl; the mean T value for 6- to 8-year-olds was 8.0 ± 2.8 ng/dl (data published by Forest, 1989); in another study by Lashansky, Saenger, & Fishman (1991) a mean T value for 1- to 5year-olds of 1.98 ± 0.85 ng/dl and a mean T value for 6- to 12-year-olds of 6.8 ± 6.0 ng/dl was observed. Data from our own study on testosterone in 8- to 12-year-old boys found a mean T value of 0.86 ± 1.5 nmol/l (range = 0.1–6.8), with a mean T value of 0.2 nmol/l in 8-year-old boys (Van Goozen, Matthys, Cohen-Kettenis, Thijssen, & Van Engeland, 1998b). With respect to saliva, Scerbo and Kolko (1994) found a mean T level of 0.037 ng/ml in those younger than 9 years old (n = 6), and a mean T level of 0.057 ng/ml in those between 9 and 14 years old (n = 34). Clearly, T values in prepubertal children are low, and reliable norms for serum and saliva androgen levels are needed. 2. Testosterone can be reliably detected in saliva using immunoassay in boys and girls ages 8 and older (Granger, Schwartz, Booth, & Arentz, 1999). It is therefore unclear how seriously one should regard the testosterone values and findings in the study published by Sánchez-Martín et al. (2000). 3. It is beyond the scope of this chapter to discuss in any detail the possibility that the influence of testosterone on aggression could be largely non-neural and indirect, and work primarily through its effects on the body (increased physical size, muscle mass, and appearance of secondary sex characteristics) and activity. For example, Mazur and Booth (1998) conclude that testosterone affects adolescent behavior mostly through indirect social responses elicited by maturation rather than through direct activation of target receptors in organs or the nervous system. Similarly, the activity differences between girls and boys seem to be associated with play and toy preferences that are at least partly influenced by testosterone (Hines et al., 2002), leading to sex segregation and to different socialization experiences in girls and boys.

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DETERMINANTS Executive Function OF in Aggression AGGRESSION

15 Executive Function in Early Physical Aggression J EAN R ICHARD S ÉGUIN and P HILIP D AVID Z ELAZO

Physical aggression is characteristic of early childhood but typically becomes less frequent with development (Tremblay et al., 1996). During this same period of their development, there are marked age-related increases in children’s executive function (Zelazo & Müller, 2002). Executive function generally refers to the self-regulation of thought, action, and emotion—processes that depend on the integrity of neural systems involving prefrontal cortex (e.g. Owen et al., 1999; Robbins, 1996; Stuss, 1992). We propose that this pattern of declining aggression and increasing executive function reflects the fact that, during development, children typically acquire the executive function skills needed to regulate physical aggression. Moreover, we propose that in those cases (about 4–6% of the population) where children’s levels of physical aggression remain high (Nagin & Tremblay, 1999; Tremblay et al., 2004), the development of executive function will be atypical. The literature is replete with studies that have examined the relation between global cognitive measures and global indices of antisocial or externalizing behavior problems. To date, however, very few studies have tested the specific hypothesis that executive function development is particularly relevant to the regulation of physical aggression. Executive function is a specific aspect of cognitive function that is rarely captured by global measures. Similarly, physical aggression is a specific aspect of aggression that may not be captured by externalizing behavior problems or global scales of aggression, disruptiveness, antisocial behavior, or delinquency. Thus, a test of the hypoth307

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esis requires taking into account (1) that executive function is a specific subset of more global cognitive abilities and (2) that physical aggression is a specific behavior within externalizing, aggressive, disruptive, antisocial behavior problems or delinquency.

PHYSICAL AGGRESSION AMONG GLOBAL MEASURES OF BEHAVIOR PROBLEMS Physical aggression can be found in the form of hitting, kicking, biting, assaults, confrontation with a weapon, getting involved in fights, threatening to use physical force, rape, and homicide. Physical aggression is also studied indirectly, via its relation to various externalizing disorders, and we now know from retrospective and longitudinal studies that externalizing disorders begin a chronic course in early childhood (Tremblay et al., 1999). Physically aggressive behavior is found in conduct disorder (CD), and it is related to, but not a diagnostic feature of, attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD). ADHD itself can be subdivided into a subtype in which attention deficits predominate and another subtype characterized by hyperactive and impulsive behavior (Milich, Balentine, & Lynam, 2001). Within ADHD, it is the hyperactive–impulsive subtype that is more strongly associated with ODD and CD (Willcutt, Pennington, Chhabildas, Friedman, & Alexander, 1999), and possibly with physical aggression, although early ADHD behavior problems are not typically related to later violence (Farrington & Loeber, 2000; Lahey, Loeber, Burke, Rathouz, & McBurnett, 2002; Loeber, Burke, & Lahey, 2002; Nagin & Tremblay, 1999; Stouthamer-Loeber, Loeber, Wei, Farrington, & Wikström, 2002). CD, ADHD, and ODD co-occur at a greater than chance level, and this has been a growing source of concern in understanding the development of externalizing disorders (Lilienfeld, 2003). In a longitudinal study of a community sample of more than 1,000 boys from low-socioeconomic-status (SES) schools (Séguin, Boulerice, Harden, Tremblay, & Pihl, 1999), close to 90% of adolescents who met criteria for ADHD or CD between the ages of 14 and 16 were found to have had a history of occasional or chronic physically aggressive behavior (based on teacher ratings of physical aggression between the ages of 6 and 12 years). This is in contrast to 61% of boys without such a diagnosis. It should be noted, however, that although a history of physical aggression during childhood is relatively common in most adolescents with ADHD or CD, only about a quarter of boys with a history of physical aggression meet the criteria for ADHD or CD (Séguin et al., 1999). Finally, besides externalizing disorders, physical aggression is also found among other global categories such as “disruptive disorders,” in children defined as “hard to manage,” among “antisocial disorders,” and in “delinquency” and “criminality.”

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Developmental Course of Physical Aggression Research on the developmental course of physical aggression per se suggests (Robins, 1991) that the frequency of physical aggression actually peaks at around 2 years of age (See Tremblay & Nagin, Chapter 5, this volume). Most children who begin with high levels of physical aggression gradually desist at various rates. However, there is a small but significant proportion of children (about 4–6%) for whom frequencies of physical aggression remain very high throughout childhood and adolescence (Broidy et al., 2003). We propose that these children will display early impairments in executive function.

EXECUTIVE FUNCTION AND ITS DEVELOPMENT Executive function is a popular topic in contemporary research, but definitions of executive function differ widely. A traditional approach is to treat executive function as a higher order cognitive mechanism or ability, as when Denckla and Reiss (1997) suggest that “executive function refers to a cognitive module consisting of effector output elements involving inhibition, working memory, and organizational strategies necessary to prepare a response” (p. 283, emphasis in original). Unfortunately, this approach (see also Baddeley & Della Sala, 1996; Norman & Shallice, 1986) essentially invokes a homunculus, or little man in the head, rather than explaining in detail how executive function, including inhibition, working memory, and strategy use, is accomplished (Parkin, 1998; Zelazo & Müller, 2002). An alternative and more common approach is more empirically driven. This approach involves devising comprehensive neuropsychological batteries and using factor analysis to reveal the underlying structure of executive function (see Zelazo & Müller, 2002, for a review). Such studies generally reveal three or four factors—a result that has been taken to suggest that there are dissociable dimensions of executive function, consistent with efforts to “fractionate” executive function based on lesion studies in nonhuman animals (Robbins, 1996). Although the results of factor-analytic studies are potentially misleading, because providing labels for factors may give the erroneous impression that researchers actually understand the cognitive processes underlying performance on various tasks, this approach does suggest that there are both common and diverse aspects of the measures that have been used to assess executive function (Miyake et al., 2000). Research on executive function has demonstrated that executive function first emerges early in development, probably around the end of the first year of life, and it develops across a wide range of ages, with important changes occurring between about 2 and 5 years of age. Adult-level performance on many standard tests of executive function is reached at about 12 years of age, and performance on some measures continues to change into adulthood (see

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Zelazo & Müller, 2002, for review). One of the most widely studied examples of executive function in infants is performance on the A-not-B task. In this task, an infant watches as an object is hidden at one location (A). Following a brief delay (e.g., 3 seconds), the infant is permitted to search for the object. After a number of A trials, the object is then hidden conspicuously at a different location (B). Despite witnessing the hiding event at B, most 9-month-olds continue to search perseveratively at A on the first B trial, thereby committing the A-not-B error (for a recent meta-analysis, see Marcovitch & Zelazo, 1999). However, by about 12 months of age, most infants search flexibly on this task. The changes occurring between about 2 and 5 years have been carefully documented using a variety of measures of rule use. The ability to use a rule systematically to control behavior seems to be acquired at about 2.5 years of age. However, children at this age are highly susceptible to perseverative responding, and it is not until 3 years that most children are able to use two rules simultaneously (Luria, 1973; Zelazo, Frye, & Rapus, 1996a; Zelazo & Reznick, 1991). Then, although 3-year-olds can use a pair of rules, it not until about 5 years that most children can switch flexibly between two incompatible pairs of rules, or two different perspectives on a situation, as seen in tasks used in assessing causal reasoning (e.g., Frye, Zelazo, Brooks, & Samuels, 1996; Zelazo, Reznick, & Piñon, 1995), behavioral prediction (Zelazo, Helwig, & Lau, 1996b), card sorting (e.g., Zelazo et al., 1996a), and understanding false beliefs (see Wellman, Cross, & Watson, 2001, for a meta-analysis). The Wisconsin Card Sorting Test (WCST) has frequently been used to explore the development of executive function beyond about 5 years of age. In the WCST (Grant & Berg, 1948; Robinson, Heaton, Lehman, & Stilson, 1980), participants are presented with four target cards that differ on three dimensions (number, color, and shape) and asked to sort a series of test cards that match different target cards on different dimensions. Participants must discover the sorting rule by trial and error, and after a certain number of consecutive correct responses, the sorting rule is changed. In a representative study, Chelune and Baer (1986) documented a linear increase in performance on the WCST between the ages of 6 and 10 years, with 6-year-olds performing at the level of patients with prefrontal cortical damage (e.g., Milner, 1963) and 10-year-olds performing like healthy adults. This pattern was obtained for the three variables assessed: number of perseverative errors, number of categories achieved, and failures to maintain set.

THE RELATION OF EXECUTIVE FUNCTION TO EXTERNALIZING OR ANTISOCIAL DISORDERS Most research on the relation between executive function and physical aggression has relied on relatively global measures of both executive function and aggression. In most cases, the measures of executive function correspond to

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standard neuropsychological tests that are either taken directly from the adult literature or adapted from adult tasks. For example, several studies have used the WCST. The WCST taps numerous aspects of executive function, and, as a result, the origin of errors on this task is difficult to determine (e.g., see Delis, Squire, Bihrle, & Massman, 1992). To perform correctly on the WCST, one must first construct a representation of the problem space, which includes identifying the relevant dimensions. Then, one must choose a promising plan—for example, sorting according to shape. After selecting a plan, one must (1) keep the plan in mind long enough for it to guide one’s thought or action and (2) actually carry out the prescribed behavior. Keeping a plan in mind to control behavior is referred to as intending; translating a plan into action is rule use. Finally, after acting, one must evaluate one’s behavior, which includes both error detection and error correction. Inflexibility can occur at each phase, so there are several possible explanations of perseverative performance on the WCST—and on global executive function tasks more generally. For example, perseveration can occur after a rule change in the WCST either because a new plan was not formed (one type of representational inflexibility; Zelazo et al., 1995) or because the plan was formed but not carried out (an example of lack of response control; Zelazo et al., 1995). Nonetheless, research using the WCST has proven useful in documenting that executive function is diminished in groups of children who are likely high in physical aggression. Indeed, relatively high levels of perseveration on the WCST have been documented in individuals with antisocial behavior (Kandel & Freed, 1989), in children with externalizing behavior problems (Matson & Fisher, 1991), in children with ADHD (Pennington, 1997), and in adolescents with CD (Toupin, Déry, Pauzé, Mercier, & Fortin, 2000). Performance on the WCST was also related to childhood social abilities (Bonino & Cattelino, 1999). Perseveration on other card-playing tasks that also involve error detection and correction has also been shown in adult psychopathic populations (Newman & Wallace, 1993) and in our work on adolescents with a welldocumented history of physical aggression (Séguin, Arseneault, Boulerice, Harden, & Tremblay, 2002). Several studies along these lines have shown that poor executive function is involved in ADHD and antisocial disorders. These have recently been reviewed, respectively, by Pennington and Ozonoff (1996) and Morgan and Lilienfeld (2000). This latter review covered studies published between 1942 and 1997 for ages 13–40 years and revealed a medium-sized effect (mean standard difference) of about 0.6 in comparing antisocial and nonantisocial groups. Unfortunately, however, the review could not focus on violent antisociality because most studies lacked information about violence. This is indeed a serious problem in the field (Tremblay, 2000). Further, Morgan and Lilienfeld (2000) and Pennington and Ozonoff (1996) point out that the studies they reviewed have typically not taken into account the comorbidity between ADHD and antisocial disorders such as CD. A third recent review further examined problems associated with tests for the specificity of executive

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function to the three externalizing disorders, and to Tourette’s syndrome and high-functioning autism (Sergeant, Geurts, & Oosterlaan, 2002). The problem of examining physical aggression per se (instead of antisocial disorders or CD/ODD) has been addressed, however, in several recent studies that have supported the hypothesis that executive function problems are related to physical aggression when observable physical aggression was entered into statistical models even after controlling for ADHD (see Giancola, Mezzich, & Tarter, 1998; Séguin et al., 1999; Toupin et al., 2000). The failure to take into account physical aggression and hyperactivity at the outset has typically resulted in a weaker assessment of one or the other behavior problem. In our earlier work we found that boys from a community sample with a history of physical aggression performed most poorly on tests of executive function even after controlling for verbal and spatial abilities as well as cerebral dominance (Séguin, Pihl, Harden, Tremblay, & Boulerice, 1995). In that study and others that followed, the core executive function tasks were derived from the neuropsychological literature and had been validated with brain imaging techniques. The Self-Ordered Pointing task and a number randomization task involved primarily rule use, and Conditional Association tasks also involved error detection and correction in addition to rule use (Petrides, Alivisatos, Evans, & Meyer, 1993a; Petrides, Alivisatos, Meyer, & Evans, 1993b). In addressing a question raised by Pennington and Ozonoff (1996) about that study, we further controlled for chronic ADHD. We also added a control for IQ and still found poor executive function in the physically aggressive boys (Séguin et al., 1999). Moreover, in an attempt to understand more fully the relation between executive function and physical aggression and hyperactivity, we selected study participants based on the histories of both behavior problems. We chose to use the narrow-band behavior of hyperactivity instead of the broader-band construct of ADHD because hyperactivity was found to attenuate the relation between physical aggression and card perseveration (Séguin et al., 2002), although ADHD, as a whole, was not related to executive function in our previous study (see Séguin et al., 1999). Using this methodology also allowed testing for additive and interactive effects of physical aggression and hyperactivity on cognitive function in general and executive function in particular (Waschbusch, 2002). We did not find an interaction, but did find clear additive effects of both behavior problems on executive function, although the effects were clearer for physical aggression than they were for hyperactivity (Séguin, Nagin, Assaad, & Tremblay, 2004).

THE RELATION OF PHYSICAL AGGRESSION AND EXECUTIVE FUNCTION IN EARLY CHILDHOOD Given that, for most children, the decline in physical aggression occurs between ages 24 and 60 months (see Tremblay & Nagin, Chapter 5, this volume) and that this period is marked by major changes in executive function, it

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seems especially important to examine the relation between aggression and executive function during the preschool years. Early identification of potential problems also has implications for the success of any interventions, because early childhood may be a period of relative plasticity and it may be easier to alter behavior before it becomes entrenched. Studies of this relation in preschoolers have addressed a broad range of relevant issues. Some studies focused more specifically on the relation between early hyperactivity and aspects of cognitive function relevant to, but not isomorphic with, executive function. For example, one community study found that three-quarters of the 2% of children who had hyperactivity problems and were “very hard to manage” in preschool still had problems at age 15 (McGee, Partridge, Williams, & Silva, 1991). They were worse off as adolescents on both behavioral and cognitive measures than preschoolers who were only “very hard to manage” (3% of that sample) and developmental control children (95% of that sample). However, it is not clear whether early poor cognitive abilities contributed to the maintenance of the behavior problems. Other studies of preschool hyperactivity have also failed to take into account concurrent conduct problems, let alone physical aggression. Such was the case in one study of hyperactive preschoolers from the community (vs. the clinic) who were found to have deficits in executive function (Mariani & Barkley, 1997).

Studies Using Global Measures of Cognition Only a handful or so of studies have examined more directly the relation between preschool cognitive function and behavior problems not restricted to hyperactivity. For example, poor intelligence assessed by the McCarthy Scales (McCarthy, 1970) was related to mother-rated Child Behavior Check List (CBCL; Achenbach, Edelbrock, & Howell, 1987) psychopathology indices in preschoolers recruited from pediatricians’ practices (Dietz, Lavigne, Arend, & Rosenbaum, 1997). However, because performance on the McCarthy Scales was related to internalizing as well as externalizing problems and because the McCarthy score was taken either as a whole or only broken down into verbal and performance IQ, the study does not provide information about the specificity of behavior problems in relation to cognitive function. Another longitudinal study with assessments at about 55 and 80 months of age found that preschool IQ was related to CBCL teacher ratings of externalizing problems at follow-up and that preschool expressive language abilities were related to CBCL maternal ratings of externalizing problems at follow-up (Heller, Baker, Henker, & Hinshaw, 1996). However, these associations were accounted for by maternal education and socioeconomic status. This again suggests that parental characteristics may influence both cognitive development and externalizing problems, but it is not clear that this poor cognitive development represents an incremental risk factor beyond parenting effects, because interactions with cognitive abilities were not tested. Interestingly, preschool ratings of

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externalizing behavior problems did not attenuate first-grade IQ and language abilities over and above the variance explained by preschool cognitive abilities. Although preschool language abilities predicted stability and pervasiveness of externalizing disorder across assessments, this was not the case for IQ. Another prospective longitudinal study failed to support Moffitt’s (1993) hypothesis that adolescents with early-onset/persistent conduct problems would show early neuropsychological deficits (Aguilar, Sroufe, Egeland, & Carlson, 2000). Based on CBCL externalizing scores, the authors contrasted four groups (i.e., never antisocial, child-limited, adolescent-limited, and early onset/persistent) in a one-factor (group) design instead of a 2 × 2, child by adolescent, factorial design. Adolescent scores differentiated the adolescentonset and early-onset/persistent groups, as in Moffitt’s earlier work (see Moffitt, 1990; Moffitt & Henry, 1989; Moffitt & Silva, 1988b; Moffitt & Silva, 1988a), but the effect seems to be the result of having had behavior problems as a child, because those children who recovered from behavior problems (i.e. child-limited) appear to have performed as poorly as those that did not (i.e. early-onset/persistent). Nonetheless, early cognitive scores were associated with later ones, but stability of cognitive performance was not used to identify those children who performed poorly in childhood and adolescence. Despite the many merits of that study, its test of Moffitt’s hypothesis may be severely limited. First, most children in that sample were at high risk for behavior problems. Second, about a third of the sample was assigned to the early-onset/persistent category, when we would expect about 4% of chronic cases in normative samples (Broidy et al., 2003). Third, the study included a roughly equal number of males and females, yet trajectories of early-onset problems do not predict the same maladaptive outcomes in males and females (Broidy et al., 2003; see also Archer & Côté, Chapter 20, this volume). Fourth, Moffitt suggested that the presence of aggression and hyperactivity should be used as a criterion for early onset, and it is not clear that this is the case here. Finally, there were no tests of executive function. Raine and colleagues (Raine, Yaralian, Reynolds, Venables, & Mednick, 2002) have proposed a different cognitive interpretation of persistent antisocial behavior. Their early-starter spatial impairment model of antisocial behavior suggests that early visuospatial (right hemisphere) impairments can predispose a child to persistent antisocial behavior by interfering with early attachment via emotion recognition and regulation. The model is admittedly speculative, but is reasonably well based on a series of community studies, including a longitudinal study of children from ages 3–17 years. Unlike most studies reviewed so far, this study included stability of behavior as an important design feature. As in the Aguilar et al. (2000) study, four groups were formed, based on whether children were above or below the top 33rd percentile of an antisocial behavior problem index at ages 8 and 17 years: a comparison group, a child-limited group, an adolescence-onset group, and a persistent group. Results show that spatial abilities at age 3 years were poorest in the

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persistent group, and that this effect appeared to be stronger than the effects of groups on verbal deficits. This effect was robust to statistical control for level of hyperactivity and test motivation at age 3 years. However, by the time the children reached age 11 years, spatial and verbal deficits were equally impaired in this group and social adversity attenuated considerably the group effect on spatial deficits. There appears to be a loss of specificity of spatial deficits over time; the persistent children now seemed generally impaired. Although a spatial deficit hypothesis was formulated, it is difficult to argue that the tasks that formed that spatial index (which represents essentially performance IQ tasks) were not contaminated by several other abilities. The problem of task purity is found everywhere in this type of research, and, unfortunately, tasks that more explicitly and specifically involve executive function were not administered in that study. A close examination of the battery does not suggest that any tasks could have been construed in terms of executive function either. Although the Wisconsin Intelligence Scale for Children (WISC) Mazes subtest, which involves some degree of planning, was administered, individual subtest scores were not available. Further, physical aggression was not examined. Thus, the question of the specific relevance of preschool executive function to the concurrent or later regulation of physical aggression remains unanswered.

Studies Using Specific Measures of Executive Function in Community Samples Moving more closely toward the concept of executive function, “disruptiveness” in preschoolers, aged about 4½ years, was found to be negatively associated with verbal and visuospatial abilities (Cole, Usher, & Cargo, 1993). “Executive function” was related to another measure of behavioral control (i.e., following the rule not to play with a forbidden but attractive object) but not to disruptiveness. In that study verbal and visuospatial abilities were assessed with the McCarthy Scales (Kaufman & Kaufman, 1977; McCarthy, 1970), as well as with the Florida Kindergarten Screening Battery (Satz & Fletcher, 1982), which includes the Beery Visual-Motor integration test (Beery, 1982) and the Peabody Picture Vocabulary Test (Dunn & Dunn, 1981). The executive function composite was made up of a tapping test (Becker, Isaac, & Hynd, 1987), a rapid-alternating-stimulus-naming test (Wolf, 1986), a hand movement test (Kaufman, 1983), a block sort (based on the WCST; Heaton, 1981), and a visual search test (adapted from Plude & Doussard-Roosevelt, 1989). All five tests loaded onto one principal component accounting for 42% of the variance, but the sum of scale scores was used instead of the principal component score. Individual scores correlated significantly with one another between r = .27 and r = .64. Cognitive risk was defined as scores below one standard deviation from the mean. Behavior was assessed with four scales. The mothers completed the CBCL (Achenbach, 1999; Achenbach & Edelbrock, 1983) and the Eyberg Child Behavior Inventory (Eyberg & Robinson,

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1983), and teachers completed the Teacher Report Form (TRF; Achenbach & Edelbrock, 1986) and the Preschool Behavior Questionnaire (Behar & Stringfield, 1974). In regard to behavior, three risk levels had been identified in this study on the basis of combined informants and scale scores (i.e., low < 1 SD below mean for all informants, high > 1 SD above mean according to at least one informant or T score > 70 on CBCL total score or > 85th percentile on the TRF, and moderate for the rest of the sample). We note that these criteria for behavior risk definition were very liberal and may have increased the chance for false positive identification of risk. Analyses contrasted a combination of the two high groups (moderate and high) with the low-risk group. Therefore, we do not know the relative positions of performance scores between the three groups. It was also clear that the “high” group was elevated not only in disruptive behavior but also in other behavior problems, which may limit further the specificity of the finding to disruptive behavior. Another study also referring explicitly to the concept of executive function found that “hard-to-manage” children performed more poorly than control children not only on executive function tasks, but also on theory of mind and emotion understanding tasks (Hughes, Dunn, & White, 1998). Interestingly, the relation between number of successful executive function tasks and behavior problems was partly accounted for by the introduction of socioeconomic status and verbal abilities to the model, although the executive function battery was explicitly designed to require minimal verbal abilities. In that study, executive function was measured with six tasks, and the authors were guided by a model of executive function put forward by Welsh, Pennington, and Groisser (1991). This model emphasized three components: working memory and planning (measured with the Tower of London task ([Shallice, 1982] and a “noisy book” auditory sequencing task [Hughes, 1998]), inhibition of maladaptive prepotent responses (measured with Luria’s hand game [Hughes, 1998] and a “detour-reaching box” [Hughes & Russell, 1993]), and self-monitoring/attentional flexibility (measured with a pattern reproduction task [Frith, 1971] and a card sort [Hughes, 1998] similar to the WCST). All test scores were converted to success/failure scores following Hughes (1998), and significant differences were observed on four of the six tasks, excluding the “noisy book” and card sort tasks. In the first of two follow-up studies with these same children, poor executive function and poor language ability were both related to violent fantasy (Dunn & Hughes, 2000). A second follow-up study of these “hard-to-manage” children involved playing with a teacher-nominated best friend in a room with an attractive toy (Hughes, White, Sharpen, & Dunn, 2000). Scores on the “detour-reaching box” and the Tower of London tasks, seen as the two tasks most sensitive to antisocial behavior by Hughes et al. (1998), were used to estimate executive function. Although the “hard-to-manage” children did not display more verbal aggression relative to the control group, they snatched toys, teased, bullied, broke rules or the other child’s toy, hurt the other child, and engaged in sex play (i.e., with a doll, themselves, or the other child in the room) more often. Verbal

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abilities were negatively related to hurting the other child (an observational index of physical aggression) within the “hard-to-manage” group. The executive function scores were associated with frequency of observed antisocial behavior in this group even after controlling for verbal abilities and maternal education, but this was not the case for theory of mind scores. This latter study suggests that executive function problems, as opposed to verbal abilities or theory of mind, may be specifically related to antisocial behavior in children observed in the laboratory. However, this study does not focus on physical aggression in the analyses involving executive function nor does it take into account the potential behavior problems of the teacher-nominated best friend. Thus, it is not clear whether antisocial peers, which are more likely to associate with one another, have contributed to the escalation of behavior problems in the “hard-to-manage” group. Peer dynamics is a different but relevant issue (see Boivin, Vitaro, & Poulin, Chapter 18, this volume).

Studies Using Specific Measures of Executive Function in Clinic Samples Most of the preschool studies reviewed so far have focused on community samples. One study examined clinic-referred preschool boys (ages 47–68 months) with ODD and ADHD, an ODD group without ADHD, and a matched nonclinic control group (Speltz, DeKlyen, Calderon, Greenberg, & Fisher, 1999). In addition to being referred and having a primary DSM-III-R (American Psychiatric Association, 1987) diagnosis of ODD, these children also had a T score > 65 on the CBCL aggression scale. Executive function was operationalized with two measures, one of motor planning (adapted from the Luria–Nebraska Battery for Adults) and the other of verbal fluency (taken from the McCarthy Scales). Verbal abilities were measured with the Expressive One Word Picture Vocabulary Test—Revised (Gardner, 1990), the Peabody Picture Vocabulary Test (Dunn & Dunn, 1981), the Wechsler Preschool and Primary Scales of Intelligence—Revised (WPPSI-R; Wechsler, 1989) arithmetic and comprehension subtests, a Test of Early Reading Ability, and a test of vocabulary for affective states. Visual–motor abilities were measured with the Beery Visual-Motor Integration Test (Beery, 1982) and the WPPSI-R block design and picture completion subtests. Although confirmatory factor analyses showed that this dimensional grouping of variables was appropriate, test scores were summed within dimension and reliabilities were ranging from poor to moderate, that is, from .41 for executive function, .52 for visual– motor, and .68 for verbal abilities. Clinic-referred boys combined did more poorly on all dimensions and on test behavior in univariate analyses. However, contrary to the authors’ hypothesis, the effect for executive function was accounted for by test behavior (even after removing test inattention and persistence) and by verbal abilities. However, when breaking down the clinicreferred group into its subtypes, univariate comparison of the groups with ODD-ADHD and ODD-only revealed poorer verbal (about 0.4 mean standard difference) and executive function abilities (about 0.6 mean standard dif-

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ference, a moderate effect size) in the comorbid group. Although it was not tested for significance, the ODD-only and comparison groups differed by about 0.5 SD in verbal abilities and 0.4 SD on executive function. Further, the contrast for executive function was not controlled for performance in verbal abilities. In the absence of an ADHD-only group, support for a specific relation of ODD-ADHD to poor executive function remains elusive. In a second follow-up study, these same clinic-referred boys also generated more aggressive solutions to social information–processing vignettes than nonclinic boys, independently from ADHD (Coy, Speltz, DeKlyen, & Jones, 2001). However, verbal abilities at age 57 months, which were then worse in clinic-referred boys, were no longer associated with clinic status at age 82 months. Unfortunately, executive function at age 57 months was not used as a predictor of later cognitive abilities or behavior in this follow-up study. Interestingly, and surprisingly, several physically aggressive behaviors (e.g. occasional shoving or hitting, or hitting of parent or sibling during a tantrum) were explicitly discounted for establishing the diagnosis of CD in that study so that the diagnosis would emphasize deliberate confrontation. If most expressions of aggression are reactive instead of proactive, and poor executive function is more likely to be associated with reactive aggression (Giancola, Moss, Martin, Kirisci, & Tarter, 1996), then these studies may be missing important opportunities to understand the cognitive underpinnings of CD. (See Vitaro & Brendgen, Chapter 9, this volume, for a more detailed discussion of reactive and proactive aggression.) Further, despite the longitudinal design of the second study, we do not know anything about the stability of problems across the three measurement times. The longitudinal study did not examine whether the children with comorbid ODD-ADHD at time 1 were more likely to have an externalizing disorder at time 3. The effects of having been referred and presumably being under professional care are also unknown.

THE UTILITY OF A PROBLEM-SOLVING FRAMEWORK FOR UNDERSTANDING AGGRESSION We have already emphasized the need for greater specificity of behavior problems that are the object of study instead of broad-band categories such as delinquency, externalizing disorders, or even CD. We also suggest that measurements across time may be more powerful in determining children at highest risk for later violence. This concept is becoming the standard, as many of the studies reviewed thus far indicate. Similar methodological features need to be systematically implemented for the study of cognitive aspects involved in the behavior problems of interest. In their empirical review, Pennington and Ozonoff (1996) point to difficulties (1) in isolating components of executive function and (2) in considering also the many factors that may disrupt executive function performance on traditional tasks. Because executive function appears to be more strongly and specifically involved in physical aggression

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than does general cognitive development, indexed, for example, by IQ tests, at least in adolescence and young adulthood, we propose that executive function in preschoolers be examined from a functional perspective according to a problem-solving framework. This approach, which follows Luria (e.g., 1973), views executive function as a functional construct that makes reference to (but cannot be equated with) the psychological processes involved in self-regulated, goal-directed problem solving (Zelazo, Carter, Reznick, & Frye, 1997). Like all functions, executive function is defined solely in terms of what it accomplishes—not the mechanisms that accomplish the function. From this perspective, the various subfunctions of problem solving, from initially representing a problem, planning a strategy, executing the plan, to eventually evaluating the adequacy of an attempted solution, can all be seen as contributing to the function of goaldirected problem solving. For example, when searching for a hidden toy, children need to represent the problem, select a plan for action, actually execute the plan, and then evaluate the outcome. Treating executive function as a functional construct does not explain executive function (it remains something to be explained), but it does lay the groundwork for an explanation by facilitating the formulation of specific hypotheses regarding the role of basic cognitive processes (e.g., attention, memory, action monitoring) in different aspects of executive function. It also provides a framework for devising more precise measures of executive function (e.g., measures of planning that do not also require rule use). A major advantage of the problem-solving framework is that it integrates diverse executive function processes (and disparate lines of research) into a single, coherent model of components. The problem-solving framework allows one to understand executive function in a way that suggests specific executive function assessments (see Zelazo et al., 1997, for an exhaustive list) and clarifies the way in which different aspects of executive function work together to fulfill the higher-order function of problem solving while avoiding conceptualizing executive function as a homuncular ability (e.g., as a supervisory attentional system; Shallice, 1988). Further, by designing tasks in light of this framework, one can discover more precisely when performance breaks down in the process of problem solving, and this, in turn, bears on specific issues regarding the cognitive bases of unwarranted physical aggression. 1. Do some children engage in physical aggression because they fail to represent a problem adequately? For example, some children may be biased to represent certain situations as threatening because they have an underlying difficulty in attaining a more objective perspective and flexibly reinterpreting several situations more adaptively. 2. Alternatively, or in addition, some children may fail to plan or think ahead properly. They may fail to anticipate the negative consequences of a strategy that can be aggressive, for example. 3. In some cases, children may understand the rules that govern a social

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situation (e.g., “I should not hit others” or “I should be quiet during class” or “I should do as I am asked by my teacher”) but fail to use these rules much in the same way that children fail to use rules that they know on tests of rule use (Zelazo & Frye, 1998). 4. Finally, difficulties with action evaluation may contribute to inflexibility and persistence of inappropriate responding despite relevant feedback (e.g., failing to learn from negative consequences of behavior).

THE UTILITY OF DISTINGUISHING BETWEEN HOT AND COLD EXECUTIVE FUNCTION In addition to the distinctions between different phases of problem solving, one might usefully differentiate between the relatively “hot” affective aspects of executive function associated more with ventral and medial regions of prefrontal cortex and the more purely cognitive “cool” aspects associated more with dorsolateral prefrontal cortex (Zelazo & Müller, 2002). Whereas cool executive function is more likely to be elicited by relatively abstract, decontextualized problems, hot executive function is required for problems that involve the regulation of affect and motivation (i.e., regulation of basic limbic system functions). This characterization of hot executive function in contradistinction to cool executive function is consistent with several recent proposals regarding the function of orbitofrontal cortex (e.g., Damasio, 1994; Rolls, 1999). For example, based on single-cell recordings of neurons in orbitofrontal cortex together with neuroimaging data and evidence that damage to orbitofrontal cortex impairs performance on simple tests of object reversal and extinction, Rolls (e.g., 1999) suggests that orbitofrontal cortex is required for the flexible representation of the reinforcement value of stimuli. Damasio proposed a rather different theory, the somatic marker theory (e.g., 1994). According to this theory, orbitofrontal cortex is required for processing learned associations between affective reactions and specific scenarios, and this processing plays a crucial but often overlooked role in decision making. Despite their differences, however, both approaches capture the fact that the control of thought and the control of action depend on different cortical systems, depending on whether or not such control occurs in motivationally significant contexts. Although a strict orbitofrontal cortex account of antisocial behavior, and particularly physical aggression, is questionable (Séguin, 2004), the relevance of hot executive function is not. Traditionally, research on executive function in human beings has focused almost exclusively on cool executive function, using measures such as the WCST. Recently, however, there has been growing interest in hot executive function. The hot aspect of executive function appears to be involved, for example, in theory of mind (Zelazo & Müller, 2002), delay of gratification (Mischel, Shoda, & Rodriguez, 1989), and affective decision making (Damasio, 1994). An experimental approach to hot executive function using tasks such as delay of gratification or the children’s gambling task (Kerr & Zelazo, 2004)

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might reveal that hot executive function may also play an important role in regulating physical aggression. However, an approach that integrates hot and cool executive function is likely to be most informative. As shown earlier, cool executive function was related to behavioral control—that is, following the rule not to play with a forbidden but attractive object (Cole et al., 1993). The toy’s attractiveness invokes hot executive function, but it seems likely that children regulate their behavior in this type of situation in part by translating the problem into a more cool, decontextualized problem (Mischel et al., 1989). We also found that boys with a history of physical aggression played more cards associated with rewards and punishments than nonaggressive boys even after controlling for cool executive function (in this case working memory; Séguin et al., 2002). Whereas one group of stable aggressive boys did so perhaps because of an underlying attentional problem, card perseveration was related to emotional regulation (in this case neuroticism) in a group of unstable aggressive boys. Individuals high in neuroticism are more likely to be responsive to the hot or motivationally significant aspects of task demands, which increases their likelihood of dysregulated behavior.

CONCLUDING COMMENTS Implicit in the problem-solving framework is the idea that deficits in physically aggressive preschoolers are not necessarily global, although they may be for a subset of children. Much research in childhood and adolescence has attempted to specify the nature of the cognitive deficit in physical aggression (e.g., Séguin et al., 1999; Séguin et al., 1995) and hyperactivity (e.g., Pennington, Bennetto, McAleer, & Roberts, 1996). As this review shows, only a handful of studies of preschoolers have attempted to break down cognition into subcomponents (e.g., Raine et al., 2002) and isolate executive function deficits from more global deficits (e.g., Cole et al., 1993; Dunn & Hughes, 2000; Hughes et al., 1998; Speltz et al., 1999). Still, many of the poor executive function abilities identified in physical aggression (i.e., working memory; Giancola, 1995; Séguin et al., 1995) and in hyperactivity (i.e., planning, inhibition; Pennington & Ozonoff, 1996) can be reformulated in terms of the problem-solving framework. For example, much research on child aggression (not specifically physical) has focused on the way in which children represent problems. This research emphasizes distortions, biases, beliefs, and schemas (Huesmann, 1997), such as those that are the object of cognitive therapies (Lochman, Magee, & Pardini, 2003) and that often fall under the label of social information processing (Pardini, Lochman, & Frick, 2003). In their formulation of an information-processing model, Crick and Dodge (1994) emphasized four stages: encoding, attribution, problem solving, and response evaluation. This model is strongly based on distortions and biases that predispose an individual to automatically construe problems in preconceived ways. Yet there are deficit models that emphasize more fundamental processing diffi-

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culties (Séguin et al., 1995; Wallace & Newman, 1997), which could be more directly based in brain anatomy or physiology but still interact with individual motivational predispositions and which may be influenced greatly by early experience (Mezzacappa, Kindlon, & Earls, 2001). Thus the problem-solving framework suggests that a child’s inability to take another person’s perspective in a relatively cool task (underlying deficit) is unlikely to change a more emotional bias. Conversely, the child who can show flexibility on a relatively cool task (no underlying deficit) is more likely to be able to change perspective on a problem that is laden with affective tone and for which that child shows a maladaptive response bias. Several studies have also examined family characteristics and early experiences that influence not only preschoolers’ behavior problems but also their cognitive development (e.g., Heller et al., 1996; Mezzacappa et al., 2001; Morrell & Murray, 2003; Pierrehumbert, Ramstein, Karmaniola, & Halfon, 1996). As such studies refine their measurement of executive function and behavior problems, we will not only be able to see how family characteristics affect specific as opposed to global behavior problems but will also be able to identify family characteristics that may more specifically influence the subphases of the problem-solving framework. As they become embedded in longitudinal designs, a study of the components of executive function will better inform early intervention strategies that will target families or the child at risk. In conclusion, there is growing evidence that poor executive function is involved in externalizing problems as early as the preschool years. However, the findings lack consistency largely because there is considerable variability in study objectives, and in cognitive and behavioral assessments across studies. Further, very few studies have explicitly examined preschool executive function or focused on physical aggression. However, on the basis of studies spanning childhood to adulthood, we would expect that physical aggression alone, or in combination with other externalizing problems, becomes more specifically related to poor executive function. There is thus a need for studies that explicitly chart the joint development of physical aggression, its comorbid characteristics, and executive function. Those studies would also do well to consider predisposing and maintenance factors that affect this joint development in order to better inform prevention and intervention studies.

