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International Journal of Behavioral Development 2006, 30 (5), 466–480 http://www.sagepublications.com

© 2006 The International Society for the Study of Behavioural Development DOI: 10.1177/0165025406071904

Proactive and reactive aggression in childhood and adolescence: A meta-analysis of differential relations with psychosocial adjustment Noel A. Card

Todd D. Little

University of Arizona, USA

University of Kansas, USA

Aggressive behavior in childhood has long been separated into that which is proactively motivated and that which is reactive. We report a meta-analytic review of the existing empirical literature that examines the associations of each type of aggression with six indices of psychosocial adjustment: internalizing problems, emotional dysregulation and ADHD-type symptoms, delinquent behaviors, prosocial behavior, sociometric status, and peer victimization. Even though not detectable in most single studies, meta-analytic combination revealed that reactive aggression was more strongly related to most of the indices of adjustment than was proactive aggression. This difference was small, however, and we argue that the difficulty in detecting differential correlates is due to the high intercorrelation between the functions of aggression, which appears to be an artifact of traditional measurement procedures. It is recommended that future research use measures that provide distinct assessment of the functions in order to more clearly distinguish the correlates of proactive and reactive aggression. Keywords: adjustment; aggression; aggressive behavior; instrumental aggression; meta-analysis; proactive aggression; reactive aggression; research synthesis

Childhood aggression is consistently associated with various aspects of concurrent maladjustment, including depression, emotional dysregulation, victimization, and poor peer relations (e.g., peer rejection). It is also associated with later psychosocial maladjustment, including peer rejection, academic failure, and adolescent delinquency, as well as unemployment, antisocial behavior, and criminality in adulthood (for reviews see Coie & Dodge, 1998; Farrington, 1991; Hodges, Card, & Isaacs, 2003). However, diverse ways of reconceptualizing and subdividing aggressive children have led to converging conclusions that all aggressive behavior is not equally maladaptive, and in some cases that it may be associated with positive adjustment. Hawley (2003; Hawley, Little, & Pasupathi, 2002), for example, has argued that a subset of aggressive individuals who combine aggressive behavior with prosocial behavior (“Machiavellians” or bistrategic controllers) are highly effective in controlling resources and exhibit positive psychosocial adaptation. Rodkin (Rodkin, Farmer, Pearl, & Van Acker, 2000) and others (Cillessen & Mayeux, 2004; Rose, Swenson, & Waller, 2004) have also shown that some aggressive youths are perceived as “cool” or popular by their peers, and hence are presumably more interpersonally well-adjusted than prior portrayals of aggressive youths as rejected social misfits (based on often-found relations between aggression and peer rejection) (Newcomb, Bukowski, & Pattee, 1993). An extensive body of work on bullying and victimization

commonly distinguishes between those who are aggressive only (i.e., bullies) and those who are both aggressive and victimized (i.e., aggressive-victims), and ample evidence suggests that aggressive youths who are not victimized are more psychosocially adjusted than those who are also victimized (see Pellegrini, Bartini, & Brooks, 1999; Schwartz, 2000; Schwartz, Proctor, & Chien, 2001). Distinctions are commonly made between overt (e.g., hitting or pushing) and social (e.g., gossiping or spreading rumors) forms of aggression (Cairns, Cairns, Neckerman, Ferguson, & Gariépy, 1989; Crick & Grotpeter, 1995; Lagerspetz, Björkqvist, & Peltonen, 1988). This work indicates that overt aggression is more common among boys than girls, whereas social aggression appears to be more equitably performed by boys and girls (Crick, 1997; Crick & Grotpeter, 1995; Lancelotta & Vaughn, 1989). Some evidence suggests that enacting forms of aggression that are gender non-normative is more strongly linked to psychosocial maladjustment than is gender normative forms of aggression (see Crick, 1997; cf., Phillipsen, Deptula, & Cohen, 1999; Salmivalli, Kaukiainen, & Lagerspetz, 2000). Although each of these distinctions may hold promise in explaining differences in the relations of aggressive behavior to psychosocial adjustment, we focus on the functional distinction that aggression serves. The distinction between proactive and reactive functions of aggression has a long history, and these different functions are believed to have

Correspondence regarding this article should be addressed to Noel Card, Family Studies and Human Development, 1110 E. South Campus Drive, University of Arizona, Tucson, AZ 85721-0033, USA; e-mail: [email protected] This work was supported in part by a National Institute of Mental Health Individual National Research Service Award (F32 MH072005) to the first author while at the University of Kansas, a NFGRF grant

(2301779) from the University of Kansas to the second author, and grants from the NIH to the University of Kansas through the Mental Retardation and Developmental Disabilities Research Center (P30 HD002528) and the Center for Biobehavioral Neurosciences in Communication Disorders (P30 DC005803). Its contents are solely the responsibility of the authors and do not necessarily represent the views of these sponsoring agencies.

INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT, 2006, 30 (5), 466–480

distinct underlying social cognitions. Mixed empirical evidence suggests that these two types of aggression are differentially related to psychosocial adjustment. The primary goal of this meta-analysis is to help clarify these differential relations of proactive and reactive aggression to psychosocial adjustment.

Proactive and reactive functions of aggression The functions of aggression refer to the motive of the aggressor, and have historically been distinguished along the lines of proactive versus reactive aggression (e.g., Dodge & Coie, 1987; Hartup, 1974; Lorenz, 1966). Proactive aggression (also called instrumental or “cold-blooded” aggression) refers to deliberate acts that are directed toward obtaining desired goals. In contrast, reactive aggression (also called defensive or “hotblooded” aggression) refers to angry, often emotionally dysregulated, responses to perceived offenses or frustrations. Different theoretical perspectives posit distinct socialcognitive processes for each function of aggression (see Crick & Dodge, 1994; Gifford-Smith & Rabiner, 2004). Proactive aggression is rooted in Bandura’s (1973, 1986) social-cognitive learning theory, which views aggression as a product of high self-efficacy for aggression, favorable outcome expectations for aggression, and valuing outcomes that are obtained through aggressive means. Each of these social-cognitive processes has been demonstrated to independently predict proactive aggression among children (Boldizar, Perry, & Perry, 1989; Crick & Dodge, 1996; Egan, Monson, & Perry, 1998; Guerra & Slaby, 1989; Perry, Perry, & Rasmussen, 1986; Schwartz et al., 1998; Slaby & Guerra, 1988; Smithmyer, Hubbard, & Simons, 2000). Dodge’s social information-processing model of aggression (1986; see Crick & Dodge, 1994) incorporates these social cognitions most directly in steps 4 (response access or construction) and 5 (response decision) of his model. Reactive aggression is rooted in the frustration-aggression model (see Berkowitz, 1993) and is incorporated as steps 1 (encoding of cues) and 2 (interpretation of cues) in Dodge’s social-information processing model. Indeed, there is evidence that reactively aggressive youths have biases in these social information-processing components, such as hostileattribution biases, consistent with this model (Crick & Dodge, 1996; Dodge & Coie, 1987; Dodge, Coie, Pettit, & Price, 1990; Graham & Hudley, 1994; Schwartz et al., 1998). Several lines of reasoning also suggest that proactive and reactive aggression differentially relate to maladjustment. First, given its often angry and emotionally dysregulated quality, one could expect that reactive aggression, more so than proactive aggression, would elicit greater negative reactions from peers (i.e., peer rejection, low peer acceptance, lack of friends, and victimization; e.g., Dodge et al., 1990; Perry, Perry, & Kennedy, 1992; Schwartz et al., 1998). The resulting quality of the child’s peer relations would further contribute to his or her psychological maladjustment (e.g., internalizing problems; see Parker & Asher, 1987). This rationale suggests that the function of aggression directly contributes to maladjustment. Engaging in reactive or proactive aggression may also serve as a marker for different underlying factors that more directly impact psychosocial adjustment. These factors may involve proximal social cognitions: for example, one might expect that the different social cognitions underlying each type of aggression may be distinctly related to other aspects of psychological functioning (e.g., internalizing problems) as well as differentially affect peer functioning (e.g., peer acceptance; for