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DETERMINANTS Language Development OF AGGRESSION and Aggressive Behavior

16 Language Development and Aggressive Behavior G INETTE D IONNE

Aggression has been associated with low language proficiency as early as the second year of life and throughout the lifespan. Although language deficits are not sufficient or necessary correlates of aggressive behavior, they have received much attention as frequently co-occurring with behavior problems (for reviews, see Beitchman, Cohen, Konstantareas, & Tannock, 1996; Cantwell & Baker, 1977, 1987; Cohen, 2001; Donahue, Cole & Hartas, 1994; Gallagher, 1999; Goodyer, 2000; Howlin & Rutter, 1987; Silva, 1987; Stevenson, 1996). This has led to a consensus around the view that the link between language and behavior is functional, not spurious. Just what this functional link is, however, remains unclear. Previous reviews of the association between language and behavior have mainly focused on the variety of behavioral and emotional correlates of language deficits in childhood. One difficulty in attempting to write a chapter specifically on aggression and language is that aggression is rarely directly assessed in developmental psychopathology. Yet aggression, possibly leading to violence and criminality, has a huge social impact. As such, it is important that we understand how it comes about, and language should not be disregarded as an associated factor. This chapter examines empirical evidence and surveys theoretical explanations of the association between language deficits and aggression. The goal is to look at the numbers, then search for the story (or, possibly, stories) behind the numbers. For the sake of brevity, it does not attend to specific syndromes in which aggression and pervasive language deficits are severely incapacitating, as in general developmental delay, pervasive developmental disorders, autism, childhood-onset schizophrenia, psychosis, or structural brain injuries. Where aggression is not assessed per se, as is the case in most studies 330

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of early development, the review is extended to include conduct disorders. Early-onset conduct disorders have been shown to be particularly characterized by the use of physical aggression (Lahey et al., 1998). Finally, more broadly defined externalizing behavior problems are also included, but with an added caution in regard to making inferences about aggression. In line with the developmental focus of this book, this chapter takes a developmental approach to the review of prevalence data from clinical, epidemiological, and longitudinal studies. As the picture unfolds from descriptive data, theoretical models of the language–aggression association are outlined, with a focus on the empirical evidence available to support these models. As this empirical evidence still remains scarce, this chapter concludes with a look at some considerations that research designs could address to take on the current challenges in understanding the functional links between language and aggression.

THE HISTORICAL PERSPECTIVE The notion that language and behavior are intrinsically linked in humans is hardly new. Although it can be traced back to ancient philosophers, the functional role of language in moral action and social order became a favorite topic of late 17th- and 18th-century philosophers such as Locke and Rousseau. By the early 20th century, the renewed interest from an empirical perspective largely stemmed from observations in clinical settings. British language and literacy specialist Samuel T. Orton concluded, in his classic 1937 essay on dyslexia and language, that communication problems led to secondary behavior and social problems. A few years later, Stella Chess (1944) echoed this view in an early paper in which she presented language disabilities as a factor in “personality distortions” in children. On another front, early Russian psychologists were speculating on possible causal processes linking language to behavior regulation. Pavlov’s (1927) concept of language as a second signaling system, on which excitatory and inhibitory processes operate to direct and control behavior, pointed to the possible role of language in the inhibition of aggressive impulses. Both Luria (1961) and Vygotsky (1962) later formalized the notion that language, spoken or as an inner process, was a necessary means to behavior regulation. Although much of this earlier work was speculative in nature, it created the basis for the next four decades of theorizing and research. In the early 1970s, Montare and Boone (1973) formulated an explicit “language–aggression hypothesis”: They proposed that language was related to physical aggression in two ways—low levels of proficiency linked to higher levels of observable aggression, and high proficiency linked to lower levels of aggression. Their empirical work on a group of children and teenagers from diverse ethnic backgrounds provided mitigated support for the hypothesis (Boone & Montare, 1976), and subsequent investigations of a specific link be-

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tween aggression and language proficiency have been few and far between (Cole, 2001; Dionne, Tremblay, Boivin, Laplante, & Pérusse, 2003; Mack & Warr-Leeper, 1992; Stattin & Klackenberg-Larsson, 1993; Piel, 1990). During this time frame, general intelligence became the focus of many studies as a correlate of delinquency and criminality, low intelligence more often characterizing violent offenders (see Moffitt, Gabrielli, Mednick, & Schulsinger, 1981). However, as Stattin and Klackenberg-Larsson (1993) point out, early language delays have been shown to be highly correlated with lower verbal and nonverbal intelligence. In this regard, they hypothesize that “the early differences between future delinquents and nondelinquents might be found in the area of language development” (p. 370). Is there support for this assertion? The next sections of this chapter look into empirical evidence of concurrent and longitudinal links between language development and aggression at different periods of development. But first, the terms and criteria used to define atypical development in both fields are addressed and the normative developmental course of language and socialized behavior is outlined to provide a background against which empirical data may be understood.

DEFINING LANGUAGE DEFICITS AND AGGRESSION To study the interface between language and behavior in psychopathology, one must be aware of the variety of terms and criteria used to define atypical development in both fields. In psycholinguistics, a deficit may permeate the whole language system or may affect specific aspects of language differentially. On one hand, general deficits are often referred to as specific language impairments (SLI)—although what is specific to SLI remains somewhat controversial—indicating language proficiency below that which is expected for an otherwise normally developing child’s IQ range. Speech and language difficulties (SLD), on the other hand, is a more general construct that refers to more or less severe nonoptimal functioning in many language-related skills. A variety of general and specific measures of language deficits are used in the prevalence studies reviewed. Basically, language skills may be affected at three different levels: production, content, and use of language. Production problems linked with speech processes such as stuttering or articulation have, for the most part, not been linked with a higher occurrence of conduct problems (Beitchman et al.,1999; Cantwell & Baker, 1987; Gualtieri, Koriath, Van Bourgondien, & Saleeby, 1983; Love & Thompson, 1988). The content and use of language however, have been linked with behavioral problems. The content of language refers to the mastery of a sufficient number of words (lexical development) and their meaning (semantic development) and of the rules that govern how they come together to form sentences and convey meaning. To understand and create these sentences, a child must master phoneme recognition, be able to segment the stream of speech to decipher basic units, and be able to memorize and use these units effectively. Deficits at this level, whether

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expressive or receptive, are more readily diagnosed because the resulting communication impairment is often obvious. In addition, they are assessed more systematically in screening procedures. Although emotional and social problems appear to be the most prevalent forms of psychopathology in children with deficits in the content of language (Cantwell & Baker, 1977), a few studies suggest that there may be long-term effects of early deficits in regard to violent behavior (Beitchman et al., 1999; Stattin & Klackenberg-Larson, 1993). Finally, use of language comprises the notions of turn taking in communication and use of contextually appropriate and socially efficient language. Deficits in the pragmatics of language, as they are called, are more readily missed because they do not audibly impair everyday communication. Yet, over time, they result in a breakdown in communication with others and unrewarding communication experiences. A few studies point to pragmatics as the prevailing language deficit in aggressive children (Cole, 2001; Mack & Warr-Leeper, 1992; Minutti, 1991). As pragmatics are often overlooked unless audible language presents some concern, it is not surprising to find that a majority of children referred to clinics for externalizing behavior problems have undiagnosed language deficits (Cohen, 2001). Aggression, on the other hand, is rarely assessed directly in most largescale studies dealing with the language–behavior interface. For one thing, aggression is not a psychiatric diagnosis, but rather a criterion associated with conduct or behavior disorder. Most large-scale studies reviewed have dealt with either psychiatric outpatient clinic populations or populations ascertained for language deficits. When behavior problems are considered, they may be labeled as conduct disorders or externalizing problems (including or excluding ADHD) in preschool and school-age children, antisocial personality, or delinquency or registered criminality in adolescents and adults. Any of these labels may or may not imply overt aggression. For instance, although 7 of 15 criteria for conduct disorder refer to overt aggression, a diagnosis of conduct disorder may be given in the absence of an aggression component. In addition, although aggression studies point to different developmental trajectories involving overt, covert, and verbal aggression as well as reactive versus proactive types of aggression, these distinctions have never been addressed in studies looking into comorbid language deficits. Inferences are thus limited with respect to specific forms of aggression. Nonetheless, the convergence or absence thereof, between studies of aggression and those looking at more general forms of externalizing behavior problems, may be of particular interest to decipher what, if any, developmental processes they may share.

PREVALENCE THROUGHOUT DEVELOPMENT How the Developmental Story Unfolds These conceptual limitations aside, the first question to address is the prevalence of these co-occurring problems throughout development. As with many

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other considerations in developmental psychopathology, most of what we know about co-occurring language and behavior problems is documented for school-age children, and to a much lesser extent, adolescents and adults, often in follow-up studies. Although the exact proportions of overlap vary from study to study, it is estimated that more than 50% of children with behavior problems have language deficits, many of them undiagnosed (Cohen, 1998). Similar proportions of language-impaired children are reported to display behavior problems severe enough to warrant intervention. It is safe to assume that a significant proportion of these behavior problems would include some forms of aggression. Whether the initial focus is on behavior or language, the general outlook is the same: A child with one of these problems is up to three or four times more likely to have the other, than a child in the community at large (Goodyer, 2000; Stevenson, 1996). This childhood snapshot, however, says little about what leads to these compelling statistics and even less about when and how the story unfolds. Which came first? In any attempt to understand co-occurring problems, this question inevitably arises. And as with hens and eggs, the answer in this case may be equally problematic. Decades of research on aggression in humans still leaves the century-old question of the onset of physical aggression unresolved or, at best, with controversial answers (Tremblay, 2000). Psycholinguists, however, have less difficulty in agreeing that early infancy is the vessel of early language development. The first spoken words typically appear around the first birthday, but a child is able to comprehend words and link them to objects somewhat earlier. By the end of the second year most children experience a vocabulary spurt, which generally precedes the onset of word combinations into sentences. By age 3, simple grammatical forms are used to make complete sentences, albeit language remains somewhat telegraphic at this age. At any point in time, a child’s understanding of language, and thus his or her receptive abilities, precede the ability to use the same grammatical forms in expressive language. At ease with the rudiments of spoken language, most 3-year-olds are able to make demands, give information verbally, and have an active role in conversation. With the availability of normed instruments of early language development, we are able to diagnose early delays in the lexical and grammatical content of spoken language, as well as in a child’s ability to understand spoken language. Although most delays before age 3 appear transient (Dale, Price, Bishop, & Plomin, 2003), some 40% of slow talkers still show signs of delay by the end of the preschool years and beyond. Those with receptive delays, who show early difficulties in understanding language, tend to have a worse prognosis. Theoretical disputes aside, the developmental story of aggression shares some interesting milestones with language development. As Goodenough (1931) illustrated years ago, the frequency of aversive types of behavior, from fussing and crying in the first year, to kicking, biting, hitting, and tantrums when physical ability enables such behavior, shows a marked increase from 6

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months onward to reach a peak between the ages of 18 and 36 months. Goodenough, and others after her (Vygotsky, 1962; Luria, 1961), have argued that a child’s growing verbal ability is instrumental in the following decrease of physically disruptive behaviors after 36 months. This milestone does coincide with the onset of efficient communicative skills in most children, as stated earlier. In an attempt to prospectively track the onset of physical aggression in a representative birth cohort, Tremblay and colleagues (Tremblay et al., 1996) showed that by 17 months, 80% of children were reported to exhibit some form of physically aggressive behavior. From the third year onward, physical aggression was shown to decrease (Tremblay et al., 1996), with a second peak around midadolescence, mainly for boys. As with early language deficits, high levels of physical aggression in infancy tend to remain stable in a proportion of children (Hay, Castle, & Davies, 2000; Keenan & Shaw, 1993), placing them most at risk of following a high aggression trajectory leading to later violence and criminality. Some forms of physical aggression and rough-and-tumble play may be normative during the period fondly known to parents as the “terrible twos.” In most children, after this period, physical aggression is replaced by less overt forms of aggression, namely, verbal and indirect aggression (Bjorkvist, Osterman, & Kaukiainen, 1992). Although minimal language ability is required to use verbal aggression, it remains unclear whether the use of verbal aggression is highest among verbally proficient toddlers. If, as is the case in school-age children, rates of verbal and physical aggression remain associated (Pepler, Craig, & Roberts, 1998), it may be that some physical aggressors add verbal aggression to their repertoires and others move from physical to verbal forms of aggression. In time (it is hoped), language becomes for most children a social tool for increased prosocial interactions. Whatever the case may be, from both the behavior and language perspectives, the early toddler years serve as the center stage for emergent individual differences that may have a profound impact on later adjustment. From that point onward, language abilities continue to progress and physically aggressive behaviors diminish in frequency. At no other moment in life will the frequency of aversive-type behaviors reach the peak and subsequent sharp decline observed in the toddler years; similarly, at no other point in time will language abilities show a growth as staggering as that evidenced in the first 3 years of life. For some children, however, language has not progressed as anticipated at this milestone, and for some, physical aggression continues to attract increasing concern. The question is to what extent are these the same children? Studies offer different answers, using different methodologies at various periods of development. Two separate concerns are generally addressed in regard to prevalence: (1) concurrent behavior and language problems and (2) longitudinal outcomes of earlier language deficits. The following sections offer a review of prevalence studies throughout development.

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Concurrent Prevalence in Infancy and the Preschool Years The youngest age at which epidemiological data are available on the language– behavior association comes from two recent twin studies addressing the genetic etiology of this association and a small community sample. We return to the etiological answers provided by the genetic studies later. A first question they attend to pertains to the age of onset of this association. How early is there evidence of an association between language deficits and aggression? In the Québec Newborn Twin Study (QNTS), a modest but significant correlation of –.20 was found between expressive vocabulary assessed via a parent checklist and parent reports of physical aggression at 19 months (Dionne et al., 2003). Although there were no sex differences in either vocabulary or aggression at this age, the correlation was slightly higher for boys than for girls. In contrast, when more general conduct problems were considered in relation to vocabulary in the Twin Early Development Study (TEDS), Plomin and colleagues (Plomin, Price, Eley, Dale & Stevenson, 2002) found correlations of –.05 at 24 months for both boys and girls. In addition, languagedelayed children (below the 5th and 10th percentiles) in this sample did not show a higher incidence of conduct problems. There was also no significant association between language and behavior in a small community sample comparing language-delayed (n = 11) and language normal (n = 53) 24month-olds on a CBCL measure of total externalizing behavior (Carson, Klee, Perry, Muskina, & Donaghy, 1998). Subsequent analyses of the Québec sample, however, show this not to be the case when physical aggression is considered. Indeed, posthoc analyses on this sample of 900 twins indicate a significantly higher incidence of physical aggression in 19-month-olds below the 15th percentile on vocabulary (p < .05). Although there appears to be an association, albeit very modest, of delayed language with aggression before age 2, this does not seem to be the case when more general conduct problems are considered. By age 3, prevalence reports markedly differ. In the TEDS sample, correlations at follow-up assessments at 36 and 48 months remain modest: –.13 for boys and –.09 for girls at 36 months and –.18 for boys and –.15 for girls by 48 months. Again, the incidence of conduct problems and total behavior problems is not higher in the delayed children at both ages. This is in sharp contrast with results from an earlier U.K. study by Stevenson and Richman (1978), in which half of the language-delayed children, from a sample of 828 3-year-olds, showed behavior problems. A majority of these problems pertained to general immaturity and overactive behavior. The most frequent language delay pertained to difficulty with language structure. In a later study, Silva, Williams, and McGee (1987) assessed a normative sample of 1,037 3-year-olds in New Zealand. In this study, a higher incidence of behavior problems, as rated by parents and teachers on the Rutter Scale, was found for

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children with general language delay and comprehension delay but not for those with expressive delay. The variety of language and behavior measures make comparisons and conclusions difficult before age 3, but the general trends in the U.K. and N.Z. studies of 3-year-olds appear sharper by age 4–5. In the late 1970s, Cantwell and Baker (1977) studied behavioral outcomes in incoming patients to a community speech and hearing clinic. Two-thirds of these children were of preschool age (median 4.8 years). The 600 children identified within a 3-year period were divided into three language attainment categories: pure speech disorder, speech and language disorder, and pure language disorder, based on a comprehensive speech and language assessment. Speech-disordered-only children showed fewer concurrent psychiatric disorders. Overt behavioral disorders were identified in 30% of the speech and language group, and in 47% of the pure language group. However, approximately two-thirds of the overt behavioral disorder were related to attention deficits, and the incidence of conduct disorder was only slightly more elevated in these groups than would be expected in the normal population. Cantwell and Baker (1977) cautioned that because a conduct disorder diagnosis requires a long pattern of behavior, it was rarely given for the younger children. This may account for the low incidence. However, as there is a high prevalence of physical aggression in attentiondeficit disorders, the co-occurrence of language deficits and aggression in the late preschool period may have been underestimated in this sample. A stronger association has been shown in one of the most extensive longitudinal investigations of psychopathology in language-delayed children. This study was initiated in a community-based sample of 5-year-olds in Ottawa, Canada, by Joseph Beitchman and his colleagues (Beitchman, Nair, Clegg, Ferguson, & Patel, 1985). At initial assessment, the boys (n = 90) among the 142 children in the language-delayed group showed a higher incidence (13.6% versus 3.4% in controls) of conduct disorder than controls, but not the girls. A recent community study of 4- and 5-year-old preschoolers also reports this gender difference (Ortiz, Stowe, & Arnold, 2001). Lower levels of expressive and receptive vocabulary skills in this sample (n = 56) were strongly associated with disruptive behavior as coded from video observations and from teacher ratings, but for boys only. Although none of these studies focused specifically on aggression, the gender-biased results are consistent with those of previous studies (Beitchman et al., 1985; Dionne et al., 2003). Thus, during infancy and the preschool years, some studies show evidence of a higher incidence of aggressive behaviors in preschoolers with lower language proficiency, particularly for boys. However, other studies report no such evidence. In the studies where there is a significant association in this age range, pure speech impairments are not the culprit. Some studies report a stronger association for receptive deficits, whereas other studies report associations for both receptive and expressive language deficits, mainly for vocabulary. Overall, however, these associations remain very modest.

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Concurrent Prevalence in Childhood and Adolescence By the early school years, the specificity of language deficits linked with aggression emerges. In one of the earlier childhood studies, Camarata, Hughes, and Ruhl (1988) showed that the language performance of children identified as having mild to moderate behavior disorder was typically 2 or more standard deviations below the normative mean. These children displayed problems with expressive syntax while having a satisfactory knowledge of vocabulary. Results from Cohen and colleagues (Cohen, Davine, Horodezky, Lipsett, & Isaacson, 1993) point to similar language deficiencies linked with use of language more than content of language in aggressive children. They systematically screened 399 psychiatric outpatients ages 4–12 years and found that one-third of the referred children had an unsuspected language impairment. Overall, more than 50% of these children exhibited some form of language impairment, previously identified or not. Although semantics, syntax, and phonology were more affected in the group with previously identified language impairment, a higher proportion of children from the unsuspected language impairment group showed problems with receptive syntax, auditory memory, and fluency. Cohen (1998) later reported that although the prevailing behavior diagnosis for children with language impairments was ADHD, the children with unsuspected language impairment were rated as more aggressive and having more problems with delinquency. These two studies suggest that aggressive children may have more problems with the use and understanding of complex language structures than with lexical knowledge. The specificity of pragmatic difficulties associated with aggression or behavior problems is reported in other studies on smaller samples. In a study of 54 special education second- and third-grade children, Minutti (1991) found that among children in special classes, with either behavioral problems or learning problems, language deficiencies of more than 2 standard deviations below the normative mean identified those having more behavior problems, based on teacher ratings. The most important deficit in this subgroup was associated with difficulty in formulating coherent sentence structures to convey meaning. A more thorough investigation of pragmatic language development in association with physical aggression was conducted in two separate studies by Cole (2001) and Mack and Warr-Leeper (1992). In the study by Cole (2001), aggressive (n = 19) and nonaggressive (n = 26) 8–13-year-old boys were compared on standardized receptive and expressive language measures, as well as measures of syntactic and narrative complexity. Although the groups did not differ on the composite scores of expressive and receptive language, the aggressive boys did perform more poorly on both the syntactic and narrative complexity measures. Mack and Warr-Leeper (1992) had previously identified similar problems in chronic-behavior-disordered boys, even once IQ level was taken into account. In their sample, 16 of 20 boys scored below the average range on at least 4 of 20 language assessments. The main areas of language compromised were use of complex linguistic structures, use of abstract

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language, and use of concepts. More important, however, for half of these boys, language assessments were below expected levels based on IQ. This suggests that pragmatic and sentence structure difficulties may be associated with the more severe forms of behavior problems and aggression in childhood and early adolescence, over and beyond IQ level. Although these studies offer compelling results, inferences remain limited by the fact that they are based on clinical populations of behaviorally compromised children and that, for the most part, these are mainly boys (from 75– 100% of the samples). Do normative samples of boys and girls replicate the association between language deficits and conduct disorder or aggression in this age range? For the most part, they do. Although total prevalence is higher in boys, the co-occurence rates with language impairments appear to be similar for boys and girls (Stevenson, Richman, & Graham, 1985). In one of the few studies looking simultaneously at physical and verbal aggression, Piel (1990) added another consideration to gender differences. He studied language maturity in association with responses on an apperceptive test of aggressive behavior in 108 second- and third-grade children. Although children’s behaviors were not assessed directly, the best predictor of physically aggressive responses to vignettes was low language maturity, accounting for 20% of the variance in both boys and girls. Sex and social class were not associated with the selection of physically aggressive responses. Interestingly, girls did use verbally aggressive responses more often than boys, and language maturity was associated positively with this form of aggressive response in girls, albeit less strongly (4% of the variance). The more verbally proficient girls were more prone to offer verbally aggressive responses to the vignettes. Even though apperceptive tests have important methodological limitations in generalizing to behavior, these results suggest that the developmental shift from physical aggression to verbal aggression may be mediated by language maturity, yet differently in boys and girls. Tomblin and colleagues (Tomblin, Zhang, Buckwalter, & Catts, 2000) offered yet another consideration in looking at the co-occurence of behavior and language problems in school-age children. They studied language, reading, and behavior in a normative sample of second-grade boys and girls. The overall association between externalizing behavior problems assessed by teachers and parents and a composite language score (including expressive and receptive vocabulary and pragmatic complexity) was –.30. Both were negatively associated with reading problems. Subgroups of children were then identified as language impaired or reading impaired. When investigating the pattern of association between reading, language, and behavior problems at this age, log-linear model fitting indicated that behavior problems in the children with language impairments were mediated by reading problems whereas behavior problems in the reading-impaired group were not mediated by language problems. This suggests that by the early school years, reading difficulties may act as an additional risk factor for behavioral problems, either linked with early language impairment or as a novel liability. Written forms of lan-

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guage may have specific links with aggression and externalizing behaviors that need to be addressed separately. In sum, by the early school years and adolescence, many studies have documented the link between language proficiency and behavior problems. Although both problems are more prevalent in boys at this age, their rate of co-occurrence appears generally similar across genders. Contrary to what was observed in the preschool years, studies specifically pertaining to aggression show patterns of co-occurences similar to those shown in studies of general behavior problems or conduct disorders. But although the co-occurence may be of the same magnitude, these studies suggest that low pragmatic language skills and difficulties with sentence structure may be more specifically associated with aggression during this period.

Longitudinal Data: Do Early Language Deficits Predict Later Aggression? Probably the most striking findings of the association between language and aggression are those reported in longitudinal lifespan studies. Although language has been a continuous focus in studies of early development, studies in adulthood shifted to low IQ as a concurrent correlate of physical aggression, delinquency, and criminality (Moffitt et al., 1981). Language proficiency may have appeared as an unlikely concurrent candidate by adulthood, as, for the most part, adults seem to have mastered the basic linguistic skills, even the less educated adults. Prospective longitudinal studies, however, tell a different story when early language skills are associated with adulthood outcomes. But first, we consider longitudinal results during childhood. In three studies described earlier, children assessed as preschoolers were followed into later childhood. In all of these studies, early behavior problems (ages 3–4) predicted later behavior problems (at age 8 in Stevenson et al., 1985, and Benasich, Curtiss, & Tallal, 1993; at ages 7, 9, and 11 in Silva et al., 1987). However, early language delays were limited in predicting later behavior problems. In Benasich and colleagues’ U.S. sample of language-impaired preschoolers and controls, neither degree of language impairment at the initial assessment nor the language improvement between assessments predicted behavioral outcomes at age 8. In Stevenson and colleagues’ U.K. sample, low language structure at age 3 did not predict antisocial behavior scores at age 8 but did predict neurotic problems. In the N.Z. sample of Silva and colleagues, however, the general language delay group at age 3 did score significantly higher for total behavior problems on the Rutter Teacher Scale at age 9 and on the Rutter Parent Scale at 11. Although behavior problems remained quite stable, the predictive value of early language impairment appears mitigated in these samples of boys and girls. The story, when looking at late adolescence and early adulthood followups, is quite different. Beitchman’s Canadian sample of language-impaired children initially assessed at age 5 were followed well into late adolescence. Boys and girls with initial language impairement had strikingly divergent

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trajectories by age 19 (Beitchman et al., 1999). Both speech- and languageimpaired girls showed a higher prevalence of psychiatric disorders than controls, predominantly affective and anxiety disorders. However, antisocial personality disorder was the most prevalent diagnosis for the boys in the language-impaired group. Boys in this group were up to four times more likely to have this diagnosis than controls. Similar results are shown for boys in relation to registered criminality in a longitudinal follow-up of a sample of 122 Swedish boys (Stattin & Klackenberg-Larsson, 1993). Infant measures of language development were conducted at 3, 6, 9, 12, 18, and 24 months. Of the 122 boys, 36 were sporadic (n = 22) or frequent (n = 14) offenders by age 17. Registered criminality was significantly but modestly correlated with 6-, 18-, and 24-month infant language measures (correlations ranging from –.16 to –.19). Moreover, language ratings by a psychologist were obtained at ages 3 and 5. Registered criminality was both related to boys language maturity at age 3 (r = –.16, p < .05) and age 5 (r = –.17, p < .05) and to the mother’s self-reported difficulty in understanding the speech of the child at ages 4 and 5. Intelligence measures were also obtained (ages 3, 5, 8, 11, 14, and 17 years), and all except one (age 8) predicted later registered criminality. However, once SES was controlled for, only the age 3 intelligence measure differentiated offenders from nonoffenders, but 18- and 24-month language ability, 3-year comprehension of language, and 5-year maturity of language use and comprehension of language remained significant predictors of criminality. Thus, early language development appeared as the early aspect of these boys’ lives that better distinguished later offenders from nonoffenders, even once SES and IQ were taken into account. The longitudinal picture these studies paint appears to vary according to two criteria: gender and the specificity of the behavior measures. Longitudinal outcomes for children with early language delays seem to differ considerably as a function of gender. The antisocial trajectory, possibly more directly associated with the use of aggression, is up to 4 times more likely in boys with language impairments than in control boys, but almost 10 times more likely than in girls with language impairments. Girls with language impairments at age 5 do not even reach the rate of antisocial disorder in control boys. The specific behavior measure also distinguishes the predictive value of early language deficits. Results in childhood studies assessing general behavior problems are more inconsistent. However, when criminality and antisocial disorders were targeted, early language impairments distinguished offenders from nonoffenders, beyond SES measures, whereas intelligence measures in childhood did not. Overall, the striking feature of the prevalence studies reviewed is not the strength of the association between language deficits and aggression. The coprevalence may be high in clinical populations, but the linear association remains modest, with correlations ranging at best from –.17 to –.33. Rather, it is the consistency with which results appear in many studies based on a variety of designs, populations, age ranges, and even construct definitions.

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Is the Association between Language Proficiency and Aggression Linear? A major question arises from the consistency of the modest association between low language proficiency and aggression throughout development. Why are correlations so low when the prevalence of one problem can reach as much as 80% when children have the other? Low correlations, aside from indicating a modest association, could also stem from one of two other situations: Either good language skills are not associated with lower aggression scores—that is, the relationship is not linear—or heterogeneous subgroups, with respect to the association between language skills and aggression, create competing effects that outweigh each other in the assessment of a linear trend. Although studies have looked at the higher co-occurrences of the problematic aspects of language and aggression, few have considered looking at whether good language skills predicted lower aggression scores. This question is important, because if the trend is not linear in nature, the resulting correlations may have been underestimations of the true underlying relationship between language impairment and aggression. In addition, if better language skills are not associated with less aggression and more prosocial skills, then there is little to infer from these studies in terms of prevention. Post hoc analysis of the Québec sample offers some reassurances in that respect. At 19 months, the infants above the 85th percentile for vocabulary development did show a lower incidence of physically aggressive behaviors (p < .05), but more important, they also showed a higher incidence of prosocial behaviors (p < .05). This trend persists at 30 months and is true for both boys and girls. Thus, language proficiency may be playing a protective role in the process of early socialization of behavior. The other possibility for the modest correlations is that physical aggression occurs in some verbally proficient individuals, just as some languageimpaired individuals show no signs of using aggression at higher rates. In other words, language deficits, although they occur more frequently in aggressive individuals, may lead to other behavioral and emotional problems not involving aggression, or to no other specific problem. In our attempts to make sense of co-occurring milestones of language and socialized behavior in toddlerhood, we may have overlooked the possibility that distinct subgroups of aggressive individuals with differing levels of language proficiency may emerge in early development. In an examination of communicative strategies in preschool classroom disputes, Danby and Baker (2001) have shown how dominant boys in such group disputes use a variety of verbal strategies to assert their identity, construct group affiliations, and generate terror in targeted rejected children. Although it is unclear whether these boys are in fact more proficient verbally, it is clear that they are able to use language to attain goals involving some forms of aggression. If such different subgroups exist, the etiology of aggression accompanied by low language proficiency may differ from the etiology of aggression in verbally proficient individuals. Different statistical strategies are needed if we are to distinguish these nonlinear associations

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and, more important, identify individuals following at-risk developmental trajectories for aggression with or without language impairment. This possible missing piece to the puzzle suggests that we may only be starting to understand the complexity of the interface between language and aggression, and to some degree, between language and socialized behavior.

THEORETICAL MODELS OF THE LANGUAGE–AGGRESSION ASSOCIATION There have been numerous theoretical propositions put forth to explain the language–aggression association. By and large, these fall within two sets of developmental models. Models of the first type are those that assume language deficits and aggression share similar origins. The second type of models are those that contend that one problem leads to the other as a secondary consequence, either via distinct pathways or through a combination of multiple pathways acting in transaction, or that both problems feed on each other during development, creating a consolidation of the co-occurence in time.

Shared Etiology Pathways There are three types of shared etiology models that have been suggested to explain the language–aggression association. First, there are models that imply that both language deficits and aggression may stem from the same genetic and biologically based predispositions (Stevenson, 1996). The origins of both problems would then be organic in nature. Stevenson (1996) has demonstrated that ADHD and reading problems do share a common genetic etiology in school-age children. However, even though language and reading problems often co-occur, and aggression and ADHD often co-occur, there are no studies showing that this generalizes to language deficits and aggression. In fact, both the Québec Newborn Twin Study and the U.K. Twin Early Development Study have found no evidence of shared genetic influences—between physical aggression and delayed vocabulary in the Québec sample, and between general conduct problems and delayed vocabulary in the U.K. sample. The shared genetic liability pathway thus seems unlikely in early childhood. However, as genetic influences on most traits tend to increase with time, a possible shared genetic etiology may emerge only later. In addition, empirical tests of this model should take into account the possibility that the etiology of the association of behavior and language may vary, depending on the specific behavior and language deficits. Second, there are models that suggest at-risk environmental features can lead to both unsocialized behavior and poor cognitive-intellectual development, including or secondary to poor language skills. In this macro-social pathway, parenting styles and harsh economic conditions are viewed as environmental liabilities that steer children into trajectories of poorly socialized behavior and leave them poorly stimulated in language development. The link

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between aggression and parenting has been documented in numerous studies, such as in work by Diana Baumrind (1993) and Gerald Patterson and his colleagues (Patterson, 1982; Patterson, Reid, & Dishion, 1992) at the Oregon Social Learning Center. These have generally demonstrated that inconsistant and harsh parenting, with poor child supervision, create a context within which a child is more susceptible to develop behavior problems. In a similar fashion, but within a completely different field, psycholinguists have demonstrated how parental input (moderated by such factors as socioeconomic status, parental education levels, and neighborhood safety, to name a few) has a profound effect on children’s language development (Storch & Whitehurst, 2001). Michael Tomasello (2003) offered compelling empirical evidence of the effect of input in tasks of non-word learning in helping a child learn new words to designate novel objects. Others have shown how parents’ reading to children (Lyytinen, Laakso, & Poikkeus, 1998; Sénéchal, LeFèvre, Thomas, & Daley, 1998), and parents’ rephrasing of early language mistakes (Bohannon & Stanowicz, 1989) also play a role in the development of language in children. The absence of these forms of early language stimulation is more likely to be accompanied by parental discipline lacking in attention to a child’s needs. Such parental discipline may be characterized by harshness and lack of appropriate supervision, often associated with behavior problems in children, and may account for the association of problems regarding both language and behavior. Finally, the co-occurence of both traits has been suggested to be linked to the same cognitive deficit, such that poor judgment and/or lack of ability to understand others’ perspectives may be accompanied by language difficulties but also heighten the risk for social exclusion and deviant behaviors. The next section of this chapter explores in more detail the theoretical propositions involving a causal contribution of language to the development of aggression.

Causal Pathways Causal models of the language–behavior association have received more attention than their shared etiology counterparts. The prevailing hypothesis in this respect suggests that low language proficiency makes one more liable to use aggression (Cohen, 2001). Two studies have conducted direct tests of this hypothesis, the Québec Newborn Twin Study (Dionne et al., 2003) and an intervention study conducted more than three decades ago (Slaby & Crowley, 1977). In the Québec study, the investigators compared models specifying shared etiological contributions and models testing the significance of unidirectional and reciprocal contribution paths from language to aggression at 19 months. These analyses were conducted using structural equation modeling and the additional statistical flexibility offered by genetically informative data. Results indicated no significant shared etiology component, whether genetic or linked to environments shared by twins at this age, except for a unique environmental component specific to twins within families. However,

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causal genetic models revealed that a causal path from vocabulary to physical aggression could account totally for the covariance between the two. Assumptions of the genetic methodology should, however, be taken into consideration in generalizing these results. In addition, the results remain specific to the time frame for which models were tested. The most compelling evidence of causal effects comes from experimental designs using and assessing interventions. Many preschool programs targeting at-risk children have an incorporated intervention focus on language and literacy, yet these rarely supply a proper control group to assess the efficacy of interventions. In a study conducted in the late 1970s (Slaby & Crowley, 1977), when the language–aggression hypothesis attracted attention, disruptive children were identified in classroom settings. Half of them received an intervention based on increasing their linguistic skills in social contexts, the other half did not. Teachers reported that the children having received the intervention had significantly decreased their use of disruptive behavior in class and aggression in the schoolyard. There was no significant change in the nonintervention group. The authors concluded that these results were indicative of a causal contribution of enhanced language proficiency toward more socialized behavior. Because there was not a separate group receiving intervention targeting the behavior problems, it is difficult to conclude that regulating behavior does not also contribute to better language learning. Although there were many methodological limitations to this small study, it serves to highlight the necessity of conducting experimental intervention studies to assess causal pathways. Another limitation of these two studies is that although they suggest that language proficiency can affect behavior, they do not address the mechanisms possibly involved. Three major views on how language deficits can lead to behavior problems, including aggression but not specific to it, have been outlined. They are referred to here as the micro-social pathway, the self-regulation pathway, and the social-cognition pathway. The first of these views assume that language plays a significant role in sustaining fulfilling social interactions. This micro-social pathway, along with others reviewed later, has been formalized and explored by Brinton, Fujiki, and colleagues (Brinton & Fujiki, 1993; Brinton, Fujiki & McKee, 1998). In one study, language-delayed school-age children were compared with controls in regard to their negotiation skills in a series of negotiating sequences with two other peers. As compared with controls, the language-delayed children contributed significantly less and developmentally lower-level negotiation strategies to their teams. Interestingly, the language-delayed children did not speak less often than controls. Rather, the maturity level of their verbal contributions to the team was what distinguished them from their peers. The authors caution that lack of efficient negotiation skills may place the languagedelayed children at risk for confrontations with peers and lead them to adopt more disruptive behaviors. Brinton and Fujiki have also documented the fact that language-delayed

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children show more emotion regulation problems (Fujiki, Brinton, & Clarke, 2002). Cohen (2001) points out that language is an important means by which one controls one’s behavior and emotions. This notion goes back to early propositions by Luria (1961) and Vygotsky (1962) to the effect that inner language is a necessary tool to inhibit antisocial impulses, among other things. Emotion regulation and self-regulation are generally viewed as requiring complex linguistic tools such as the ability to analyze social situations, organize thoughts about one’s own emotions, and plan behavior according to social rules. Given this central role of language in emotion regulation, in the self-regulation pathway, children with language difficulties are expected to be at a disadvantage (Gallagher, 1999). There is some evidence showing that language-delayed children are more at risk of also having regulation problems. In a study of 82 school-age children, half of whom were language delayed, Fujiki and colleagues (Fujiki et al., 2002) reported lower scores overall for the language-delayed children on the Emotion Regulation Checklist, especially for boys. Although emotion regulation problems may stem from overregulation as well as underregulation (Cole, Michel, & O’Donnell-Teti, 1994), it may be expected that the underregulated children would be the ones at risk for aggression. Empirical evidence is, however, not yet available to support the assumption that the contribution of language delays to aggression is mediated by underregulation problems. Social cognition pathways offer yet other explanations for possible mediators of language deficits leading to aggressive behaviors. Among these, Dodge’s social information-processing model suggests that aggression develops as a consequence of deficits in social problem-solving abilities. The model assumes that there are six steps involved in the social problem-solving process. Once a child has (1) encoded cues, the child must (2) interpret those cues before deciding (3) what his or her goal is, (4) constructing his or her response, (5) choosing it, and (6) acting on it (Crick & Dodge, 1994). Although aggressive children tend to construct more aggressive responses and act on them, Lochman and Dodge (1994) have shown that what mainly distinguishes them from nonaggressive children is the tendency to perceive hostile intent in ambiguous situations. This presumably causes them to act on these perceived hostile intents by choosing aggressive responses. It is less clear, however, how language delay may lead a child into this attribution biases pathway. If, as Cohen (2001) points out, language-delayed children have had more negative social encounters, and have more difficulty in making complex analyses because of their linguistic limitations, they may in fact be more at risk of forming hostile attributions. However, this needs to be documented empirically. In addition, the attribution biases pathway seems an unlikely explanation for aggression that appears as early as late infancy. The same can be said about another approach to the social cognition pathway. Theory of mind has been receiving much attention in recent years as a possible central cognitive impairment, linked to autism in particular. Theory of mind involves understanding that individuals may have different views

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about a given situation, and that sometimes one may act on the basis of an assumption that appears true, which is in fact a false belief (Dunn, 1996). Children begin to be able to consider another person’s perspective, and understand that thoughts, beliefs, and emotions are determined by a person’s unique perspective, at about age 4. Autistic children do not master this task (Wimmer & Perner, 1983). Happé and Frith (1996) have shown that children with social/emotional problems have more problems mastering this task as well, and Cutting and Dunn (1999) have shown theory of mind mastery to be more difficult for language-delayed children. However, there is no evidence to support a theory of mind pathway by which the effects of language delay on socio-emotional problems and/or aggression are mediated. Finally, although it has received much less attention, the alternative causal pathway, whereby aggression leads to secondary language delays, has not been ruled out. For instance, aggressive individuals could be less sensitive to linguistic stimulation in their environment or too disrupted by their own behavior to benefit from this stimulation, leaving them with linguistic deficits they are unable to overcome. As Cantwell and Baker (1977) pointed out decades ago, the main impediment to this hypothesis has been that language delays have always appeared to precede the onset of aggressive behaviors in development. But because overt aggression has rarely been assessed around the time language appears, their conclusion may have been premature. Until proven otherwise, we should consider the possibility that aggression may play the causal role at one moment of development, and not at another, or both may influence each other reciprocally. For example, language-based formal schooling represents a specific time frame within which specific demands are placed on children, requiring both good language skills and social skills. If low language skills appear to drive aggressive behavior in early childhood, can we infer that low language skills drive aggressive behavior once schooling starts? Or does aggression lead to social interactions and choices of peers that have adverse consequences on schooling and limit the sophistication of language skills that comes with schooling? If this is the case, concurrent language skills may not be the best focus for intervention with adult delinquents or violent criminals, but may be targeted in early development to promote prosocial development. For now, we are unable to discern whether any or all of these alternatives are at play.

LOOKING FOR ANSWERS As this review illustrates, research designs of the past decades have been mainly concerned with documenting the prevalence of and, to a lesser extent, exploring the etiology of the language–behavior association. The initial clinical observations of Orton (1937) and Chess (1944) hold true across many samples, large and small, from the normative to the clinical, concurrently and longitudinally. Research on aggression, although more scarce, also suggests

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language and aggression are associated. That much we know. Any answers to the question concerning how language and aggression become linked during development, however, are at best, tentative for the time being. For the most part, we are left to speculate, given incomplete correlational information. To be more efficient, research designs will need to incorporate measures of mediating variables, such as economic considerations, concurrent measures of IQ, literacy, and discipline-oriented parental practices, to assess their specific contributions in developmental pathways. In addition, aggression should be targeted specifically if designs seek to understand the specificity of the language–aggression association. Similarly, a survey of language skills should include the full array of linguistic abilities. To assess possible shared physiological contributions to both problems, lower-level cortical functioning, such as executive functions and time processing, could be assessed. Obviously, gender differences in both prevalence and developmental mechanisms need to considered. Finally, the true test of causality rests on experimental designs. To scan the full array of possibilities, such designs should divide groups to consider the etiology and course of aggression and language deficits separately, as well as in association, and study the impact of interventions on both aspects longitudinally.

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Fujiki, M., Brinton, B., & Clarke, D. (2002). Emotion regulation in children with specific language impairment. Language, Speech, and Hearing Services in Schools, 33, 102– 111. Gallagher, T. M. (1999). Interrelationships among children’s language, behavior, and emotional problems. Topics in Language Disorders, 19, 1–15. Goodenough, F. L. (1931). Anger in young children. Minneapolis: University of Minnesota Press. Goodyer, I. M. (2000). Language difficulties and psychopathology. In D. V. M. Bishop & L. B. Leonard (Eds.), Speech and language impairments in children: Causes, characteristics, intervention, and outcome (pp. 227–244). Philadelphia: Psychology Press. Gualtieri, T., Koriath, U., Van Bourgondien, M., & Saleeby, N. (1983). Language disorders in children referred for psychiatric services. Journal of the American Academy of Child and Adolescent Psychiatry, 22, 165–171. Happé, F., & Frith, L. (1996). Theory of mind and social impairment in children with conduct disorder. British Journal of Developmental Psychology, 14, 385–398. Hay, D. F., Castle J., & Davies L. (2000). Toddlers’ use of force against familiar peers: A precursor of serious aggression? Child Development, 71, 457–467. Howlin, P., & Rutter, M. (1987). The consequences of language delay for other aspects of development. In W. Yule & M. Rutter (Eds.), Language development and disorders (pp. 271–294). Oxford, UK: Blackwell. Keenan, K., & Shaw, D. S. (1993). The development of aggression in toddlers: A study of low income families. Journal of Abnormal Child Psychology, 22, 53–77. Lahey, B. B., Pelham, W. E., Stein, M. A., Loney, J., Trapani, C., Nugent, K., Kipp, H., Schmidt, E., Lee, S., Cale, M., Gold, E., Hartung, C. M., Willcutt, E., & Baumann, B. (1998). Validity of DSM-IV attention-deficit/hyperactivity disorder for younger children. Journal of the American Academy for Child and Adolescent Psychiatry, 37, 695–702. Lochman, J. E., & Dodge, K. A. (1994). Social-cognitive processes of severely violent, moderately aggressive, and nonaggressive boys. Journal of Consulting and Clinical Psychology, 62, 366–374. Love, A., & Thompson, M. G. G. (1988). Language disorders and attention deficit disorders in young children referred for psychiatric services. Journal of Orthopsychiatry, 58, 52–63. Luria, A. R. (1961). The role of speech in the regulation of normal and abnormal behavior. Oxford, UK: Pergamon Press. Lyytinen, P., Laasko, M.-L., & Poikkeus, A.-M. (1998) Parental contribution to child’s early language and interest in books. European Journal of Psychology of Education, 13(3), 297–308. Mack, A. E., & Warr-Leeper, G. A. (1992). Language abilities in boys with chronic behavior disorders. Language, Speech, and Hearing Services in Schools, 23, 214– 223. Miniutti, A. M. (1991). Language deficiencies in inner-city children with learning and behavioral problems. Language, Speech, and Hearing Services in Schools, 22, 31–38. Moffitt, T. E., Gabrielli, W. F., Mednick, S. A., & Schulsinger, F. (1981). Socioeconomic status, IQ, and delinquency. Journal of Abnormal Psychology, 90, 152–156. Montare, A., & Boone, S. L. (1973, February). Language and aggression, an exploratory study among black, Puerto Rican youth. Paper presented at the meeting of the Educational Research Association, New Orleans.

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DETERMINANTS Intergenerational Transmission OF AGGRESSION of Aggression

17 The Intergenerational Transmission of Aggression and Antisocial Behavior M ARK Z OCCOLILLO, E LISA R OMANO, D AVID J OUBERT, T ANIA M AZZARELLO, S YLVANA C ÔTÉ , M ICHEL B OIVIN , D ANIEL P ÉRUSSE , and R ICHARD E. T REMBLAY

In this chapter the intergenerational transmission of childhood-onset persistent aggression (CPA) is reviewed. The evidence for both genetic and environmental risk is presented. The association between parental antisocial behavior and environmental risk factors is examined, and some new data from a large longitudinal study are presented. The difficulties posed by the strong association between parental antisocial behavior and environmental risk factors and the lack of adequate control for parental antisocial behavior and gene–environment correlation in past studies are also discussed. The chapter concludes with a discussion of how future studies of risk factors for childhoodonset persistent aggression can be improved by incorporating assessments of parental antisocial behavior when examining environmental risk and by studies of the early environment of children with antisocial parents.

CHILDHOOD-ONSET PERSISTENT AGGRESSION AND THE PROBLEM OF DEFINING AGGRESSION A recent review of the development of aggressive behavior has noted that defining aggression in studies has been problematic: “The aggregation of different types of aggressive behaviours, and the aggregation of aggressive behaviours with different forms of antisocial behaviour clearly creates an important problem for a developmental science aiming to understand the origin and development of these behaviours” (Tremblay, 2000, p. 130). For example, the aggression scale for one of the few longitudinal and intergenerational studies 353

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of aggressive behavior included the following items: disobeys teacher, gives dirty looks, makes up stories and lies, does things that bothers others, gets in trouble (Huesmann, Eron, Lefkowitz, & Walder, 1984). Another problem in regard to studying aggression has been requiring an intent to harm as part of the definition. This would preclude studies of aggressive behavior in infants where intent to harm cannot be assessed, and of aggression following anger or fear as “anger and fear [that] lead to reactions which are clearly not under the control of anyone’s will” (Tremblay, 2000, p. 131). Nonetheless, despite these problems with defining aggression, several longitudinal studies of physical aggression in children (rigorously defined as fighting, bullying, or threatening others) have all concluded that there is a small group of children who are persistently aggressive from preschool into adolescence or adulthood (Broidy et al., 2003). Furthermore, children in this high-aggression group are much more likely to engage in violent delinquency than nonaggressive children. It is this childhood-onset persistent aggression (CPA) that is the focus of this chapter. Studies of the intergenerational transmission of rigorously defined CPA are few. There are many more studies of more broadly defined childhoodonset and persistent antisocial behavior (CPASB), which includes both aggressive and nonaggressive antisocial behaviors (Zoccolillo, Price, Hwu, & Ji, 1998; Moffitt, Caspi, Rutter, & Silva, 2001; Robins, 1966). This group has been given different names depending on the domain of research, including the diagnoses of antisocial personality disorder (APD) (within the DSM-IV (American Psychiatric Association, 1994) diagnostic framework) and childhoodonset and life course persistent antisocial disorder (Moffitt et al., 2001). Individuals who are severely and persistently aggressive also engage in less serious and nonviolent antisocial behaviors (Zoccolillo et al., 1998; Robins, 1996; Moffitt et al., 2001; Loeber, Burke, Lahey, Winters, & Zera, 2000). Conversely, among both men and women who met full DSM-III diagnostic criteria for APD in a general population survey of the prevalence of psychiatric disorders in the United States, 85% of men and 83% of women with APD met the criterion for violent behavior defined as follows: hit or threw things at partner more than once, spanked a child hard enough to bruise, had more than one physical fight (other than with spouse) (Robins & Regier, 1991, p. 261). Children with rigorously defined CPA are also more likely to engage in nonviolent delinquency (Broidy et al., 2003). Studies that focus on the more broadly defined CPASB are also informative in regard to CPA and are included in this chapter. Studies of rigorously defined CPA are highlighted.

WHAT CAUSES CHILD-ONSET PERSISTENT ANTISOCIAL BEHAVIOR OR AGGRESSION? Two recent studies have focused specifically on risk factors for childhood persistent aggression. In one study, risk factors for high versus low trajectories of

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physical aggression, defined using three items (fights with other children; kicks, bites, or hits other children; bullies or intimidates other children), were examined in boys of ages 6–15 from a high-risk sample (Nagin & Tremblay, 2001). Maternal low education status, teenage mother, and family not intact were environmental variables that were significantly associated with trajectories of high aggression. In a study of infants’ trajectories of aggression from 17 to 42 months of age in a random population sample, using the same items for aggression, three trajectories of aggression were found, including one group with stable high aggression (Tremblay et al., 2004). Risk factors for this trajectory of high stable aggression included young siblings, low family income, early motherhood, mother’s own history of conduct problems, maternal smoking during pregnancy, high family dysfunction, and maternal coercive parenting. Loeber and Farrington (2000) have recently reviewed the literature on young children who commit crime, and listed 40 factors across five domains (child, family, school, peers, and neighborhood). Hinshaw has reviewed issues related to process and mechanism in regard to externalizing behavior (Hinshaw, 2002). In commenting on the list of risk factors generated by Loeber and Farrington, he notes “The sheer size of this list, which must be considered only a partial consideration of potential risk factors, betrays the field’s lack of ability to synthesize or to tell a fully coherent story about the development and maintenance of externalizing behavior.” In regard to methodologic issues and promising practices for the field, he warns investigators of psychosocial influences: “Environmental factors may well account for independent variance in the field; but the typical means of inferring their effects (i.e., correlating a socialization variable with a child outcome) are sufficiently confounded and uninformative that considerably more sophisticated tests are in order.” As to promising avenues of investigation, he highlights the importance of genetically informative designs and conceptually driven investigations of interactions and transactions across multiple levels of influence.

CPASB/CPA IS A FAMILIAL DISORDER A major, and often neglected, aspect of CPASB/CPA is that it is a familial disorder. A recent meta-analysis has examined the association separately between maternal and paternal antisocial personality disorder and offspring externalizing disorders and found significant associations between both mother and father antisocial personality disorder and child externalizing disorder (Connell & Goodman, 2002). The weighted mean r for mothers was .17 and for fathers .16, or small effect sizes. A number of intergenerational studies have found that CPASB/CPA runs in families. As noted earlier, maternal history of conduct problems was a significant risk factor for persistent high levels of aggression in infants.

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Why Does Antisocial Behavior and Aggression Run in Families? Familial transmission can be due to genes, environment, or both. Genetically informative designs can disentangle genetic and environmental effects through twin and adoption studies (Plomin, 1997; Lahey et al., 1998). Environmental risk (e.g., hostile parenting) in parents with antisocial disorder is likely to affect all children in a family. If shared environment effects are found, this suggests (but does not prove) that early-onset antisocial disorder runs in families, in part due to cultural transmission. A longitudinal twin study has attempted to address the specific contributions of genetic influences, shared environment influences, and nonshared environmental influences separately for aggressive and nonaggressive antisocial behavior (Eley, Lichtenstein, & Moffitt, 2003). This study is of particular interest because both aggression and nonaggressive antisocial behavior, child versus adolescent onset, and persistence were examined. Twin pairs (n = 1,232) from the population-based Swedish Twin Registry were assessed at two different ages (8–9 years and 13–14 years). Aggressive antisocial behavior was rated by a parent using the Aggression subscale of the CBCL, and nonaggressive antisocial behavior was rated using the Delinquency subscale of the CBCL. At both ages aggressive and nonaggressive antisocial behavior were highly correlated. At age 8–9 aggressive behavior was highly heritable, with little evidence for shared environment. Nonaggressive antisocial behavior was influenced by both genes and shared environment. At age 13–14 both aggressive and nonaggressive antisocial behavior were influenced by genes and shared environment. Continuity in aggression was largely mediated by genetic influences, and continuity in nonaggressive antisocial behavior was mediated by both genes and shared environment. A limitation of this study is that the measure of aggression included nonaggressive items such as arguing a lot, stubborn, and jealous. A meta-analysis of 51 twin and adoption studies was conducted recently (Rhee & Waldman, 2002). Antisocial behavior was operationalized four different ways: (1) diagnosis of antisocial personality disorder or conduct disorder by DSM criteria, (2) criminality or delinquency by official records, (3) behavioral aggression, and (4) antisocial behavior (antisocial behaviors but not operationalized as diagnoses). For diagnosis, aggression, and antisocial behavior, the models that included additive genetic effects, shared environmental effects, and nonshared environmental effects were the best-fitting models, with genetic effects explaining between 44 and 47% of the variance.

CPASB/CPA and Environmental (Nongenetic) Risk Given the evidence that there is a shared environment effect on CPASB and, possibly, aggression, what might the risk factors be? This is a difficult question to answer because of possible gene–environment correlations. In regard to environmental risk factors, three questions can be asked:

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1. What are the potential environmental (nongenetic) mechanisms by which antisocial behavior may be transmitted within families and which occur early enough (prenatally to kindergarten) to precede or coincide with the first signs of early-onset antisocial disorder or aggression? 2. Are these risk factors confounded with genetic risk for early antisocial disorder or aggression, as measured by either parental antisocial behavior or aggression or through genetically informative designs? 3. Have researchers adequately controlled for gene–environment correlations in examining environmental risk factors for child antisocial behavior? Five specific environmental risk factors are discussed briefly in this chapter: having a young or teen mother, maternal cigarette smoking during pregnancy, maternal sensitivity and attachment, coercive parenting practices, and child maltreatment. A composite risk of multiple adversity is also discussed. These risk factors are chosen because they are believed to be the final pathway through which other factors operate, are supported by developmental theory, are potentially modifiable and therefore candidates for intervention studies, or, if causal, open up a new field of investigation (e.g., prenatal exposure to tobacco smoke). In addition, they also illustrate the difficulties of disentangling gene from environment effects in studying the intergenerational transmission of early-onset antisocial disorder.

Young or Teenage Parenting In two longitudinal studies of trajectories of physical aggression, teen motherhood was a significant risk factor for trajectories of high aggression. This was the case for aggression trajectories between ages 6 and 15 years (Nagin & Tremblay, 2001) and 7 to 42 months of age (Tremblay et al., 2004). For boys ages 6–15, having a teen mother also predicted which boys would be in a chronic high aggression path versus a high but declining path. Young maternal age at birth is associated with serious offspring antisocial behavior (Nagin, Pogarsky, & Farrington, 1999; Wakschlag et al., 2000; Martin & Burchinal, 1992; Jaffee, Caspi, Moffitt, Belsky, & Silva, 2001a; Hardy et al., 1997; Christ et al., 1990; Fergusson & Lynskey, 1993). This association is strongest for maternal age at first birth rather than maternal age per se (Wakschlag et al., 2000; Jaffee et al., 2001a).

Maternal Cigarette Smoking during Pregnancy Maternal smoking was a significant risk factor for stable high aggression trajectories in infancy (Tremblay et al., 2004). A number of research studies have suggested that maternal prenatal tobacco smoking is a risk factor for conduct disorder or related constructs (criminality, delinquency, and violent criminal-

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ity) (Olds, 1997; Fergusson, Woodward, & Horwood, 1998; Rasanen et al., 1999; Weissman, Warner Wickramaratne, & Kandel, 1999; Brennan, Grekin, & Mednick, 1999; Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002; Wakschlag et al., 1997). A recent study has found an interaction between maternal sensitivity and maternal smoking on the development of conduct disorder in offspring (Wakschlag & Hans, 2002).

Maternal Responsiveness and Attachment Maternal responsiveness to infant behaviors is broadly defined as action by the mother that is contingent on a cue from the infant and is appropriate in its type, timing, and intensity to the needs of the infant. Unlike coercive parenting behaviors, which are dependent on response to oppositional behaviors seen in toddlers and older children, maternal responsiveness can be assessed near birth and in the context of infant behaviors that are unrelated to aggression or oppositional behavior. It is also believed that maternal responsiveness provides the foundation for the development of behavioral regulation and social competence in children (Wakschlag & Hans, 1999). Maternal responsiveness during infancy (rated at 4, 12, and 24 months) has been shown in one study to predict offspring disruptive behavior (diagnoses of DSM-III-R conduct disorder or oppositional defiant disorder or a symptom count of criteria from these disorders) in middle childhood. The mothers were either opiate addicts or controls for low-income neighborhoods (Wakschlag & Hans, 1999). In a subsequent study on the same sample, maternal responsiveness was found to interact with exposure to cigarette smoke prenatally in predicting offspring conduct problems (Wakschlag & Hans, 2002). Although early research on the role of attachment in the development of aggression has highlighted the importance of the avoidant category (Renken, Egeland, Marvinney, Mangelsdorf, & Sroufe, 1989), more recent work has uncovered an association between attachment disorganization, specifically, and aggressive behaviors in children. In a sample of high-risk infants, clinically elevated levels of aggressive behavior at age 5 were found in 44% of disorganized children but in only 5% of the secure group (Lyons-Ruth, Alpern, & Repacholi,1993). The association between attachment disorganization and aggression was observed in the same sample 2 years later (age 7). Another study found that the majority (60%) of children classified as disorganized also showed clinically elevated levels of aggressive behavior, as compared with 17% of their peers classified as secure (Shaw, Owens, Vondra, & Keenan, 1996). Although attachment disorganization seems to be a significant contributor to the development of aggression in children, recent evidence indicates that it is better considered in interaction with other risk factors. In one study, attachment disorganization predicted child aggression only in the context of problems in information processing (“mild mental lag”) (Lyons-Ruth, Easter-

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brooks, & Cibelli, 1997). Infants both classified as disorganized at age 1 and perceived by their mothers as having a difficult temperament at age 2 were particularly at risk for manifesting high levels of aggression at school age (Shaw et al., 1996).

Coercive Parenting Practices A test of one of the most comprehensive models in the field of child aggression (Patterson, 1982; Reid & Patterson, 1989, Eddy, Leve, & Fagot, 2001) provided evidence for a link between coercive maternal behavior and aggressive behavior for both boys and girls. Maternal coercive behavior and lack of affectionate behavior predicted both high and increasing levels of aggressive behavior, especially in boys (McFadyen-Ketchum, Bates, Dodge, & Pettit, 1996). In research on aggression in toddlers, maternal negative dominance in interaction with male gender and difficult (dysregulated) temperament was a predictor of aggression in the child (Rubin, Hastings, Chen, Stewart, & McNichol, 1998). Observed aggression and mother-reported externalizing problems were associated significantly with dysregulated temperament only for boys with mothers who demonstrated relatively high levels of negative dominance. In a study designed to clarify the influence of socioeconomic factors (operationalized as mother’s and father’s years of education and occupational status) in the development of conduct problems and aggressiveness in young children, several socialization indicators predicted externalizing and aggressive behavior (Dodge, Pettit, & Bates, 1994). Of this set, the strongest individual contribution to the prediction of aggressive behavior in the children came from the level of exposure to harsh discipline as experienced by the child. In a study of 46 parent-referred problem children, negative and directive maternal behaviors were predictive of maternal ratings of aggressive behavior in the child (Campbell, Breaux, Ewing, & Szumoski, 1986). The authors concluded that negative and coercive mother–child interactions are significant contributors to the long-term maintenance of early-onset aggressive behavior. Maternal coercive parenting at 5 months predicted a stable high trajectory of infant aggression from 17 to 42 months (Tremblay et al., 2004).

Child Maltreatment Child maltreatment has been associated with a number of problematic developmental outcomes, especially physical aggression and aggression-related behaviors. A number of researchers have found that physical abuse, in particular, is predictive of elevated levels of aggression in toddlers, preschoolers, and school-age children (Dodge, Bates, & Pettit, 1990; Dodge, Pettit, Bates, & Valente, 1995; Downey & Walker, 1992; Erickson, Egeland, & Pianta, 1989; Malinosky-Rummel & Hansen, 1993). Moreover, physical abuse during childhood has been linked to aggression-related behaviors, such as delinquency, antisocial behavior, and criminal activity, during adolescence and

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adulthood (Herrenkohl, Egolf, & Herrenkohl, 1997; Muller & Diamond, 1999; Widom, 2001). A recent longitudinal birth cohort study suggests that child maltreatment may interact with a common gene on the X chromosome for monoamine oxidase A (MAOA) to produce CPA, at least in boys (Caspi et al., 2002). In that study, 36.8% of the males had the low-MAOA-activity form of the gene. By itself, the low form did not confer risk for antisocial behavior or for being maltreated, as compared with the high-MAOA-activity form. Maltreatment alone, however, did confer some increased risk. The low-MAOA gene, in interaction with maltreatment, had a significant and meaningful increased risk for antisocial behavior, defined four different ways: conduct disorder, conviction for violent offenses, a continuous score of disposition toward violence, and a continous score measure of antisocial personality disorder.

Multiple Adversity Some studies suggest that it is the cumulation of risk factors that is important in the development of early-onset antisocial disorder (Rutter, Tizard, Yule, Graham, & Whitmore, 1976; Shaw, Vondra, Hommerding, Keenan, & Dunn, 1994; Fergusson, Horwood, & Lynskey, 1994). The evidence is strong that the more adversity, the greater the probability of developing CPA/CPASB. The effect of multiple risks is above and beyond that of the additive effects of each risk, suggesting that it is multiple risk itself that is possibly causal.

The Association between Parental Antisocial Behavior and Risk Factors Do these risk factors occur more commonly in families in which parents exhibit antisocial behavior? The evidence for the association between the aforementioned risk factors and parental antisocial behavior comes from two types of studies—studies of adult outcomes of children with CPASB and studies that have assessed the relationship between antisocial disorder in parents and the risk factors. The adult outcomes of children with early-onset antisocial disorder include the very outcomes that are also considered risk factors for early-onset antisocial disorder. Girls and boys with antisocial behavior are more likely to become teen parents. In a recent adult outcome study of a birth cohort of children in Dunedin, New Zealand, the authors stated: “Research into the consequences of teenage parenthood should begin to address the implications of the strong link between antisocial behaviour and teenage parenthood. Most of the infants born to teenage parents have at least one antisocial parent, and many are born to two [antisocial] parents” (p. 197) (Moffitt et al., 2001). There are also strong associations between conduct disorder in girls and smoking (Boyle et al., 1993; Hawkins, Catalano, & Miller, 1992; Kandel et al., 1997). Multiple adversity in adult life appears to be particularly associated with childhood histories of conduct problems. Among a sample of adults who in

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childhood were either in the care of child welfare authorities or from a poor neighborhood, multiple social adversity was found almost exclusively in those with a history of conduct disorder (Zoccolillo, Pickles, Quinton, & Rutter, 1992). The current diagnostic construct of antisocial personality disorder is based on the empirical observation that adults with pervasive dysfunction across several domains and who have antisocial behavior almost always have histories of child conduct problems (Robins, 1966). Turning to studies on parents, there is again good evidence for an association between antisocial behavior and the five risk factors examined here. Coercive parenting has been found to be associated with parental antisocial behavior (Verlaan & Schwartzman, 2002; Patterson, DeGarmo, & Knutson, 2000; Bosquet & Egeland, 2000; Johnson, Cohen, Kasen, Smailes, & Brook, 2001). Adults who report child neglect have higher rates of antisocial personality disorder (Robins & Regier, 1991, Table 11-1, p. 261), and infants and toddlers of women who were aggressive in childhood have higher rates of hospitalization for accidents (Serbin, Peters, & Schwartzman, 1996). Maternal sensitivity has been found in three separate studies to be associated with maternal conduct disorder (Cassidy, Zoccolillo, & Hughes, 1996), a history of maternal aggression (Serbin, Peters, McAffer, & Schwartzman, 1991), or maternal antisocial personality disorder (Hans, Bernstein, & Henson, 1999). Maternal smoking during pregnancy is associated with paternal antisocial personality disorder and parental criminality (Fergusson et al., 1998; Wakschlag et al., 1997).

Parental Antisocial Behavior and Risk Factors for CPASB/CPA in Québec Although many studies have found an association between parental antisocial behavior and/or disorder and risk factors for CPASB/CPA, there has been no population-based study of child development that has prospectively assessed both maternal and paternal antisocial behavior and risk factors. This has made it difficult to estimate the strength of the association between risk variables and parental antisocial behavior. To supplement these data, we present findings from the Longitudinal Study of Child Development in Québec (LSCDQ) (Jette, Desrosiers, Tremblay, & Thibault, 2000; Zoccolillo, 2000). The LSCDQ assessed maternal and paternal antisocial behavior in a sample of 2,223 infants who were 5 months old. These infants were selected from birth certificate records using a three-stage sampling design in order for them to be representative of all infants of the province of Québec, Canada. Maternal and paternal conduct problems, specified as behaviors occurring before the end of high school, were assessed by self-report. Maternal behaviors included stealing more than once (17.8%), starting more than one fight (3.3%), involvement with the police or youth protection because of misbehavior (4%), skipping school more than twice in one year (47.6%), and running away from home overnight (9.6%). Paternal behaviors included stealing more than once (27.1%), starting more than one fight (10%), involvement

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with the police or youth protection because of misbehavior (8.7%), and suspension/expulsion from school (20%). The associations between the number of maternal conduct problems and a variety of potential risk factors for adverse child development are shown in Table 17.1. Note that maternal conduct problems predicted whether the biologic father was missing from the home. Table 17.2 shows the association between the number of paternal conduct problems for biological fathers living in the home and potential risk factors. Tables 17.1 and 17.2 illustrate very clearly, in this population-based sample, the association between a measure of parental antisocial behavior (number of conduct problems) and a variety of possible risk factors. The risk is most pronounced at the level of 3–5 conduct problems, which is similar to the DSM-IV cutoff for a diagnosis of conduct disorder. What proportion of infants with multiple risks come from homes with antisocial parents? An index of multiple risk was created by a sum score of

TABLE 17.1. Risk Factors by the Number of Maternal Conduct Symptoms Number of conduct symptoms 0 (n = 955)

1 (n = 759)

2 (n = 275)

3–5 (n = 129)

7.3

12.9

13.4*

24.7*

< .001

13.5

18.5

18.8

32.2

< .001

7.1

8.6

10.2*

19.3 *

< .05

24.5

24.0

28.4

41.7

< .01

13.0 *

< .001

p

Sociodemographic status Had first child when age 19 or younger No high school degree Biological father no longer in the home Insufficient household income (Statistics Canada definition) Substance use Used illegal drugs in the past 12 month

1.2**

Ever drunk (5 or more drinks on one occasion) in past 12 months

9.2

16.2

23.5

31.8

< .001

15.0

29.4

38.8

50.2

< .001

Smoked during pregnancy Used illegal drugs during pregnancy

0.2**

3.7

2.1**

4.2**

2.0**

5.9 **

Note. Data from Institut de la Statistique du Québec, ELDEQ 1998–2002. *Coefficient of variation between 15% and 25%; interpret with caution. **Coefficient of variation higher than 25%; imprecise estimate for descriptive purposes only.

< .001

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363

TABLE 17.2. Risk Factors by the Number of Paternal Conduct Symptoms in Two-Parent Families Number of conduct symptoms 0 1 (n = 1,067) (n = 457)

2 (n = 208)

3–5 (n = 102)

p

No high school degree

13.2

17.6

24.6

25.6*

< .001

College degree

43.2

35.4

26.9

12.5**

< .001

Unemployed

11.6

11.4

18.0*

20.3*

< .05

Currently daily smoker

21.5

33.8

42.8

55.3

< .001

Used illegal drugs in the past 12 month

4.6*

7.6*

11.0*

20.6*

< .001

Mean number of times drunk (5 or more drinks on one occasion)

4.2

7.4

7.0

13.1

< .001

Maternal behaviors of partner Mother had 2 or more conduct symptoms

12.9 20.0 (n = 1,048) (n = 451)

30.8 (n = 204)

30.7* (n = 101)

< .001

Mother smoked during pregnancy

19.4 26.1 (n = 1,062) (n = 456)

31.3 (n = 208)

42.7 (n = 103)

< .001

Note. Data from Institut de la Statistique du Québec, ELDEQ 1998–2002. *Coefficient of variation between 15% and 25%; interpret with caution. **Coefficient of variation higher than 25%; imprecise estimate for descriptive purposes only.

four risk factors: (1) mother does not have high school diploma, (2) family in lowest income category, (3) mother smoked during pregnancy, (4) mother had first child before age 21. A dichotomous measure of parent antisocial disorder was created. Because one conduct problem was relatively common in the mothers and studies have suggested that it is the presence of multiple conduct problems that is particularly associated with pervasive and persistent antisocial disorder (Zoccolillo et al., 1992; Robins, 1966), infants were dichotomized into two groups where data on antisocial disorder was available for both parents—infants who had mothers and fathers who had no or one conduct symptom versus all other infants. Studies have suggested that biological fathers not living in the home are more antisocial than nonmissing fathers (Caspi et al., 2001; Jaffee, Caspi, Moffitt, Taylor, & Dickson, 2001b), and in our sample infants with the most antisocial mothers were also the most likely to have biological fathers not living in the home. Therefore, infants with biologic fathers not living in the home were also placed in the “all others” group. Finally, some mothers and fathers living in the home did not return the self-administered questionnaires that contained the questions on antisocial behavior, and a small subset of infants not participating in the longitudinal followup (103) were removed from the analyses, leaving a total of 1986 infants.

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The association between the number of risks was cross-classified by the dichotomous parental antisocial disorder/father not in the home measure (Table 17.3). There was a strong and significant association between multiple risk and parental antisocial behavior/father not in the home. Most infants without risk do not have antisocial parents, and most infants with multiple risk have at least one parent with at least two conduct problems or have fathers not living in the home. The association between multiple risk and CPASB/CPA is confounded by parental antisocial behavior.

Controlling for Parental Antisocial Behavior When Examining Risk Factors for CPASB/CPA To summarize the findings: (1) Parental antisocial behavior and offspring early antisocial behavior are associated; (2) parenting practices, maternal sensitivity, child maltreatment, young motherhood, maternal smoking during pregnancy, and multiple adversity are all predictors of CPASB and or CPA; (3) these same risk factors are also associated with parental antisocial behavior; (4) genetically informative designs have consistently found evidence for both shared environment and genetic effects for antisocial behavior and aggression. Given these strong relationships between environmental risk and parental antisocial behavior, have previous studies adequately controlled for gene–environment correlations in examining environmental risk factors for child antisocial behavior? An important question is how can the confound of genetic association be

TABLE 17.3. Proportion of Infants with Nonantisocial Parents by Level of Adversity

Adversity indexa

Mother and father have no or one conduct problem and father is not missingb

None (n = 1,117)

75.1%

One (n = 453)

56.5%

Two (n = 179)

50.3%

Three (n = 107)

36.6%

Four (n = 40)

21.4%

Note. n = 1,896; χ2 = 121.34, 4 df, p < .000 (corrected for design effect of 1.3). aSum of 4 risks: Mother does not have high school degree; in lowest income category; mother smoked during pregnancy; mother had first child before age 21. bInfants classified into two parent groups: (1) Mother and father have no or one conduct problem and father is not missing; (2) all other combinations of maternal and paternal conduct problems and those with fathers not living in the home. Homes where mother or father was present but did not return valid questionnaire on antisocial behavior were excluded.

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controlled for when testing a specific risk factor? A critical question is whether genetically informative designs (twin and adoption studies) are necessary to control for parental antisocial disorder when testing a specific risk factor. The adoption design is not feasible to examine the critical question of why children exposed to maltreatment and multiple adversities are more likely to grow up to be antisocial, because adopted children are generally not placed in adoptive homes where maltreatment and severe adversity will occur (Rutter, 1997). Another, related, problem with adoption studies is that the maternal prenatal environment is often not well assessed. Given the association between maternal and paternal antisocial disorder, maternal prenatal smoking, and offspring antisocial behavior, this could lead to an overestimate of genetic effects. Twin studies are limited because the families most of interest are those of twins with one or more antisocial parents and/or twins with severe adversity, maltreatment, or other risk factors. Furthermore, the ideal studies are prospective studies and studies based on observational data collected before the twins show aggressive or antisocial behavior. This requires recruiting from the pool of twin births. Because approximately 1 in 100 deliveries is a twin birth, recruiting 100 twin pairs requires screening 10,000 births (Vogel & Motulsky, 1996). However, if twins with an antisocial parent are required (assuming 10% of twins have an antisocial mother or father), then 100,000 births will have to be screened and 1,000 twin pairs recruited. Even this is limiting, as the end result will be approximately 30 monozygotic and 70 dizygotic twin pairs with an antisocial parent. A recently developed twin study of high-risk infants is the Environmental Risk (E-Risk) Longitudinal Twin Study (Jaffee, Moffitt, Caspi, & Taylor, 2003). This sample of twins was based on the Twins Early Development Study, a register of all twins born in England and Wales in 1994–1995. During this time 15,906 twin pairs were born, of whom 71% joined the register. From this pool, a subset of 1,116 twin pairs was drawn, of whom one-third were those of mothers whose first birth was less than 20 years of age and the rest were representative of all twins. Of note is that this twin sample was specifically designed to look at environmental risk and includes assessments of antisocial behavior in the parents. Few researchers, however, are able to access such large twin samples. Can the twin design be useful in identifying specific environmental effects? First, as noted earlier, it is important to study twins with antisocial parents so as to have the twins exposed to the type of risk seen in infants of antisocial parents. Apart from the large number of twins needed to find twins meeting this criterion, the twin design itself poses a particular problem for studying children of antisocial parents. Mothers of dizygotic twins are considerably older than mothers of monozygotic twins (Vogel & Motulsky, 1996). Furthermore, mothers who postpone childbearing to later in life, because of education and/or career, and who then require fertility treatment are likely have dizygotic twins as a result. Because antisocial mothers have children at a

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younger age, this raises the possibility that identical twins will be more likely to have antisocial parents than dizygotic twins. Differences in environment between monozygotic and dizygotic twins must be properly examined and accounted for, as the key assumption of twin studies is that the environments of monozygotic and dizygotic twins are similar. Nonetheless, a twin high-risk design is a powerful tool for examining environmental effects. In the E-Risk study noted earlier, combining behavior genetic and epidemiologic analysis showed that “children who resided with antisocial fathers received a ‘double whammy’ of genetic and environmental risk for conduct problems” (Jaffee et al., 2003, p. 109). Because adoptive designs are not feasible, and twin designs suitable for addressing questions such as maltreatment or multiple risk are methodologically intensive and require large populations of twin births, is there another alternative? The answer is a qualified yes. The solution is to control for antisocial behavior in both biological parents when measuring the effects of the suspected risk factor. It is important to note that this method can be used to control for genetic transmission but cannot be used to address the question of proportion of variance of the outcome explained by genes or environment. It is also important to note that the “genotype” measured is very imperfectly measured through parental phenotype. If the wrong phenotype is measured, then it will not be an adequate control. An example of how this can occur is provided by the adoption and family studies examining the association between unexplained somatic complaints in women and antisocial behavior or disorders in their male relatives. The evidence is strong that multiple somatic complaints in women are genetically related to antisocial behavior in men, seen most dramatically in the excess of somatic complaints in the adopted daughters of violent alcoholic fathers (Bohman, Cloninger, von Knorring, & Sigvardsson, 1984). Controlling for overtly antisocial behaviors in the mother may still not adequately control for genotype. Before turning to the literature to see whether studies of suspected risk factors for offspring early-onset antisocial disorder have controlled for parental antisocial disorder, some issues of measurement need to be addressed: (1) classification of parents for use as a control variable, (2) assessing both parents, and (3) modeling both parents. These issues are discussed in turn in the following paragraphs. Classifying parents for use as a control variable is problematic because there is no clear boundary between “antisocial” and “not antisocial.” For example, even one child conduct-disorder symptom in childhood is associated with an increased risk for antisocial behavior in adult life (Robin, 1966). Because the reason for controlling for parental antisocial behavior is to remove any covariance between parental antisocial behavior and child antisocial behavior in order to test the independent effects of other variables, the measure of parental antisocial behavior should be broad enough to capture the full continuum of parental antisocial behavior.

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Two common measures used as a control for parental antisocial behavior are a diagnosis of antisocial personality disorder and criminality (e.g., arrests, convictions). Both are problematic because they are dichotomous measures, and many parents without a diagnosis or without criminality are still likely to have antisocial behavior. With regard to DSM-IV antisocial personality disorder (APD), three child symptoms and three adult symptoms are required to meet the criteria (American Psychiatric Association, 1994). This means that those with three child symptoms and two adult symptoms, or two child symptoms and three adult symptoms, would be classified as “No disorder.” In previous work, it was shown that DSM-III (American Psychiatric Association, 1980) criteria for APD identified only about half of young adults with childhoodonset persistent and pervasive antisocial behavior (Zoccolillo et al., 1992). It is highly likely that many parents with some antisocial symptoms, but not enough to meet DSM criteria for APD, will have childhood-onset persistent and pervasive antisocial behavior. Classifying these parents as not antisocial when investigating risk factors for offspring CPASB/CPA does not adequately control for the possibility of confounding by parental antisocial behavior. Similarly, criminality is also a poor control because, in population samples of adults with DSM-III diagnoses of APD, almost half the men and most women with APD did not have major criminal convictions (Robins & Regier, 1991). Both biological parents need to be assessed for antisocial disorder. The heritability for antisocial behavior was not found to differ for men and women (Rhee & Waldman, 2002), and the effects of parental APD on offspring externalizing disorder were also the same (Connell & Goodman, 2002). Assessing both parents is particularly important because environmental risk factors may be associated with antisocial disorder in one or the other parent. For example, antisocial men may be more prone to mate with teenage females, independent of whether the female also had an antisocial disorder. Although there is good evidence for assortative mating, it is not complete (Krueger, Moffitt, Caspi, Bleske, & Silva, 1998). This means that there will be a large proportion of families in which only one parent has an antisocial disorder. Another major concern is missing biological fathers. Missing biological fathers are likely to be more antisocial than fathers who are present in the home (Jaffee et al., 2001b). Asking the biological mother about the missing biological father is essential and appears to give reliable information (Caspi et al., 2001). Alternatively, missing biological fathers can be incorporated in the theoretical model being tested as a separate category. Both parents also need to be included in the analyses with the child as the unit of analysis. For example, in the LSCDQ there was a strong association between maternal smoking during pregnancy and the number of paternal conduct symptoms (Table 17.2). Controlling only for maternal antisocial behavior when evaluating the effect of maternal prenatal smoking would not adquately control for the child’s genetic background. We have been unable to find any studies of the environmental risk factors

368

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that meet all the aforementioned criteria, except for one recent study of infant aggression (Tremblay et al., 2004) and the Environmental Risk (E-Risk) Longitudinal Twin Study (Jaffee et al., 2003). Although some investigators have attempted to measure antisocial behavior in the parent, most used a diagnostic category of parental antisocial personality disorder versus no disorder (Johnson et al., 2001; Wakschlag et al., 1997), relied on parental criminality (sometimes specified only as familial criminality) (Moffitt et al., 2001; Patterson et al., 2000; Fergusson et al., 1998; Rutter et al., 1976), or used personality disorder scales from the Minnesota Multiphasic Personality Inventory (Patterson et al., 2000; Wakschlag et al., 1997). To summarize, none of the studies have demonstrated good control of parental antisocial disorder. It would be difficult to conclude that maternal smoking during pregnancy, teenage motherhood, maternal sensitivity, parenting practices, maltreatment, or multiple adversity is causal for the development of early-onset antisocial behavior, as these factors are confounded by parental antisocial disorder.