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a review see, for example, Gifford-Smith & Rabiner, 2004). Alternatively, differential relations of each function of aggression to adjustment may involve more distal variables: here, for example, various aspects of the early home environment (e.g., parental abuse; Dodge, Lochman, Harnish, Bates, & Pettit, 1997; Shields & Cicchetti, 1998) may predict both the use of reactive aggression and various forms of maladjustment. Finally, poor psychosocial adjustment may predict increasing reactive aggression more so than it does proactive aggression: peer rejection and victimization, for example, might promote many situations in which a child would be angry and react to peer provocations (as well as foster beliefs that peers’ intentions are hostile; Schwartz et al., 1998), thus leading to increases in reactive but not proactive aggression. Although disentangling these processes requires longitudinal and experimental work (which we further discuss later), the possibility of each raises questions of the extent to which reactive and proactive aggression are differentially related to various indices of maladjustment. A difficulty in detecting distinct relations of proactive and reactive aggression to maladjustment has been that measures of these two functions are often highly inter-correlated. Evidence for this is readily apparent in even a casual perusal of the literature: e.g., r = .76 (Dodge & Coie, 1987), r = .87 (Dodge et al., 1990), r = .82 (Poulin & Boivin, 2000). Although factor analytic studies have demonstrated that these two functions emerge as two constructs (Day, Bream, & Pal, 1992; Poulin & Boivin, 2000), questions remain regarding the ability to assess proactive and reactive aggression distinctly, and indeed, whether such a distinction is meaningful (Bushman & Anderson, 2001). At best, this extremely high overlap likely obscures differential correlates that each type of aggression may have. We aim to clarify the obscurity that exists within single studies by applying the power of meta-analysis to detect differential relations of proactive and reactive aggression to psychosocial adjustment.

Goals of the quantitative review The primary goal of this meta-analytic review is to synthesize the available research in order to illuminate the potentially different relations proactive and reactive aggression have with six indices of psychosocial adjustment: internalizing problems, emotional dysregulation and attention deficit/hyperactivity disorder (ED/ADHD) symptoms, delinquent behaviors, prosocial behavior, sociometric status, and peer victimization. These six indices were selected to reflect a wide range of adjustment, including personal maladjustment (internalizing problems, ED/ADHD-type symptoms, and delinquent behaviors), personal adjustment or social competence (prosocial behaviors), and interpersonal functioning (sociometric status and peer victimization). Toward this end, we will metaanalytically summarize the bivariate and semipartial (controlling for the other function) relations of proactive and reactive aggression with each of these indices, and identify whether these functions of aggression are differentially related to each adjustment index. As described below, we suspect that differential relations, which most individual studies have inadequate power to detect, will become evident when the literature is combined using meta-analytic techniques. A minor goal, but one necessary in order to examine differential relations of proactive and reactive aggression to maladjustment, is to examine the degree of intercorrelation between

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CARD AND LITTLE / PROACTIVE AND REACTIVE AGGRESSION IN CHILDHOOD AND ADOLESCENCE

measures of proactive and reactive aggression. Although examining this degree of intercorrelation and moderators of it are an important focus of research in and of itself, full examination of this association is beyond the focus of this study.1 In addition to answering general questions about the relations of proactive and reactive aggression to psychosocial functioning, we test whether these relations differ across development (age moderation) and source by which aggression is assessed (reporter moderation). Although the existing literature is not clear in guiding these hypotheses, we investigated the following. We expected that relations of proactive aggression with maladjustment would diminish with age, under the assumption that the instrumental use of aggression becomes increasingly sophisticated with development. In contrast, we suspected two competing developmental forces might account for the associations of reactive aggression with maladjustment. First, assuming that reactive aggression becomes increasing nonnormative, one can expect stronger links to maladjustment with increasing age. On the other hand, it might be the case that reactively aggressive youths develop compensatory mechanisms to minimize the impact of their behavior on peer relations or that the social cognitions underlying reactive aggression and maladjustment become more differentiated with age – both of these possibilities would result in decreasing associations between reactive aggression and maladjustment with age. In terms of reporter moderation, we expected that peerreports of aggression (especially reactive aggression) would be most strongly related to social maladjustment (i.e., sociometric status and victimization), and that there would be greater differential relations of proactive versus reactive aggression with social adjustment with peer reports than with other information sources. Although self-reports have been infrequently used, we expected that studies using these assessments of the functions of aggression would also find higher differential relations to personal maladjustment than would other information sources because children’s own attributions for aggressive incidents (e.g., as purposeful versus uncontrollable) might be expected to be most tightly linked to their internal functioning (Graham & Juvonen, 1998). Predicated on the belief that trained observers would be better able to distinguish the two functions of aggression than would other reporters, we hypothesized that observational measures of proactive and reactive aggression would show large differentials in their associations with both personal and social aspects of adjustment.

Method Selection of studies Studies were obtained through (a) computerized literature searches of the PsycINFO database using the keywords 1 During the preparation of this review, we learned that another group (Polman, Orobio de Castro, & Koops) is conducting a thorough meta-analytic review of the intercorrelation between proactive and reactive functions of aggression, focusing on numerous characteristics of the child, definitions of the functions of aggression, and methodological features that might moderate the strength of this relationship (J.D.M. Polman, personal communication, August 31, 2004). We encourage interested readers to consult this meta-analysis when it is published, but expect that our less ambitious review of this intercorrelation will suit the purposes of our central aim (which is not considered in the metaanalysis by Polman and colleagues) of examining relations of proactive and reactive aggression to psychosocial adjustment.

“proactive aggression”, “instrumental aggression”, and “reactive aggression” and (b) by examining references cited in other papers. We chose to be lenient in our initial review of studies in order to be as inclusive as possible, and reviewed a total of 149 journal articles, chapters, books, and dissertations in selecting studies for potential inclusion. Studies were included if they met the following criteria: (a) they presented data regarding either the inter-correlation of proactive and reactive aggression or the relations of both functions of aggression to a correlate of interest; (b) the sample consisted of children under the age of 18 (i.e., adult samples were excluded); and (c) the sample could be considered normative (as opposed to including only children in psychiatric or criminal settings). Using these criteria, a total of 42 independent studies presented in 49 reports and consisting of 20,266 children were included.

Coding of studies For all studies we coded sample size, mean age, method of assessing aggression (i.e., self-, peer-, teacher-, parent-reports, or observations), and effect sizes. Effect sizes were calculated as correlations either between proactive and reactive aggression or of both functions of aggression with indices of psychosocial adjustment. The adjustment indices included internalizing problems (clinical or subclinical depression and anxiety), ED/ADHD-type symptoms (including impulsivity, frustration intolerance, tendencies to become angry or upset easily, inattention, and hyperactivity), delinquent behaviors (oppositional or defiant behaviors, destruction of property, deceitfulness and theft, and rule violations), prosocial behavior (e.g., helping others, sharing, cooperative), sociometric status (social preference, peer acceptance, peer rejection), and peer victimization (being the target of peers’ aggression).

Statistical analysis Effect size calculations. Effect sizes were represented as Pearson correlations, r. For studies reporting results in other metrics, these data were transformed to r using standard procedures (e.g., Rosenthal, 1991). Studies reporting only a significant association (at a certain p, or assumed to be .05 if not otherwise stated) were given the minimum r that would achieve that level of significance given the sample size (5.2% of effect sizes coded), and studies reporting only that a particular effect size was not significant were assigned r = 0 (6.6% of effect sizes coded). These standard practices represent a conservative approach, and may lead to slight underestimation of overall effect sizes. We sought to (a) compute the bivariate correlation of each function of aggression with the adjustment index (as described in the previous paragraph), (b) estimate the independent correlation of each function of aggression with the adjustment variables, and (c) to compare whether each adjustment variable was more strongly associated with proactive or reactive aggression. To estimate the relation of each function of aggression independent of the other function (e.g., reactive after controlling for proactive aggression), we computed semipartial correlations (sr) from the bivariate correlations of proactive and reactive aggression with the adjustment variable and between proactive and reactive aggression using the following formulas (see Cohen & Cohen, 1983):


srpro =

rpro − rreac rcorr 2 1 − rcorr

and srreac =

rreac − rpro rcorr 2 1 − rcorr

(1)

where rpro = correlation of proactive aggression to the correlate rreac = correlation of reactive aggression to the correlate rcorr = correlation between proactive and reactive aggression.

d=

where |R| r– n r pro r reac r corr

(rpro − rreac ) (n − 1)(1 + rcorr ) 2(n − 1) |R |+ r(1 − rcorr )3 n −1

×

1 n−3

ΣwZr /Σw where w = N – 3 and mean Zsr = ΣwZsr /Σw where w = N – 4; see Hays, 1994). Difference scores were analyzed in their d metric, and were also weighted by their inverse variance weight (w) when combined (Lipsey & Wilson, 2001), where: w=

To compare the relative magnitudes of the correlations of proactive versus reactive aggression with the adjustment variable, we computed a d score for each study representing the difference in associations (r’s) of proactive and reactive aggression to the correlate. Adapting traditional methods of comparing dependent correlation coefficients (e.g., Cohen & Cohen, 1983), the following formula was used: (2)

1 – r 2pro – r 2reac – r 2corr + 2r pror reacr corr (r pro + r reac)/2 number of participants in study correlation of proactive aggression to the correlate = correlation of reactive aggression to the correlate = correlation between proactive and reactive aggression.

= = = =

The semipartial correlations (sr) and the difference scores (d) both index the unique relations of proactive and reactive aggression with adjustment, but in different ways. The semipartial correlations indicate the direction and magnitude of the relations of each function of aggression to adjustment that are independent of the other function of aggression (specifically, the positive or negative square-root of the variance in the adjustment variable that overlaps with that function of aggression only). These semipartial correlations do not directly evaluate the differential relations each function of aggression has with the adjustment variable, however. This differential relation is instead captured by the difference score (d), which indexes the magnitude of the difference in the relations of each function of aggression with adjustment (but says nothing of the magnitude of association of either one of the functions of aggression with adjustment). Therefore, both the semipartial correlations and difference scores are needed to evaluate the distinct relations proactive and reactive aggression have with psychosocial adjustment. Combining and comparing effects across studies. All effect sizes were combined using sample-size weighted analyses. Namely, effect sizes in correlation metrics (r and sr) were first transformed to Fisher’s Zr (or Zsr) to provide an approximately normally distributed metric (averaged values of Zr and Zsr were — for reporting; see Rosenthal, transformed back into r– or sr 1991). Multiple results (Zr’s, Zsr’s, or d ’s) from the same study were averaged in order to yield one effect size per study in any given analysis to avoid violating independence assumptions when testing significance and computing standard errors. When averaging across multiple studies, Zr’s and Zsr’s were weighted by an inverse variance weight (i.e., mean Zr =

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1 d2 4 (1 + ) df 8

(3)

When sufficient studies existed, we systematically examined potential moderation by aggression reporter and age (see introduction for specific hypotheses). Moderation by aggression reporter was examined by classifying studies into those using self-, peer-, teacher-, parent-reports, or observations of aggression, and using variance partitioning procedures analogous to ANOVA (see e.g., Lipsey & Wilson, 2001, for details). Specifically, heterogeneity of effect sizes (Zr’s, Zsr’s, or d ’s) among studies (Qtotal) was divided into within moderator groups (Qwithin; e.g., among studies using teacher reports) and between groups (Qbetween = Qtotal – ΣQwithin) components. This between-group heterogeneity is distributed as χ2 (with df = number of groups – 1) under the null hypothesis that population effect sizes are equal across moderator groups. Significant between-group heterogeneity is indicative of statistically significant reporter moderation. In order to test age moderation, procedures analogous to weighted regression were performed (for details see e.g., Lipsey & Wilson, 2001). Specifically, age was centered at 10 years (approximately the midpoint of sample ages among the studies) in order to provide a meaningful intercept, and then the Zr’s, Zsr’s, or d ’s from each study were regressed onto this centered age term, weighted by the appropriate inverse variances described above. The heterogeneity among studies accounted for by age, QRegression, is also distributed as χ2 (with 1 df ) under the null hypothesis that population effect sizes do not change linearly across age. Significant relations between age and effect size were interpreted by considering the effect size intercept (i.e., predicted effect size at age 10) and slope (i.e., predicted change in effect size per one-year change in age; note that the standard errors of this weighted regression were modified according to the procedures recommended by Lipsey & Wilson, 2001).

Results Correlation between proactive and reactive aggression Across the 36 studies (total N = 17,360) that report the correlation between proactive and reactive aggression (see Table 1), the sample-size-weighted average correlation was r– = .68 (95% C.I. = .671, .687) (Z = 108.77, p < .001).2 Although these correlations are clearly different from one (i.e., the confidence intervals do not include 1.0), supporting the differentiation between proactive and reactive aggression found in factor analytic studies (Day et al., 1992; Poulin & Boivin, 2000), they nevertheless point to the high overlap between these two functions of aggression. 2 After correcting for measurement error (using internal consistencies reported in studies, with the mean α = .88 for both proactive and reactive aggression used for studies not reporting this value), the mean estimate of disattenuated correlation = .78 (.774, .786) (Z = 122.03, p < .001). Values of these disattenuated correlations for all studies and all levels of moderators are available from the first author upon request.

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Table 1 Correlations between proactive and reactive aggression Study

N

Age

Reporter

r

Arsenio et al. (2004) Atkins et al. (2002) Brendgen et al. (2001) Brown et al. (1996) Camodeca et al. (2002) Crain (2002) Crick & Dodge (1996) Day et al. (1992) Dodge & Coie (1987) – study 1 Dodge & Coie (1987) – study 2 Dodge et al. (1997) Frick et al. (2003) Hegland & Rix (1990) Marcus & Kramer (2001) Orobio de Castro et al. (2005) Phillips & Lochman (2003) Poulin & Boivin (2000) Poulin et al. (1997) Price & Dodge (1989)a " " Prinstein & Cillessen (2003) Pulkkinen (1996)a " " Ramsden (2001)/Ramsden & Hubbard (2002) Roland & Idsøe (2001) Salmivalli & Nieminen (2002)a " " Salmivalli et al. (2005) Schippell et al. (2003) Schwartz (1994)a " " Schwartz et al. (1998) Smithmeyer (2001)/Hubbard et al. (2002) Strassberg et al. (1994) Van Manen et al. (2001) Vazzana (2001) Vitaro et al. (2002) Vitaro et al. (1998) Waschbusch et al. (1998) Washburn et al. (2004)a " "

100 238 516 186 242 115 624 88 259 339 504 98 32 107 84 50 167 66 70 70 235 369 369 348

15.9 10.4 13.0 9.0 8.8 10.2 11.0 8.6 10.0 7.0 8.0 12.4 6.2 5.3 10.1 11.0 11.0 8.0 6.0 6.0 16.3 8.7 8.7 10.0

teacher teacher teacher teacher teacher peer teacher teacher teacher teacher teacher self & parent observation mother teacher teacher teacher observation observation teacher peer peer teacher teacher

.68 .62 .68 .70 .87 .95 .68 .41 .76 .76 .64 .70 .06 .62 .71 .78 .73 .47 .04 .83 .23 –.27 –.32 .82

3884 1062 1062 589 90 442 334 66 556

11.5 12.0 12.0 12.0 12.9 12.0 12.0 8.0 8.0

self peer teacher peer teacher peer teacher observation teacher

.66 .67 .32 .82 .55 .89 .73 .48 .78

273 115 222 3825 742 405 116 233

5.0 9.4 9.3 11.0 12.0 7.5 12.5 12.5

observation teacher teacher teacher teacher teacher teacher self

.18 .43 .79 .72 .71 .68 .76 .69

Weighted fixed effects mean: Median:

.68 .68

a Results

averaged (averaged Z-transformed r) for all analyses except those for reporter moderation.