DIRECTIONS FOR FUTURE RESEARCH It is critical for studies that are attempting to identify the causes of antisocial behavior to take into account the familial transmission of antisocial disorder and that antisocial disorder in parents is strongly associated with a multiplicity of environmental risk factors for their offspring. At the population level, the association between parental antisocial disorder and adversity, particularly multiple adversity, is large. Researchers cannot ignore that fact that a significant proportion of children living in adversity he found to have an antisocial parent. There are several implications of these findings. First, it is critical to study families with antisocial parents. Although the difficulties of studying these families and the complexity of multiple risk factors may appear to be daunting, these families are not rare and account for a large proportion of antisocial youth, particularly the most severely affected children. Second, children with antisocial parents are exposed to multiple risk factors that start very early. Teasing out which risk factors are causal for antisocial disorder in the child is the challenge. Tests of hypotheses need to be well structured to control for confounds and to test for interactions. Of critical importance are studies of the developmental sequence of risk factors and behaviors. Priority should be given to studies that start prenatally or at birth. To test whether poor parenting practices are a causal risk factor for early antisocial disorder requires demonstrating that these parenting practices precede the emergence of early-onset antisocial disorder. This is not an easy task, inasmuch as coercive parenting practices may emerge only when the child develops normal opposition behaviors in the toddler years, making it difficult to determine the time order of effects. Controlling for parental antisocial disor-

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der is critical in such design because the same genetic mechanism could potentially lead to an antisocial parent, poor parenting practices, and offspring antisocial disorder (Ge et al., 1996; O’Connor, Deater-Deckard, Fulker, Rutter, & Plomin, 1998). Third, as much attention needs to be paid to defining “antisocial behavior” in the parent as in the child. Future studies should avoid using criminality as the sole measure of parental antisocial disorder, as it is neither sensitive nor specific enough to be useful. The LSCDQ study has shown that parents in a population sample will answer questions on their own child and adult antisocial behaviors. An advantage of assessing a broad range of child and adult antisocial behaviors in parents is that the researcher can then use latent variable methods to cluster parents into homogenous groups or to create a latent continous variable. It also becomes possible to test whether there are distinct familial types of antisocial behavior—for example, early-onset versus adolescentonset. Ideally, the same dimensions of aggression and antisocial behavior assessed in the child should be assessed in the adult. Little is known about whether parental aggression is specifically associated with child aggression, for example. Fourth, both biological parents must be assessed. Controlling for one parent only is not adequate, as assortative mating is incomplete and antisocial disorder is more common in males than in females. Missing biological fathers need to be accounted for, either by proxy interview of other informants or by having a separate category of “missing father.” Analytic strategies for incorporating data by proxy interview on missing fathers with data from present fathers need to be refined. The analysis of data that incorporates measurements of antisocial behavior in both parents is more complex than treating maternal and paternal antisocial disorder as separate variables in a logistic or linear regression model. For example, fathers are more likely to be missing if the mother is antisocial and are therefore not missing at random which regard to many analyses of interest. This poses considerable problems for most statistical analyses in that maximum likelihood estimates for parameters often cannot be estimated (Little & Rubin, 1987). Analyses of interactions between parental antisocial disorder and other variables (as proxy measures for gene– environment interactions) are also complex. For example, a parent contributes only half of his or her genes to offspring, and path models of parent effects on offspring would need to take this into account (Vogel & Motulsky, 1996). Fifth, randomized controlled trials of interventions to prevent CPA/ CPASB should assess parental antisocial behavior. Little is known about whether promising prevention interventions are also effective in families with antisocial parents. Furthermore, if modifying a risk factor is effective in preventing CPA/CPASB even among children with parents with antisocial behavior, then this strongly suggests a causal role for that factor. In a recent review of studies of conduct disorder, the authors noted,

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“Parsing out the contributions of genetic effects from environmental risk factors to familial antisocial behavior is a significant task that remains largely incomplete” (Burke, Loeber, & Birmaher, 2002, p. 1277). A major challenge of the next 10 years is to fill in the holes in our knowledge of genetic and environmental contributions to the development of early-onset antisocial behavior and aggression through new and better research designs.

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DETERMINANTS Peer Relationships and OF Aggressive AGGRESSION Behavior

18 Peer Relationships and the Development of Aggressive Behavior in Early Childhood M ICHEL B OIVIN , F RANK V ITARO, and F RANÇOIS P OULIN

Children’s peer relationships have been the object of persistent attention by the developmental research community in the last decades. The prevalent view among members of this community is that children’s peer relationships serve important developmental functions (Asher & Coie, 1990; Hartup, 1983, 1996; Rubin, Bukowski, & Parker, 1998). They provide contexts where children may acquire new social skills, learn to self-regulate and solve interpersonal conflict, expand and validate their self-knowledge, and discover the social roles, norms, and processes involved in interpersonal relationships (Rubin et al., 1998). Unfortunately, peer relationships are not always beneficial to the child, as we discuss in this chapter; there are many ways in which specific features of peer relations may impede child development. The present review focuses on peer relationship problems as they relate to aggressive behaviors, inasmuch as aggression has been identified as the prime behavioral correlate of a variety of peer relationship problems in childhood (Rubin et al., 1998; Coie & Dodge, 1998). However, a comprehensive understanding of the association between aggressive behaviors and peer relation problems requires a differentiated view of childhood peer relationships.

THE MANY FACES OF PEER RELATIONSHIPS In examining children’s peer relationships, it is important to recognize that childhood peer relations are multifaceted. Children experience peer relations 376

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through the group aggregate—for example, positive peer status, peer rejection, and peer victimization—through peer networks (Cairns, Leung, Buchanan, & Cairns, 1995), and through dyadic relationships, generally within friendship relations (Hartup, 1996). The distinction between these broadband classes of peer experiences is especially relevant when examining the association between aggressive behaviors and peer relationships. At least two main streams of research have extensively documented the link between aggressive behaviors and peer relationships in childhood. The first line of research is on peer rejection. Indeed, aggressive behavior is the most commonly cited behavioral correlate of peer rejection, an index of negative peer status derived from aggregated sociometric nominations (Rubin et al., 1998). Peer rejection is assumed to reflect difficulties in social integration within the peer group. The second stream of research focuses on the nature of the peer affiliations of aggressive children. According to this line of research, aggressive children, mostly boys, are not socially left out by their peers, but rather tend to associate with each other (Boivin & Vitaro, 1995; Cairns, Cairns, Neckerman, Gest, & Gariépy, 1988; Dishion, Andrews, & Crosby, 1995a). Thus, aggressive children may suffer from exclusion and ostracism by normative peers, as well as from problematic associations with deviant peers. More fundamentally, this distinction in peer experiences also pertains to putative processes of peer influence (i.e., peer exclusion processes), which are mostly derived from aggregate measures, versus deviant peer socialization processes, which mainly stem from dyadic relationship assessments. In other words, processes of peer influence are heterogeneous; that is, peers may marginalize, as well as provide support to, aggressive children. This review is organized to reflect this distinction in peer experience and process. Over the past 50 years there has been substantial research aimed at documenting, and then at understanding, the nature and meaning of the link between aggressive behaviors and peer relation problems (Hartup, 1983; Rubin et al., 1998). However, most of the more recent research effort has been centered on school-age children. To our knowledge, no one has specifically reviewed the evidence concerning the association between aggressive behaviors and peer relation problems during the preschool period. This lack exists despite evidence that peer relationships are already well established and quite differentiated in the preschool years (see the following section), and notwithstanding their potential influence on the early developmental course of aggressive behaviors. Furthermore, this question is especially timely and relevant to social policy issues because a growing number of children are exposed to peers early in their lives through daycare (NICHD Early Child Care Research Network, 2003). The purpose of this chapter is to provide an overview of the research bearing on the issue of peer relationships and aggressive behaviors in early childhood, that is, during the preschool years and in kindergarten. We start by

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reviewing some of the basic milestones in the early development of peer relationships and aggressive behaviors.

THE FOUNDATIONS OF PEER INTERACTIONS AND PEER RELATIONSHIPS IN EARLY CHILDHOOD Early toddlerhood witnesses the development of many social skills underlying peer interactions. Social interest in peers is clearly present in the first year of life (Buhler, 1931; Vandell, Wilson, & Buchanan, 1980), but it is really during the second year that important gains in interactive skills can be observed. By the end of that year, toddlers have the ability to coordinate behavior in games with play partners. They can reciprocally imitate each other and progressively learn to alternate roles in play, thus indicating that they have acquired expectations about the behaviors of the other (Ross, Lollis, & Elliot, 1982; Strayer, 1989). With the onset of language, peer interactions become more refined and elaborate. Between age 3 and age 5, there is a dramatic increase in pretend play and in positive dyadic social behaviors, reflecting the augmented capacity of the child to adopt the perspective of the play partner (Rubin, Watson, & Jambor, 1978). These emerging social interactive skills are the foundation of early peer relationships. Signs of these relationships are seen in toddlers’ increasing behavioral preference for specific peers (Howes, 1987; Strayer, 1989), and those preferences culminate in stable preschool friendships. These early friendships are often, but not exclusively, embedded in extensive affiliative networks (Strayer & Santos, 1996) and progressively become sex-segregated (Lafrenière, Strayer, & Gauthier, 1984; Maccoby, 1998; Pellegrini, in press). By age 3–4 years, children initiate more play behavior and display more mutual activity with friends than with nonfriends. Further, behavioral homophily, that is, the tendency to befriend or affiliate with peers whose behavior is similar to their own, is already present by the end of preschool. Nevertheless, preschool friendships are not without disagreements, quarrels, and conflicts; there is indeed more conflict among preschool friends than among preschool nonfriends. However, these conflicts are resolved more equally and more often by the use of negotiations and disengagement among friends than among nonfriends (Hartup & Laursen, 1991). Preschoolers also progressively internalize their perceptions about their friends, as well as about other peers with whom they are in contact. At least by age 4, and when asked appropriately, preschoolers will readily and reliably identify best friends, as well as peers they like and peers they dislike. The aggregation of these perceptions reveals a coherent peer status structure within the larger group (Boivin & Bégin, 1986; Boivin, Tessier, & Strayer, 1985; Howes, 1987). Physically aggressive behaviors are also manifested very early in life (Caplan, Vespo, Pederson, & Hay, 1991; Goodenough, 1931; Tremblay,

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2000). They become prevalent by the age of 2, peaking around age 3, before declining steadily with age (Strayer, 1989; Tremblay, 2000; see also Tremblay & Nagin, Chapter 5, and Archer & Coté, Chapter 20, this volume). The emergence of sex differences in aggressive behaviors seems to coincide with the time children start interacting more regularly in preschool groups (see Archer & Coté, Chapter 20, this volume). This transition is also characterized by a shift toward affiliation in the dyadic structure of social participation. Social dominance hierarchies based on agonistic behaviors are established very early, even among groups of infants. However, the ratio of initiated agonistic activity to initiated affiliation is much lower among older preschoolers (Strayer, 1989). Many factors may explain the decline in physical aggression, including language development (Dionne, Chapter 16, this volume), an augmented capacity for perspective taking and empathy (Selman, 1980; Zahn-Waxler, Radke-Yarrrow, & King, 1979), and an increasing awareness of dominance hierarchies (Strayer & Trudel, 1984). There is also the possible emergence of peer group norms and implicit rules with respect to aggressive behaviors. These norms and rules are likely to curb aggressive behaviors by providing a convergent feedback from group members to aggressors. All of this suggests that maturational changes and peer experiences compel a majority of young children to progressively develop a capacity to use other means than overt physical aggression to meet their goals. However, not all of them do. Physical aggression is one specific form of aggressive behavior, and we also need to attend to the other types and functions of aggressive behaviors to fully understand the nature of the developing association between these behaviors and peer relationships. Of special interest here is the distinction between direct and indirect or relational aggressive behaviors, as well as between reactive and proactive aggression, as they reflect changes in the maturational and social processes underlying aggression. For instance, Bjorkqvist, Lagerspetz, and Kaukiainen (1992) have argued that the prevalent form of aggressive behaviors is likely to change over the years, with physically aggressive behaviors giving way to more verbal forms of aggression, and then to more subtle and indirect forms (see Archer & Coté, Chapter 20, and Vaillancourt, Chapter 8, this volume). According to Bjorkqvist and colleagues (1992), these changes would be brought about by the parallel maturational changes in language and social cognitive skills. It is important to determine whether there is heretotypic stability in this normative change (i.e., the same children displaying these different forms of aggressive behaviors over the years) and to assess to what extent peer relationships play a role in the various developmental trajectories of aggression. Clearly, the social lives of preschoolers are elaborate and refined, and the development of peer relationships and aggressive behaviors are intertwined in the preschool years. It is thus important to document and understand the nature of the early association between peer relations and aggressive behaviors. Thus, in the following section of this chapter, we focus on experiences of seg-

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regation by peers in early childhood, specifically peer rejection or ostracism, as they relate to aggressive behaviors. Then we turn our attention to the role of affiliating with aggressive peers in the development of aggressive behaviors during the same age period. In doing so, we adopt an ecological perspective; we consider different contexts of peer influence (e.g., friends and cliques, larger peer groups, daycare centers and schools) and examine the potential influence of specific nonpeer agents (parents, teachers) on children’s relationships with peers.

AGGRESSIVE BEHAVIORS AND PEER REJECTION AND OSTRACISM IN THE PRESCHOOL YEARS Between 5 and 10% of children experience chronic rejection by peers (Coie & Dodge, 1983). These children are at risk for a variety of future adjustment problems, including both internalizing and externalizing difficulties, dropping out of school, and delinquency (Rubin et al., 1998; McDougall, Hymel, Vaillancourt, & Mercer, 2001). Peer rejection could be a cause of these adjustment problems, but this predictive association could also result from an underlying factor, such as the child’s tendency to aggress or another related factor (see Parker & Asher, 1987). There has been much valuable research aimed at confirming the truly causal contribution of peer rejection to later maladjustment (see McDougall et al., 2001). However, evidence substantiating the causal model has been mixed, especially in studies examining the longitudinal associations between peer relationships and aggressive behaviors. This is why the nature of the association between peer rejection and aggressive behaviors has been, and is still, the focus of much interest. There has been abundant research linking aggressive behaviors and negative peer status. Some of this research has been conducted with preschool children (e.g., Boivin, Dorval, & Bégin, 1990; Hartup, Glazer, & Charlesworth, 1967; Masters & Furman, 1981). This research indicates that preschool negative peer status is not only associated with a negative aggressive behavior style, but is also linked to more negative peer experiences (Boivin et al., 1990; Masters & Furman, 1981). These negative peer experiences could reflect the give-and-take of aggressive exchanges. They could also antecede, or follow from, the child’s aggression. However, because behavior and status were measured concurrently in these studies, the causal nature of the relation was in doubt. The question of the direction of the relation between aggressive behaviors and peer rejection was tested more straightforwardly in a series of experimental play-group studies (Coie & Kupersmidt, 1983; Dodge, 1983). In these studies, unacquainted boys were typically assembled and observed in small groups, where their emerging peer status was also assessed. Verbal and physical aggressive behaviors were shown to antecede the emergence of peer rejection, which suggested that these behaviors could be considered as a proximal

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determinant of these difficulties (Coie, 1990). However, because these studies were conducted with school-age children, it is not clear whether this could be the case in preschool. Dodge, Coie, Pettit, and Price (1990) came close to providing an answer to this question in a study that looked at the play-group behaviors of firstgrade children and those of third-grade children in order to investigate age differences in the behavioral predictors of peer status. They also looked at different forms of aggressive behaviors, including reactive aggression, instrumental aggression, bullying, and rough play. Both angry reactive aggression and instrumental aggression, but not rough play, were associated with negative peer status at the end of the sessions at both ages. Bullying was negatively related to status, but only in the third-grade groups. In the first-grade groups, the more popular boys displayed more bullying against aggressive boys, as if to establish their dominance, whereas for older boys, this goal could be attained by more sophisticated strategies. However, it was not clear whether this could be a finding specific to the social ecology of first-graders or whether it reflected a more general developmental trend. Further research in the preschool years is needed to clarify this issue. The studies described so far concur in indicating that aggressive behaviors could be a proximal cause of peer rejection, at least in middle childhood. However, it is actually difficult to form a definitive conclusion for the preschool period. Experimental play-group studies aimed at assessing different types of aggressive behaviors of unacquainted young children may thus be a good strategy to determine whether specific aggressive behaviors antecede peer rejection in the preschool years. The fact that aggressive behaviors may be a proximal cause of peer experiences does not mean that the experience of peer rejection could not also be a cause of aggressive behaviors. In other words, the relation between aggressive behaviors and peer rejection could very well be bidirectional. In fact, there is at least some indirect evidence suggesting that rejection by peers yields aggressive interactions. For instance, when the same behavior is manifested by a popular child and a rejected child, the rejected child received a less positive answer (Dodge, 1983). In familiar groups, rejected boys are more often the target of aggression than popular boys, whereas no difference is found in nonfamiliar groups (Coie & Kupersmidt, 1983). These observations are in line with the two studies of preschoolers presented earlier (Masters & Furman, 1981; Boivin et al., 1990). They suggest that status acquisition in peer group differs from status maintenance, in which reputation biases and scapegoat processes operate (Coie, 1990; Hymel, Wagner, & Butler, 1990). Thus, once established, peer rejection may be associated with negative peer experiences, and aggressive behaviors could also be adopted as a response to these experiences. Could peer rejection and negative peer experiences during the preschool years contribute to subsequent adjustment problems, including aggressive behaviors? The evidence with preschool children is scarce, but a series of studies

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showed that cumulative peer rejection, starting in kindergarten, predicted growth in reactive aggression (rather than proactive aggression; Dodge et al., 2003). Interestingly, in one of these studies, peer rejection in kindergarten contributed uniquely to the prediction of aggressive behaviors in third grade, beyond peer rejection in first grade and peer rejection in second grade. Furthermore, early aggression also moderated the effect of rejection: Only children who were above the median in aggression were likely to show increases in aggression linked to their cumulative experience of peer rejection over the years. These results strongly suggest that the experience of rejection in kindergarten may exacerbate aggressive behavior development only among children initially disposed toward aggression. The fact that it affected reactive aggression, rather than proactive aggressive behaviors, also supports the view that peer rejection is a condition predisposing the child to aggressive behaviors. In sum, the empirical evidence favors a bidirectional model of the association between peer rejection and aggressive behaviors. Aggressive behaviors may lead to rejection by peers, and the experience of being rejected by peers in childhood may play an incremental role in the later development of aggressive behaviors. Not only can this evidence be traced back to the preschool years, but the experience of rejection in kindergarten seems critical in that prediction. It would be highly relevant at this point to substantiate further the potential contribution of peer rejection experiences in preschool to later forms of aggression. In particular, there are specific lines of inquiry that would require attention. The first line of inquiry is process oriented. We need to move beyond the simple description of the associations between aggressive behaviors and peer relations, however specific they may be, to better understand the “dynamics” of these specific behavior–relationship associations during early childhood. Specifically, intraindividual sociocognitive and emotional processes (e.g., social information processing deficits; Crick and Dodge, 1994) may underline, moderate, or mediate the links between peer relations and aggressive behaviors. The early experiences of rejection could influence the child’s sociocognitive processes, leading to social-cognitive deficits and biases, and result in increased aggressive behaviors. For example, retrospective reports of harsh parenting has been associated with the child’s aggressive behaviors in kindergarten, and specific social-cognitive deficiencies, including hostile biases in attributions, accounted for this relation (Dodge, Bates, & Pettit, 1990). These results suggest that social-cognitive processes may mediate the relation between specific aversive experiences and the early development of aggressive behaviors. Mediation through social-cognitive process was also found by Dodge et al. (2003): Negative peer status significantly predicted later aggression, and a significant part of that prediction was accounted for by socialcognitive processes. What is needed is a closer examination of these processes as a function of different forms and functions of aggressive behaviors in preschool. The second line of inquiry is also process oriented, but aims at describing

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the nature of the peer experiences that are conducive to higher aggression. Research on peer victimization may be highly relevant to this objective in that it specifically targets children who truly experience negative treatments by peers. Indeed, peer rejection and peer victimization are related phenomena, but they should not be confounded. Peer rejection is a measure of disliking and reflects a negative attitude of the peer group toward a child, whereas peer victimization is a class of negative behaviors displayed toward a child (Boivin & Hymel, 1997; Boivin, Hymel, & Hodges, 2001). Peer victimization has mostly been documented in middle childhood, but there is evidence that such difficulties may exist in the preschool years (Alsaker & Valkanover, 2001; Kochenderfer & Ladd, 1996), even as early as age 3 for specific forms of indirect or relational victimization (Crick, Casas, & Ku, 1999). However, the main point here is that we need to document the nature of the peer interactions that are associated with actual peer rejection in preschool. Asher, Rose, and Gabriel (2001) have recently identified more than 30 types of rejecting behaviors, which they classified in six different categories (from controlling and dominating a child, to preventing a child from having access to a friend). Some of these ways of rejecting may be relevant for preschoolers. What is needed is a more complete and integrated view of how preschoolers reject another child. Third, social peer interaction processes may also underlie, mediate, or moderate the negative impact of aversive peer experiences, as well as the association between peer relations and aggressive behaviors. For example, group norms (Boivin, Dodge, & Coie, 1995; Stormshak, Bierman, Bruschi, Dodge, & Coie, 1999) and specific relationships (e.g., affiliation with aggressive children; Boivin & Vitaro, 1995; having a protective friend; Hodges, Boivin, Vitaro, & Bukowski, 1997) have been shown to moderate the links between peer experiences and aggressive behaviors among school-age children. We need to know whether and how these moderation effects operate in the preschool period. Two final considerations are warranted: First, it is important to note that some aggressive children may actually possess fairly high social status in the group (e.g., Prinstein & Cillessen, 2003; Rodkin, Farmer, Pearl, & Van Acker, 2000), especially if the groups norms are supportive or neutral in regard to aggressive behaviors (Boivin et al., 1995). This is more likely the case among young children, because specific forms of aggressive behaviors (i.e., the instrumental/ proactive type) are sometimes positively related to popularity. When this is the case, aggressive behaviors may be more likely to be valued and reinforced by, as well as generalized within, the peer group. Consequently, high-status aggressive preschoolers should be the focus of attention in future research. Finally, despite the growing awareness that girls and boys may express aggressive behavior differently (Bjorkqvist et al., 1992; Crick & Grotpeter, 1995; Underwood, 2003), most of the research on peer relations and aggression has been conducted with boys. Greater attention should be devoted to sex differences in the early study of the linkages between direct and indirect/ relational aggression and peer rejection in the preschool years.

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AN ECOLOGICAL PERSPECTIVE OF PEER INFLUENCE ON AGGRESSIVE BEHAVIOR DURING EARLY CHILDHOOD A full understanding of the role played by the child’s peer affiliates must take into account the fact that these peer relationships are embedded in other, larger social contexts (Dishion, French, & Patterson, 1995b). Accordingly, different levels of the young child’s social world are discussed in the following sections of this chapter. The interactions between friends and clique members are examined first. Typically, however, these interactions are embedded in a larger peer group and take place in settings such as children’s homes, neighborhoods, daycare centers, and schools. These settings vary greatly in terms of the amount of structure, adult supervision, and type of peers encountered, all conditions that may have a bearing on the development of aggressive behaviors. Finally, in analyzing these different contextual “levels,” we examine the roles of parents and teachers in overseeing, supervising, and managing the child’s relationships with peers during the preschool period (Ladd & Le Sieur 1995; Parke & O’Neil, 1999).

Friends and Cliques Although they are rejected by conventional peers, many aggressive preadolescents and early adolescents have friends, and most of them participate in cliques (Boivin & Vitaro, 1995; Cairns et al., 1988). This seems to be true also for young children (Farver, 1996; Snyder, Horsch, & Childs, 1997). For instance, Farver (1996) showed that children at the center of teacher-identified peer networks of 4-year-olds were also the most aggressive. Only a few studies have examined whether homophily with respect to aggression (i.e., the tendency for aggressive children to affiliate with other aggressive children) exists among young children. For instance, members of teacher-identified cliques of 4-year-olds were found to be moderately similar in aggression, as assessed by independent observers (Farver, 1996). Four- to five-year-old children were more likely to select friends who were similar in respect to teacher-rated aggression; that is, 50% of aggressive children’s friends were aggressive, as compared with 12% of nonaggressive children’s friends (Snyder et al., 1997). A further study is worth considering, in spite of the fact it was conducted with grade school children; in this study, clique membership in first grade was associated with similar characteristics in respect to aggression (Estell, Cairns, Farmer, & Cairns, 2002). Thus, the few available studies suggest that aggression-related homophily exists in early childhood at the dyadic and the clique levels, conditions that extend onward, and perhaps increase, into middle childhood and adolescence. Many convergent processes may account for aggression homophily (Kandel, 1978). Aggressive children may associate because they are actively rejected by conventional peers and gradually cast out of the group, leaving them with no other choice than to affiliate with other aggressive children

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(Patterson, Reid, & Dishion, 1992). It may be that aggressive children proactively select other aggressive children, partly because they share an interest for rough play, but also because their mutual selection allows them to dominate other peers and to have better access to resources in the peer group (Boivin & Vitaro, 1995; Poulin & Boivin, 2000). This latter view is in line with the confluence model of Dishion, Patterson, and Griesler (1994) that posits a gradual convergence of aggressive children into homogeneous groups of aggressive and risk-taking adolescents. The confluence model implies an increasingly active selection of aggressive peers who share similar attitudes toward aggression. Once established, these deviant associations may also accentuate the behavioral similarity by having aggressive children mutually influencing each other, through deviancy training (Dishion et al., 1995a; see the discussion of “mechanisms” below). To the extent that these mechanisms have cumulative effects over time, aggressive children could be progressively trapped in a social environment that is increasingly segregated from that of their better-adjusted peers. There is evidence that aggression homophily increases with age from middle childhood to late adolescence (Dion & Boivin, 2003; Neckerman, 1992). However, whether these processes are operative in the preschool years is not known.

Are (Deviant) Friends Significant for Later Adjustment in Early Childhood? Very few studies have examined this question among preschool children. Snyder et al. (1997) reported a short-term effect of interacting with aggressive peers. They found that the amount of time preschoolers spent with aggressive peers predicted an increase in observed and teacher-rated aggressive behavior over a 3-month interval. Conversely, children who spent minimal time (less than 15%) with aggressive peers showed a decrease in aggression over the subsequent 3-month period. The findings of Snyder et al. (1997) indicate that aggressive friends may have a negative influence during early childhood. However, this effect was measured only over a 3-month period. Whether a similar long-term effect exists at that age is still unknown.

What Are the Mechanisms That Could Account for the Possible Influence of Aggressive Friends? The answer to this question assumes that aggressive peers mutually influence each other through some form of socialization mechanisms and that this influence is not spurious, that is, attributable to a third factor such as a personal disposition or a family factor (see Vitaro, Tremblay, & Bukowski, 2001). Work by Dishion and colleagues on rule-breaking talk during dyadic interactions involving deviant adolescents indicates that positive verbal reinforcement by peers of past, actual, and future deviant behaviors becomes increasingly important in shaping social behavior (Dishion et al., 1995a). This process, labeled “deviancy training,” has received substantial empirical sup-

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port. For example, the association between exposure to deviant peers by age 10 and growth in arrests, substance use, and sexual intercourse from ages 10 to 18 is mediated by deviancy training at age 14 (Patterson, Dishion, & Yoeger, 2000). However, very little is known about deviancy training in young children. A precise examination of this process with young children is needed to confirm its existence in early childhood. Direct training through conflicts and coercion among friends or clique members may also play a role in explaining how and why affiliation with aggressive friends might instigate or increase aggressive behaviors. In their classic observational study of preschoolers’ aggressive interactions, Patterson, Littman, and Bricker (1967) showed that the principles of operant conditioning maintain aggressive behavior in the peer context. They found that the response to an aggressive behavior conditioned the likelihood of reenacted aggression in the future. When a child who was the victim of aggression reacted by withdrawal and submissive behaviors, the aggressor was more likely to subsequently attack the same target than when the victim retaliated. Negative reinforcement in coercive peer interactions may thus shape young children’s behaviors in the same way it shapes this behavior during child–adult coercive interchanges. Similarly, the use of verbal aggression is followed by termination of a conflict episode for aggressive children, whereas a positive verbal interchange or the absence of a response terminates the conflict episode for nonaggressive children (Snyder & Brown, 1983). In other words, aggressive children are negatively reinforced for using coercive behaviors with their peers, whereas nonaggressive children are reinforced for using nonaversive strategies. Hence, peer interactions during preschool years are sometimes occasions for coercive interchanges among peers which may, under some conditions (e.g., child’s submissiveness, adult and peer tolerance of aggression), serve as learning opportunities for aggression. If these conditions are present, then preschool and early elementary school settings may provide training grounds for further shaping of aggressive behaviors in children who may already have learned them at home. It is not clear, however, whether this type of training is taking place within dyadic friendships or among members of a clique. Given the higher incidence of conflicts among preschool friendships involving at least one aggressive child, this could be the case (Snyder et al., 1997). However that may be, there are possible caveats to the long-term impact of deviancy training in preschool.

Caveats to Deviancy Training in Preschool Why would affiliating with aggressive friends have little long-term effect on the behavior trajectory of young children? One possible reason is that preschool children do not systematically and exclusively affiliate with other aggressive children as much as preadolescents or adolescents do. Indeed, in the three preschool studies reviewed earlier, aggression-related homophily was

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moderate. Hence, behavioral homophily may not yet be firmly established and specialized during the preschool years. Young aggressive children may have access to a variety of peers and friends, and these experiences may mitigate the negative influence of deviant peers. For instance, to the extent that many aggressive children are not rejected by conventional peers during early childhood, they would be less likely to be deprived of positive socialization experiences. Another related possibility is that the associations among aggressive preschoolers may be short-lived. There is indeed evidence showing that childhood friendships are not always stable and that clique composition may change substantially over a period of weeks, especially when involving aggressive children (Cairns et al., 1995; Parker & Seal, 1996). However, Snyder et al. (1997) found no difference in the stability of strong mutual affiliations of aggressive and nonaggressive children, although aggressive children were less likely than nonaggressive children to establish strong mutual affiliations with classmates. Other researchers also reported that friendships during the preschool years can be relatively stable and intimate (Howes, 1987). Furthermore, young children’s friendships may not carry the same weight as those of older children. Indeed, these early friendships are based on concrete exchanges rather than shared values and interests, loyalty, and mutual support (Bigelow, 1977), qualities that may induce greater mutual influence on behavior. Finally, aggressive preschoolers may simply be more sensitive to adult rules than older aggressive children. Hence, parents and teachers may exert a moderating effect on aggressive friends’ influence by controlling children’s behavior more closely and effectively. Parental supervision may also play a similar role. In contrast to those of adolescence, the preschool peer environments are more closely structured and supervised by adults. However, even during preschool years the social settings may vary greatly in terms of adult structure and supervision, and this could make a difference with respect to exposure to deviant peers. For instance, the degree of parents’ monitoring of their kindergarten child has been associated with the child’s exposure to deviancy-producing experiences and aggressive peers in a variety of contexts (Kilgore, Snyder, & Lentz, 2000). Longitudinal studies that examine whether aggression-related homophily increases from the preschool years to late childhood are clearly needed. In addition, it would be important to determine whether homophily is driven by specific forms of aggressive behaviors (i.e., proactive aggression rather than reactive aggression), as this seems to be the case with older children (Poulin & Boivin, 2000). Moreover, it would be relevant to learn about the qualitative features of friendships during this period in order to understand why the early encounters with aggressive children may or may not leave traces in the long term.

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The Larger Peer System By and large, our discussion of the peer influence on aggression in early childhood has been limited so far to the peers with whom the child forms affective bonds and spends more time interacting with, such as friends or clique members. However, the larger peer group to which the child is exposed may also have a unique impact on the level of aggression, especially in the case of stable peer groups, such as daycare groups or kindergarten classrooms. As already suggested, group norms with respect to aggression seem to be very salient during early childhood and may interact with initial dispositions for aggression. For example, it was found that a high level of aggression in a first-grade classroom uniquely contributed to an increase in aggression over a 5-year period for children who were already displaying high levels of aggression (Kellam, Ling, Merisca, Brown, and Ialongo, 1998). In other words, aggressive firstgraders may become more aggressive when they are placed in a classroom where the level of aggression is high. A recent observational study found evidence of a contagion effect in daycare: Children were significantly more likely to behave aggressively after an aggressive act had occurred than when no aggressive act had occurred (Goldstein, Arnold, Rosenberg, Stowe, & Ortiz, 2001). Interestingly, contagion was stronger for aggressive behaviors directed toward another child than for aggressive behaviors directed at an object. Aggressive behaviors are not isolated acts in the classroom, but rather seem to be part of a larger group system, characterized by chain reactions. A next step would be to examine whether such contagion effects are associated with changes in individual behaviors. These findings suggest that the ecology of peer influence during early childhood is complex and that all levels of the peer system should be considered.

The Behavior Settings As early as 2 years of age, children start to spend more time with peers than with adults (Ellis, Rogoff, & Cromer, 1981). During the early years, these peer interactions are mainly confined to the home, where parents are more likely to orchestrate and supervise social interactions with siblings and other children. Indeed, there are some indications that interactions with peers within the family may account for individual differences in early developmental trajectories of aggression. In particular, siblings appear to be a predominant source of agonistic behavior for preschoolers and may provide a training ground in aggressive behaviors for younger siblings (Dunn & Kendrick, 1982). For instance, Tremblay et al. (2004) found that having a sibling of close age (i.e., less then 2 years in age difference) was the best overall predictor of being described as highly physically aggressive between 17 and 42 months of age. These findings underscore the potential contributing role of sibling relationship for revealing, and perhaps fostering, aggressive behaviors very early in life.

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However, parental monitoring of these aggressive episodes are key to mitigating this potential negative effect. There are different ways in which parents may influence their child’s peer interactions and relationships. For example, parents can provide opportunities for positive friendships while prohibiting deviant ones. Parents may provide direct opportunities for peer interactions by organizing social encounters between their child and selected other children. They can also provide indirect opportunities by coaching their child about peer interactions (Ladd & LeSieur, 1995). In doing so, parents may improve their child’s ability to access more competent peers (Parke & Ladd, 1992). Parental practices such as monitoring their children’s peer affiliations (Dishion & McMahon, 1998) and prohibiting their interactions with deviant peers (Mounts, 2001) have been extensively studied during the late childhood/ adolescence period. More research is needed on how parents manage young children’s affiliation with aggressive peers. As children get older, they interact with peers in a larger variety of settings (Sinclair, Pettit, Harrist, Dodge, & Bates, 1994). Other significant adults, such as classroom teachers, daycare staff, or after-school activity leaders, may then also contribute in shaping a child’s peer environments (Searcy & Meadows, 1994). These settings are likely to vary with respect to the degree of structure and supervision provided by adults, as well as of the characteristics of the peers (i.e., heterogeneity in age, level of peer aggression, etc.). Some settings may be more likely than others to provide opportunities for associations among aggressive children, as well as for deviancy training. Typically, these are settings where the demands placed on the child and the degree of adult supervision are low. Three behavioral settings are relevant to this discussion: (1) the neighborhood, (2) the childcare facility, and (3) the school.

The Neighborhood During the preschool years, children gradually begin to form informal peer groups in their neighborhoods (Ladd & Golter, 1988). These peer groups are typically mixed-aged groups (Ellis et al., 1981). The behavioral characteristics of a child’s friends in this setting are likely to vary according to the socioeconomic status of the families living in the neighborhood. In socially disadvantaged neighborhoods, such as public housing neighborhoods, the density of aggressive children is higher, potentially increasing the child’s exposure to deviant peers. In these neighborhoods, close parental supervision is crucial for limiting the child’s access to deviant peers (Pettit, Bates, Dodge, & Meece, 1999). Deviant friendships in a neighborhood have been studied mostly with adolescents (Dishion et al., 1995b), but this context is also relevant for younger children because their friendship networks are mostly composed of peers from the same neighborhood (Ladd & Golter, 1988). According to Sinclair et al. (1994), the neighborhood is where 4–5-year-old children, especially children from low SES families, spend the greatest amount of time with peers. This is also where they are most frequently exposed to aggressive peers. Devi-

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ancy training in these settings is likely, given the lack of structure and the lack of adult supervision. However, it is not clear whether these experiences predict an increase in children’s aggressive behaviors over time, above and beyond personal dispositions, family characteristics, and social interactions at the dyadic level.

Daycare and After-School Care Programs In western societies, the amount of time young children spend in daycare has been steadily increasing in the last decades (NICHD Early Child Care Research Network, 2003). In typical daycare settings, children spend most of their time interacting with peers. Preliminary evidence seems to indicate that time spent in daycare may be associated with higher rates of aggression (Belsky, 2002; NICHD Early Child Care Research Network, 2003). Peer effects may partly be responsible for this (Fabes, Hanish, & Martin, 2003). At about 2–3 years of age, a clear social structure involving specific patterns of affiliations and cliques emerges (Strayer & Santos, 1996). Children of that age, especially boys (Hawley, 1999), often use aggressive means to reach high status in the social structure. Some of these cliques may thus contribute to the use of aggression by modeling or reinforcement processes. As already alluded to, the degree of adult supervision and structure may play a moderating role with respect to the possibility of a peer influence on aggression in daycare settings. Indeed, research on the impact of daycare on children’s adjustment constantly points to adult variables (e.g., child–staff ratio, staff qualifications) to explain the observed effects (Vandell & Shumow, 1999). For example, Goldstein et al. (2001) found that the immediate presence of the daycare teacher was associated with less contagion of aggression in 36–72-month-old children. With close supervision of peer interactions, adults may simply prevent aggressive interactions from occurring at all. Arrangements for child care are still necessary when children reach kindergarten and first grade. Indeed, because of the increasing rates of maternal employment, the 3:00–5:00 P.M. period represents a new opportunity for additional peer interactions (Vandell & Shumow, 1999). Some arrangements for this period of time involve a low level of peer contact, such as staying with a parent or with a sitter, whereas others involve more peer contact, such as after-school centers and out-of-school formal activities including lessons (music, dance), clubs (scouts), and organized sports. After-school centers vary considerably in respect to child–staff ratio, degree of structure, types of activities, and heterogeneity in children’s age (Vandell & Shumow, 1999). Some of these settings may be a fertile ground for peer influence on aggression. Pierce, Hamm, and Vandell (1999) found that negative peer interactions in afterschool care settings were associated with boys displaying high levels of externalizing behaviors at school, suggesting continuity in peer difficulties from one setting to another. Similar findings concerning after-school care were also reported (Vandell & Corasaniti, 1988).

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Deviant peer processes are less likely to take place in out-of-school formal activities: First-graders involved in these activities tend to show fewer behavioral problems (Posner & Vandell, 1994). In these settings, aggressive behaviors are not tolerated because they disrupt the activities. The levels of structure and adult supervision are usually high, and participants also tend to come from higher-income families.

The School When they reach kindergarten, children spend several hours every day interacting with a stable group of same-age classmates. Most of the research on children’s friendship networks and aggression reviewed earlier has been conducted in such same-age classroom settings. However, the school structure may also influence the nature of the peer relations of aggressive children. As early as first grade, aggressive children may be assigned to a segregated setting, such as a special classroom that involves other students with behavior problems. These special classrooms create an environment where aggressive children are given opportunities for developing friendships with each other (Searcy & Meadows, 1994). In addition to increasing aggression through the mechanisms already described, these friendship groups may contribute to the creation of an in-group/out-group type of social division between aggressive children and their mainstream nonaggressive peers.

CONCLUSION Preschoolers’ peer relationships are complex. Preschool children may face a variety of peer experiences in a diversity of contexts, and it is important not to neglect the potential role of these experiences in the development of aggressive behaviors. A review of the research suggests that starting in preschool, there is a bidirectional and differentiated association between peer relationship problems and aggressive behaviors. Hostile/reactive aggressive behaviors, rather than instrumental/proactive forms of aggression, appear associated with, and perhaps augmented by, peer rejection. Homophily, in respect to aggression, is noticeable during the preschool years. This pattern of association should be of concern. Be that as it may, the empirical evidence linking peer relationships and aggressive behaviors in preschool is still thin. For instance, most of the research effort has been conducted with kindergarten children, and we still know very little about the association between early experiences with peers and aggressive behaviors in prekindergarten children. Nor is it clear whether these early preschool peer experiences have long-term consequences. Longitudinal studies, starting early in life, are necessary to evaluate the potential impact of peer experiences in the long term with respect to subtypes of aggressive behaviors. These future studies should measure the various

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forms of peer relationships at different levels (e.g., dyads, cliques, groups) and in a variety of contexts (i.e., home, daycare, neighborhood). They should examine the microprocesses involved in interactions between aggressive children and their friends, in addition to the mediating and moderating processes linking aggressive behaviors and peer experiences. Specifically, gender differences, as well as the direct and indirect role of parents, other adults, and siblings, should be documented more systematically. Research may also take advantage of genetically informative and longitudinal designs to test specific models relative to the personal and family determinants of peer relationships, and to examine the specific role of peer relationships in later adjustment. Of special interest is the possibility that peer experiences may account for a significant part of nonshared environmental influences on children’s later aggressive behaviors. Such studies could also help unravel the developmental processes presiding over the development of children’s peer relationships. Specifically, there is a possibility that gene– environment correlation may partly explain the nature of young children’s peer experiences, for instance, rejection by peers of a child’s behavior, but also his or her selection of specific peers (see Deater-Deckard, 2001). Finally, future research may also examine the feasibility and the impact of experimental interventions aimed at exposing young aggressive children to nonaggressive peers and modifying the composition of their social networks. These interventions could serve as experimental manipulations in order to test more decisively the putative causal role of these peer-related variables in respect to aggressive behaviors.

ACKNOWLEDGMENTS Preparation of this chapter was supported in part by grants from the Canadian Institute of Health Research and the Canada Research Chair Program awarded to Michel Boivin.

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Rubin, K. H., Watson, K., & Jambor, T. (1978). Free play behaviors in preschool and kindergarten children. Child Development, 49, 534–536. Searcy, S., & Meadows, N. B. (1994). The impact of social structures on friendship development of children with behavior disorders. Education and Treatment of Children, 17, 255–266. Selman, R. L. (1980). The growth of interpersonal understanding. New York: Academic Press. Sinclair, J. J., Petit, G. S., Harrist, A. W., Dodge, K. A., & Bates, J. E. (1994). Encounters with aggressive peers in early childhood: Frequency, age differences, and correlates of risk for behaviour problems. International Journal of Behavioral Development, 17, 675–696. Snyder, J., & Brown, K. (1983). Oppositional behavior and noncompliance in preschool children. Behavioral Assessment, 5, 333–348. Snyder, J., Horsch, E., & Childs, J. (1997). Peer relationships of young children: Affiliative choices and the shaping of aggressive behavior. Journal of Clinical Child Psychology, 26, 145–156. Stormshak, E. A., Bierman, K. L., Bruschi, C., Dodge, K. A., & Coie, J. D. (1999). The relation between behavior problems and peer preference in different classroom contexts. Child Development, 70, 169–182. Strayer, F. F. (1989). Co-adaptation within the early peer group: A psychobiological study of social competence. In B. H. Schneider, G. Attili, J. Nadel, & R. Weissberg (Eds.), Social competence in developmental perspective (pp. 145–174). Boston: Kluwer Academic. Strayer, F. F., & Santos, A. J. (1996). Affiliative structures in preschool peer groups. Social Development, 5, 117–130. Strayer, F. F., & Trudel, M. (1984). Developmental changes in the nature and function of social dominance among young children. Ethology and Sociobiology, 5, 279–295. Tremblay, R. E. (2000). The development of aggressive behavior during childhood: What have we learned in the past century? International Journal of Behavioral Development, 24, 129–141. Tremblay, R. E., Nagin, D. S., Séguin, J. R., Zoccollillo, M., Zelazo, P., Boivin, M., Pérusse, D., & Japel, C. (2004). Physical aggression during early childhood: Trajectories and predictors. Pediatrics, 114(1), e43–e50. Underwood, M. K. (2003). Social aggression in girls. New York: Guilford Press. Vandell, D. L., & Corasaniti, M. A. (1988). The relations between third graders’ afterschool care and social, academic, and emotional functioning. Child Development, 59, 868–875. Vandell, D. L., & Shumow, L. (1999). After-school child care programs. The Future of Children, 9, 64–80. Vandell, D. L., Wilson, K. S., & Buchanan, N. R. (1980). Peer interaction in the first year of life: An examination of its structure, content, and sensitivity to toys. Child Development, 51, 481–488. Vitaro, F., Tremblay, R. E., & Bukowski, W. M. (2001). Friends, friendships, and conduct disorders. In J. Hill & B. Maughan (Eds.), Conduct disorder in childhood (pp. 346– 378). Cambridge, UK: Cambridge University Press. Zahn-Waxler, C., Radke-Yarrow, M., & King, R. A. (1979). Child-rearing and children’s prosocial initiations toward victims of distress. Child Development, 50, 319–330.

DETERMINANTS Social Capital and Physical OF AGGRESSION Violence

19 Social Capital and Physical Violence U BERTO G ATTI and R ICHARD E. T REMBLAY

Man is made fit for Society not by nature, but by training. —THOMAS HOBBES, On the Citizen (1647/1998, p. 25) God makes all things good; man meddles with them and they become evil. —ROUSSEAU, Émile (1762/1986, p. 5)

Although Rousseau and Hobbes disagreed on the nature of “natural” dispositions, they agreed on the fact that the social environment has an important impact on social development. It is generally accepted today, as it has been by philosophers since Plato and Aristotle, that the social development of children is influenced by the environment in which they live, and in particular by the relationships they have with their own families and communities. The assumption is that “good” social environments will contribute to good psychosocial development, whereas, on the contrary, “bad” social environments will facilitate social adjustment problems. The aim of this chapter is to review the literature on the effects of social environments on the development of physical aggression. We have chosen to consider the social environment in terms of a relatively recent unifying concept, social capital. In recent years, this concept has increasingly come to the fore. Initially formulated to explain such phenomena as social stratification and economic development, it has since been utilized to interpret various aspects of life in society. Social capital has been defined as interpersonal relationships that facilitate action (Bourdieu, 1980). Social capital therefore represents an aspect of social reality that individuals (or groups) utilize as a resource in order to further their own interests and to achieve goals that would otherwise be beyond 398

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their reach (Coleman, 1990); that is to say, it is the investment and the instrumental use of the resources inherent in social networks (Lin, 1999). Or, again, it has been seen as interpersonal trust (Fukuyama, 1995), or networks, norms, and trust that enable participants to act together more effectively to pursue shared objectives (Putnam, 1993). Social capital constitutes a resource that is often compared to physical capital (tools, machinery, etc.) and human capital (skills acquired by the individual through education and socialization). Physical capital is created through the transformation of raw materials; human capital through the transformation of persons; social capital through changes in the relationships between persons (Coleman, 1990). These succinct definitions hint at two different (though not entirely independent) interpretations of the concept of social capital: The first, which is chiefly microsocial, stresses the importance of relationships, social networks or links that the individual can utilize; the second, which is mainly macrosocial, attaches greater importance to the norms of reciprocity and civic engagement as the features of a given society. In general, however, it has to be admitted that the definitions proposed for social capital are quite numerous; indeed, debate is currently under way with a view to clarifying and defining the concept, the excessive extension of which may compromise its heuristic value (Portes, 1998). The notion that social capital is linked to the development of children has been argued especially by Coleman (1990), who draws a distinction between social capital within the family and outside the family. In reality, however, leaving aside this dichotomy, it can be claimed that many diverse forms of social capital exist and that these can be detected at different levels, ranging from the microsocial, which centers on the family, to the macrosocial, which takes the nation, region, or city as its unit of analysis; at an intermediate level, the district or neighborhood may be used as the unit of observation. Moreover, social capital may exert different effects in different phases of development. It therefore seems appropriate to reflect on how the different types of social capital might influence aggressive behavior at various ages. By setting the developmental phases against the greater or lesser breadth of the context in which the effect is felt, we created a classification for our analysis of the effects of social capital. Table 19.1 illustrates the hypothesis that, in general, social capital at the microsocial level acts primarily in the early years of life, and at the macrosocial level its effects are chiefly felt during adulthood.

THE CHILD WELFARE SYSTEM A form of social capital that may affect children’s adjustment, and therefore the likelihood of aggressive behavior, is constituted by social and financial assistance to parents (generally mothers) in difficulty. In modern societies, welfare systems have been developed that loosen the bonds between the citizen and the labor market and compensate for financial disadvantages, thereby

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TABLE 19.1. Action of Social Capital at Different Ages and in Different Contexts 0–2 years 3–5 years 6–11 years 12–18 years > 18 years Child welfare system

+

+

+

Family

+

+

+

+

Daycare, preschool, school

+

+

+

+

Peers

+

+

+

+

Neighborhood

+

+

+

Town or region

+

+

Gang

+

+

Violent subculture and organized crime

+

+

making health, social, and educational services available to people who would otherwise be unable to afford them. The relationships between such investments and crime rates have generally been examined through synchronous data. Messner and Rosenfeld (1997), for example, showed that investments in welfare were able to reduce anomic pressure and, consequently, homicide rates in the various nations considered. In an investigation involving several countries, Pampel and Gartner (1995) examined the effect of demographic changes—particularly increases in the number of young people—on general homicide rates. These authors found that in countries where institutions for collective social protection were weak, an increase in the number of young people led to a rise in the homicide rate, whereas no such effect was recorded in countries where these institutions were strong. In comparing homicide rates in various countries, Savolaien (2000) found that the effect of economic inequality on this type of crime was nonexistent in countries with high rates of investment in welfare. DeFronzo conducted a series of studies on the relationship between the financial level of welfare aid and crime rates. In a study of 39 U.S. metropolitan areas, he found, after controlling for other social and economic factors, that the level of public assistance to poor families correlated negatively with the rates of various crimes, including homicide, sexual assault, and burglary (DeFronzo, 1983). In a subsequent study (DeFronzo,1997) he examined the effect of the mean level of social assistance, per person, in 141 U.S. cities, on homicide, while controlling for a whole range of socioeconomic variables, and found that the level of social assistance (Aid to Families with Dependent Children, AFDC) had a direct negative impact on homicide rates; moreover, it exerted an indirect negative effect on these rates through its association with family status (by reducing the number of families headed by a single mother). The high level of economic support therefore apparently reduced homicide rates through two different causal mechanisms. Note that all these studies concerned general crime rates, resulting from both juvenile and adult crime.

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These results fall within the framework of the broader question of the effects of welfare intervention that have been debated in recent decades. Indeed, such intervention is regarded by some as being counterproductive, fostering dependence and passivity, stifling effort, and promoting marginalization; others, however, regard it as an indispensable tool for reducing the deprivation of those who belong to the marginal sectors of society, and, in the final analysis, for improving their social adjustment. Awareness of the effects of welfare intervention acquired particular importance in the United States when, in 1996, a radical change in welfare policy took place. In that year the AFDC program was abolished and was replaced by the more restrictive Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), which limited the period of eligibility for aid and imposed prescriptions in the field of work. As a result, the number of families on assistance, which had peaked at 5 million in 1994, had been halved by June 1999 (Ku, 2001) and further declined to about 2 million in 2001. According to The Economist (2001), the success of this reform went beyond the most optimistic forecasts, yet other commentators judged it to be a substantial failure (Cancian, 2001). Still other experts, however, viewed the results of the reform as partly positive and partly negative. Zaslow, Tout, Smith, and Moore (1998), for instance, saw the results as positive in those cases in which mothers actually succeeded in finding and keeping a job, thus increasing family income, but as potentially negative when mothers were unable to find or keep a job once the maximum permitted time on assistance had been reached. Morris (2002) analyzed the main evaluation studies and concluded that the new welfare structure may be advantageous for children but potentially harmful to adolescents; since the reform was implemented, smoking, alcohol use, small-time delinquency, and maladjustment at school appear to have increased among teenagers, who receive less supervision from their families. A particular negative effect of the reform has been highlighted by Paxon and Waldfogel (2001), who claim that as a result of reduced aid to families in difficulty, cases of child abuse have increased. The heated debate and the research efforts aimed at assessing the results of aid programs emphasize the importance of welfare systems in the politics of a nation, especially in regard to their repercussions on families and child development. From a criminological point of view, it has been suggested (Vila, 1994) that all of the factors that enhance child development, such as health care, education, and parenting, have a long-term effect and are able to reduce crime a generation later (the “nurturance” hypothesis). To test this hypothesis, Savage and Vila (1997) carried out analyses, with countries as units, aimed at ascertaining whether indicators of child welfare were able to predict crime levels 20 years later. The nurturance hypothesis was not supported for crime in general, but only for crimes of violence. In a further study, again carried out on a sample of countries, Savage and Vila (2002) examined the relationships between changes in child care services and changes in crime rates recorded in a later period. As covariates, the authors considered measures of economic

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growth and inequality, factors that reflected the opportunities to commit crimes, and demographic factors. The results supported the nurturance hypothesis: (1) Improvements in primary school enrollments and in the number of hospital beds available per capita predicted declines in homicide rates, (2) improvements in infant mortality rates, life expectancy at birth, and the number of hospital beds predicted declines in the rates of violent crime, (3) and improvements in life expectancy at birth were associated with lower rates of theft. Similar results were obtained by Gatti, Schadee, and Tremblay (2002a), who tested the hypothesis that better maternal and infant health care will be reflected in reduced crime rates a generation later. They analyzed the relationship between infant mortality and the lagged rates of homicide (20 years later) in the 95 Italian provinces, controlling for gross domestic product. Another form of social capital is constituted by programs that provide support for high-risk families. The Elmira Home Visitation Study (Olds et al., 1997) is one of the best examples. This randomized clinical trial showed that home visitation by a nurse, starting during pregnancy and lasting until the child’s second birthday, significantly reduced child abuse by the parents, substance abuse and arrests among the mothers, and juvenile delinquency among the children. The relationships between the quality and intensity of welfare intervention, on one hand, and children’s adjustment, on the other, may be various when viewed from the standpoint of social capital. These interventions may help weave a network of relationships that goes beyond the nucleus of the family and facilitates access to different types of resources (e.g., educational and recreational). To some extent, proper welfare intervention should make up for the deficiencies in the family’s social capital, even though, as mentioned earlier, the effects of the welfare system are not completely clear and are still debatable.

FAMILY SOCIAL CAPITAL How social capital should be defined at the family level is controversial. On one hand, some, such as Wright, Cullen, and Miller (2001), claim that a very broad conception should be adopted—one that includes any type of relationship involving the child, both within and through the family, and which therefore takes into account the time and effort that parents devote to their children, the intense and lasting affective links that are forged, and the prosocial directives that are proposed. On the other hand, according to Sampson, Morenoff, and Earls (1999), many researchers adopt an excessively broad conception of social capital, including aspects of life within the family, such as parental monitoring and expectations, which should not be included; in this perspective, the notion of social capital should concern links with the local community. In this review we adopt an intermediate stance—one that considers those aspects of family life that imply a greater or lesser link with the com-

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munity. This is in line with the suggestions made by Coleman (1990), who stressed that some characteristics of the family, in particular single-parent status and the presence of a working mother, may weaken links with the community. In regard to the single-parent family, several studies revealed a correlation between this condition and antisocial behavior on the part of children (see, e.g., Rutter, Giller, & Hagell, 1998). Vaden-Kiernan, Ialongo, Pearson, and Kellam (1995) investigated the relationships between the family structures and teacher-rated aggression of children, within the framework of a longitudinal study of 1,197 children from 19 public elementary schools in Baltimore, Maryland. The relationships between fourth-grade family structure and sixthgrade aggression were examined separately for boys and girls, using logistic regression analyses comparing mother-alone families with the other families, and controlling for income level, urban area, and fourth-grade aggression. The boys from mother-alone families were more likely to be rated as more aggressive by their teachers, whereas this was not the case for the girls. Pagani, Boulerice, and Tremblay (1997) conducted a similar study with a random sample of the population of kindergarten children in the Canadian province of Québec (947 girls and 882 boys). They used logistic regressions to predict age12 fighting from family status, controlling for age-6 fighting and other family characteristics (education, age, poverty). A short-term increase in fighting for boys and girls could be attributed to family transitions in both directions, that is, divorce (becoming a single parent) and remarriage (ending single-parent status). With a large sample (n = 1,037) of kindergarten boys from low socioeconomic areas of Montreal, Nagin and Tremblay (2001) studied the predictive value of family break-up before school entry for trajectories of physical aggression from 6 to 15 years of age. After controlling for parent characteristics (age at birth of child, education, employment status) and child characteristics (IQ and behavior problems), they showed that family breakup before school entry increased the odds of being on a high physical aggression trajectory by close to 50%. In the Dunedin study, the fact that a 13-year-old was the child of a single parent predicted the likelihood of convictions for violent crimes at 18 years (Henry, Caspi, Moffitt, & Silva, 2004). In London, Farrington (1989) found that parent–child separation before the age of 10 years predicted self-reported violence in adolescence and adulthood, as well as the likelihood of convictions for violent crimes. In a more recent study, Tremblay et al. (2004) found that children born in Canada in 1997–1998 to single mothers were more at risk of being on a high-level physical aggression trajectory between 17 and 42 months after birth than other children. These results were obtained after controlling for a large number of parent and family characteristics. Another aspect of family life that has long been investigated concerns the relationship between the delinquency of parents and that of their children. This relationship has been variously interpreted in terms of genetic predisposition, psychological influence, or environmental factors. From the

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social capital perspective, it may also be claimed that parental delinquency reduces family social capital, in that involvement in illicit activities might not only restrict children’s access to socially valid interpersonal and community relationships, but also facilitate contact with groups involved in crime. Several longitudinal studies have revealed the link between parental delinquency and violence on the part of children (Smith & Farrington, 2003), as recorded through self-reported surveys and official records of violent offenses committed either in adolescence or adulthood. Particularly significant in this field is the research conducted by Keenan and Shaw (1994), who measured the frequency and pervasiveness of aggression from videotapes of the behavior of 98 mother–child couples when the children (males and females) were 18 and 24 months old. This is one of the very few studies that have examined physical aggression at a very early age, and measured it not only through parental perception but also through direct observation. These authors found that parental delinquency was one of the strongest predictors of aggression for boys at 24 months (but not at 18 months). They therefore claimed that the link between familial delinquency and boys’ aggression was stronger when the children had reached a developmental stage at which the parents began to discipline their children. Using the U.S. National Youth Study, Wright et al. (2001) evaluated family social capital, using a composite index that included the time parents spent with their children, the strength of the bonds between various family members, and the parents’ critical attitude toward delinquency. They found an inverse relationship between social capital and both short- and long-term involvement in delinquency, evaluated through answers given by the youths about their involvement in a range of crimes, such as theft, assault, robbery, and drug dealing. McCord (2002) obtained similar results with data from the Cambridge–Somerville study. Social capital was measured by social workers’ observations of 232 families with children between 10 and 16 years of age at the start of the research. Outcome data, collected more than 40 years after the beginning of the study, indicated that the social capital of parents reduced the risk of their children’s being convicted of violent crimes. According to Coleman (1990), maternal employment also has an effect on social capital. He suggests that if a mother works, she will have less chance to participate in the life of the community, to develop relationships with neighbors, and to share educational problems, and that this will have a negative influence on children’s adjustment. This aspect of family social capital assumes particular relevance in modern societies, in which women’s employment outside the home has become the norm. Some have expressed concern regarding the well-being of children on the grounds that their development and adjustment may be hindered if their mothers work (Belsky, 2001). Vander Ven, Cullen, Carrozza, and Wright (2001) used data from the National Longitudinal Survey of Youth and found that the features of the mothers’ jobs had relatively little or no direct influence on the delinquency of their children, but did have a slight indirect effect through supervision. Lack of supervision had

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an effect regardless of whether early or current employment was considered. It was found that the effects of maternal employment might differ according to the population considered. For instance, Han, Waldfogel, and Brooks-Gunn (2001) found that, in the general population, maternal employment in the first year of the child’s life had an effect that could be perceived in the sphere of externalizing problems when the child was 7–8 years old, but among African American children this effect did not emerge. However, research on the effects of maternal employment must include research on the impact of the quality of care given to young children while their parents are working. We turn next to this topic.

DAYCARE AND EARLY CHILDHOOD DEVELOPMENT CENTERS In the last few decades, a heated debate has raged in regard to children’s daycare, to the extent that the term daycare war has been coined to describe the widespread and fierce clash of views on such institutions (Karen, 1994). Some argue that early child care services are an important social resource that mothers can exploit to improve their children’s socialization. Others argue that daily separation from the mother during the first few years of the child’s life may put the child’s development at risk. We obviously need good data to decide which resources constitute a sound capital for children’s development. But few good studies have been carried out to date, and fewer than a handful deal with the development of aggression. There appears to be a consensus that the effects will depend on the quality of the daycare environment rather than on the presence or absence of daycare (Tremblay, Barr, & Peters, 2003). Some early studies on children’s disruptive behavior concluded that those who spent several hours of the day away from their mothers during the first year of life were more disobedient and more aggressive toward their peers between 3 and 8 years of age (Haskins, 1985; Rubenstein & Howes, 1983). These studies were criticized because they often failed to take into account the quality of the daycare environment and selection effects, that is, family and child characteristics before the beginning of daycare. For example, a study of a representative sample of 3,431 Canadian children 2–3 years of age (Borge, Rutter, Côté, & Tremblay, 2004) found a higher level of aggression among children who were not sent to daycare groups, but were looked after by their parents. This relationship emerged only among children in high-risk families; among those in low-risk families, who constituted the majority (87%), no difference in the level of aggression was recorded. Moreover, within the subgroup of children attending group daycare, placement instability was associated with a higher level of aggression after controlling for a family risk index (occupational level, maternal education, number of siblings, and family functioning). The U.S. National Institute of Child Health and Human Development created the NICHD Early Child Care Research Network (2002, 2003) to tackle the shortcomings of previous studies. It regularly assessed 1,300 chil-

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dren and their families starting with the children at 6 months of age. Children who spent more time in child care during the first years of life displayed higher levels of externalizing problems and problems with aggression at 24 months and 54 months, as well as in kindergarten and first grade. These results certainly fueled the public debate. However, we will need much more information before the debate is settled. First, the differences were statistically significant, but more time in daycare did not increase the risk of being considered in the clinical range; second, developmental trajectories of aggression were not studied to determine which type of children are more likely to be affected. Are the affected children those who tend to be highly aggressive? For example, Raine, Reynolds, Venables, Mednick, and Farrington (1998) reported that 3-year-olds who had a larger body size were more likely to use aggression at 11 years of age. One can imagine that being with peers for longer periods of time, and dominating them, makes it less likely that a child will learn not to use physical aggression. Alternately, could the affected children be those who normally tend to learn rapidly not to use physical aggression? These children may need to keep their level of aggression high enough to survive in a tough peer environment. Developmental trajectories during the preschool years, coupled with data from the elementary school years, should help in understanding who is affected and whether these effects are long lasting. A third caveat is that we are looking at a longitudinal study. We will need experiments to determine which types of preschool environments help children learn alternatives to aggression. Experimental designs are indeed needed to answer questions concerning cause and effect. A number of randomized experiments have attempted to test the effect of early preventive interventions, carried out in the preschool years. The Perry preschool project, also known as the High Scope project, is probably the best known of these experiments (Weikart, 1998; Weikart & Schweinhart, 1992). The main aim of this program was to prevent school failure among poor African American children by intervening when they were 3 and 4 years old. Children attended quality day centers and teachers visited mothers at home. The long-term results revealed not only that the treated subjects were more successful at school than the control subjects, but also that they were arrested less often both as adolescents and as adults (at ages 19 and 24 the treated subjects were five times less likely to have been arrested). They committed less serious crimes and had lower rates of recidivism. Significant reductions in antisocial behavior were also found in the Syracuse University Family Development Project, and a reduction in aggressive behavior was observed in both the Yale Child Welfare Project and the Houston Parent Child Development Center (for a review of the results, see Tremblay & Craig, 1995). Administered during the preschool years, all these programs increase social capital, in that they improve relationships between children and parents, and between parents and the community. Unfortunately, none of these studies appear to have specifically studied their subjects’ development of aggression.

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SCHOOL SOCIAL CAPITAL Hagan and McCarthy (1997) have stressed that school is an important component of the social institutions network within which social capital is generated. Indeed, in the light of the social capital paradigm, school is seen as a context in which relationships that are important for the pupil’s adjustment are developed—relationships that also involve teachers and parents. A ready indication of the relationships between school social capital and pupil adjustment can be deduced from those studies that have correlated the size of the school with the pupils’ behavior. Some studies revealed that students in larger schools experience a greater sense of alienation and frustration than those in small schools, and that the smaller schools are able to provide their students with a better social environment. Moreover, it has been shown that large schools report a far higher number of serious crimes and behavior problems (Ferris & West, 2002; National Center for Education Statistics, 2002) than small schools; it may be supposed that the social relationships within the smaller institutions are more closely knit, that the people know each other better and are more inclined to lend a hand in solving one another’s problems. Social capital at the school level particularly concerns the involvement of parents in school activities. By using different samples of adolescents (in residential treatment, ambulatory treatment, and untreated) Buysse (1997) found that a lack of social capital in the family and at school engendered a high risk of antisocial behavior on the part of the youth. Parcel and Dufur (2001) also analyzed the influence of capital at home and at school and considered both human and social capital. Using the National Longitudinal Survey of Youth (NLSY), to which they added indicators in the children’s schools (such as a measure of school-wide parental involvement in school activities and scales that reflect school environment), they observed that family social capital and child human capital had a large impact; but effects of school social capital could also be detected, and interactions between family and school social capital were important as well. In studying the relationships between school environment and the antisocial behavior of youth, Rutter, Maughan, Mortimore, Ouston, and Smitj (1979) identified a set of characteristics that apparently prevented deviant behavior on the part of pupils. The school environment thus created was one in which teachers provided an example of good conduct, monitored and stimulated their pupils, and implemented firm and consistent disciplinary measures. More recently, Leblanc, Swisher, Vitaro, and Tremblay (2004) measured the social climate (discipline and academic pressure, in regard to teacher–pupil relationships, and autonomy and job satisfaction, concerning relationships within the teaching staff) of 217 high schools attended by 1,233 pupils who had been followed since kindergarten. Students attending high schools where teachers perceived fewer classroom behavior problems reported less physically aggressive antisocial behaviors. The analyses controlled for the students’ de-

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velopmental trajectory of aggression during elementary school, as well as for the adverse family environment of the pupil and the sociodemographic factors of the school, including school size. Prevention experiments are, of course, better tools than correlational studies to test the causal effects of school social capital. Four experiments— the Seattle Social Development Project (Hawkins, Catalano, Kosterman, Abbott, & Hill, 1999), the Baltimore Prevention Study (Kellam, Rebok, Ialongo, & Mayer, 1994), the Montreal Longitudinal-Experimental Study (Tremblay, Kurtz, Mâsse, Vitaro, & Pihl, 1995), and the Fast Track prevention trial (Bierman et al., 2002)—measured the development of antisocial behavior after attempting to improve relationships among pupils, parents and teachers, and the school environment in general. These four prevention experiments started in the first 2 years of elementary school and lasted between 2 and 6 years. Both the Baltimore and Montreal experiments lasted 2 years and showed a significant long-term reduction (4–8 years after the intervention) of aggression in boys with the highest levels of physical aggression when they started school (Kellam et al., 1994; Lacourse, Nagin, Tremblay, Vitaro, & Claes, 2003). The Seattle experiment also showed a significant reduction of violent delinquency during adolescence for boys and girls who participated in the program from first to sixth grade, but not for those who participated only during fifth and sixth grade. Fast Track is the latest of these four preventive trials. Four years after the start of the intervention, the authors reported that children in the control group, as compared with those in the intervention group, displayed less aggressive behavior, according to teacher and parent ratings (Bierman et al., 2002; Conduct Problems Prevention Research Group, 2002). The results from these four experimental programs suggest that trajectories of physical aggression can be deflected by interventions that improve relationships between the pupil, his or her parents, peers, and teachers. They indicate, however, that the younger the children when the intervention starts, the more impact it will probably have.

PEER SOCIAL CAPITAL Well-socialized peer groups are an important aspect of social capital—a resource that is available to children and may influence socialization in a positive manner. As the child grows up, the peer group apparently becomes increasingly important, while the impact of the family environment declines. In reference to the social capital paradigm, and therefore to resources in terms of social relationships that can be utilized, we concentrate here on the effect exerted by the presence of prosocial peers, or the lack of this resource resulting from the phenomenon of peer rejection. Various studies have reported that nondeviant friends are able to reduce involvement in antisocial behavior (Brown, Lohr, & McClenahan, 1986) and that a prosocial group seems to lighten the impact of other risk factors

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(Quinton, Pickles, Maughan, & Rutter, 1993). It has also been observed that peer disapproval of delinquency reduces the likelihood that the individual will subsequently commit violent crimes in general (Elliott, 1994), and sexual crimes in particular (Ageton, 1983). With a sample of 868 boys selected from kindergarten classrooms in poor areas of Montreal, Vitaro, Brendgen, and Tremblay (2002) observed that, by early adolescence, those who were most influenced by the aggressive–disruptive characteristics of their friends were those who already had moderate behavior problems. These problems tended to become milder if their friends were not aggressive–disruptive, but if their friends were aggressive–disruptive, then their own problems increased. It is interesting to note that boys who had serious problems, and boys who had no problems, were not influenced by the characteristics of their friends. In a similar study of 585 families in which there was a 5-year-old boy or girl, Criss, Pettit, Bates, Dodge, and Lapp (2002) found that peer acceptance and friendship acted as a moderator between the degree of family adversity and the child’s externalizing behavioral problems. In contrast, peer rejection can cause a child to miss out on a fundamental experience in the socialization process (Vitaro, Tremblay, & Bukowski, 2001b) and can facilitate the emergence of adjustment problems and deviant behavior. In a review of the literature on this subject, Parker and Asher (1987) concluded that there was a relationship between peer rejection and subsequent problems of social adjustment and delinquency. However, they also raised the question of whether this rejection exerted an independent effect on the subsequent behavioral disorders, or whether peer rejection was linked to the subject’s aggressive behavior from the outset, and the subsequent disorders were chiefly linked to this early aggressiveness. Subsequent investigations enabled this issue to be tackled and yielded some preliminary answers. On the basis of behavior observation, teacher and peer ratings, and peer interviews, Bierman, Smoot, and Aumiller (1993) subdivided a sample of 95 children examined at three successive times (when they were 6–8, 8–10, and 10–12 years old) into four subgroups: aggressive and rejected, aggressive and nonrejected, rejected and nonaggressive, and neither aggressive nor rejected. Aggressive-rejected children exhibited more diverse and severe conduct problems than aggressive children, in that the former displayed high levels of aggressiveness and disruptive behavior and a low level of prosocial activity, whereas the latter displayed only a higher level of aggressive behavior. Moreover, 2 years later, the aggressive-rejected children continued to manifest a higher degree of aggressive and disruptive behavior and a greater deficiency in prosocial activities than the children initially classified as aggressive-nonrejected. In a longitudinal study, which involved subjects from third grade to adolescence, Coie, Lochman, Terry, and Hyman (1992) observed that both aggressiveness and rejection, as evaluated in the third grade, independently predicted externalizing problems in the sixth grade. The combination of aggressiveness and rejection predicted (only in males) acts of criminal assault and, in general, forms of antisocial behavior that were more serious than those predicted by aggressiveness alone.

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Reactive aggression appears to be associated with peer rejection, whereas active aggression is enacted by children who are accepted by their peers (Dodge, Lochman, Harnish, Bates, & Pettit, 1997). The effects of peer relationships on aggressive behavior have been also described in a relatively new field of research, concerning the consequences of mutual antipathies (i.e., relationships characterized by reciprocal disliking) in childhood and adolescence. In a study on 2,348 school-age children and 2,768 adolescents, Abecassis et al. (2002) found that, controlling for peer rejection, same-sex antipathies were associated with aggressive behavior (perceived by peers) and bullying others (self-reported), both in childhood and in adolescence, and to emotionality and lack of friendship support among adolescents; however, mixed-sex antipathies were related to antisocial and bullying behavior in boys but not in girls. Finally, it should be noted that the influence of the peer group in reducing and controlling aggressive behavior can also be evaluated through experimental interventions. Vitaro, Brendgen, Pagani, Tremblay, and McDuff (1999), for instance, found that association with less deviant peers partly mediated the effect on conduct disorders, assessed at the age of 13 years, of a multicomponent prevention program that targeted disruptive boys when they were ages 7–9. In a subsequent study with the same sample, Vitaro, Brendgen, and Tremblay (2001a) showed that reduced disruptiveness and increased parental supervision by age 11, as well as association with nondeviant peers by age 12, were part of a chain of events that mediated the effect of the program on the initial level of delinquency at 13 years. Results of this kind have therefore confirmed the notion that relationships with prosocial companions provide a form of social capital that exerts a positive influence on the socialization process and on the progressive control over disruptive behavior, including aggression.

NEIGHBORHOOD SOCIAL CAPITAL At the beginning of the 1980s, Sampson and Groves (1989) used data from 238 localities in Great Britain with a view to ascertaining whether some parameters of community life, drawn from a national survey of 10,905 residents, were able to predict crime rates. They demonstrated that some features of the community, which today would be identified as social capital (friendship networks, participation in community activities, and supervision and control of adolescent groups), were associated with lower crime rates, as measured both through self-reports and through victimization surveys. Sampson, Raudenbush, and Earls (1997) subsequently utilized the concept of “collective efficacy” to interpret differences in the occurrence of violence in Chicago neighborhoods. Collective efficacy refers to social cohesion in a neighborhood, combined with the willingness of residents to act in favor of common interests. It was measured by a scale of social control and a scale of social cohesion and trust. Controlling for race, age, and homicide rates in the previous years,

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collective efficacy at the neighborhood level correlated inversely with homicide, violence as perceived by citizens, and violence assessed through victimization surveys. Using the same indexes employed by Sampson et al. (1997), Browning (2002) found that collective efficacy was negatively associated with both intimate homicide rates and nonlethal partner violence and that, furthermore, in neighborhoods displaying higher levels of collective efficacy, women were more likely to disclose relationship conflicts to potential sources of support. In order to understand the origins of collective efficacy, Sampson et al. (1999) conducted a subsequent study in which they tried to identify, again at the local community level, three aspects of social organization that influence children’s lives, development, and adjustment: intergenerational closure for children (when adults know the parents of their children’s friends, watch out for the safety of children, etc.), reciprocal exchanges (the degree of interaction among families regarding their children’s education and the swapping of advice, material possessions, and information on childcare), and the degree of informal control combined with reciprocal support (expectations of action within a community). They used the data from investigations conducted in 1995 on a sample of 8,782 residents in 342 different Chicago neighborhoods. Residential stability and wealth were good predictors of the bond between generations and of reciprocal exchanges. However, concentrated disadvantage correlated strongly with low expectations of shared social control over children. Spatial aspects proved to be very important, in that proximity to an area with strong bonds between generations, frequent reciprocal exchanges, and good informal control had a favorable impact above and beyond the structural features of the neighborhood. Sampson et al. (1999) introduced these indicators on the grounds that some aspects of social capital, such as the existence of groups, associations, and networks, might not, on their own, be sufficient to favor child development and might even have a negative effect on social life if they operated in such a way as to exclude others. They therefore claimed that the objectives of local associations should be examined before deciding whether such groupings favor children’s collective needs. Bellair (1997) used an interesting and innovative research method to investigate the effect of various types of social interaction on crime across 60 urban neighborhoods. He found that getting together once a year or more with neighbors had a strong negative association with burglary, motor vehicle theft, and robbery and that this form of interaction mediated a significant proportion of the effect of ecological characteristics on crime. Bellair suggested that even infrequent interaction and knowing one another could prompt neighbors to engage in supervision and guardianship. This infrequent interaction corresponds to what Granovetter (1973) defined as “weak ties,” which can strengthen the community by creating linkages across networks. The preventive effect of social bonds may not, however, be homogeneous. For instance, Warner and Rountree (1997) showed that strong social ties exerted a preventive effect in regard to assault rates in predominantly white neighbor-

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hoods, whereas in predominantly minority and mixed-race neighborhoods such ties were largely ineffective. A particular form of violent behavior, child maltreatment, has been seen to be associated, at the neighborhood level, with the lack of social resources, when income levels are equal (Vinson, Baldry, & Hargreaves, 1996). Dubet (1987), through ethnographic studies, identified another relationship between violent behavior and scant social bonds. He ascribed the outbreaks of youth violence seen in recent years in the suburbs of some French cities to the disappearance of the traditional working-class culture. In workingclass neighborhoods there used to be a whole range of meeting places and spare-time activities and groups, which provided the young with role models and common objectives. In traditional working-class neighborhoods the factory provided a nucleus for aggregation and socialization; children and adolescents therefore grew up within a network of relationships and expectations that fostered social and occupational development and provided models that were endorsed by the whole community. Although this setting also featured social conflicts, the community was somewhat close-knit and rich in social relationships. De-industrialization and suburban transformation have demolished this social fabric; commerce is rare, meeting places nonexistent, buildings dilapidated, and transport inadequate. What has emerged is a sort of no-man’s-land, where the young try to survive, drug pushing abounds, crime and violence are endemic, and a deep sense of insecurity prevails. In the light of the social capital theories, what has disappeared from these neighborhoods is a set of social networks, shared expectations, and community commitment. These are so essential to the social life and socialization of the young that their disappearance has facilitated the outbreaks of violence that have afflicted many urban districts in Europe.