Results of the age moderation analyses indicated that the correlations between proactive and reactive aggression increased linearly with age (QRegression(1) = 9.35, p < .001). Specifically, the correlations between these two functions of aggression were rˆ = .67 (Zˆr = .82) at age 10, and increased .013 per year increase (BZr = .013).3

3 Note that these regression coefficients represent the relation of age to Zr. For smaller values of B and when extrapolating over short periods of time, these will be reasonable approximations of the expected change in r. However, to obtain the most accurate expected r at a given age, use the intercept and regression coefficients provided to compute the expected value of Zr at a given age, then transform this value to r.

In assessing proactive and reactive aggression, researchers have relied primarily on teacher reports, often using the scale developed by Dodge and Coie (1987) or that developed by Brown, Atkins, Osborne, and Milnamow (1996). Of the 36 studies shown in Table 1, 26 utilized teacher reports to assess proactive and reactive aggression, whereas peer reports were used in seven studies, observations in five, self-reports in three, and parent reports in two studies (note that this count does not sum to 36 because some studies used multiple informants). Comparisons of teacher reports, peer reports, self-reports, and observations (parent reports were excluded because one study used a combined self and parent measure, and parent reports were thus used independently in only one study) revealed significant differences in correlations depending on the reporter (Qb(3) = 160.21, p < .001). The relation between proactive and reactive aggression was similar when assessed by teacher- (r– = .68), peer- (r– = .68), or self- (r– = .66) reports. Studies using observations of aggression, however, had substantially lower correlations between proactive and reactive aggression than did studies using teacher-, peer-, or selfreports (r– = .24).

Relations with psychosocial adjustment Separate meta-analyses were performed to examine the relations of proactive and reactive aggression to each of six indices of psychosocial adjustment: internalizing problems, ED/ADHD-type symptoms, delinquent behaviors, prosocial behavior, sociometric status, and peer victimization. The studies used in these meta-analyses, as well as summary statistics and results of moderator analyses, are shown in Table 2. Internalizing problems. Meta-analytic combination of eight studies (total N = 3083) revealed that reactive, but not proactive, aggression exhibits a small but statistically reliable positive zero-order correlation with internalizing problems. Combining the semipartial correlations of the independent associations of proactive and reactive aggression yielded similar results. Although data from only one individual study (Day et al., 1992) was able to significantly differentiate these associations, meta-analytic combination of the d scores (i.e., magnitude of differential relation of proactive and reactive aggression to internalizing problems) revealed that reactive aggression is more strongly related to internalizing problems than is proactive aggression. Age did not moderate this d score, but it did moderate the zero-order correlations of both proactive and reactive aggression to internalizing problems. Here, the associations of both functions of aggression with internalizing problems decrease with age (proactive: intercept Zˆr = .02, BZr = –.054; reactive: intercept Zˆr = .05, BZr = –.053). Similarly, age moderated the independent association (sr) of proactive aggression with internalizing problems such that this becomes more negative with age (intercept Zˆsr = –.02, BZsr = –.023), but age did not moderate the independent relation of reactive aggression with internalizing problems. Reporter moderation was limited to comparisons of teacherand peer-reported aggression, but did indicate significant differences in the both the zero-order and semipartial correlations of internalizing problems with both proactive and reactive aggression across reporters. Specifically, teacher — = .08) aggression (but only the reports of reactive (r– = .11, sr zero-order correlation for proactive aggression, r– = .07) are

471


Table 2 Relations of proactive and reactive aggression to psychosocial adjustment Correlate Study

N

Age

Reporter

Proactive (r)

Proactive (sr)

Reactive (r)

Reactive (sr)

Difference (d)

8.6 7.0 8.0 10.1 8.7 12.0 12.9 10.5

teacher teacher teacher teacher teacher & peer peer teacher teacher

–.25* –.09 .31*** .10 –.04 –.17*** –.01 .03

–.33** .00 .10* .18 –.06 –.10* –.06 –.02

.14 –.12 .36*** –.04 –.07 –.14*** .07 .07*

.26* –.08 .21*** –.16 –.09 .00 .09 .07*

–.76*** .09 –.13 .37 .04 –.10 –.17 –.10

Weighted fixed effects mean: Median: Age moderation, Q(1) Reporter moderation, Qb(1)

.02 –.02 22.39*** 28.29***

–.02 –.04 21.21*** 7.73**

.05** .01 3.97* 42.97***

.05** .03 1.24 19.38***

Internalizing problems: Day et al. (1992) 88 Dodge & Coie (1987) – study 2 158 Dodge et al. (1997) 502 Orobio de Castro et al. (2005) 84 Pulkkinen (1996)a 369 Salmivalli et al. (2005) 589 Schippell et al. (2003) 90 Vitaro et al. (2002) 1203

ED/ADHD-type symptoms: Day et al. (1992) Farver (1996) Hubbard et al. (2002) Little et al. (2003) Orobio de Castro et al. (2005) Price & Dodge (1989)a Pulkkinen (1996)a Ramsden (2001) Schippell et al. (2003) Vorbach (2002) Washburn et al. (2004)a

Delinquency: Atkins et al. (2002) Brown et al. (1996) Frick et al. (2003) Pulkkinen (1996) Schippell (2001) Vitaro et al. (2002)

Prosocial behavior: Day et al. (1992) Dodge & Coie (1987) – study 2 Hegland & Rix (1990) Marcus & Kramer (2001) Price & Dodge (1989)a Salmivalli et al. (2005) Vorbach (2002)

88 64 272 1723 84 70 369 120 90 112 211

teacher observations teacher self teacher teacher & obs. teacher & peer teacher teacher peer self & teacher

–.05 .31* .01 –.07** .30** .14 .14** .35*** .35*** .16 .15*

–.08 –.02 –.03 –.04 .05 –.08 .16** .08 .01 .16 .03

.05 .48*** .04 .28*** .37*** .37** .02 .42*** .62*** .25** .18*

.08 .37** .05 .28*** .23*** .35** .06 .25** .51*** .25** .10

–.19 –.48 –.08 –.50*** –.21 –.52* .16 –.21 –.72** –.14 –.08


.04* .15 22.63*** 28.61***

.00 .01 2.32 12.07**

.24*** .28 10.00** 18.90***

.23*** .25 11.65*** 8.98*

–.32*** –.21 18.82*** 37.67***

.23*** .42*** .35*** .14** .55*** .09**

.03 .11 .22* .15** .19* .06

.34*** .49*** .28** .00 .57*** .07*

.25*** .27*** .05 .04 .24** .00

–.26* –.21 .19 .18 –.07 .06

Weighted fixed effects mean: Median: Age moderation, Q(1) Reporter moderation

.18*** .29 2.80 –

.09*** .13 0.00 –

.16*** .31 7.68** –

.07*** .14 0.02 –

.03 .00 0.06 –

88 158 64 107 70 589 112

teacher teacher teacher mother teacher & obs. peer peer

–.20 .01 –.16 –.57*** .07 –.28*** –.24*

–.09 .01 –.14 –.26*** .19 .01 –.24**

–.29** .01 –.10 –.59*** –.17 –.35*** –.30**

–.23* .00 –.04 –.30*** –.24* –.21*** –.30**

.16 .01 –.12 .06 .51* .25* .08


–.24*** –.20 .71 46.89***

–.30*** –.29 1.72 31.38***

–.19*** –.23 .21 8.57*

.17** .08 .80 2.98

157 186 98 369 96 1203

8.6 4.3 8.0 13.7 10.1 6.0 8.7 9.0 12.9 13.1 12.5

–.08* –.10 .14 0.10

10.4 9.0 12.4 8.7 13.0 10.5

8.6 7.0 6.2 5.3 6.9 12.0 13.1

teacher teacher self & parent teacher parent & teacher teacher

–.04 –.09 .21 14.72**

Continued

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Table 2 Continued Correlate Study

N

Age

Reporter

Proactive (r)

Proactive (sr)

Reactive (r)

Reactive (sr)

Social preference: Dodge et al. (1990) Dodge et al. (1997) Poulin & Boivin (1999) Price & Dodge (1989)a Prinstein & Cillessen (2003) Ramsden (2001) Smithmyer (2001)

129 422 149 70 235 120 76

7.0 8.0 10.5 6.0 16.3 9.0 8.0

observations teacher teacher teacher & obs. peer teacher teacher

–.28** –.25*** –.32*** –.06 .14* –.26** –.42***

–.20* –.04 –.02 .13 .15* –.10 –.01

–.20* –.35*** –.41*** –.32** –.02 –.28 –.56***

–.02 –.25*** –.26*** –.34** –.05 –.14 –.36***


–.19*** –.26 24.93*** 34.78***

–.29*** –.32 16.68*** 29.19***

–.23*** –.25 4.64* 11.14**

Peer acceptance: Dodge et al. (1990) Volling et al. (1993) Vorbach (2002)

Peer rejection: Brown et al. (1996) Coie et al. (1991) Day et al. (1992) Dodge et al. (1990) Volling et al. (1993) Vorbach (2002) Waschbusch et al. (1998)

23 896 112

7.0 7.6 13.1

.22*** .26 .16 5.41

.05 .02 –.09

.39 –.11** –.14

.26 –.09** –.14

Weighted fixed effects mean: Median: Age moderation Reporter moderation

–.05 –.05 – –

.01 .02 – –

–.10** –.11 – –

–.09** –.09 – –

186 131 88 23 889 112 405

.26*** .22** –.17 .66*** .21*** .34*** .73***

.11 .20* –.27* .47* .04 .34*** .27***

.26*** .10 .18 .47* .29*** .42*** .78***

.11 .00 .18 .47* .29*** .42*** .78***

.00 .24 –.68** .62 –.19** –.13 –.22*

.36*** .26 3.38 .93

.12*** .20 2.24 9.80**

.42*** .29 1.51 13.89***

.23*** .20 3.49 13.04**

–.15** –.13 .05 8.48*

teacher observations self self teacher & peer teacher & peer observations

–.17** –.11 –.06* .10*** .16*** .18*** –.07

–.79*** –.31*** –.07** –.04* .01 –.09* –.34**

.25*** .17 –.05* .20*** .29*** .28*** .48***

.81*** .33*** –.06* .18*** .24*** .23*** .59***

–2.96*** –.75*** –.01 –.24*** –.28*** –.35*** –1.33***


.06*** –.06 .63 30.50***

–.08*** –.09 69.02*** 25.41***

.16*** .25 55.54*** 63.21***

.17*** .24 215.26*** 100.08***

–.26*** –.35 109.90*** 48.28***

teacher observations teacher observations teacher peer teacher

Weighted fixed effects mean: Median: Age moderation, Q(1) Reporter moderation, Qb(2) Peer victimization: Camodeca et al. (2002) Lento (2001) Little et al. (2003) Roland & Idsøe (2001) Salmivalli & Nieminen (2002)a Schwartz (1994)a Schwartz et al. (1998)

–.20 .25* .28 .57* .26 .05 .44

.29 –.05 –.09

9.0 7.0 8.6 7.0 7.6 13.1 7.5

observations teacher peer

–.01 –.02 6.79** 6.34*

Difference (d)

242 127 1723 3884 1062 442 66

8.8 6.5 13.7 11.5 12.0 12.0 8.0

–.26 .13 .07 .12* .07 – –

Note. Significance levels computed by sample sizes and effect sizes reported in studies, *p < .05; **p < .01; ***p < .001. a Averaged (averaged Z-transformed r’s) results across multiple reporter types (separated for analyses of reporter moderation).

related to high levels of internalizing problems, whereas peer reports of these functions of aggression are related to lower — ’s = –.10 levels of internalizing problems (r– ’s = –.13 and –.14, sr and –.07, for proactive and reactive aggression, respectively). Emotional dysregulation and ADHD (ED/ADHD) symptoms. As shown in Table 2, across 11 studies (total N = 3203),

proactive aggression has a small zero-order correlation with ED/ADHD-type symptoms, but reactive aggression is more strongly associated with these symptoms. Moreover, the independent relation of proactive aggression to ED/ADHD symptoms, after controlling for reactive aggression, is not significant, whereas reactive aggression is uniquely related to these symptoms. In summary, ED/ADHD-type symptoms


exhibit negligible relation to proactive aggression and a moderate relation to reactive aggression. Age moderation of the zero-order association between ED/ADHD-type symptoms and aggression was evident for both proactive and reactive functions, as well as their differential relation to these symptoms. The relation of proactive aggression to these symptoms was found to decrease with age (BZr = –.032; intercept Zˆr = .09), whereas the relation of reactive aggression with these symptoms becomes stronger with age (BZr = .021; intercept Zˆr = .21). As expected, proactive and reactive aggression becomes more differentially related to ED/ADHD-type symptoms with age (Bd = –.059; intercept Zˆd = –.22; note that negative values indicate a stronger relation of reactive aggression relative to proactive aggression). The unique relation (sr) of reactive aggression with ED/ADHD-type symptoms increases with age (BZsr = .023; intercept Zˆsr = .19), whereas the independent relation of proactive does not significantly change with age. The zero-order and semipartial correlations with ED/ ADHD-type symptoms are also moderated by the reporter of proactive and reactive aggression, as are the differential relations (i.e., d ) scores. Teacher reports (r– = .14), peer reports (r– = .15), and observations (r– = .12) of proactive aggression exhibit larger zero-order correlations with these symptoms than do self-reported proactive aggression (r– = –.03, ns), although only peer reports of proactive aggression exhibit a — = .16). In contrast, selfsignificant semipartial correlation (sr — = .25), along with observations (r– = .34, reports (r– = .27, sr — = .28), of reactive aggression are more strongly related to sr ED/ADHD-type symptoms than are teacher reports (r– = .18, — = .18) and peer reports (r– = .09, sr — = .12). The largest sr differential relations were found among studies using self– – reports (d = –.41) and observations (d = –.41), whereas – – teacher (d = –.10) and peer reports (d = .07, ns) were significantly less discriminating. Delinquent behaviors. Six studies (total N = 2190) report associations with delinquent behaviors (Table 2). Both proactive and reactive aggression exhibit small-to-moderate average zero-order correlations and small independent correlations with delinquency (which are not significantly different from one another). Analyses of age moderation must be considered in light of the limited age range across which associations of the functions of aggression with delinquent behaviors have been studied (i.e., no studies have reported on this relationship before age 8). The zero-order (but not semipartial) correlations of reactive aggression to delinquent behaviors are higher in studies with older samples (BZr = .057, intercept Zˆr = .15), whereas the correlations (zero-order or semipartial) of proactive aggression with delinquent behaviors do not significantly increase with age. The stronger relation of reactive aggression to delinquency with increasing age may be tenable given that rates of delinquency increase from childhood to adolescence (e.g., Loeber & Stouthamer-Loeber, 1998), and hence there is greater variability during that period. Reporter moderation could not be tested because none of these six studies used a measure of aggression that was not composed at least partly from teacher reports. Prosocial behavior. Both proactive and reactive functions of aggression exhibit small-to-moderate zero-order correlations with low prosocial behavior across eight studies (total N = 1272; Table 2). However, the independent (semipartial)