TOWN AND REGION The relationship between regional social capital and violent crimes has recently been examined in a series of studies in the United States. Using data from the 50 U.S. states, Kennedy, Kawachi, Prothrow-Stith, Lochne, and Gupta (1998) measured social capital by membership of groups and associations and social trust, two items from the U.S. General Social Survey. They found a correlation between a low level of social capital and marked inequality on one hand, and violent crimes on the other. In a cross-sectional analysis that also included the 50 U.S. states, Putnam (2000) found that an index of social capital was inversely correlated with homicide rates and that this correlation was very high (r = –.80) for the period 1980–1995. Controlling for the variable “fear of crime,” the (partial) correlation between social capital and homicide remained high (r = –.53). Putnam concluded that the direction of the relationship could not possibly be from homicide to social capital, because any such relationship would have been mediated by the fear of crime. To ob-

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tain a clearer picture of the relationship that had emerged, he introduced a range of social and economic factors as independent variables in a multiple regression. He found that the model best able to predict homicide rates in the various states included four variables: social capital, mean poverty level, ethnic makeup of the population (percentage of nonwhites), and the proportion of the population living in cities. In a similar study, Hemenway, Kennedy, Kawachi, and Putnam (2001) measured, at the state level, the degree of interpersonal trust (through the replies provided to the U.S. General Social Survey) and social commitment (assessed through participation in voluntary activities, religious observance, etc.). After controlling for the level of urbanization, poverty, and the percentage of nonwhite residents, they concluded that these indicators of social capital were inversely associated with the percentages of homicides and suicides committed with firearms. Focusing their analysis on a more restricted territorial area, and thus increasing the sample size, Rosenfeld, Messner, and Baumer (2001) investigated the relationships between social capital and homicide in 99 geographical areas of the United States. They measured two aspects of social capital, civic commitment and social trust: The former was measured through voter turnout and membership in voluntary associations, and the latter through respondents’ replies to the U.S. General Social Surveys of 1993, 1994, and 1996. A low level of social capital was found to be associated with a high homicide rate, after controlling for a range of socioeconomic variables. Social capital mediated the effect of the area’s being located in the southern states, but it did not mediate the effect of economic deprivation. The statistical relationship between social capital and homicide was not due to the influence of homicide on social capital. Subsequently, Messner, Baumer, and Rosenfeld (2002) broadened this focus to include robbery and assault, demonstrating that these crimes were also inversely related to social capital. In one of the rare studies on social capital and violence outside the United States, we used Italian data and calculated an index of “civicness” (Putnam, 1993) for each of the 20 administrative regions (Gatti, Tremblay, & Larocque, 2003) and 95 provinces (Gatti, Tremblay, & Schadee, 2002b). The civicness index included three indicators: (1) voter turnouts in referendums or elections, (2) the percentage of citizens over the age of 13 years who read a newspaper every day, and (3) the number of recreational, sporting, and cultural associations per 100,000 inhabitants. The results revealed a negative correlation between civicness and the reported number of some types of serious crimes of violence, as recorded in the 1970s, 1980s, and 1990s, at the regional level. Data from the vast victimization survey conducted by the Istituto Nazionale di Statistica/National Institute of Statistics (ISTAT) confirmed the negative association between civic sense and violent crimes. At the provincial level, multiple regression analyses were carried out, using as control variables unemployment, family breakdown, and urbanization as predictors of homicide, in addition to civic sense. Notwithstanding the introduction of these control variables, civic sense continued to be negatively associated with homicide;

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however, the interactions among variables revealed that the protective effect of civic sense was exerted only in the southern provinces, where homicide rates are higher. The criminogenic effect of urbanization and unemployment was also observed only in the southern provinces, whereas family breakdown was associated with homicide in the whole of Italy. Finally, the preventive effect of civicness in regard to robbery was examined. This analysis revealed that civic sense has a preventive effect on this type of crime, but only in the more urbanized provinces, where robbery rates are higher.

NEGATIVE SOCIAL CAPITAL Although the majority of authors stress the positive aspects of social capital, some also underline its possible negative consequences (e.g., Portes, 1998). Indeed, social networks and the norms of reciprocal cooperation may be used to exclude those who do not belong to the group from access to resources (see Vaillancourt, Chapter 8, this volume). Community bonds may constitute a pervasive social control tool, which hampers autonomy and privacy, and members of marginal minority groups may be tied down by bonds of solidarity that make it difficult for them to accept the dominant social norms and to gain access to the world of traditional work. Finally, strong social bonds may be used for patently illegal purposes within the sphere of organized crime or youth gangs (Portes, 1998). In regard to children’s development, the fact that youth gangs may constitute an environment in which aggressive behavior is facilitated has been well documented, especially for males. Numerous studies have revealed that youths who belong to a gang commit more crimes than those who do not, and that this difference is greater with respect to serious crimes and crimes of violence. Longitudinal studies are especially suited to test three models, which Thornberry, Krohn, Lizotte, Smith, and Tobin (2002) have defined as the selection model, the socialization model, and the enhancement, or mixed, model. According to the selection model, the high level of delinquency and violence among gang members does not depend on the influence of the gang, but rather is due to the fact that gangs attract and select those youths who already commit the most crimes. In contrast, the social facilitation model holds that it is the gang that facilitates and triggers deviant behavior in youths who, before joining the gang, are no different from other young people. The enhancement model combines these two views: Youths who join gangs already display a higher level of delinquency, and joining the gang exacerbates their deviant behavior. Using data from the Rochester Youth Development Study, Thornberry, Krohn, Lizotte, and Chard-Wierschem (1993) showed that, before joining a gang, members did not display higher rates of delinquency or drug use than nonmembers. However, such behaviors increased upon entry into the gang, and delinquency declined once an individual left the gang (Thornberry et al.,

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1993). In a subsequent study, covering a longer period of time, Thornberry et al. (2002) found that, in addition to a strong facilitation effect, a weaker selection effect was also present. Strong evidence for the social facilitation model and partial support for selection was provided by Zhang, Welte, and Wieczorek (1999) through their analysis of the data from the Buffalo Longitudinal Survey of Young Men. The enhancement model was confirmed by the Denver Youth Survey, a longitudinal study of families in high-risk neighborhoods (Esbensen & Huizinga, 1993), by a longitudinal study of schools in six American cities (Esbensen, Peterson, Freng, & Taylor, 2002), and by the Montreal Longitudinal Experimental Study (Lacourse et al., 2003; Vitaro, Tremblay, Kerr, Pagani, & Bukowski, 1997). The latter study also revealed that the criminogenic influence of the gang was independent of other risk factors, such as previous delinquency, disruptiveness, and lack of parental supervision; gang membership emerged as a significant predictor of the frequency of aggressive behavior, above and beyond the effects of having delinquent friends (Gatti, Tremblay, Vitaro, & McDuff, in press). Data from the Seattle Social Development Project revealed that respondents who were gang members always had the highest frequency of delinquent behavior and drug use, and that comparing gang members, nongang youths who had delinquent friends, and nongang youths who did not have delinquent friends, gang membership predicted selfreported and officially recorded delinquency beyond the effects of having delinquent friends and prior delinquency (Battin-Pearson, Thornberry, Hawkins, & Krohn, 1998). The results from these studies demonstrate that the criminogenic effect is not due simply to contact with other delinquent youths, but that it is also linked to the influence of the gang itself. Some ethnographic studies have revealed that the gang may constitute an important form of social capital for youths—a resource that they can exploit in order to achieve their own objectives. Jankowsky (1991) obtained participant observations over a 10-year period among 37 gangs in the metropolitan areas of Los Angeles, New York, and Boston. He concluded that in the American suburbs, gangs are not only an expression of social disorganization, but they are also an organizational response aimed at enhancing the competitiveness of their members in acquiring scarce resources. Indeed, gang members enjoy certain advantages in terms of money, status, and power, and the gang accepts youths as members if they are able to contribute to its prestige and efficiency. Criminal organizations and subcultures may also be regarded as a form of social capital that facilitates violence. In particular, violent subcultures, which were first investigated by Wolfgang and Ferracuti (1967) and subsequently analyzed by numerous criminologists, may, like the army or a boxing coach, train the individual in using physical aggression. According to Wolfgang and Ferracuti, a subculture is “a normative system of some sub-group smaller than the whole society,” which implies a process of learning shared values. There are subcultures that value the use of physical violence, and certain members (e.g., adult males) are required to use violence in certain circumstances. In such situations, the individual is expected to act violently, and

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nonviolence may lead to ostracism or condemnation; in contrast, violence is rewarded rather than condemned and does not arouse guilt feelings in the individual. There are a few published biographies that shed light on the relationships between criminal organizations, subcultures, and aggressive behavior. A biography of Raffaele Cutolo (Marrazzo, 1984), a Neapolitan crime boss who reigned over the Campania region for many years, and who is now in prison, provides us with the following illuminating episode. Raffaele’s father was an agricultural worker, who for years tilled a field as a sharecropper to support his family. One day, when Raffaele was still a child, the owner of the land told his father that the following year the field would be used for a different purpose, and that his services would therefore no longer be required. In desperation, Raffaele’s father turned to the local Mafia boss, whose word was law in the village. The Mafia boss invited the Cutolo family to his home, and after Mass one Sunday, dressed in their best clothes, both parents and children respectfully presented themselves at the boss’s door. Raffaele’s father was ushered into another room by the boss, while the lady of the house offered cakes to Mrs. Cutolo and her children. When the two men reemerged, Mrs. Cutolo anxiously asked her husband if there was any news. She was told that everything had been settled. The following day, the landowner informed Mr. Cutolo that he had changed his mind and that his contract would be renewed. It is easy to imagine the psychological impact that this event must have had on all the members of the family, and especially on the young Raffaele, who had seen this family crisis solved by appealing to a local institution that was both powerful and efficient, although illegal. A few years later, however, when Raffaele was an adolescent, he was summoned by the Mafia boss, who instructed him to deliver a pistol secretly to a mafioso in another village. Other requests followed, and finally Raffaele Cutolo found himself involved in serious crimes. From there, he went on to become the head of a powerful organized crime syndicate. It is clear from this account that the criminal fraternity constituted a form of social capital—a resource to be exploited in order to solve problems and achieve otherwise unreachable goals. But this social capital was also permeated by norms of reciprocity and expectations centered on the use of violence, which ended up conditioning the social development of those living within this culture. Some systematic studies have also evaluated the importance of violent subcultures. Felson, Liska, South, and McNulty (1994), for example, studied 2,123 boys in 87 public high schools. Respondents were asked a series of questions designed to measure whether they approved of nonaggressive responses to some types of provocation. The questions consisted of a series of personal values, and respondents were asked whether certain acts were “good thing[s] for people to do.” Disagreement with these values was deemed to indicate a high score on the subculture of violence scale. The authors reached the conclusion that group-level values predicted violent behavior, regardless of individual-level values. Furthermore, this research demonstrated that subcul-

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ture differences in values were more frequently encountered within small groups involving interactions between their members, rather than within broad aggregations based on race, social class, or religion. Such examples illustrate the fact that social capital may also exist in illegal forms and that, in some cases, crime and violence constitute a shared resource that can be exploited in order to achieve ambitions or, in certain circumstances, simply to survive.

CONCLUSIONS We have seen that social capital can be defined in various ways and may operate in more or less broad contexts and at different ages from early childhood to adulthood. From the developmental standpoint, several empirical studies have demonstrated that both familial and extrafamilial social capital have an effect, even in the long term, on children’s adjustment, on academic results and socioeconomic success (Furstenberg & Hughes, 1995), and on health and well-being (Morrow, 1999). In general, the social capital perspective has proven useful in helping us to understand aggressive behavior and violence, though much more research is needed. Not all forms of social capital act in the same way, and several studies have found that social capital seems to exert a preventive effect on aggressive behavior only in certain circumstances and only in regard to some types of persons. We have seen that the development of children and young people can be influenced by the quality of relationships within the family, at school, and among peers, and by the characteristics of the communities and regional environments in which they live. For the most part, each of these levels of influence has been studied separately, though some researchers have begun to consider different aspects of social capital simultaneously. This appears to be an important advancement, in view of the multidimensional nature of social capital and its potential to link “the overly narrow purview of psychology and the overly broad purview of sociology” (Furstenberg and Hughes, 1995). In addition to its multidimensional character, the developmental aspect of social capital should also be considered, by examining how the loss or acquisition of a given form of social capital during the course of the individual’s life might influence engagement in aggressive behavior. The various types of social capital have a differential impact according to the age of the individual. Family social capital and the relationship resources offered by the child welfare system chiefly act during early childhood to middle childhood, when learning to regulate physical aggression appears to be at its peak. The influence of peers has been shown mainly during late childhood and adolescence; however, it is most likely present very early at home, through siblings, and in daycare. Violent subcultures and organized crime are more likely to exert a direct effect on adolescents and adults. Broadly speaking, it seems that social capital at the

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microlevel plays a stronger role during childhood, whereas the macrolevel acts especially during adolescence and adult life. Thus, the influence of social capital on the regulation of aggressive behavior should be studied from a developmental perspective. It can be claimed that the process of progressively waning physical aggression from early childhood to adulthood (Sampson & Laub, 2003; Tremblay & Nagin, Chapter 5, this volume) is facilitated by the majority of the social relationships we have defined as social capital. All cultures, including nonhuman cultures, benefit from helping their young ones to control their ability to physically aggress others. This does not mean that they completely inhibit the power to physically aggress. Armies are, or should, always be ready for war. Individuals and subgroups are at an advantage if they can defend themselves from an aggression. Thus, social capital that is advantageous for one group can be disadvantageous for another. This is why gangs and organized crime are considered threats to the mainstream, but constitute a resource for individuals who, for different reasons, are not or have chosen not to be part of this mainstream. In general, attempts should be made to improve social support (Colvin, Cullen, & Vander Ven, 2002) at all levels—through the family, welfare, and academic institutions, formal and informal groups, neighborhoods and cities— to strengthen social networks, to increase community participation and social commitment, and to reduce individualism in favor of a community spirit. These objectives should be pursued both through specific intervention, for example, by providing support for mothers in difficulty, and through a broader cultural evolution toward greater cooperation and solidarity. Research on the effects of these interventions should help us to understand which are the most effective strategies for a given culture, while testing our theories concerning the origins and development of aggressive behavior. We will, of course, need to study to what extent different types of social capital have different effects on different types of aggressive behavior, at different periods of the life course.

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DETERMINANTS Sex Differences in Aggressive OF AGGRESSION Behavior

20 Sex Differences in Aggressive Behavior A Developmental and Evolutionary Perspective J OHN A RCHER and S YLVANA C ÔTÉ

INTRODUCTION: EVOLUTIONARY AND DEVELOPMENTAL EXPLANATIONS Explanations of Behavior Tinbergen (1963) set out four types of explanation of behavior. Two concerned the evolution of behavior, its historical antecedents and its survival value, and two concerned causes within the individual, its development and immediate causation. A full explanation of any form of behavior that humans share with animals involves all four explanations. Aggression is such a form of behavior, having its origins in evolutionary history. Psychologists studying human aggression typically concentrate on individual-level explanations, immediate causation and development, referred to as proximal explanations. Evolutionary psychologists and ethologists are also concerned with the two evolutionary-based explanations, referred to as distal explanations. In this chapter we consider the development of sex differences in human aggression in relation to evolutionary explanations.

Evolutionary History The evolutionary history of aggression can be appreciated by noting its widespread occurrence throughout the animal kingdom, from animals with very simple nervous systems, such as sea anemones, to humans (Archer, 1988). It is therefore not something that can realistically be viewed only as a consequence of social influences on human development, although there are social environments that greatly increase an individual’s level of aggression, and individuals 425

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who are more aggression-prone than others whatever their social environment.

Evolutionary Function Fighting is widespread throughout the Animal kingdom. It occurs in two main contexts, in warding off danger and as a consequence of competition for resources (Archer, 1988). Competition is a wider term than physical aggression and results from a simple ecological principle. Organisms typically produce more offspring than their environment can sustain; resources are therefore scarce, and some will obtain more than others. Occasionally, this is the result of chance, but animals are typically selected for features that enable them to outcompete and outbreed others of their kind. This process often occurs over a period of time and is not immediately obvious. For example, one animal’s digestive system may be more efficient than another’s, or one animal may be better at finding food than another. Aggressive behavior is a form of competition that has evolved where organisms have the ability to displace one another quickly, and there are resources worth fighting over. Thus, animals that can remove others by force will seek to do so. Resources that are located in one place and can be obtained by actively displacing a rival will be fought over, whereas those that are evenly and abundantly distributed over a wide area will not. Thus, hyenas fight over a carcass whereas cows do not fight over grass. Broadly speaking, the occurrence of aggression in animals can be understood in terms of the costs and benefits of fighting (Archer, 1988), and this principle can be extended to human aggression.

Sexual Selection A more specific application of the cost–benefit analysis is incorporated into the principle of sexual selection (Darwin, 1871), which involves intermale competition and female choice. With a few exceptions, males have more to gain than females have through fighting one another (or more to lose through not fighting). Trivers (1972) explained why this is the case. The specialization of germ cells leads to unequal parental investment. Females show greater initial investment in terms of the energy and time costs of producing egg cells, and therefore a greater cost is sustained if they choose a low-fitness mate. Males show less initial investment, and therefore sustain a lower cost through choosing a low-fitness mate. These factors result in females being more selective in their mate choice. They also lead to males being in competition with other males for both access to females and the resources that make them more acceptable to females. These considerations enable us to understand why greater physical aggression by males than females is observed in many animal species and is com-

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mon throughout the mammals. Trivers’s (1972) theory of parental investment predicts that sex differences in aggression (and in associated features such as size and strength) are most pronounced when male parental investment is absent and competition between males is at its most intense. This is observed in species such as the elephant seal (Le Boeuf, 1974), when one male defends a group of as many as 40 females against other males. In species in which the male contributes considerably to subsequent parental investment, sex differences are minimal. In those relatively unusual cases in which male parental investment exceeds that of females, it is the females who are larger and more aggressive.

Human Sex Differences in Evolutionary Perspective Comparison of sex differences in body size with those in other primates suggests that there has, in evolutionary history, been a tendency toward mild polygyny in humans (Plavcan & van Schaik, 1997). A range of studies suggests that the sexual natures of men and women, and sex differences in aggression, fit this pattern (Archer & Lloyd, 2002), although there is also considerable variation between males (Archer & Mehdikhani, 2003). A range of evidence on direct physical aggression shows that it is greater among males than females—at least toward adults of the same sex. There are large sex differences in measures of physical aggression (Archer, 2004), and in recorded violent crime (Courtwright, 1996; Daly & Wilson, 1990), for same-sex encounters.

Development from an Evolutionary Perspective Given this evolutionary background, we can understand why human aggression occurs and why there are sex differences in direct forms of human aggression. However, how aggression develops and when the sex differences first appear in development is another question, not readily answered by these evolutionary considerations alone. To appreciate some of the complexities that are involved when we consider development from an evolutionary perspective, it is worth noting a number of general principles that have arisen from research on development from an evolutionary perspective (Archer, 1992a; Bjorklund & Pellegrini, 2002; Stamps, 2003). In each case, we indicate briefly how the principle might apply to the development of aggression and sex differences in aggression. The first principle is that behavior serving an evolutionary function may arise from different developmental processes in different animals. Thus, greater aggressiveness by males is achieved in different ways in different species. In some birds and mammals, testosterone directly enhances male aggressiveness, but as we show in this chapter, it is likely that different processes operate to produce this same end point in humans.

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Second, some types of behavior that develop during childhood serve the function of preparing the individual for a particular role in adulthood. Sex differences in aggression and rough-and-tumble play are likely examples of this in humans (Bjorklund & Pellegrini, 2002). In other cases, behavior may serve an adaptive function during childhood itself. We show that physical aggression develops early in childhood, and that the objective of obtaining and retaining resources may be one reason why this occurs. Third, children are born not with a tabula rasa, but with a program for development that has evolved in human ancestral environments to serve an adaptive outcome. However, the potential range of outcomes, or phenotypes, that can be produced from this program is wide. This is termed the norm of reaction, and it is a particularly important principle for considering development in modern human environments, which are very different from those of our prehistoric ancestors. Thus, the modern school environment may lead to once-adaptive behavior, such as high levels of aggression and rough-and-tumble play, being viewed as maladaptive. Fourth, some evolved forms of behavior are little affected by variability in the environments in which the individuals develop, whereas others are much affected by it. The onset of physical aggression early in life may not be readily susceptible to environmental modification, whereas its subsequent development is likely to be influenced to a much greater extent by the type of social and physical environment in which the individual develops. Fifth, individuals select and modify the environments in which they develop. For example, as a consequence of their own preferences, boys and girls form sex-segregated groups early in their social development, and these last through to the teenage years (Maccoby, 1998). Such groups constitute different social environments, in which boys and girls come to develop different patterns of behavior including aggression, boys showing more direct physical forms, and girls more indirect forms involving manipulation of relationships. A sixth principle is that selection may favor phenotypic diversity rather than a single adaptive type. There are various reasons for this, such as that different phenotypes are adapted for different environments, or that a rare phenotype has an advantage simply because it is unusual. Males of many animal species show what are termed alternative reproductive strategies, for example, specialized either for fighting other males or for sneaking up on females when other males are distracted. In humans, it has been suggested that males vary from the more aggressive risk-prone male who favors a short-term promiscuous reproductive strategy to the less aggressive, more risk-averse male who favors a longer-term parental reproductive strategy (Archer & Mehdikhani, 2003). It follows that a variety of interlinked characteristics, or trait syndromes, are likely to develop together in the same individual. Thus, an aggression-prone individual may show a number of other high-risk and impulsive types of behavior that in our society are typically labeled as antisocial or criminal.

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THE DEVELOPMENT OF PHYSICAL AGGRESSION The social learning perspective has provided an influential account of the development of social behavior, including aggression, in terms of principles originally derived from learning theory (Bandura, 1973; Loeber & StouthamerLoeber, 1998; Reiss & Roth, 1993). Aggressive and violent behaviors are viewed as being learned during childhood and adolescence through exposure to social influences such as violent television, aggressive role models, or deviant peers (Johnson, Cohen, Smailes, Kasen, & Brook, 2002; Patterson, Dishion, & Bank, 1984; Thornberry, 1998). From this perspective alone, we would expect children to become more aggressive and violent as they become older. The social learning perspective provides a stark contrast with a view of development informed by evolutionary principles. First, there is no recognition of an evolved program for the development of aggression to serve the immediate function of resource competition during childhood or as a preparation for conflicts during adulthood. Evolutionary approaches to development recognize that social learning is an important influence in behavior (Stamps, 2003). However, it is one among a wider range of genetic and environmental influences and is likely to extend beyond the facilitation of aggression by social learning that has been the focus of most investigations from this perspective. Recent longitudinal studies indicate that children become less, not more, physically aggressive and violent over time (Broidy et al., 2003; Cairns, Cairns, Neckerman, Fergusson, & Gariepy, 1989; Nagin & Tremblay, 1999; Tremblay et al., 1999). Studies have found that most children followed declining trajectories of physical aggression between kindergarten and grade 6 (Broidy et al., 2003; Nagin & Tremblay, 1999). If the development of aggression were dependent solely on the cumulative effects of social influences tending to promote aggressive behavior, we would expect a significant group of children to begin their use of physical aggression during the elementary school years. Such a group has not been not identified (Kingston & Prior, 1995; Loeber & Stouthamer-Loeber, 1998; Tremblay et al., 1991). The majority of those at risk for later violent behavior were already on high trajectories of physical aggression in kindergarten (Broidy et al., 2003; Nagin & Tremblay, 1999). The possibility that aggression in middle childhood simply reflects the continuation of a behavior pattern already present during the first years of life is supported by research on the development of disruptive behavior disorders during the preschool years. Physically aggressive behavior is common among infants and toddlers (Goodenough, 1931; Hay, Castle, & Davies, 2000; Tremblay et al., 1999). However, most studies have examined the development of aggression during limited periods of development. An exception is the National Longitudinal Study of Canadian Youth (NLSCY), in which the developmental trajec-

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tories of physical aggression between infancy and preadolescence were estimated, with longitudinal data collected on a population sample (n = 8,208). The developmental patterns identified with mother reports indicated that aggression was part of most (65.5%) preschoolers’ behavioral repertoire, but that the majority of children had successfully ceased to use physical aggression by the end of the elementary school years. As shown in Figure 20.1, four distinct trajectory groups were identified in the NLSCY. The first comprised children with stable low levels of aggression. The second group—the rapid-desister group—included children with moderate levels of physical aggression in toddlerhood, who desisted rapidly and maintained low levels from school entry to preadolescence. The third group was labeled the “moderate desisters”: it included children with slow but constant declines in physical aggression between 2 and 11 years. Finally, children

FIGURE 20.1. Trajectories of physical aggression for boys and girls (n = 8,208).

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in the high physical aggression group were also desisting. However, their declines were of such small magnitude that in preadolescence (age 11) they still exhibited notably higher levels of physical aggression than did their peers. It is important to note that no significant group of children with an onset of physical aggression during this period (between 2 and 11 years) was identified. According to a retrospective study with younger children, most infants start to use physical aggression between the first and the second years after birth (Tremblay et al., 1999). Its onset is therefore likely to be earlier and to be relatively stable, rather than being dependent on specific environmental influences that may lead to variable onset (see Tremblay & Nagin, Chapter 5, this volume). This suggests that physical aggression is an evolved pattern of behavior that develops early in life, irrespective of the sort of social influences highlighted by social learning theory. From the evidence reviewed in this section, it is clear that human aggression appears early in life and is part of social interactions right from their beginning. Social learning theory has perhaps laid too much emphasis on the learning of specific forms of aggressive behavior as a general mechanism for explaining the developmental progression of aggression. Although such specific aggressive actions can undoubtedly be learned from peers, parents, and media representations, they do not account for broad changes with age. However, social factors such as coercive parenting, violent models, or violent media may be related to the failure, for a minority of children, to inhibit and regulate their aggression. Why do high levels of physical aggression appear at such young ages? We have already highlighted the importance of competition for resources in functional explanations of aggression. Among young children, we would predict that aggression arises when more than one child claims the same resources. In modern affluent societies, children do not have to fight for their lives, as occurs occasionally in other species (Frank, 1997; Stinson, 1979), or over resources necessary for survival, such as food, as occurs in the young of many birds and mammals (e.g., Bekoff, 1981; Geist, 1978). They may, however, fight over other resources, such as a preferred food, a toy, or a play location. Campbell (1999) argued that most conflicts at preschool ages involve competing for limited resources, such as guarding a toy or a territory.

THE DEVELOPMENT OF SEX DIFFERENCES IN PHYSICAL AGGRESSION Sex differences have been found from the onset of physical aggression itself, in children as young as 17 months, according to mothers’ reports of specific acts of physical aggression (Baillargeon, 2002). In this study, boys were twice as likely as girls to hit another child frequently. Observational studies show differences of fairly substantial magnitudes at around 3 years of age. Hay et al. (2000) found an effect size of d = 0.64, for a (relatively large) sample of 66 children between 18 and 30 months of age. Campbell, Shirley, and Caygill

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(2002) observed considerably more negative interactions with peers by boys than girls in children who were 27 months old. Negative interactions included a child’s grabbing another child’s toy (d = 1.42) and a child’s resisting another’s attempt to grab his or her toy (d = 0.86).1 Observational studies of children 4 years of age have also yielded large effect sizes (e.g., Sears, Rau, & Alpert, 1965: d = 1.27; McGrew, 1972: d = 1.29). The conclusion that sex differences in physical aggression are present early in life is counter to earlier accounts based on the assumption that they arise as a result of the differential socialization of boys and girls (e.g., Tieger, 1980). In a review of sex differences in several types of childhood behavior problems, Keenan and Shaw (1997) put forward a similar view. They reviewed findings from five observational studies (n = 20–90) concerned with the development of aggression during the preschool years. They reported that boys were more aggressive than girls in only one of these studies (Gunnar, Senior, & Hartup, 1984) and concluded that there is no sex difference in aggression for toddlers, although there is an increasing divergence in girls’ and boys’ behavior during the preschool period. This was based on two longitudinal studies indicating that girls exhibited less aggression by age 5. Keenan and Shaw’s conclusion that there are no sex differences for toddlers is not supported by closer examination of the evidence they cite. Their own study of children ages 18 and 24 months interacting with their mothers showed sex differences in global aggression at both ages (18 months: d = 0.49; confidence interval [CI] = 0.07–0.91; p = .02; 24 months: d = 0.39; CI = 0.02– 0.80; p = .06), those at the younger age being greater (figures calculated from Table 2 in Shaw, Keenan, & Vondra, 1994). Jacklin and Maccoby (1978) observed dyads of 33-month-old children: Comparing aggression among male dyads with that among female dyads (i.e., taking each dyad as a unit) produced a small effect size in the male direction (d = 0.18). Cummings, Iannotti, and Zahn-Waxler (1989) observed children playing with their best available friends at 2 and at 5 years. For the two ages combined (the only calculation possible), effect sizes for sex differences in aggression were d = 0.26 in the male direction. Caplan, Vespo, Pedersen, and Hay (1991) observed 1- and 2year-olds in mixed-sex groups of three for 25 minutes. The main comparison was between the level of conflict in groups with one male and groups with one female. A footnote indicated that there was no significant sex difference at an individual level, but no direction was reported (for this sample size, the d value could have been anywhere between -0.57 and 0.57). The remaining study (Gunnar et al., 1984) found significantly longer duration of conflicts among male than female dyads (d = 1.04). A meta-analysis of the four studies that enabled effect sizes to be calculated produced a weighted mean of d = 0.44 (CI = 0.15–0.74; p = .003), showing that there was a moderate sex difference in the male direction. This contrasts with Keenan and Shaw’s conclusion, based on a narrative review, that there are no sex differences at young ages. It supports the conclusion from the

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other studies described above, that the sex difference occurs as early as it is possible to measure children’s aggressive behavior. Keenan and Shaw’s (1997) review also raised the question of how sex differences in physical aggression change throughout childhood, as they claimed that it increased from about 2 to 5 years of age, based on two longitudinal studies. A meta-analysis of 40 observational studies carried out between 1965 and 2000 (Archer, 2004) showed no significant difference in the effect size for the sex difference in aggression (overall d = 0.53) between three age categories, under 6 years, 6–11 years, and over 11 years. However, this involved cross-sectional comparisons of different studies, and there are limitations to the inferences that can be drawn from such evidence. Large-scale representative samples provide a way of overcoming the limitations, although at younger ages they involve less direct assessments of behavior, inasmuch as they generally rely on mothers’ reports. In the NLSCY (see the preceding section), sex differences in physical aggression were examined by comparing the proportion of boys and girls assigned to the different trajectory groups. The results showed that boys were more likely to be on the highest physical aggression trajectories (odds ratio [OR] = 1.56; 95% CI = 1.41–1.71) and less likely to be on the lowest trajectories (OR = 0.85; 95% CI = 0.82–0.89). This suggests that boys were already more physically aggressive than girls at 2 years of age, a difference that persisted throughout childhood. These sex differences are consistent with the findings from the individual observational studies presented earlier. The NLSCY study also found that the initial sex difference became more pronounced during the course of childhood, as boys were less likely to be assigned to the rapid-desister trajectory group (OR= 0.88; 95% CI = 0.82– 0.94). These findings support Keenan and Shaw’s (1997) conclusion that sex differences in physical aggression increase during the preschool years and that this is attributable to girls’ faster rate of decline between 2 and 5 years. Thus, girls may learn more quickly than boys to inhibit or control (physically) aggressive behaviors (Kochanska, Murray, & Harlan, 2000). Finally, there were no significant sex differences for the moderate desister group (OR = 1.05; 95% CI = 1.00–1.09). One further point about the sex differences found in the NLSCY study is that they are far from absolute. Many boys are found in the low groups and the rapid-desister groups, and many girls are found in the high-trajectory group. Such variation may be worth investigating in relation to the evolutionary hypothesis of alternative reproductive strategies, which would predict consistent ways of responding, with an early developmental onset and a consistent outcome. A meta-analysis of sex differences in self-reports of physical aggression (Archer, 2004) showed similar effect sizes for the age categories 6–11 years, 12–3 years, and 14–17 years. The lack of any further widening in the sex difference at puberty provides indirect evidence that pubertal testosterone does not increase male aggressiveness, as it does in some other mammals (e.g.,

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Beeman, 1947; Edwards, 1969). More direct support for this conclusion comes from a longitudinal study of boys going through puberty (Halpern, Udry, Campbell, & Suchindran, 1994), which found no influence of rising testosterone levels on physical aggression. The meta-analysis of self-reported physical aggression (Archer, 2004) did find larger sex differences in the age categories 18–21 and 22–30 years than at younger (14–17 years) or older ages (31–55 years). Studies of violent crime and of homicides show that there is a pronounced peak in males between about 20 and 29 years of age. This was found for homicides in data sets from four locations with different homicide rates, England and Wales, Canada, Chicago, and Detroit (Daly & Wilson, 1990), and for violent crimes in the modern United States, 19th-century England and Wales, and early 19th-century Europe (Courtwright, 1996; Quetelet, 1833/1984). Although these studies differ from those we have considered so far in that they involve much rarer violent acts, defined by their damaging consequences rather than the type of behavior, they show a striking parallel in their pattern of age and sex distribution. The evidence reviewed in this section indicates that there is a large sex difference in physical aggression, beginning early in life, suggesting that it is not the product of a gradual process such as socialization (Tremblay et al., 1999). However, there is also evidence from a longitudinal study that the sex difference in physical aggression, such as hitting, biting, and attacking others, may become larger between toddlerhood and kindergarten. There is no evidence that the sex difference widens at puberty as a consequence of the action of the male hormone testosterone. However, studies of self-reported physical aggression and of violent acts converge to suggest a widening of the sex difference between 18 and 30 years of age. These are peak years for the development of a constellation of characteristics that enable a young man to successfully compete with other males.

THE DEVELOPMENT OF SEX DIFFERENCES IN PHYSICAL AGGRESSION: AN EVOLUTIONARY VIEW We noted that resource competition provides an evolutionary reason for the appearance of physical aggression early in life. However, it is less clear why there would be sex differences in this aggression early in life. We might expect, in the absence of reproductive competition, boys and girls to behave similarly, inasmuch as they would be competing for similar resources. Campbell (1999) articulated this view, arguing that, as toddlers, children’s conflicts are mainly related to competing for limited resources, such as guarding a toy or a territory. She also argued that there are no sex differences in this type of resource-oriented aggression among toddlers, whereas there is a sex difference in status-oriented aggression by 4 years of age. The first conclusion was based on a narrative review of a very small number of studies that sought to

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distinguish these different categories of aggression. It is inconsistent with other findings (e.g., Gunnar et al., 1984; Jacklin & Maccoby, 1978), and with a later study by Campbell et al. (2002), which reported very large sex differences at 27 months in negative interactions (including a child’s grabbing another child’s toy and a child’s resisting another’s attempt to grab his or her toy). Campbell is more likely to be correct in her identification of status disputes as an important area in which the sexes diverge in the early years. It is clear that as children become older there is increasing sex segregation and different types of social relations in boys’ and girls’ groups, based initially on self-selection of playmates (Archer, 1992b; Maccoby, 1998). Boys are more concerned with status and dominance—for example, who is tough and who is the boss (Weisfeld, 1994)—and they operate in larger play groups. Girls form more intense relations with one or two close friends (Archer, 1992b). These contrasting patterns have wide-ranging implications for later sex differences in several areas of social behavior, including other forms of aggression (Maccoby, 1998). Because of the greater emphasis on physically based dominance in childhood, boys’ exchanges are more likely to develop into physical aggression, whereas girls develop strategies of indirect aggression that become prominent in the teenage years. Nevertheless, as we noted earlier, the expectation that there will be a greater contrast between the frequencies of physical aggression in boys’ and girls’ groups as they become older has, as yet, only limited empirical support. Sex differences in physical aggression prior to the ages of reproductive competition are found in the young of many mammals, together with sex differences in rough-and-tumble play. In addition to the advantages during childhood of gaining tangible rewards, such as food and other valued resources, success in physical fights, whether over status or resources, may have two other longer-term consequences. The first involves the learning of techniques of fighting that may prove valuable in young adulthood, and the learning of cues associated with when it is preferable not to fight (assessment strategies; Archer, 1994). The second involves the longer-term advantage, conferred by a physically based dominance acquired during childhood, for dominance in young adulthood. This may have been considerable in the ancestral environment, and may still be so where physical prowess forms the basis of dominance orders in adulthood, as occurs in many masculine subcultures. If the sex difference in physical aggression found in childhood arises mainly from the concern of boys with dominance relations and the learning of ways of fighting in preparation for adulthood, we would expect it to be largely manifest in relation to same-sex disputes. If instead it arises from resource competition (as suggested for early ages), we would expect the aggression to be directed to any child who has a preferred toy, irrespective of his or her sex. There are relatively few studies that have separated the sex of the opponent when considering children’s aggression. Where they have, the evidence supports the view that sex differences in physical aggression concern aggres-

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sion to same-sex opponents. A different pattern (in the female direction) is found whenever the (less frequent) between-sex physical aggression is studied. For example, an observational study by Barrett (1979) of 6- to 7-year-old children found a substantial sex difference in physical aggression in the male direction for same-sex opponents (d = 1.05)2, and a difference in the female direction for opposite-sex opponents (d = –0.53). Pellegrini and Long (2002) followed up a sample of children at 6-monthly intervals from 12.8 years of age and found at all ages except the youngest one, a sex difference in the male direction for same-sex aggression and in the female direction for opposite-sex aggression. Effect sizes were in the moderate range, from 0.29 to 0.46. Cairns and Cairns (1994) reported similar findings using questionnaires at 11 and 14 years of age. A questionnaire study involving an older age (16.8 years) found a similar pattern, with d = 1.03 for same-sex aggression and –0.95 for oppositesex encounters (Hilton, Harris, & Rice, 2000). Gergen (1990) and Harris (1992) found similar results using self-reports at 19 years of age.

SEX DIFFERENCES IN VERBAL AGGRESSION The evolutionary origins of verbal aggression are seen in the vocal threat displays of animals. Some aspects of human aggression are directly comparable, such as shouting in a loud and intimidating way at someone, accompanied by threatening gestures. These forms are found as early as children show social interactions, and accompany physical aggression. Other types of verbal aggression are uniquely human, for example, making verbal threats that specify intended violent actions, such as “I’ll smash your head in.” Insults are also uniquely human and generally involve remarks or accusations that challenge important aspects of a person’s identity, denigrating the person in some way. For example, a teenage boy may be called names that imply that he is cowardly, such as “chicken” or “yellow,” whereas a teenage girl may be called names that imply that she is sexually promiscuous, such as “slag” or “slut” (Campbell, 1995). These insults challenge characteristics that are especially valued in the particular sex. Traditionally, insults were viewed as attacks on a person’s honor or reputation and, in circumstances where there was no effective rule of law, had to be avenged to prevent loss of face and status for both the person and his or her family (Nisbett & Cohen, 1996; Ruff, 2001). Thus, insults such as “son of a bitch” or “bastard,” which have largely lost their potency in modern society, were once regarded as denigrating statements about a person’s whole family. More subtle forms of verbal aggression develop later in childhood, for example, making someone the butt of remarks that are denigrating to that person, but humorous to others. Being able to use language in this way is particularly important in groups of teenage boys and young men (Benson & Archer, 2002). There is therefore considerable diversity within the category “verbal aggression.” Yet verbal aggression by both sexes has generally been considered as a

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single overall category, so that the use of particular forms of verbal aggression by the two sexes has seldom been studied. Meta-analytic summaries of sex differences in aggression can only provide a broad view of changes with age. The sex difference for self-reported verbal aggression is in the same direction as that for physical aggression, but is generally smaller in size (Archer, 2004). The difference was smaller at 6–11 years (d = 0.19) than at 11 to 17 years (d = 0.36). Studies involving observations showed little difference across age categories for verbal aggression. However, there are individual studies showing sex differences in verbal aggression at young ages. Fagot and Hagan (1985) found differences in the male direction of d = 0.31 between 2 and 3 years of life. McGrew (1972) and Sears et al. (1965) found larger differences (d = 0.53 and 1.05) at 4 years of age. As in the case of physical aggression, these sex differences are restricted to same-sex encounters, when the sex of the opponent is considered (Barrett, 1979; Tucker, 1989; Hilton et al., 2000).