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correlation of proactive aggression to prosocial behavior is not significant, whereas reactive aggression has a small-to-moderate independent relation to low prosocial behavior. Furthermore, the differential relation (d ) scores indicate that the association between aggression and low prosocial behavior is significantly stronger for reactive than for proactive aggression. In summary, reactive aggression is primarily related to low prosocial behavior, whereas proactive aggression has little or no association independent of reactive aggression. Age did not moderate either the zero-order or the semipartial correlations of either proactive or reactive aggression with prosocial behavior (or their differential relation to prosocial behavior). On the other hand, reporter moderation, which should be viewed with caution given the few studies assessing aggression other than via teacher reports, is significant for both the zero-order and semipartial correlations of proactive aggression and reactive aggression to prosocial behavior. The patterns of associations across reporters are similar for both functions of aggression. Peer reports of proactive (r– = –.27) and reactive (r– = –.34) aggression have stronger zero-order correlations with low prosocial behavior then do teacher reports of these functions of aggression (r– ’s = –.10 and –.13, respectively). This difference between peer and teacher reports is only evident for reactive aggression when the — ’s = –.22 versus –.10, unique relations to prosocial behavior (sr respectively) are examined. The single study using parent reports (Marcus & Kramer, 2001) of aggression found strong relations of both proactive (r = –.57) and reactive (r = –.59) aggression with low prosocial behavior (and similar semipartial correlations, sr = –.26 and –.30, respectively). In contrast, the one study using observations of aggression (Price & Dodge, 1989) found that proactive aggression is related to higher levels of prosocial behavior (r = .32, sr = .32) whereas reactive aggression has a small (nonsignificant) relation with low prosocial behavior (r = –.06, sr = –.07). The Price and Dodge (1989) study also used teacher reports of proactive and reactive aggression, finding results similar to those in other studies using teacher reports (i.e., the relations of proactive and reactive aggression to prosocial behavior were r’s = –.19 and –.27). Therefore, although we must be cautious in interpreting the findings of a single study, the positive relation between prosocial behavior and observations of proactive aggression may represent an interesting exception to the general pattern found in other studies. Sociometric status. Three indices of sociometric status were examined in relation to proactive and reactive aggression: social preference (measures including liking and disliking by peers, often computed by subtracting standardized number of dislike nominations received from the standardized number of like nominations received), peer acceptance (measures of being liked by the peer group), and peer rejection (measures of being disliked by peers). We initially performed a metaanalysis with all three indices combined, with correlations involving peer rejection reversed in sign so as to capture relations between aggression and positive peer-group status. Combining across these 13 independent studies (total N = 3019) revealed that (a) both proactive (r– = –.26) and reactive (r– = –.34) aggression are related to poor group status, (b) both — = –.06) and reactive (sr — = –.19) aggression are proactive (sr independently related to poor group status, and (c) the relation of reactive aggression to poor sociometric status is significantly – stronger than that of proactive aggression (d = .17). However,

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tests of moderation by the status index used (i.e., social preference, peer acceptance, and peer rejection) indicate that treating the measures as equivalent indices of social status in relation to aggression is inappropriate (Qb(2) = 74.84, p < .001 and Qb(2) = 81.27, p < .001 for proactive aggression and reactive aggression, respectively), consistent with prior literature showing that these three variables capture different aspects of social status (see Bukowski, Sippola, Hoza, & Newcomb, 2000). Therefore, we performed three separate meta-analyses for social preference, peer acceptance, and peer rejection, summarized in Table 2. Across seven studies (total N = 1201) social preference is negatively associated with both proactive and reactive aggression. However, analyses of the semipartial correlations revealed that only reactive aggression is independently related to low social preference. Further, the difference scores indicated that this relation is stronger for reactive than proactive aggression. Age significantly moderates the zero-order and semipartial correlations of both proactive and reactive aggression with social preference (though not their differential relation). For both functions of aggression, there are stronger negative zeroorder and semipartial correlations with social preference at younger ages than at older ages (proactive aggression: BZr = .043, intercept Zˆr = –.19 and BZsr = .022, intercept Zˆsr = –.01; reactive aggression BZr = .035, intercept Zˆr = –.29 and BZsr = .019, intercept Zˆsr = –.19). In other words, the relation between both functions of aggression and low social status diminishes with increasing age. Aggression reporter also moderates the zero-order and semipartial correlations of both proactive and reactive aggression with social preference. Teacher-reported proactive aggression has a medium zero-order relation (r– = –.29) but no independ— = –.03, ns) to low social preference, and obserent relation (sr vations of proactive aggression exhibit a small zero-order — = –.07, ns) relation (r– = –.12) and no independent relation (sr to social preference. In contrast, peer reports of proactive aggression are associated with higher social preference (r– = .14 — = .15 both p’s < .05). For reactive aggression, teacher and sr reports are most strongly related to low social preference (r– = — = –.26 both p’s < .001), while observations (r– = –.38 and sr –.19) and peer reports (r– = –.02, ns) do not significantly differ in their relations to social preference (and neither is independ— = –.07 and –.05, ns, ently associated with social preference, sr respectively). The evidence from three studies (total N = 1031) fails to indicate a significant correlation between proactive aggression and peer acceptance. However, reactive aggression has small zero-order and semipartial relations to low peer acceptance. With only three studies, there was not adequate evidence to conclude that the magnitude of these relations differs. There were also an inadequate number of studies to meaningfully examine age or reporter moderation of these effects. Correlations of proactive and reactive aggression with peer rejection have been examined in seven studies (total N = 1834). Results of this meta-analysis reveal a moderate zeroorder correlation of rejection with proactive aggression and a moderate-to-large zero-order correlation with reactive aggression. Both proactive and reactive aggression are independently associated with peer rejection, but the relation of rejection to reactive aggression is significantly stronger than to proactive aggression. Age did not significantly moderate the zero-order or semipartial relations of rejection with either

proactive or reactive aggression. Aggression reporter moderates the zero-order correlations of reactive, but not proactive, aggression with peer rejection, such that peer (r– = .42) and teacher reports (r– = .45) of reactive aggression are more strongly related to rejection than are observations of reactive aggression (r– = .16). Aggression reporter moderates the semipartial correlations of reactive aggression with peer rejection in — = .42 and .24 versus .00, ns for peer and a similar manner (sr teacher reports versus observations, respectively). The differential correlations of proactive and reactive aggression to rejection are also moderated by aggression reporter, with reactive aggression being more strongly related to rejection when – assessed with teacher reports (d = –.20; with the same trend in the one study using peer reports, d = –.13; Vorbach, 2002) but proactive aggression being more strongly related to rejec– tion when assessed via observation (d = .30). Peer victimization. Relations of proactive and reactive aggression with peer victimization were examined in seven studies (total N = 7546). Whereas the zero-order correlation between victimization and proactive aggression is small in magnitude, the relation with reactive aggression is small-tomoderate. The semipartial correlations provide an even more telling story; reactive aggression has an independent relation to higher victimization whereas proactive aggression has an independent relation with lower victimization. These associations are significantly different from one another. These findings indicate that it is primarily reactive aggression, more so than proactive aggression, that is associated with being victimized by peers. Age significantly moderates the zero-order relations of victimization with reactive aggression but not proactive aggression, the semipartial correlations with both proactive and reactive aggression, and the differences in magnitudes of these relations. Specifically, reactive aggression is associated (both zero-order and semipartial) with victimization more strongly at younger ages than at older ages (BZr = –.065, intercept Zˆr = .29; BZsr = –.127, intercept Zˆsr = .42), while the magnitude of the independent (but not zero-order) relation of proactive aggression to low victimization diminishes with age (BZsr = .072, intercept Zˆsr = –.22). These age effects account for the larger differential relations in younger than in older samples (Bd = .195; intercept Zˆd = –.64; note that the positive value of the regression coefficient indicates a diminishing differential of the relation of reactive relative to proactive aggression with increasing age). Relations between victimization and the functions of aggression are also moderated by aggression reporter. For proactive aggression, the two studies using peer reports exhibited the greatest zero-order correlation (r– = .19), followed by teacher (r– = .08) and self reports (r– = .05). Observations of proactive aggression show a nonsignificant negative trend (r– = –.10). The independent (i.e., semipartial) relations of proactive aggression with victimization are also moderated by reporter, though the follow-up comparisons reveal a different trend than was found for the zero-order relations: observations of proactive aggression have the largest independent association — = –.32), followed by teacher reports with low victimization (sr — — = –.07) and self (sr — = –.05) reports (sr = –.15), while peer (sr have small but statistically significant independent associations with low victimization. The strength of the zero-order correlation between reactive aggression and victimization also varies by reporter, with the strongest correlations found in studies


using peer reports (r– = .32) or observations (r– = .28), followed by teacher reports (r– = .24, which are not significantly different from observations), and finally by self-reports (r– = .12). Reporter moderation of semipartial correlations between reactive aggression and victimization indicates the largest inde—= pendent relations for observations of reactive aggression (sr — — .43), followed by teacher (sr = .32) and peer (sr = .28) reports, with self-reports having the smallest (but still statistically — = .11). Expectedly, significant) independent associations (sr differences in the magnitudes of the associations of proactive and reactive aggression to victimization are largest among – studies using observations of aggression (d = –.93), followed – by teacher- (d = –.43) and peer-reports (= –.39), with self– reports showing the smallest (d = –.17) but still statistically significant difference.

Discussion Relations of proactive and reactive aggression to psychosocial functioning The primary goals of this study were to identify the degree of associations (both zero-order and independent) of proactive and reactive aggression to several indices of psychosocial functioning, and to compare the magnitudes of these associations to determine if one type of aggression is more strongly linked to maladjustment than the other. For all eight indices examined, reactive aggression has a significant zero-order relation to poorer psychosocial adjustment. These effect sizes range from small (with internalizing problems, low peer acceptance), small-to-moderate (ED/ADHD-type symptoms, delinquency, peer victimization), moderate (low prosocial behavior, low social preference), to moderate-to-large (peer rejection). Proactive aggression is significantly related to six of these eight indices (unrelated to internalizing problems and peer acceptance), with these effect sizes ranging from small (ED/ADHD-type symptoms, victimization), small-to-moderate (delinquency, low prosocial behavior, low social preference), to moderate-to-large (peer rejection). The independent (i.e., semipartial) relations of each function of aggression, controlling for the other, reveal an even more striking pattern. Reactive aggression is independently related (beyond the relations of proactive aggression) with internalizing problems, ED/ADHD-type symptoms, delinquency, low prosocial behavior, low social preference and peer acceptance, higher peer rejection, and victimization; in other words, reactive aggression is independently related to all eight indices of maladjustment examined. In contrast, proactive aggression, after controlling for reactive aggression, is related only to greater delinquency and peer rejection; it is not significantly related to internalizing problems, ED/ADHD-type symptoms, prosocial behavior, social preference, or peer acceptance, and it is related to lower levels of victimization. These results indicate that the aspects of reactive aggression that are independent of proactive aggression are generally related to maladjustment, whereas the aspects of proactive aggression that are independent of reactive aggression are related to only two aspects of maladjustment and one aspect of positive adjustment. Calculating a d score of the differential relation of proactive and reactive aggression to adjustment within each study, then meta-analytically combining these d scores across studies

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represents a statistically powerful method of examining the differential relations of each type of aggression to adjustment (i.e., the relative magnitude of the relations of proactive and reactive aggression with adjustment). Although examination of Table 2 revealed that few individual studies would have been able to detect this differential association (even if all study authors had attempted to detect this difference), we were able to detect reliable differences for six of eight analyses: internalizing problems, ED/ADHD-type symptoms, prosocial behavior, social preference, peer rejection, and peer victimization. For all six of these indices, reactive aggression is more strongly related to psychosocial maladjustment than is proactive aggression. These outcomes of our meta-analysis provide evidence that reactive aggression is generally more strongly related to maladjustment than is proactive aggression. There are several potential explanations for this differential relation. First, reactive aggression may be viewed as more aversive by peers than is proactive aggression, a possibility that would overlap with recent research showing that some aggressive individuals are viewed favorably by peers (Cillessen & Mayeux, 2004; Hawley, 2003; Hawley et al., 2002; Rodkin et al., 2000; Rose et al., 2004). The greater negative impact of reactive versus proactive aggression on peer relations may also translate into greater personal maladjustment (e.g., internalizing problems, low prosocial behavior). Alternatively, poor peer relations and personal maladjustment may translate into reactive acts of aggression, perhaps directly (e.g., ED/ADHD-type symptoms causing more frequent reactive outbursts) or indirectly through social cognitions (e.g., peer victimization causing increasing attributions of others’ hostile intentions). A third possibility is that the antecedents of these various forms of maladjustment (e.g., social cognitive deficits) also lead to more reactive than proactive aggression. Unfortunately, the reliance on concurrent correlations for this meta-analysis precludes any conclusions of causality, so these possible mechanisms remain speculative until future experimental and longitudinal research is conducted. Although this meta-analysis revealed several statistically significant differential relations of reactive versus proactive aggression with maladjustment, we do not wish to overstate the practical significance of these conclusions. Both proactive and reactive aggression are generally associated with psychosocial maladjustment when zero-order correlations are considered, and it is only the aspects of proactive aggression that are independent of reactive aggression that show little association with maladjustment. Furthermore, none of the indices examined showed evidence that proactive aggression is related to positive psychosocial adjustment; that is, no zero-order correlations suggest positive adjustment, although one semipartial correlation did indicate proactive aggression being related to greater adjustment (i.e., low victimization). Finally, the magnitude of the differential associations (i.e., d’s) is generally quite small, with significant differences ranging in (absolute) magnitude from .08 to .32. Thus, even the largest average differences found in this quantitative review can be considered only small-tomoderate in magnitude (compared to standards of d = .20, .50, and .80 as small, medium, and large effect sizes; Cohen, 1969).

Difficulties in detecting differential associations Several reasons may explain why it is difficult to detect differential relations to maladjustment in individual studies and why the magnitudes of these differential relations are generally

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small. First, both proactive and reactive functions of aggression may in fact be associated with poor psychosocial adjustment to roughly equal degrees. For example, being rejected by peers may result from either type of aggression if the peer group is unaware of or indifferent to the factors responsible for the aggressor’s behavior (i.e., proactive versus reactive). Second, proactive and reactive aggression may truly be so highly intercorrelated that there is little possibility of differential relations to adjustment. This degree of overlap would be the case if both functions of aggression were manifestations of a single underlying characteristic, or if both shared common antecedents. If they highly co-occur, then there is little possibility for one type of aggression to predict later maladjustment in the absence of the other type. Our meta-analysis of 36 studies reporting intercorrelations between proactive and reactive aggression suggested that, although the two types are not perfectly overlapping, the existing research indicates that they co-occur at an extremely high level (i.e., r = .68). A third possibility, and the one that we favor, is that the high correlation between proactive and reactive aggression evident in most prior research is an artifact of traditional measurement approaches. In other words, the problem is not so much that proactive and reactive aggression co-occur, but rather the measurement approaches most often used to assess these functions of aggression produce high intercorrelation. Indirect evidence that the high intercorrelation may be related to the measurement approaches used is provided by the reporter moderation of this effect. Studies using observational approaches to assessing proactive and reactive aggression (which are less commonly used in studying these functions of aggression) yield markedly lower intercorrelations than those using peer-, self-, or teacher-reports. This difference suggests that measurement practices may play at least some role in the observed correlation between these types of aggression. The finding that observational measures of proactive and reactive aggression are far less intercorrelated than are measures using other information sources may indicate that trained observers are better able to distinguish the functions of aggression than are children (via self- or peer-reports) or teachers. If this is the case, then future research using observational methods may be recommended. However, such techniques can be costly and time-consuming, especially since aggression may often be a relatively rare behavior (cf., Pepler, Craig, & Roberts, 1998) that necessitates substantial periods of observation to reliably measure. A complimentary approach to observational methods of assessing proactive and reactive aggression would be to employ methods that use other reporters, but yields less correlated measures of these functions of aggression by removing certain measurement artifacts. Little and colleagues (2003) provided a persuasive argument for why the high correlation between proactive and reactive aggression may be largely an artifact of measurement techniques. They pointed out that traditional methods of assessing proactive and reactive aggression have typically used items that include overlapping forms of aggression (e.g., proactive and reactive items that both imply acts of overt aggression, such as “hits or pushes others to get what they want” and “hits or pushes other when angry”). Thus, part of the overlap between these measures of proactive and reactive aggression is due to the variance shared in the form of aggression. To overcome this problem, Little and colleagues (2003) developed a self-report measurement system that assesses six subscales of aggressive