THE DEVELOPMENT OF SEX DIFFERENCES IN INDIRECT AGGRESSION Indirect aggression refers to covert forms of aggression, as opposed to direct or face-to-face forms. It may be physical, such as in destroying someone’s property, or verbal, through deliberately attacking a person’s social standing or via malicious gossip or social ostracism (Archer, 2001). Most studies have concentrated on verbal forms, such as getting others to dislike a person, becoming friends with another as a form of revenge, telling a person’s secrets to another, saying bad things about people behind their backs, and telling others to avoid someone. Lagerspetz, Björkqvist, and Peltonen (1988) were the first to carry out a systematic study of indirect aggression using peer ratings, which are particularly suited to a study of this form of covert aggression. They documented large sex differences in the female direction, which were found in later studies (Björkqvist, Lagerspetz, & Kaukiainen, 1992a). Sex differences have also been found in a very similar form of aggression, termed relational (Crick & Grotpeter, 1995). It is a matter of dispute whether relational aggression is the same as indirect aggression (Björkqvist, 2001) or closely overlaps with it (Archer, 2001). Björkqvist, Osterman, and Kaukiainen (1992b) proposed that the expression of aggression changes over the life course. Normatively, as children mature, aggression changes from mainly physical to verbal, and then from verbal to indirect. In their cross-sectional analysis, levels of particular forms of indirect aggression, such as gossip, were much lower in both sexes at 8 years of age, but were higher at 11, 15, and 18 years, and sex differences were particularly pronounced at these three older ages. A meta-analysis of studies using peer reports to investigate indirect aggression (Archer, 2004) showed that effect sizes increased with age over the range of 6–17 years, so that by the teenage years they were substantial. This coincides with the larger sex differences

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found from 11 years onward in Björkqvist’s analysis, and with evidence from the NLSCY, presented in the following discussion. Vaillancourt (Chapter 8, this volume) presents in detail theories of the development of indirect aggression, as well as developmental trajectories (for ages 4 and 11 years) estimated from the NLSCY (see also Vaillancourt et al., 2004). Briefly, the results indicate that the development of indirect aggression follows a pattern opposite to that for physical aggression in the same sample: While physical aggression decreases during childhood, indirect aggression increases. The development of physical and indirect aggression found in the NLSCY support the notion that boys and girls use different types of aggressive behavior over the course of childhood. Indeed, the results show not only a stronger tendency for girls to cease using physical aggression, they also show a stronger tendency for girls to increasingly use indirect aggression over time (i.e., girls are more likely than boys to follow rising trajectories of indirect aggression). It is noteworthy that the NLSCY shows that both sexes use both forms of aggression, physical and indirect. Early in childhood (from age 2), girls already use less physical aggression and more indirect (or relational) aggression than boys do. These sex differences become even more pronounced over time, with boys being less likely to exhibit declining levels of physical aggression prior to kindergarten, and girls being more likely to follow rising trajectories of indirect and relational aggression during middle childhood. Even so, boys and girls were represented on all types of trajectories, so that we again have to caution that these generalizations hide considerable individual variation. For instance, a substantial proportion of girls (33.1%) followed a high and mostly stable trajectory of physical aggression, and a substantial proportion of boys (40.3%) followed a high and rising trajectory of indirect aggression. Thus, the sex differences were related to the proportion of boys and girls on trajectories reflecting high levels or changing levels of physical and indirect aggression. These longitudinal data broadly agree with the cross-sectional analysis of Björkqvist and his colleagues, and with the meta-analysis of age differences. An analysis of the same data found distinct factors for physical and indirect aggression, which were stable over time (Vaillancourt, Brendgen, Boivin, & Tremblay, 2003). Sex differences at younger ages (4 to 7 years) were in the female direction, but small in size, across four cohorts. Generally, they became larger from 8 to 11 years, –0.26 and –0.28 being the largest values.3

THE EVOLUTIONARY SIGNIFICANCE OF SEX DIFFERENCES IN INDIRECT AGGRESSION Campbell (1999) proposed that females tend to use forms of aggression that carry low risks for physical injury, such as indirect aggression (see also Björkqvist, 1994). She related this, in evolutionary terms, to the greater value

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attached by women to protecting their own lives, because the survival of their infants is more dependent on the mothers’ care and defense than the fathers’. In this context, the cost of direct and physical aggression, the forms that represent risk for one’s physical safety, is greater for women than men. The greater use of indirect and relational aggression among girls, and of physical aggression among boys, is also relevant for competition with peers in the social domain. In an earlier section, we referred to the importance of same-sex peer groups during childhood, and the values adopted in these groups, for explaining sex differences in physical aggression. This can be extended to an understanding of indirect aggression. Specifically, Maccoby (1998) and Crick and Grotpeter (1995) suggested that the structure of female friendships, which tend to be based on intimacy and cohesiveness, facilitates the use of indirect and relational forms of aggression among girls. A cohesive social network enables this form of covert aggression to be used more effectively (Green, Richardson, & Lago, 1996).

CONCLUSIONS In this chapter we have sought to place the development of human sex differences in aggression into an evolutionary context. The evolution of aggression can be understood in terms of its origins in the natural world, and its benefits and costs in particular situations. Sex differences in aggression can be understood in similar terms, by considering the imbalance in parental investment in the two sexes. Aggression begins early in postnatal life in many animals, and data from small-scale observational studies, and from a large-scale longitudinal study, indicate that this is the case for humans. Such aggression consists largely of physical forms, with accompanying vocalizations. Higher levels are found in boys than girls from an early age, and these encounters arise from both property-related and dominance disputes. Following the trajectories of aggression in a large representative sample showed a gradual decline in physical aggression overall, suggesting that rather than having to be socialized into being aggressive, children gradually learn to inhibit their direct forms of aggression. More boys than girls were found on the developmental trajectories containing the highest rates of physical aggression, and more girls than boys were found on the lowest trajectories. Indirect or relational aggression appears later in development, and girls were more likely than boys to follow rising trajectories in this form of aggression, coinciding with findings that the sex difference in indirect aggression is particularly pronounced in the teenage years. These contrasting developmental pathways in girls’ and boys’ aggression are not absolute differences, but show an overlap between the sexes. Nevertheless, they can be understood in terms of the different forms of social relations that are typical of boys’ and girls’ social groups, as well as in terms of the different selection pressures on males and females resulting from sexual selection.

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NOTES 1. All these effect sizes were calculated from the published data using DSTAT (Johnson, 1989). 2. Effect sizes were calculated by the first author, using D-STAT (Johnson, 1989). 3. Values calculated from the authors’ data.

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morphism in anthropoid primates. American Journal of Physical Anthropology, 103, 27–68. Quetelet, A. (1984). Research on the propensity for crime at different ages. (S. F. Sylvester, Trans.). Cincinnati, OH: Anderson. (Original work published 1833) Reiss, A. J., & Roth, J. A. (1993). Understanding and preventing violence. Washington, DC: National Academy Press. Ruff, J. R. (2001). Violence in early modern Europe 1500–1800. Cambridge, UK: Cambridge University Press. Sears, R. R., Rau, L., & Alpert, R. (1965). Identification and childrearing. Stanford, CA: Stanford University Press. Shaw, D. S., Keenan, K., & Vondra, J. I. (1994). Developmental precursors of externalizing behavior: Ages 1 to 3. Developmental Psychology, 30, 355–364. Stamps, J. (2003). Behavioural processes affecting development: Tinbergen’s fourth question comes of age. Animal Behaviour, 66, 1–13. Stinson, C. H. (1979). On the selective advantage of fratricide in raptors. Evolution, 33, 1219–1225. Thornberry, T. P. (1998). Membership in youth gangs and involvement in serious and violent offending. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 147–166). Thousand Oaks, CA: Sage. Tieger, T. (1980). On the biological basis of sex differences. Child Development, 51, 943– 963. Tinbergen, N. (1963). On the aims and methods of ethology. Zeitschrift fur Tierpsychologie, 20, 410–413. Tremblay, R. E., Japel, C., Perusse, D., Boivin, M., Zoccolillo, M., Montplaisir, J., & McDuff, P. (1999). The search for the age of “onset” of physical aggression: Rousseau and Bandura revisted. Criminal Behavior and Mental Health, 9, 8–23. Tremblay, R. E., Loeber, R., Gagnon, C., Charlebois, P., Larivée, S., & LeBlanc, M. (1991). Disruptive boys with stable and unstable high fighting behavior patterns during junior elementary school. Journal of Abnormal Child Psychology, 19, 285– 300. Trivers, R. (1972). Parental investment and sexual selection. In B. B. Campbell (Ed.), Sexual selection and the descent of man (pp. 136–179). Chicago: Aldine. Tucker, M. L. (1989). Anger and aggression in early adolescence: The influence of hormones and social context. Dissertation Abstracts International, 50(2), 761B. (UMI No. 8821665) Vaillancourt, T., Brendgen, M., Boivin, M., & Tremblay, R. E. (2003). Longitudinal confirmatory factor analysis of indirect and physical aggression: Evidence of two factors over time? Child Development, 74, 1628–1638. Vaillancourt, T., Côté, S., Farhat, A., Leblanc, J. C., Boivin, M., & Tremblay, R. E. (2004). The development of indirect aggression among Canadian children. Manuscript submitted for publication. Weisfeld, G. (1994). Aggression and dominance in the social world of boys and girls. In J. Archer (Ed.), Male violence (pp. 42–69). London and New York: Routledge.

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Part IV CHALLENGES FOR THE FUTURE

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CHALLENGES Where Are We Going? FOR THE FUTURE

21 The Developmental Origins of Aggression Where Are We Going? R ICHARD E. T REMBLAY and S YLVANA C ÔTÉ

The aim of this book was to review the state of knowledge on the developmental origins of aggression. Contributions were divided in two categories: Chapters 2–10 describe different types of aggressive behavior and the changes that occur as individuals increase in age; Chapters 11–20 review factors often considered to be proximal and distal determinants of aggressive behavior. Like all attempts to carve nature at its joints, separating the development of aggressive behavior from putative determinants is a perilous enterprise, especially when nature has not yet been precisely described. The aim of this final chapter is to summarize where we come from, where we stand, and where we appear to be going with reference to selected key issues. As we planned this book, it became clear that we were following a path traced by another book published 30 years earlier (De Wit & Hartup, 1974). In Chapter 1 of this volume, Willard W. Hartup, an editor of the previous book, highlights three important changes that have occurred over these past three decades. First, investigators shifted their attention from the aggressive act to the aggressive individual. Second, the research became truly developmental; that is, longitudinal data were collected, enabling investigators to look at changes over time within individuals. Third, investigators increasingly aggregated the concepts of aggression and antisocial behavior. In this chapter, we add four more changes that we believe are important to future research on aggression: More studies are focused on aggression during the first 3 years after birth; there is an explosion of studies on the biological bases of human aggres447

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sion; we have started to systematically study gene–environment interactions; and preventive interventions are being used as experiments to test causal factors. Six of these seven changes should mark the next few decades of research, because they are essential for the unraveling of the developmental origins of aggression. However, one of the seven changes (aggregating aggression and antisocial behavior) may be a serious handicap in achieving this task.

CHANGES IN AGGRESSIVE ACTS OVER TIME WITHIN INDIVIDUALS Two of the three changes Hartup highlights in Chapter 1 go hand in hand. If we are studying aggressive behavior, the aggressive act must obviously remain the basic phenomenon of study; however, understanding development implies a focus on changes over time within individuals. Here are examples of developmental questions that target the aggressive acts of individuals over time: When, during an individual’s life course, do different types of aggressive acts start? Does the frequency of these acts change over the life course? Do the victims of these acts change during the life course? Do the determinants of these acts change during the life course? Do the consequences of these acts change during the life course? How and when, during the life course, can we change these developmental trajectories? The traditional approach to answering these questions was a crosssectional design, that is, comparing samples of individuals of different ages. In the De Wit and Hartup (1974) book there are two very good examples of this (Hapkiewicz, 1974; Hoving, LaForme, & Wallace, 1974). Note that Hapkiewicz’s chapter has a perfect developmental title: “Developmental Patterns of Aggression.” But there are many more recent examples, such as the following chapters in other books: “The Development of Direct and Indirect Aggressive Strategies in Males and Females” (Björkqvist, Österman, & Kaukiainen, 1992) and “Do Children in Canada Become More Aggressive as They Approach Adolescence?” (Tremblay et al., 1996). We now have longitudinal data to study intra-individual changes in aggression, and these studies are reviewed in the first 10 chapters of this volume. However, many, if not most of the studies on the determinants of aggression (Chapters 11–20) provide little developmental information on aggression, because the aggressive acts (the dependent variable) to be explained by one or many determinants (independent variables) tend to be assessed at only one point in time. Many longitudinal studies are used to conduct cross-sectional analyses, or predictive analyses, that is, assessing the strength of the correlation between independent variables and aggression either at the same point or at two different points in time. For example, see Chapter 11 on genetics and aggression (Pérusse & Gendreau), and count how many of the cited studies used the within-individual development of aggressive behavior as the phenotype to be explained by genes and environment. Studies on intra-individual

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change in playful aggression (Chapter 7, by Peterson & Flanders), indirect aggression (Chapter 8, by Vaillancourt) and proactive–reactive aggression (Chapter 9, by Vitaro & Brendgen) are either nonexistent or extremely rare. Most of the studies attempt to find causes of a phenotype measured at one point in time, and hence not the development of a behavior over time. The maintenance of a cross-sectional approach is most evident in the data available for the meta-analyses of sex differences in aggression presented in Chapter 20 by Archer and Côté. It is tempting to conclude that studying the development of a phenomenon does not come naturally to humans. This is best exemplified by the behavior of many of the young, and not so young, investigators who come to work on our longitudinal data sets. They say they are attracted by the richness of the longitudinal data that we have collected. They spend weeks, and often months, reviewing the literature, examining the data that was collected, and come up with questions such as, “Do obstetrical complications predict violent behavior in late adolescence?” “Does behavior in kindergarten predict violent behavior in early adulthood?” “Do different types of aggression in early adolescence predict equally well spouse aggression?” Each of these questions has some theoretical and practical value. Each necessitates longitudinal data that span decades. But they are not asking one of the developmental questions asked at the start of this section. The preoccupation is with prediction from time X to time Y, rather than describing the development of a phenotype and identifying the mechanisms that unfold over time. Humans are in a hurry to know—“can’t wait for 20 years to confirm a theory.” From a developmental science perspective, showing that characteristics at time X predict characteristics at time Y is as simplistic as showing that one, or an array of genes predict behavior at a given point in time. Selecting two points in time from a data bank that includes repeated assessments over long periods of time is similar to dichotomizing a continuous measurement scale; there is a huge loss of information. By the same analogy, the important developmental questions are concerned with the pattern of the distribution of the scores, not by the creation of two groups that are somewhat different. Taking a developmental perspective means, first, to understand the development (change over time) of the phenomenon we are trying to predict, and second, to describe the causal chain of events over time that explain the development. However, a premium is generally given to studies that aim at testing causal theories (that is: testing the strength of the correlation between a “determinant” and an “outcome”). Although there is a need for studies with such objectives, the need for studies that describe the development of a phenomenon over time is obviously a prerequisite for understanding the cause of the development. Those who tend to value theory testing more than descriptions should look back to the revolutions created by the simple descriptions of Copernicus, Galileo, and Mendelyev (see also Tinbergen, 1963). Galileo certainly did not find it easy to convince his colleagues that Co-

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pernicus’s description of the solar planet trajectories was closer to the truth than the trajectories their theories led them to imagine, notwithstanding who or what caused the phenomenon. As the longitudinal data become available and the next generation of investigators come into their prime, the traditions should change. The research efforts aimed at explaining behavior development should be accompanied by efforts aimed at describing that development, ideally over the life course. Unfortunately, the best designed and longest running longitudinal studies with birth cohorts apparently did not obtain repeated assessments of aggressive behaviors between birth and school entry (e.g., Fergusson & Horwood, 1995; Moffitt, Caspi, Dickson, Silva, & Stanton, 1996; Power, Manor, & Fox, 1991; Raine et al., 2001). Thus, to describe the life course development of different forms of aggressive behavior, we will have to count on new birth cohorts. This means that complete life course data will become available in not less than 90 years! Someone should start soon, concentrate on collecting as much data as possible over the early years, be persistent, and be prepared to train many generations of investigators. This is the price we have to pay to make serious claims of conducting “life course” research on human development.

CLASSIFICATION: THE AGGRESSIVE AND ANTISOCIAL BEHAVIOR CASE Chapter 2 by Gendreau and Archer shows the complexity of creating a classification of aggressive behaviors, the basic building block of a science. This is not a new problem (see e.g., De Wit & Hartup, 1974), and it is a problem that all sciences have to handle with care (Appel, 1987; Burkhardt & Smith, 1988). From that perspective, we strongly believe that the tendency over the past 30 years to aggregate aggressive and antisocial behaviors (see Hartup, Chapter 1, this volume) is a serious mistake. First, from an evolutionary perspective, aggression is an adaptive behavior. It is a tool that individuals learn to control during their development. For example, playful aggression is a natural behavior of nonhuman (e.g., juvenile rats, cats, dogs, monkeys) and human animals (see Pellis, Pellis, & Foroud, Chapter 3, and Petersen & Flanders, Chapter 7, this volume). Adult humans continue to play fight through physically aggressive games such as boxing, wrestling, rugby, American football, and ice hockey. Humans also produce and consume a huge amount of fictive violence in books, plays, electronic games, and movies. Many humans learn to master different complex forms of physical aggression for defensive purposes, for example, by training in martial arts, by training in the art of boxing, or by learning to use weapons such as guns and rifles. The practice of aggregating aggression and antisocial behavior that appeared in the research over the past 30 years (see Hartup, Chapter 1, this volume; Coie & Dodge, 1998; Tremblay, 2000) probably reflects the ambivalent relationship humans have with aggression. For example, there have been strong movements in the past 30 years to prevent children from playing

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aggressive games (e.g., parents should not buy toy guns) and to protect children from aggressive contents in books, movies, and video games. It is argued that these activities train them to become “antisocial” (e.g., Anderson et al., 2003; Jones, 2002). Meanwhile, violent movies and violent video games have the biggest commercial success, games such as hockey are said to have become more violent than ever, thousands of young men are trained for preemptive wars, and we see, every day on television, the thousands of people violently killed during these wars. These are certainly not the most noble of human behaviors; however, they should not be aggregated with “antisocial behaviors” that are defined as law-breaking behaviors by criminologists and as mental illnesses by psychiatrists. Similarly, indirect aggressions (see Vaillancourt, Chapter 8, this volume) manifested by elementary school girls or university professors are aggressions, but they should not be confused with the “antisocial behaviors” that are of interest to criminologists, psychiatrists, and clinical psychologists. Second, if not all aggressions are antisocial, it is also true that not all antisocial behaviors are aggressions. For example, in their review of the state of knowledge on aggression, Coie and Dodge (1998) include behaviors such as substance abuse and risky sexual behavior in their definition of antisocial behavior. It seems a far stretch to label these “aggressive.” Many of the chapters in this book had to rely on studies of the general “antisocial behavior” concept, because there were not enough studies that specifically targeted aggressive behavior. One would expect that age of onset and determinants of verbal and indirect aggression trajectories would be different from onset and determinants of antisocial behaviors described as smoking marijuana (substance abuse) and not wearing a condom during sexual intercourse (a risky sexual behavior) (Coie & Dodge, 1998). We believe that instead of aggregating aggressive behaviors with antisocial behaviors, we need to go in the opposite direction if we are to understand the developmental origins of aggression. We need to disaggregate aggressive behaviors. Many studies over the past few years have targeted subcategories of aggression, such as physical aggression (see Tremblay & Nagin, Chapter 5, this volume), indirect aggression (see Vaillancourt, Chapter 8, this volume), playful aggression (see Pellis, Pellis, & Foroud, Chapter 3, and Petersen & Flanders, Chapter 7, this volume), and proactive and reactive aggression (see Vitaro & Brendgen, Chapter 9, this volume). We predict that in the long run, the “splitters,” those who disaggregate the components of aggressive behaviors, will make a more important contribution to understanding the developmental origins of aggression, than the “lumpers,” those who aggregate many forms of aggression and a large variety of antisocial behavior. The success of the physical and biological sciences has been strongly linked to the “splitters” approach. For instance, from measuring the circumference of the skull in the nineteenth century (Lombroso, 1896), investigators moved on to identifying the large components of the brain (MacLean, 1949) in the middle of the 20th century. We are now able to precisely describe the lifespan development of

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every part of an individual’s brain without using a scalpel (see Paus, Chapter 12, this volume), and we are discovering the importance of prions (Si et al., 2003). The work of Eric Kandel, the senior collaborator of the last cited article, is probably one of the best examples of the scientific value of “reductionism” (Kandel, 2000). The young psychoanalyst decided that the human and nonhuman primate brains were too complex to understand. He chose to study how a sea slug’s brain (Aplysia) learns. His reductionist work over four decades revealed how memory is created in the brain of a mollusk, a rat, and a human. Without doubt, Sigmund Freud, the young biologist, would be proud of the accomplishment of his Vienna-born colleague. The development of different forms of aggressive behavior appears much less complex than the development of the human brain. We simply need more investigators who will patiently observe and describe this development.

AGGRESSION DURING EARLY CHILDHOOD Aristotle starts the second chapter of Book I of Politics with the following sentence: “He who considers things in their first growth and origin, whether a state or anything else, will obtain the clearest view of them” (Aristotle, 1943, p. 248). How obvious! It has been repeated many times since then, once by Hamburg and van Lawick-Goodall in a chapter in De Wit and Hartup (1974): “There is a great need for direct studies, utilizing systematic observational techniques, of aggressive behavior and its precursors in human infancy and early childhood” (p. 72). Out of 45 chapters in that book, only three provided some information on preschool children. There were a number of important studies on preschool children in the 1920s and 1930s (see Hay, Chapter 6, and Tremblay & Nagin, Chapter 5, this volume). There was also a wave of these studies in the 1970s and 1980s, apparently stimulated by the ethological work with primates (e.g., Blurton Jones, 1972; McGrew, 1972; Restoin et al., 1985; Smith, 1974; Strayer & Trudel, 1984), but they were cross-sectional. There are still occasional observational studies on aggression in early childhood (see Hay, Chapter 6, this volume). But the vast majority of studies on the development of aggression in humans were, and still are carried out with individuals in either elementary or secondary schools. One reason why few longitudinal preschool studies have been conducted is certainly because they are exceptionally difficult to do. The tradition has been to use direct observations—methods of data collection that are time-consuming both at the data collection and the data analysis levels, even for very small samples. Yet, there are good methodological reasons for choosing to study schoolage children: (1) They are easy to find, because they all have to go to school, (2) representative samples of populations can be easily created, and (3) reports of aggressive behaviors can be obtained from different sources—teachers, parents, peers, self-reports. However, the methodological challenges of studying preschoolers should not be a sufficient cause for their paucity. Recent epidemiologi-

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cal studies with very large representative cohorts of newborns have shown that the methods used with older children (i.e., parent and educator reports on children’s behavior) can provide useful information on the developmental origins of aggression during early childhood (e.g., Côté, Vaillancourt, LeBlanc, Nagin, & Tremblay, 2004; Dionne, Tremblay, Boivin, Laplante, & Pérusse, 2003; Kingston & Prior, 1995; Tremblay et al., 2004b). A second reason for neglecting early childhood aggression over the past 30 years may have been the popularity of the social learning theory (Bandura, 1973). It is probably not an exaggeration to say that most of the research on the development of human aggression in the last few decades of the 20th century was strongly inspired by the social learning paradigm. Although Bandura had studied aggressive behavior in nursery schoolchildren, most of the longitudinal studies initiated with a social learning perspective were attempting to find how schoolchildren learn to aggress from their environment. Parents, peers, movies, and television were the obvious models (e.g., Cairns & Cairns, 1994; Farrington, 2003; Huesmann & Miller, 1994; Lefkowitz, Eron, Walder, & Huesmann, 1977; Loeber, Farrington, Stouthamer-Loeber, & Van Kammen, 1998; Patterson, 1982; Thornberry, 1998; Tremblay, Vitaro, Nagin, Pagani, & Séguin, 2003). A third reason for neglecting early childhood aggression is possibly related to funding. Research priorities have been and will remain dictated by policy issues. Each time an adolescent commits a homicide, the pressure increases to understand the causes of violence during adolescence and to find ways of helping or restraining at-risk adolescents. It is not easy to convince agencies and peers that a study of infants’ aggression is the answer to understanding, and preventing, violence during adolescence. Thus, most funding of research on violence is channeled toward studies of individuals who are big enough to hurt others seriously when they aggress. The increasing evidence that control over physically violent behavior is mostly learned by humans during early childhood (see Tremblay & Nagin, Chapter 5, this volume) should help convince policymakers and funding agencies that research on early childhood aggression could help our understanding of the developmental origins of aggression and eventually prevent the violent behaviors of adolescents who scare the population. However, if there were a sudden increase in funds to study aggression during early childhood, there would be a receptor problem, inasmuch as there are very few investigators with the necessary training. Fortunately, there are examples indicating that investigators working on violence during adolescence or adulthood can become interested in studying aggression in the early years. In fact, the investigators of aggression needed for the future are individuals who focus on the development of aggression throughout the lifespan. The development of human behavior cannot be understood if it is cut into investigator-convenient age slices. The problem with direct observation, discussed earlier, will probably be solved in the near future by multidisciplinary teams that will include this timeconsuming but important approach within a global strategy. For example,

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large population cohorts of children can be studied using parent ratings, while subsamples are strategically selected for intensive direct observations of social interactions, paired with key biological data collections such as saliva samples and brain scans (see Paus, Chapter 12, Pihl & Benkelfat, Chapter 13, and Van Goozen, Chapter 14, this volume).

BIOPSYCHOSOCIAL STUDIES OF AGGRESSION The great divide between social and biological approaches to human behavior is probably nowhere more evident than in the research on aggression over the past three decades. The De Wit & Hartup (1974) book showed a preoccupation with considering both sides of the question. But each article was concerned with either one or the other perspective. Numerous books on aggression and violence during the past decades omitted biological issues, and books on the biological bases of aggression did not include psychosocial factors. Most investigators preoccupied with the social “causes” find it difficult to learn the biological jargon. In fact, many resist considering the hypothesis that violence could in some ways be influenced by biological factors. For example, in the not so distant past, during the planning phase of one of the most expensive longitudinal studies of child development and antisocial behavior in the United States, plans for biological assessment apparently had to go underground (for the original plan, see Chapter 15 and Appendix II in Tonry et al., 1991). The National Consortium on Violence Research, another very large enterprise of the 1990s, funded by the U.S. National Science Foundation, was essentially focused on the social factors. Similarly, those who focused on the biological aspects of aggression generally did not take into account social factors. Considering these parallel trajectories, the changes that are occurring are impressive. The 1996 NATO Advanced Study Institute on the Biosocial Bases of Violence represented an important step in that direction (Raine, Farrington, Brennan, & Mednick, 1997). Compare the number of biological studies on humans reviewed in this book (especially in Chapter 12, by Paus; Chapter 11, by Pérusse & Gendreau; Chapter 13 by Pihl & Benkelfat; and Chapter 14, by Van Goozen) with those in the De Wit and Hartup (1974) book. The ideas were present in 1974. An example that strongly influenced our work comes from Hamburg and van Lawick-Goodall (1974): “We are inclined to believe that the hormonal changes of puberty, especially in males, may facilitate the learning of aggressive behavior” (p. 76) (see Van Goozen, Chapter 14, for tests of this hypothesis). The increasing number of biopsychosocial studies appears largely due to the development of biological measurement techniques that are relatively easy to use with humans. This is the case with molecular genetics, brain scans, and radio immunoassays of saliva. This methodological progress will continue, but biopsychosocial studies are still a small part of the numerous studies on human aggressive-antisocial behaviors.

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The best incentive for behavioral and social scientists to include the biological components is probably the increasingly clear demonstration that the environment, both physical and social, has an important impact on the developing organism and that, in turn, these biological consequences have a longterm impact on social behavior (Francis, Diorio, Plotsky, & Meaney, 2002; Keating & Hertzman, 1999; Meaney, 2001; Weaver et al., 2004). Smoking during pregnancy is a very good example. Children of mothers who smoked during pregnancy are at higher risk of numerous problems, including low birth weight, hypertension, hyperactivity, inattentiveness, impulsiveness, and aggression (Tremblay, Barr, & Peters, 2004a; Pausova, Paus, Sedova, & Bérubé, 2003; Tremblay et al., 2004b; Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002). At first sight, this is the domain of biologists, however, a second look shows that women who smoke during pregnancy tend to have low education, to be poor, to have a history of problem behaviors, to have a mate who has similar problems, or to be a single parent already during pregnancy. To what extent are the effects of smoking during pregnancy on aggression explained by these social characteristics or, vice versa, the effects of the social characteristics explained by the effect of the nicotine on the developing central nervous system? There is no way of knowing if the social scientist conducts a study without measuring smoking while the biologist is doing a parallel study and does not measure the history of antisocial behavior of the parents. The best alternative for the advancement of knowledge is for the biologist and the social scientist to use the same subjects and to do analyses that take into account the biological and social variables. This is actually happening, and the teams that take these multidisciplinary approaches are flourishing. The next step is to realize that if smoking during pregnancy is injuring brain development, a biological phenomenon, the preventive solutions are mostly in the domain of the psychosocial specialists. How do we get women with a history of problem behaviors to stop smoking during pregnancy? This leads back to our comments earlier concerning the importance of early childhood in understanding the development of aggressive behavior. If early in development the social environment has an important impact on biological development, and this biological change has a long-term impact on social behavior development, it becomes still more obvious that we need to follow Aristotle’s advice: Start at the beginning if you want to understand the developmental origins of aggression.

GENE–ENVIRONMENT INTERACTIONS The gene–environment interactions (G×E) issue is but a sub-section of the previous discussion. In the De Wit & Hartup (1974) book there were two chapters on genetics. One was a summary of an impressive master’s degree thesis on the criminality of adopted children in Denmark (Hutchings, 1974). The

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second was a comparative study of agonistic behavior in different strains of mice (Stewart, 1974). There were no twin studies and no molecular genetic studies. The review by Pérusse and Gendreau in Chapter 11 of this volume shows the impact of the genetic revolution over the past two decades. A new generation of social scientists can hear the word genes associated with human behavior without becoming inflamed and referring to eugenics. Many “psychosocial” investigators are recognizing that genetic information can be used as a control variable to study more adequately environmental effects. During the 1980s and 1990s, David Rowe made almost yearly presentations at the annual meeting of the American Society of Criminology, aimed at convincing criminologists that controlling for genetic factors through twin, sibling, and adoption designs was important for identifying environment effects, especially family effects, on antisocial behavior (see Chapter 15 by Rowe in Tonry et al., 1991). An important number of social scientists have moved much beyond what Rowe would have expected before his untimely death. It is obvious that most investigators with rich longitudinal data sets on human development need to collect genetic information on their subjects to add to the huge amount of data they have collected on behavior and the environment. This will lead to an important increase in G×E papers. It should eventually become next to impossible to publish a paper on human development in a top scientific journal without having a wide range of information on genes and environment. In the same way that we routinely control for socioeconomic status (SES), controlling for specific genetic polymorphism will most probably become standard practice. This will obviously not simplify our task. But it will lead to sounder knowledge, once we have learned to deal with the idea of G×E in our hypotheses and our analyses. Concerning the developmental origins of aggression, we must repeat that the first problem we need to solve is not the measurement of genes, nor the measurement of the environment, but the measurement of the phenotype. It is unlikely that there is a simple G×E leading to any expression of aggression at any point in time, or even multiple points in time, during the life course. The studies reviewed by Pérusse and Gendreau in Chapter 11 of this volume clearly used a hotchpotch of assessments at various ages, with various populations, to identify the “aggression” phenotype. We are far from a G×E science of the development of aggressive behavior in humans, but we are much closer than we were 10 years ago. Fortunately, we can count on animal studies, as can be seen in Chapter 4 of this volume, by Suomi.

TOWARD PSYCHOSOCIAL EPIGENOMICS One of the important changes of the past three decades has been the increasing awareness of the need for experimental preventive interventions (e.g., Dishion, McCord, & Poulin, 1999; Farrington, Ohlin, & Wilson, 1986;

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McCord, & Tremblay, 1992; Tremblay et al., 1999a; Tremblay, 2003). De Wit and Hartup (1974) did not include any experimental, or even quasi-experimental, intervention studies. Two studies made use of juvenile delinquents as subjects (Parke, 1974; Leyens & Camino, 1974), and Patterson (1974) presented an analysis of a boy referred to treatment for a high rate of “noxious” behavior. However, in their concluding chapter, De Wit and Hartup (1974) made an interesting set of comments on how children learn to regulate aggression. They suggested that two processes are involved: “a) moment-to-moment control of the ongoing actions of the child, and b) training the child for long-term selfcontrol.” These processes can be linked to research domains covered in this volume: Chapter 17 on family factors (Zoccolillo et al.) and Chapters 12 (Paus), 16 (Dionne), and 15 (Séguin & Zelazo), respectively, on brain development, language development, and development of executive functions. Research on parent training and children’s social skills training blossomed during the past three decades; however, judging from the reviews in this book, these efforts did not generate clear knowledge on the developmental origins of aggression. There appear to be four main reasons for this situation. First, children who were the targets of the interventions were generally school-age children, well past the “origins” phase. The study by Gross et al. (2003) is a notable exception. Second, rather than targeting aggression, intervention programs targeted the general concepts of aversive, externalizing, or obnoxious behavior (e.g., Patterson, 1982; Wahler, 1987; Webster-Stratton, 1998). Third, interventions showing long-term effects (more than a few years) were multimodal, precluding the attribution of the effect to a specific component (e.g., Lacourse et al., 2002; Olds et al., 1998). Fourth, the vast majority of these studies were not designed to test developmental hypotheses concerning aggression and did not control for most of the other potential causal effects. Chapter 17, by Zoccolillo et al., in this book describes the many competing explanations for a trajectory of chronic physical aggression: for example, genetic factors, parents’ history of problem behaviors, parents’ education, smoking during pregnancy, parental responsiveness to the child, coercive parenting, abuse and neglect. Whether parenting skills are determinant still needs to be demonstrated by controlling for alternative hypotheses, including genetic and perinatal effects (see Harris, 1998; Raine, 2002; Rowe, 1994). In regard to the gene–environment interaction, Caspi et al. (2002) reported a significant G×E for violent behavior, using assessments of child maltreatment and a MAOA genetic polymorphism. This is one good indication that studies that do not take into account both genetic and environmental factors are unlikely to provide adequate information on causal factors. However, we often forget that G×E studies, even with longitudinal data, are simply correlational studies if there is no manipulation of genes or environments. Correlational studies cannot prove causal effects. Hence, G×E studies of the developmental origins of aggression with large-population birth cohorts will simply give indications of possible causal factors. The ultimate proofs of cau-

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sality must come from experiments in which potential causal factors are manipulated. Most probably, we are far from genetic manipulations studies to test their effects on the developmental trajectories of human aggression. Manipulations of environments, however, are the daily business of thousands of people paid to help families and individuals with behavior problems or who are at high risk of having these problems. Governments are investing billions in these social programs, without much evidence that they are having the intended effects (e.g., McCord, 2003; Timmins, 2001; Tremblay, LeMarquand, & Vitaro, 1999b). The next decade should see a substantial increase in experimental manipulations of environments to test for G×E. This may sound far-fetched to some, but it is not much different from genotyping subjects in a longitudinal study. One of the new fields riding on the crest of the genetic revolution is pharmacogenomics. Chemists create medications that compensate for genetic deficits or take into account genetic differences. These chemical products act at the protein level, but they are environmental products and thus constitute an environmental manipulation. So is nutrition; special diets are given to children born with a multitude of genetic defects (e.g., Scriver & Kaufman, 2001). The aim of these diets is either to give the children proteins they are lacking because of the genetic defect or to prevent them from eating nutrients that could harm their development because of a genetic deficit. Such a diet may be needed throughout the individual’s life, or for only a limited time during a critical period for the growth of a physiological structure. We can generalize this approach by thinking about parenting as a “nutrient.” The results of the longitudinal birth cohort study in New Zealand reported by Caspi et al. (2002; see also, Pérusse & Gendreau, Chapter 11, this volume) indicates that boys maltreated by their parents (inadequate nutrient) are more or less at risk of becoming chronically aggressive, depending on which of two MAOA genotypes (high or low activity) they inherited. A practical implication of these results is that, because maltreated boys with the highactivity MAOA polymorphism appear “genetically” protected from chronic physical aggression, preventive interventions should specifically target boys without that protective factor. The parents of these at-risk boys should receive parent training, as early as possible, to prevent maltreatment. The Elmira study (Olds et al., 1998) has shown that a nurse home visitation program could prevent both child abuse by parents and delinquency when the children become adolescents. Such effects should be observed mainly for the males without the MAOA protective polymorphism. Thus, an experimental preventive intervention that targets quality of parenting, for boys who lack the protective genetic factor, would not only demonstrate the cost-effectiveness of parenting interventions based on genetic screening, but would also provide an experimental demonstration of the causal nature of the statistical interaction shown in correlational evidence. With psychosocial interventions, we can con-

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duct psycho-socio-genomic experiments, but the most exciting challenge is psycho-socio-epigenomics. There is increasing evidence that gene expression is turned on and off by environmental factors (Szyf, 2003). For example, a recent study of maternal behavior with rat pups shows that increased licking and grooming, as well as arched-back nursing altered rat pups’ DNA methylation (Weaver et at, 2004). These results suggest that environment manipulation not only can compensate for genetic defects but can also turn on or off gene expression at different points in time during the developmental process. In the not too distant future we should see numerous preventive experiments that will collect genetic information to test the cost-effectiveness of the intervention and, at the same time, test G×E hypotheses. However, we can immediately go back to subjects in successful interventions, such as the Elmira study, and genotype them to verify whether indeed the subjects who most benefited from that intervention had the low-activity MAOA genotype or any other genetic risk. Unfortunately, such analyses would probably not provide useful information on the developmental origin of early aggression, inasmuch as the published work from the Elmira study indicates that early aggression data were not collected. This leads us to underscore the fact that prevention experiments with a G×E design need to specifically target the period from pregnancy to school entry, if we are to understand the developmental origins of aggression. These early studies will also be extremely useful to test the biological embedding hypothesis (Keating & Hertzman, 1999) by studying the mediating role of endophenotypes such as brain development (see Paus, Chapter 12, this volume) and HPA activity (see Van Goozen, Chapter 14, this volume). Similar studies can also be undertaken to test other putative environmental causes of chronic aggression, such as smoking during pregnancy (see Wakschlag et al., 2002), influences of peers (see Boivin, Vitaro, & Poulin, Chapter 18, this volume), and television (see Johnson, Cohen, Smailes, Kasen, & Brook, 2002). In fact, we should be testing within the same studies the differential impact of parents, peers, and fictive aggression (on television, in movies, and in video games).

CONCLUSION Planning what is needed to take us from where we are to where we would like to be forces us, first, to take stock of what has been done; second, to identify what has not been done; third, to figure out what else needs to be done; and finally, to deal with the whirl of new ideas stimulated by the planning process. As we glance at this feast of new research within our reach, we can imagine how excited a clone of Charley Darwin would be to contribute to the next 50 years of research on the developmental origins of aggression.

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CHALLENGES FOR THE FUTURE 12 August 1849 To M. A. T. Whitby My dear Madam, I cannot express too strongly my thanks for the extraordinary trouble which you have taken in the interesting experiment, of which you send me the results.—I had given up all hopes of knowing whether peculiarities in the caterpillar state were hereditary, but now the point is amply proved: there is indeed a wide difference between a probability, however high & such an experiment as you have made.— . . . I dare not do more than hint my curiosity to know whether the Frales would prove hereditary,—i.e., whether it would be possible to make a breed with cocoons destitute of silk.—In the eyes of all silk-growers, this assuredly would appear the most useless of experiments ever tryed.— (Darwin, 1832/1985, p. 248)

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Index

Index

“f” following a page number indicates a figure; “t” following a page number indicates a table Abstract play, 142–151 Abuse. See Maltreatment Academic achievement predictors of violence and, 210 proactive and reactive aggression and, 187 Active defense, 111–112 Adjustment problems peer rejection and, 380 proactive and reactive aggression and, 186–188 schools and, 407 Adolescence. See also Development age–violent crime curve and, 85–87t aggression prior to, 87–90, 89f gender differences and, 285 homicide and, 209 indirect aggression and, 160–161, 163 language development and, 338–340, 340–341 neuromodulators and, 262–263, 271– 273 overview, 98–101, 99f proactive and reactive aggression and, 185 subtyping aggression and, 38 testosterone and, 286–287 violence during, 202 Adoption studies, 231–232 Adrenocorticotropic (ACTH) hormone, 296. See also Hormones Adrogenic gonadal hormones, 284. See also Testosterone Adrogens, 288–290. See also Hormones

Adulthood, play fighting in rats during, 50–51 Affective aggression, 37–38 Affective disorders. See Mood disorders After-school care, 390–391. See also Daycare Age differences, 160–161 Age-graded theory, 209 Age–violent crime curve aggression prior to adolescence and, 87– 90, 89f overview, 85–87f Aggression aggressive competence, 125 aggressive performance, 125 anger as a cause of, 94 antisocial behavior vs. prosocial aggression, 5–6 association with language, 343–347 brain mechanisms influences on, 36–38 child characteristics and causes of, 14, 93 during childhood, 87–90, 89f, 93–98, 97f, 430f–431, 452–454 childhood-onset persistent, 353–370, 362t, 363t, 364t cognitive antecedent of, 31–33 consequences of, 31–33 defensive, 38, 111–112 defining, 5, 108–110, 353–354 development of, influences on, 38–39 development of prior to age 6, 90–93f, 92f developmental trajectory of, 7–8

465

466

Index

Aggression (continued) direct, 34 environment and causes of, 95, 96 evolution and causes of, 95 expression of, 30f, 33–34, 38–39 friends as determinant of, 15–16, 17–18 frustration–aggression model, 178–179 game, 38 genetic–developmental model and, 224– 227, 228–234, 230f genetics and causes of, 12–13, 96–97, 100 heritability of, 355–368, 362t, 363t, 364t hostile, 31–33, 109, 183–184 impulsive, 264 indirect, 34, 158–171, 383, 437–439, 451 individual differences and causes of, 96 during infancy, 107, 108–110, 124–126 instrumental, 31–33, 38, 109, 184, 381 integrative model of, 39–41f intermale, 37–38 language–aggression hypothesis, 331– 332 language development and causes of, 96, 340–341 motivational system and causes of, 94 neocortex, influences on, 37 neural circuitries, influences on, 37 nonviolent, 5–6 offensive, 37 parental, 28 parenting as determinant of, 14 peer relationships and causes of, 15, 96 personally motivated, 32–33 physical, 83–85, 308–309 pleasure-motivated, 32 predicting, 449–450 as a predictor for antisocial behavior, 5 prefrontal cortex, influences on, 37 pregnancy and causes of, 96 in preschool age group, 90–93f, 92f, 430f–431, 452–454 proactive, 40–41f, 179–197 prosocial, 5–6, 33 punishment as, 33 rage-like, 37 reactive, 36, 40–41f, 178–197, 381 regulation of, 142–143 relational, 6, 34, 159–160, 383, 437 relief-motivated, 32 risk factors for early development of, 121–124

serotonin metabolism and causes of, 96 siblings and causes of, 97 smoking and causes of, 97 social aggression, 34, 159–160 social learning hypothesis and causes of, 94 social systems and causes of, 100 socially motivated, 32–33 studies of, 250–255, 252f, 254f, 448– 450 subtypes of, 26–29, 30f, 31–42, 41f, 450–452 taxonomies of, 27–29, 39–41f teasing, 38 testosterone and causes of, 96 during toddler years, 124–126, 430f– 431, 452–454 verbal, 108, 436–437 war as, 33, 85 weaning, 28 Aggressive competence, 125 Aggressive performance, 125 Alcohol use. See also Substance use molecular genetics and, 232, 233 neuromodulators and, 262 during pregnancy, 210 in rhesus monkeys, 76 Allelic variations, 13 Alternative reproductive strategies, 428 Androgens, 285–286 Anger. See also Reactive aggression as a cause of aggression, 94 defining aggression and, 354 during infancy, 110 overview, 179, 282 peer relationships and, 381 proactive and reactive aggression and, 188–189, 195 in young children, 91–93f, 92f Antecedents of aggression integrative model and, 40 polythetic analysis and, 30f of proactive and reactive aggression, 194–196 subtyping aggression based on, 34– 39 Anthropomorphism, 26–27 Antidepressants, 263 Antisocial behavior. See also Homicide; Violence adoption studies on, 231–232 aggression as a predictor for, 5

Index cognitive skills and, 314–315 cortisol and, 292–293 daycare and, 406 developmental pathway model of, 205f– 206 evolutionary perspective of, 450–452 executive function and, 310–312 as a familial disorder, 356 friendships and, 16 future research on, 368–370 intergenerational transmission of, 355– 368, 362t, 363t, 364t language development and, 333, 346 maltreatment and, 359–360 in parents, 360–368, 362t, 363t, 364t peer relationships and, 409 prefrontal damage and, 148–149 vs. prosocial aggression, 5–6 school environment and, 407 Antisocial personality disorder, 37 Anxiety indirect aggression and, 167 language development and, 341 molecular genetics and, 233 during pregnancy, 123 proactive and reactive aggression and, 187, 188 Appearance, 167 Arousal, 268 Attachment system childhood-onset persistent aggression (CPA) and, 358–359 as a risk factor, 123–124 Attention-deficit/hyperactivity disorder (ADHD) DHEA/DHEAS and, 289–290 executive function and, 311–312, 317– 318 genetic factors and, 122 language development and, 343–344 neuromodulators and, 270 physical aggression and, 308 proactive and reactive aggression and, 187 testosterone and, 289 Attentional control, 273–275 Attribution biases pathway, 346 Authority conflict pathway, 205f–206. See also Developmental pathway Autism, abstract play and, 148 Autonomy, during infancy, 111–112 Avoidance of conflict, 116–117. See also Conflict

467

B Behavior changes in, 12–19, 35–36 evolutionary perspective of, 427– 428 executive function and, 310–312, 320– 321, 322 explanations of, 425 language development and, 333, 336– 337, 339–340 physical aggression and, 308–309 relationship to brain mechanisms, 242– 243 Behavioral control, 261 Bilateral view of socialization, 13–18. See also Socialization Biological indicators. See also Hormones contextualism and, 18–19 overview, 13, 298–299, 454–455 proactive and reactive aggression and, 188–190 Biopsychosocial research, 454–455 Birth complications, 96. See also Pregnancy Boxing stance, across species, 26–27 Boys. See also Gender differences developmental trajectory of aggression in, 7–8 in play fighting in rats, 49–50 proactive and reactive aggression and, 196 use of indirect aggression by, 161– 162 Brain mapping. See also Brain mechanisms overview, 242–243, 255–256 principles of, 243–246, 244f, 245f, 246f studies of aggression using, 250–255, 252f, 254f Brain mechanisms. See also Brain mapping; Prefrontal cortex abstract play and, 144–146 influences of on aggression, 36–38 MRI studies of brain development and, 246–250 neuromodulators and, 262–263 relationship to behavior, 242–243 smoking during pregnancy and, 455 Bullying history of, 84 peer relationships and, 381 relationships and, 17 as a research construct, 5–6

468

Index

C Cats, gamma-aminobutyric acid (GABA) and, 269 Cause of aggression during early childhood, 93–98, 97f language–aggression association and, 344–347 of proactive and reactive aggression, 194–196 Cerebral cortex, 250–255, 252f, 254f. See also Brain mechanisms Child care contagion effect in, 388 peer relationships and, 377, 390–391 as a risk factor, 124 social capital and, 405–406 Child characteristics causes of aggression and, 93 as a determinant of aggression, 14 Child development perspectives, 10–12. See also Development Childhood. See also Development; Preschool age group aggression during, 87–90, 89f, 430f– 431, 452–454 causes of aggression during, 93–98, 97f empathy during, 136 executive function and, 309–310, 312– 318 gender differences and, 432–434 hormones and, 288–290 language development and, 334–335, 338–340 morality in, 117–118 overview, 98–101, 99f risk factors and, 121–124 violence during, 202 Childhood-onset persistent aggression (CPA). See also Childhood causes of, 354–355 as a familial disorder, 355–368, 362t, 363t, 364t future research on, 368–370 overview, 353 Chimpanzees, 135–137. See also Monkeys Cingulate cortex, 251, 252. See also Brain mechanisms Cingulate motor areas, 251. See also Brain mechanisms Classification of aggression. See Subtypes of aggression Cliques, 384–387. See also Popularity Coercive control, 25

Coercive parenting, 359. See also Parenting Cognitive antecedent of aggression, 31–33 Cognitive development, 96. See also Cognitive skills; Development Cognitive skills global measures of, 313–315 during infancy, 112 neuromodulators and, 273–275 peer relationships and, 379 play fighting and, 55–57, 58 Cold executive function, 320–321, 322. See also Executive function Collective efficacy, 410–411 Competition abstract play and, 143 reproductive objectives and, 167 for resources, 435 Complex social play, 144. See also Play Conduct disorder cortisol and, 189, 293, 294 DHEA/DHEAS and, 290 executive function and, 311–312 hormones and, 296 language development and, 333, 337 lithium and, 275 physical aggression and, 308 smoking and, 357–358, 360 subtyping aggression and, 39 testosterone and, 288–289 Conflict infancy and, 108–109 normative course of, 110–118, 114f, 115f during the toddler years, 116–117 Consequences of aggression polythetic analysis and, 30f subtyping aggression based on, 31–33 Constructs in aggression literature, 4–6 Contextualism, 18–19 Cooperation lack of, 149–150 rough-and-tumble play and, 138– 142 Corpus collosum. See also Brain mechanisms MRI studies of brain development and, 247–249 overview, 251 Cortisol. See also Hormones; Hypothalamic–pituitary–adrenal (HPA) axis overview, 282–283, 291–296 proactive and reactive aggression and, 189–190

Index Covert pathway, 205f–206. See also Developmental pathway Criminal behavior age–violent crime curve and, 85–87f childhood-onset persistent aggression (CPA) and, 355 daycare and, 406 developmental trajectory of, 206–207 genetic studies on, 228–234, 230f language development and, 333, 341 maltreatment and, 359–360 neighborhoods and, 411–412 peer rejection and, 409–410 proactive and reactive aggression and, 187–188 social capital and, 413 testosterone and, 287 welfare system and, 400–402 CSF 5–HIAA interaction with environment, 74–76f parenting and, 74 in rhesus monkeys, 67–69, 69–70, 70– 72, 71f Culture proactive and reactive aggression and, 196 role of, 133–134

D Daycare contagion effect in, 388 peer relationships and, 377, 390–391 as a risk factor, 124 social capital and, 405–406 Defensive aggression development and, 38 during infancy, 111–112 Defining aggression during infancy, 108–110 problem of, 353–354 for research purposes, 5 Delinquency childhood-onset persistent aggression (CPA) and, 354 developmental aspects of, 207–209 developmental trajectory of, 206–207 friendships and, 16 genetic studies on, 228–234, 230f language development and, 333 maltreatment and, 359–360 in the parents, 403–404 peer relationships and, 409 predictors of, 209–211

469

proactive and reactive aggression and, 187–188, 195 social capital and, 414–415 Depression indirect aggression and, 167 maternal, 123–124, 140 serotonin and, 264–265 Development. See also Adolescence; Brain mechanisms; Childhood; Infancy; Language development; Preschool age group; Toddler years abstract play and, 149 aggression prior to age six, 90–93f, 92f brain, 246–250 causes of aggression and, 93–98, 97f child development vs. lifespan perspectives of, 10–12 contextualism and, 18–19 daycare and, 405–406 determinants of change in, 12–19 evolutionary perspective of, 427–428, 429–431, 430f of executive function, 309–310 friendships and, 16 gender differences and, 439 genetic factors and, 223–224, 456 of homicide, 204–207, 205f, 207–209 influences of on aggression, 38–39 neuromodulators and, 270–273 normative change and, 6–10f, 7f, 9f overview, 98–101, 99f of physical aggression, 83–85, 309 of rhesus monkeys, 65, 67–69, 68f, 77– 78f social capital and, 399, 400t, 414, 417 of social understanding, 138 studies of aggression using, 448–450 testosterone and, 284–287 welfare system and, 401–402 Developmental model. See also Development overview, 448–450 of proactive and reactive aggression, 190–193 Developmental pathway. See also Development of homicide, 204–206, 205f prevention and, 214 Developmental trajectories. See also Development of homicide, 206–207 overview, 7–8 sociometric status and, 10 violence and, 211–214t, 212f, 213f

470 Deviancy training overview, 385–386 in preschool children, 386–387 DHEA/DHEAS. See also Hormones in childhood, 289–290 future research on, 296–298 Direct aggression, 34 Dominance, 138–142 Dominance hierarchy, 135–136 Dopamine. See also Neuromodulators development and, 270–273 executive control and, 273–275 inhibition and, 261–262, 276 overview, 265–268 play fighting in rats and, 57 Dorsal premotor cortex, 251. See also Brain mechanisms Dorsolateral prefrontal cortex. See also Brain mechanisms executive control and, 273 functions of, 144–145 Drug use dopamine and, 270–271 gang involvement and, 414–415

E Ecological perspective, 384–391 Elephant seals, 236 Emotion regulation, 346 Emotional antecedents, 34–36 Emotions, 188–190, 316 Empathy, 133–138 Empiricism, vs. nativism, 12–13 Employment, maternal, 404–405. See also Daycare; Socioeconomic status Enemies, 16–17. See also Relationships Engagement, 268 Enhancement model, 414–415 Environment. See also Social learning hypothesis biological components and, 455 causes of aggression and, 95, 96 childhood-onset persistent aggression (CPA) and, 355, 356, 356–360 contextualism and, 18–19 evolutionary perspective and, 100, 428 genetic factors and, 228–234, 230f, 455–456 hormones and, 295–296 interaction with genetics, 74–76f language–aggression association and, 343–344 maltreatment and, 457–459

Index neuromodulators and, 262 norepinephrine and, 268 predictors of violence and, 210–211 proactive and reactive aggression and, 191 as a risk factor, 123–124 role of, 398 rough-and-tumble play and, 139 school, 407–408 Escalation theory overview, 208–209 prevention and, 214 Ethnicity, 196 Etiology pathways, 343–344 Evolution of aggression causes of aggression and, 95 gender differences and, 434–436, 437– 439 indirect aggression, 158–159, 165–170 overview, 84–85, 425–428, 429–431, 430f subtyping aggression and, 450–451 Executive control, 273–275 Executive function development of, 309–310 in early childhood, 312–318 hot and cold, 320–321 overview, 307–308, 321–322 problem-solving framework and, 318– 320 relationship with externalizing or antisocial disorders, 310–312 Explanatory models, 32 Exploratory activity, 139 Expression of aggression development and, 38–39 polythetic analysis and, 30f subtyping aggression based on, 33–34

F Family. See also Family relationships; Parenting childhood-onset persistent aggression (CPA) and, 355–368, 362t, 363t, 364t, 368–370 social capital and, 402–405 Family history, 185 Family relationships. See also Relationships child development vs. lifespan perspectives and, 11 developmental trajectory of aggression and, 8 as a risk factor, 123–124

Index Fantasy, 138 Fast Track prevention trial, 408. See also Prevention Fear responses to, 35–36 rough-and-tumble play and, 139 Fear system, 37–38 Females. See also Gender differences aggressive competence and, 125 developmental trajectory of aggression in, 8 in play fighting in rats, 49–50 proactive and reactive aggression and, 196 use of indirect aggression by, 161–162, 163–170 50:50 rule. See also Play fighting adult play fighting in rats and, 51 juvenile play fighting in rats and, 55– 56 overview, 48, 58 5–HIAA concentration levels interaction with environment, 74–76f parenting and, 74 in rhesus monkeys, 67–69, 69–70, 70– 72, 71f 5–HT. See also Neuromodulators dopamine and, 265, 267 gamma-aminobutyric acid (GABA) and, 266–267 inhibition and, 261–262, 274–275 overview, 262, 263–265 5–HTT interaction with environment, 74–76f interaction with rearing conditions, 13 fMRI, 245f, 246f, 255–256. See also Brain mapping Force during infancy, 109, 112–115f, 114f toddlers’ use of, 125 Friends. See also Peer relationships; Relationships as a determinant of aggression, 15–16, 17–18 preschool age children and, 384–387 Frontal cortex adolescence and, 272–273 brain mapping studies on, 250–255, 252f, 254f Frontal lobes, 250–255, 252f, 254f. See also Brain mechanisms Frontopolar cortex, 251. See also Brain mechanisms Fruit flies, boxing stance in, 26–27

471

Frustration–aggression model, 178–179. See also Reactive aggression Functional MRI, 245f, 246f, 255–256. See also Brain mapping Funding of research, 453

G Game aggression, 38 Game theory, 51 Gamma-aminobutyric acid (GABA). See also Neuromodulators inhibition and, 261–262, 274–275, 276 overview, 262, 269–270 serotonin and, 266–267 Gang involvement, 414–416 Gender differences aggressive competence and, 125 childhood-onset persistent aggression (CPA) and, 356 development of, 431–436 dopamine and, 267 evolutionary perspective of, 427 interaction with environment, 74–76f language development and, 339, 341, 348 neuromodulators and, 262 normative change and, 8 overview, 5, 439 peer relationships and, 379 in play fighting in rats, 49–50 preschool age children and, 383 in proactive and reactive aggression, 196 serotonin, 264–265 sexual selection and, 426–427 single-parent families and, 403 testosterone and, 283–284, 284–286 in toddlers’ use of force, 118–119, 120, 120–121 in use of indirect aggression, 161–162, 163–165, 170–171, 437–439 in verbal aggression, 436–437 Genetic–developmental model. See also Genetics of aggression in animals, 224–227 of aggression in humans, 228–234, 230f overview, 234–236 Genetics causes of aggression and, 96–97, 100 childhood-onset persistent aggression (CPA) and, 355–368, 356, 362t, 363t, 364t as a determinant of aggression, 12–13 environment and, 455–456

472

Index

Genetics (continued) hormones and, 295–296 human studies and, 228–234, 230f language–aggression association and, 343–344, 344–345 maltreatment and, 457–459 mouse studies on, 224–227 neuromodulators and, 262 overview, 223–224, 234–236 rhesus monkeys and, 69–70 as a risk factor, 122 Genotype driven approaches, 223–224 Girls. See also Gender differences aggressive competence and, 125 developmental trajectory of aggression in, 8 in play fighting in rats, 49–50 proactive and reactive aggression and, 196 use of indirect aggression by, 161–162, 163–170 Grey matter, 252–254. See also Brain mechanisms

H Harm, subtyping aggression based on, 31 Health care, 402 Heritability of aggression. See also Genetics childhood-onset persistent aggression (CPA) and, 355–368, 362t, 363t, 364t as a risk factor, 122 High Scope project, 406. See also Daycare Hippocampus, 144. See also Brain mechanisms Homicide. See also Antisocial behavior; Violence developmental aspects of, 207–209 heterogeneity of, 203–207, 205f overview, 202–203 predictors of, 209–211 prevention of, 214–215 social capital and, 413 violence trajectories and, 211–214t, 212f, 213f welfare system and, 400 Hormones. See also Cortisol; Testosterone as an explanation for violence, 86–87t future research on, 296–298 genetic factors and, 295–296 overview, 281–283, 298–299, 454–455

Hostile aggression during infancy, 109 overview, 31–33, 183–184 Hot executive function, 320–321. See also Executive function Hunger, 139 Hunting, 28 Hyenas, empathy in, 136 Hypothalamic–pituitary–adrenal (HPA) axis. See also Brain mechanisms cortisol and, 291–296 future research on, 296–298 genetic factors and, 295–296 proactive and reactive aggression and, 189–190 rough-and-tumble play and, 141

I Impulsive aggression, 264 Indirect aggression. See also Relational aggression; Social aggression age differences in, 160–161 correlates of, 162–163 gender differences in, 161–162, 437– 439 overview, 34, 158–159, 159–160, 170– 171, 451 in preschool children, 383 use of by females, 163–170 Individual differences causes of aggression and, 96 changes in aggression and, 448–450 compared to normative change, 6–10f, 7f, 9f 5–HIAA concentration levels in rhesus monkeys and, 68–69 genetic factors and, 235 homicide and, 209 play fighting in rats and, 57 in rhesus monkeys, 66–67 in toddlers’ use of force, 118–121 Infancy. See also Development aggression during, 107, 124–126 defining aggression during, 108– 110 empathy during, 136 executive function and, 310 individual differences and, 118–121 innate features of, 137–138 language development and, 334–335, 336–337 normative course of conflict and aggression in, 110–118, 114f, 115f

Index proactive and reactive aggression and, 191–192 risk factors and, 121–124 Inhibition lack of, 149 neuromodulators and, 262–263, 273– 274 overview, 261, 276 proactive and reactive aggression and, 188 Inhibition theories, 142–143 Initiative, 111–112 Injury, subtyping aggression based on, 31 Innate features of aggression, 133–138 Instrumental aggression. See also Proactive aggression development and, 38 during infancy, 109 overview, 31–33, 184 peer relationships and, 381 Instrumental force, 109 Insults. See Verbal aggression Integrative model of aggression, 39–41f Intelligence executive function and, 312, 313–314 language development and, 332, 338– 339, 341, 348 neuromodulators and, 273 Intent, subtyping aggression based on, 31– 33 Intergenerational transmission of CPA future research on, 368–370 overview, 353, 355–368, 362t, 363t, 364t Intermale aggression, 37–38 Interventions child development vs. lifespan perspectives and, 11 childhood-onset persistent aggression (CPA) and, 369 daycare and, 406 language–aggression association and, 345 need for, 456–459 peer relationships and, 392 proactive and reactive aggression and, 195–196 schools and, 408 social, 11 state dependence theory and, 209 Isolation, 52–53, 56

473

L Labeling, 209 Language–aggression hypothesis, 331–332. See also Language development Language development. See also Development causes of aggression and, 96 history of, 331–332 overview, 330–331, 347–348 peer relationships and, 378, 379 prediction of future aggression and, 340–341 in the preschool age group, 314 prevalence throughout, 333–343 theoretical models of association to aggression, 343–347 Learning, 95 Lexical development, 332–333. See also Language development Lifespan perspectives, 10–12 Limbic structures, 146 Linnoila, Markku, 63. See also Rhesus monkeys Lithium, 275

M Macaques, 56–57. See also Monkeys Macro-social pathway, 343–344 Males. See also Gender differences developmental trajectory of aggression in, 7–8 in play fighting in rats, 49–50 proactive and reactive aggression and, 196 use of indirect aggression by, 161–162 Maltreatment childhood-onset persistent aggression (CPA) and, 359–360 genetic factors and, 457–459 hormones and, 295–296 monoamine oxidase and, 13 neighborhoods and, 412 play and, 150 proactive and reactive aggression and, 186 Maternal employment, 404–405. See also Daycare Maternal responsiveness, 358–359 Maturation status, 169 Mediofrontal cortex, 252. See also Brain mechanisms Memory. See also Executive function neuromodulators and, 273–275 overview, 321

474

Index

Mesial frontal cortex, 251. See also Brain mechanisms Micro-social pathway, 345–346 Mid-dorsolateral frontal cortex, 251, 252. See also Brain mechanisms Mid-ventrolateral frontal cortex, 251, 252. See also Brain mechanisms Molecular genetics, 232–234. See also Genetics Monkeys. See also Rhesus monkeys indirect aggression among, 167 neuromodulators and, 275 overview, 135–137 rough-and-tumble play in, 56–57, 284 Monoamine oxidase genetic factors and, 232–234 maltreatment and, 360, 458–459 parental maltreatment and, 13 Mood, testosterone and, 287 Mood disorders language development and, 341 serotonin, 264–265 Moralistic aggression, 28 Morality in early childhood, 117–118 play and, 143 rough-and-tumble play and, 141–142 Motivational system abstract play and, 144–146 brain mechanism research on, 37 causes of aggression and, 94 overview, 137, 151–152 predation and, 28 subtyping aggression based on, 31–33 Mouse models. See also Rodents dopamine and, 270 gamma-aminobutyric acid (GABA) and, 270 gender differences in, 285 genetic–developmental model, 224–227 norepinephrine and, 269 MRI. See also Brain mapping functional, 245f, 246f overview, 255–256 structural, 243–244f studies of aggression using, 250–255, 252f, 254f studies of brain development, 246–250

N Name calling. See Verbal aggression Nativism, vs. empiricism, 12–13 Natural selection, 166

Neglect. See Maltreatment Neighborhoods peer relationships and, 389–390 social capital and, 410–412 Neocortex influences of on aggression, 37 integrative model and, 40 Neural circuitries abstract play and, 144–146 influences of on aggression, 37 Neuroendocrinological status, 37 Neuroimaging. See Brain mapping Neuromodulators development and, 270–273 executive control and, 273–275 inhibition and, 261–262 overview, 262–263, 276 Neurotransmitters. See also Neuromodulators dopamine, 265–268 gamma-aminobutyric acid (GABA), 269– 270 inhibition and, 261–262 norepinephrine, 268–269 serotonin, 263–265 Nonviolent aggression, 5–6 Noradrenaline, 268 Norepinephrine. See also Neuromodulators inhibition and, 261–262 overview, 268–269 Norm of reaction, 428 Normative change, 6–10f, 7f, 9f

O Object-oriented nature of aggression, 38 Offensive aggression, 37. See also Proactive aggression Ontogenetic organization comparing different levels of, 26–29 overview, 39 Oppositional–defiant disorder (ODD) cortisol and, 294 DHEA/DHEAS and, 289–290 executive function and, 312, 317– 318 hormones and, 296 physical aggression and, 308 testosterone and, 288–289 Orbitofrontal cortex, 251, 252. See also Brain mechanisms Orbitofrontal–prefrontal cortex, 144 Organized crime, 416, 417–418. See also Gang involvement

Index Ostracism, 380–383 Overt pathway, 205f–206. See also Developmental pathway

P Pain, 35–36 Parallel development model, 191 Parent–child relationship, 14–15. See also Family relationships; Parenting; Relationships Parental aggression, 28 Parenting childhood-onset persistent aggression (CPA) and, 357, 358–360, 368–369 cognitive skills and, 313–314 as a determinant of aggression, 14 gene–environment interactions and, 75– 76f hormones and, 298 interventions and, 457–459 language–aggression association and, 343–344 peer relationships and, 389 predictors of violence and, 210 proactive and reactive aggression and, 185, 191 in rhesus monkeys, 73–74 as a risk factor, 123–124 rough-and-tumble play and, 140 serotonin transporter gene (5–HTT)’s interaction with, 13 social-cognitive processes and, 382 socialization and, 14–15 use of force during infancy and, 112– 115f, 114f Parents antisocial behavior of, 360–368, 362t, 363t, 364t social capital and, 403–404 Peer rejection. See also Peer relationships during the preschool years, 380–383 social capital and, 409–410 Peer relationships. See also Friends; Relationships causes of aggression and, 96 as a determinant of aggression, 15 in early childhood, 378–380, 384–391 gene–environment interactions and, 75– 76f indirect aggression and, 162–163 during infancy, 110, 112 overview, 376–378 predictors of violence and, 210

475

during the preschool years, 380–383, 391–392 proactive and reactive aggression and, 185–186, 188, 191–192 rejection from, 380–383, 409–410 in rhesus monkeys, 73–74 as a risk factor, 124 social capital and, 408–410 during the toddler years, 116–117 use of force during infancy and, 113 Performance theory, 14. See also Socialization Perry preschool project, 406. See also Daycare Person-oriented nature of aggression, 38 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), 401. See also Welfare system Personality disorders language development and, 331 molecular genetics and, 232–233 proactive and reactive aggression and, 187 Personally directed force during infancy, 109 toddlers’ use of, 119 Personally motivated aggression, 32–33 Phenotype driven approaches, 224, 235– 236 Phylogenetic organization, 26–29, 40 Play. See also Play fighting; Rough-andtumble play abstract, 142–151 overview, 152, 451 social understanding and, 138 Play fighting. See also Rough-and-tumble play in adult rats, 50–51 in juvenile rats, 52–55, 54f, 55–57 overview, 47–48, 58, 138–142 in rats, 48–50, 49f Pleasure-motivated aggression, 32 Polythetic analysis, 29–30f. See also Subtypes of aggression Popularity, 163, 165, 169 Population heterogeneity theories overview, 208 prevention and, 214–215 Postpartum period, 298 Predatory aggression. See Proactive aggression Predicting aggression, 449–450

476

Index

Prefrontal cortex. See also Brain mechanisms abstract play and, 145, 146–147 brain mapping studies on, 250–255, 252f, 254f damage to, 148–149 executive control and, 273 influences of on aggression, 37 inhibition and, 276 integrative model and, 40 overview, 251 Pregnancy causes of aggression and, 96 childhood-onset persistent aggression (CPA) and, 357–358 dopamine and, 270–271 hormones and, 285–286, 297–298 predictors of violence and, 210 risk factors and, 123 smoking during, 123, 210, 455 Premotor cortex, 251. See also Brain mechanisms Prenatal malnutrition, 271. See also Pregnancy Preschool age group. See also Childhood; Development aggression during, 90–93f, 92f, 430f– 431, 452–454 executive function and, 310, 312–318 gender differences and, 433 language development and, 334–335, 336–337 peer rejection and ostracism during, 380–383 peer relationships and, 378–380, 384– 391, 391–392 Prevention. See also Interventions of homicide and violence, 214–215 need for, 456–459 schools and, 408 state dependence theory and, 209 Primary motor cortex, 251. See also Brain mechanisms Primates. See also Rhesus monkeys indirect aggression among, 167 neuromodulators and, 275 overview, 135–137 rough-and-tumble play in, 56–57, 284 Proactive aggression. See also Instrumental aggression causality of, 194–196 correlates of, 184–190 developmental model of, 190–193 gender, ethnicity, and culture and, 196

integrative model and, 40–41f measurement and validity issues regarding, 180–184 overview, 179–180, 197 Proactive use of force during infancy, 109 during the toddler years, 119 Problem solving, 195 Problem-solving framework executive function and, 318–320 overview, 321–322 Procedural morality, 141–142. See also Morality Prosocial aggression vs. antisocial aggression, 5–6 overview, 33 Protest, 111 Proximal antecedents integrative model and, 40 overview, 34–36 Psychoanalytic view, 134–135 Punishment as aggression, 33 childhood-onset persistent aggression (CPA) and, 359 physical, 84

Q Quantitative genetics, 228–232, 230f. See also Genetics

R Rage-like aggression, 37 Rage system, 37–38 Random effect growth modeling, 206– 207 Rats. See also Rodents boxing stance in, 26–27 brain mechanism research on, 37 dopamine and, 267, 270–271 empathy in, 136 neuromodulators and, 271, 275 norepinephrine and, 268 play fighting in, 48–50, 49f, 55–57, 58, 139, 142 play fighting in adults, 50–51 play fighting in juveniles, 52–55, 54f Reactive aggression causality of, 194–196 correlates of, 184–190 developmental model of, 190–193 gender, ethnicity, and culture and, 196 integrative model and, 40–41f

Index measurement and validity issues regarding, 180–184 overview, 36, 178–180, 197 peer relationships and, 381 Reactive use of force, 109 Regions, 412–414 Regulation of aggression, 142–143 Rejection, peer. See also Peer relationships during the preschool years, 380–383 social capital and, 409–410 Relational aggression. See also Indirect aggression compared to indirect aggression, 159– 160 gender differences in, 6, 437 overview, 34 in preschool children, 383 Relationships. See also Family relationships; Peer relationships in rhesus monkeys, 64–66 socialization and, 13–18 violence in, 188 Relief-motivated aggression, 32 Reproductive objectives gender differences in, 428, 435 indirect aggression and, 166–170 Repulsion hypothesis, 17 Resistance, 111 Resolution of conflict, 116–117. See also Conflict Retaliation, 111 Revenge, 150 Rhesus monkeys. See also Monkeys development of, 67–69, 68f effects of early social experiences on, 72–74 empathy in, 136 field studies of, 70–72, 71f gene–environment interactions and, 74– 76f genetic factors and, 69–70 individual differences and, 66–67 overview of research with, 77–78f rough-and-tumble play among, 139–140 social aspects of, 64–66 Risk factors childhood-onset persistent aggression (CPA) and, 355, 355–368, 362t, 363t, 364t early development of aggression, 121– 124 homicide and, 209–211 population heterogeneity theory and, 208

477

Rodents boxing stance in, 26–27 brain mechanism research on, 37 dopamine and, 267, 270, 270–271 empathy in, 136 gamma-aminobutyric acid (GABA) and, 270 gender differences in, 285 genetic–developmental model, 224–227 neuromodulators and, 271, 275 norepinephrine and, 268, 269 play fighting in, 48–50, 49f, 55–57, 58 play fighting in adults, 50–51 play fighting in juveniles, 52–55, 54f rough-and-tumble play among, 139, 142 testosterone and, 284 Role play, 138 Rough-and-tumble play. See also Play fighting gender differences in, 284, 428, 435 overview, 138–142, 152 peer relationships and, 381 in rhesus monkeys, 65–66 social understanding and, 138

S Schizophrenia, 274 School achievement predictors of violence and, 210 proactive and reactive aggression and, 187 School departure, 167 Schools environment of, 428 peer relationships and, 391 social capital and, 407–408 Selection model, 414–415 Selective breeding, 225–227. See also Genetics Self-esteem, 167 Self-regulation language–aggression association and, 346 overview, 307–308 Self-selection model, 209 Semantic development, 332–333. See also Language development Serotonin. See also Neuromodulators dopamine and, 265, 267 gamma-aminobutyric acid (GABA) and, 266–267 inhibition and, 261–262, 274–275 overview, 262, 263–265

478 Serotonin metabolism causes of aggression and, 96 in rhesus monkeys, 66–67, 69–70 Serotonin receptors, 232–234 Serotonin transporter gene (5–HTT) interaction with environment, 74–76f interaction with rearing conditions, 13 Sex differences. See Gender differences Sex segregation, 435. See also Gender differences Sexual encounters overview, 451 play fighting and, 48, 49–50, 52, 55 Sexual selection, 166, 426–427 Shared etiology pathways, 343–344 Shared genetic liability pathway, 343–344 Siblings. See also Family relationships causes of aggression and, 97 conflicts with, 117 preschool age children and, 388–389 Single-parent family, 403. See also Family Smoking. See also Substance use causes of aggression and, 97 childhood-onset persistent aggression (CPA) and, 357–358, 362t–363t conduct disorder and, 360 during pregnancy, 123, 210, 455 Social aggression. See also Indirect aggression; Relational aggression compared to indirect aggression, 159– 160 overview, 34 Social bonding, 49 Social capital daycare and, 405–406 at the family level, 402–405 negative, 414–417 neighborhoods and, 410–412 overview, 398–399, 417–418 peer relationships and, 408–410 schools and, 407–408 town and region and, 412–414 Social cognitions language–aggression association and, 346 parenting and, 382 proactive and reactive aggression and, 183 Social development, in rhesus monkeys, 64–66. See also Rhesus monkeys Social–development perspective, 38–39 Social experience, in rhesus monkeys, 72– 74 Social facilitation model, 415

Index Social forces, 137 Social-interactionist perspective, 32 Social interventions, 11. See also Interventions Social learning hypothesis. See also Environment causes of aggression and, 94 overview, 125, 429, 453 proactive aggression and, 179 Social organization innateness of, 133–138 in rhesus monkeys, 64–66 Social skills abstract play and, 147–149 indirect aggression and, 162–163 language development and, 342 peer relationships and, 378, 379 play fighting and, 50, 52–53, 55–57, 58 proactive and reactive aggression and, 195 in rhesus monkeys, 73–74 training in, 457 Social status, 162–163 Social systems causes of aggression and, 100 contextualism and, 18–19 Social testing, 49 Socialization gender differences and, 432 language–aggression association and, 343–344 model of, 414–415 overview, 95 responses to, 151–152 in rhesus monkeys, 64–66 from unilateral to bilateral views of, 13– 18 Socially motivated aggression, 32–33 Socioeconomic status. See also Welfare system age–violent crime curve and, 89 cognitive skills and, 313–314 indirect aggression and, 169–170 language–aggression association and, 343–344 language development and, 341 peer relationships and, 389–390 physical aggression and, 308 predictors of violence and, 210–211 proactive and reactive aggression and, 187 social capital and, 413 Sociometric status, 10

Index Specific language impairments (SLI), 332. See also Language development Speech and language difficulties (SLD), 332. See also Language development Splenium, 249. See also Brain mechanisms State dependence theory overview, 208–209 prevention and, 214 Strain differences, 69–70 Stress system cortisol and, 291–292 hormones and, 297–298 Structural MRI, 243–244f. See also Brain mapping; MRI Subcortical structures, 37 Substance use. See also Alcohol use; Smoking lack of behavioral control and, 261 overview, 451 proactive and reactive aggression and, 187, 195 serotonin and, 264 Subtypes of aggression. See also Taxonomies of aggression based on its antecedents, 34–39 based on its expression, 33–34 based on the consequences, 31–33 integrative model and, 39–41f multilevel analysis of, 29–30f overview, 41–42, 450–452 phylogenetic and ontogenetic organization of, 26–29 Suicide indirect aggression and, 167 molecular genetics and, 233 serotonin and, 264 Supervision, 404–405 Supplementary motor area, 251. See also Brain mechanisms

T Tantrums, 100 Taxonomies of aggression. See also Subtypes of aggression early, 27–29 integrative model and, 39–41f overview, 39 Teasing aggression, 38. See also Verbal aggression Temperament proactive and reactive aggression and, 184–185, 191 as a risk factor, 122

479

Terrorism, 33 Testosterone. See also Hormones causes of aggression and, 96 as an explanation for violence, 86–87t future research on, 296–298 overview, 282–283, 283–291 Theory of mind abstract play and, 149–150 executive function and, 316, 320–321 language–aggression association and, 346–347 Threat, 35–36. See also Reactive aggression Toddler years. See also Development; Infancy aggression during, 124–126, 430f–431, 452–454 anger during, 110 executive function and, 310 gender differences and, 432 individual differences and, 118–121 language development and, 334–335 peer relationships and, 378–380 risk factors and, 121–124 use of force during, 114–115f Towns, 412–414 Transsexuals, 287 Tryptophan hydoxylase genetic factors and, 233 overview, 264 Type A personality, 178–179

U Unilateral view of socialization, 13–18. See also Socialization

V Ventral premotor cortex. See also Brain mechanisms abstract play and, 145 overview, 251 Ventrolateral–medial hypothalamus, 37–38 Ventromedial cortex, 251. See also Brain mechanisms Verbal abilities, 315 Verbal aggression gender differences in, 436–437 overview, 108 Verbal organization, 273–275 Victimization in preschool children, 383 relationships and, 17 as a research construct, 5–6

480 Video games, 150 Vigilance, 268 Violence. See also Antisocial behavior; Homicide development of, 83–85, 207–209 genetic studies on, 228–234, 230f language development and, 333 neighborhoods and, 412 vs. nonviolent aggression, 5–6 overview, 202–203 play and, 149, 150 predictors of, 209–211 prevention of, 214–215 proactive and reactive aggression and, 187–188, 195 serotonin and, 264 testosterone and, 287 trajectories of, 211–214t, 212f, 213f Visuospatial abilities, 315 Vocabulary. See Language development

Index W War as aggression, 33 evolution of aggression and, 85 Weaning, 52 Weaning aggression, 28 Welfare system. See also Socioeconomic status overview, 399–402 social capital and, 418 White matter, 248–250. See also Brain mechanisms Wisconsin Card Sorting Test (WCST), 310, 311. See also Executive function World wars, 85

Y Young male syndrome, 169

Z Zoomorphism, 26–27