behavior: two assessing pure overt and relational aggression in which no function is implied (e.g., “I’m the type of person who hits, kicks, or punches others”, “I’m the kind of person who gossips or spreads rumors”), and four scales assessing the four combinations of the two forms (overt, relational) and two functions (proactive, reactive) of aggression: overt-proactive (e.g., “I often start fights to get what I want”), overt-reactive (e.g., “If others have angered me, I often hit, kick, or punch them”), relational-proactive (e.g., “To get what I want, I often gossip or spread rumors about others”), and relational-reactive (e.g., “If other have hurt me, I often try to keep them from being in my group of friends”). This measurement approach allows for the decomposition of variability on the latter four scales into that due to form and that which is due to function. The correlation between proactive and reactive aggression using this approach (r = –.10; Little et al., 2003) was far smaller than that found in most other studies (with the exception of some observational studies; e.g., Hegland & Rix, 1990; Price & Dodge, 1989; Strassberg et al., 1994). These findings suggest that this decomposition approach may yield largely independent measures of proactive and reactive aggression, although further work with diverse samples (in terms of cultural setting and age) and information sources (i.e., this study used self-reports, which have not been commonly used in studying these functions of aggression) is desirable. Whether using observational assessments or the decomposition approach developed by Little and colleagues (2003), future research will need to measure proactive and reactive aggression distinctly if unique adjustment correlates of each are to be accurately evaluated. As can be seen in this review, it is extremely difficult to detect distinct effects in individual studies in which proactive and reactive aggression are highly intercorrelated (see also Formula 2, which illustrates the fact that large intercorrelations of these two functions of aggression inflate the denominator of this formula, thus providing smaller effect sizes for the differential effects). Although our metaanalytic review sheds some light on this issue, we expect that larger differentials in the relations of proactive and reactive aggression to adjustment will be evident (and thus detectable in individual studies) if the measures of these functions of aggression are less intercorrelated.

Moderators of associations between functions of aggression and psychosocial functioning There was mixed evidence that the associations of proactive and reactive aggression varied by age and sources of information used to measure aggression. Such results should be interpreted with caution, however, because there were often only a few studies utilizing samples from some ages and/or using certain methods of assessing aggression. Such sparseness of levels of moderators in meta-analytic reviews leaves open the possibility that the moderator effects detected are not due to the presumed moderating variable, but rather other confounded aspects of the studies (Lipsey, 2003). Therefore, the moderator effects found in this review, and the speculative interpretations we offer to account for these, should be interpreted with caution. Age moderation tests indicated a range of significant findings. The magnitude of the relations of proactive aggression with ED/ADHD-type symptoms and low social preference tend to diminish with increasing age, and there is a cross-over effect for the association of proactive aggression


with internalizing problems such that this relation is positive at younger ages and negative during adolescence. Together, these findings indicate that, where age moderation is evident, proactive aggression becomes less maladaptive with increasing age. This conclusion is consistent with other research showing that some adolescents seem to use aggression adaptively (e.g., Hawley, 2003; Hawley, Little, & Pasupathi, 2002) and (more so than among younger children) can be high in social status (Cillessen & Mayeux, 2004; Rose et al., 2004). For five of the eight adjustment indices examined, however, there was no evidence of age moderation; thus the overall relations (i.e., small zero-order and negligible semipartial correlations) of proactive aggression with most indices of adjustment examined in this meta-analysis are generally similar across age. The magnitude of relations of reactive aggression to internalizing problems, low social preference, and victimization also tends to diminish with increasing age, suggesting a similar decline in the relations of reactive aggression with maladjustment with age as was found for proactive aggression. It may be the case that some adolescents develop compensatory mechanisms to minimize the impact of their reactive aggression on their peer relations or, alternatively, to inhibit the tendency to translate poor peer relations into reactively aggressive behavior (note again that this meta-analysis involved concurrent correlations, so directions of influence can not be inferred). We might also speculate that the social cognitions that underlie reactive aggression and internalizing problems become increasingly specific with age, and hence the two are less strongly related with age. We also found, however, that the association between ED/ADHD-type symptoms and reactive aggression increases with age, and the differential relation of reactive versus proactive aggression with these symptoms became greater with age. Thus, with increasing age, ED/ADHD-type symptoms becomes more specifically associated with reactive aggression. Similarly, the differential relation of reactive versus proactive aggression with victimization diminishes with age, indicating greater specificity of the reactive aggression with victimization association during earlier childhood. Consistencies among the aggression-reporter moderation were difficult to identify, though it is worth noting that (a) observations of proactive (but not reactive) aggression are associated with higher levels of prosocial behavior, (b) peer reports of proactive (but not reactive) aggression are associated with higher social preference, and (c) observations most clearly distinguish the differential relations of proactive (negative correlation) and reactive (positive correlation) aggression to peer victimization. Self- and parent-reports of proactive and reactive aggression have been rarely used, so few distinctions by these information sources could be made; one exception is that self-reports of the functions of aggression show the most marked differential relations with ED/ADHDtype symptoms (self-reported proactive is not significantly related, whereas self-reports of reactive aggression has higher associations than from any other information source). Despite these findings, the reliance on teacher reports of proactive and reactive aggression in most studies limits our knowledge about potential reporter moderation, and future work using a variety of information sources is needed. Given the tentative nature of these moderator effects, we believe that the findings of significant age and reporter moderation should be viewed as hypotheses for future primary research, rather than interpreted as conclusive evidence. In

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testing many of these effects, there were limited numbers of studies across the age groups and different reporters. In all meta-analytic work, but especially in this situation of only a few studies at some levels of the moderators, one must be cautious in drawing inferences from these results. As mentioned, when few studies are used to represent a level of the moderator (e.g, early childhood in testing age moderation of associations between aggression and internalizing), it is possible that findings of significant moderation are due not to the presumed moderator, but rather to other qualities of the studies being examined. One possibility is that our tests of age moderation was confounded by reporter, and vice-versa, since observations were more commonly used at earlier ages and peer reports were more often used at older ages (a similar threat is that measures of proactive and reactive aggression via the same reporter vary with age, for example teachers may be less accurate in judging aggression with age due to lesser contact with students in the contexts in which aggression occurs). This age and reporter confound is not the only possible threat, since many other uncoded characteristics of the studies may account for the moderator effects found here. Thus, further primary research, sampling wide age ranges and using multiple reporters to assess proactive and reactive aggression, is needed before questions of age and reporter moderation can be definitively answered.

Limitations of this meta-analysis The lack of studies in several analyses speaks to the more general limitation of this review: meta-analytic techniques must work within the constraints of the existing literature. We noted earlier that a majority of studies used teacher reports to assess proactive and reactive aggression. As a result, effect sizes that would be found if other reporters were more commonly used are largely unknown (i.e., the results reported here are largely descriptive of proactive and reactive aggression when assessed via teacher-reports). We also described the difficulties in identifying distinct adjustment correlates of proactive and reactive aggression given their high intercorrelation. Although the statistical power of our meta-analysis was able to shed some light on this issue, it is necessary for further research with unconfounded measurement practices to be conducted before the full degree of distinction between these relations can be identified. In examining age moderation of several effects, it became apparent that prior research has not sampled an adequately wide range of ages (see Table 2 for specific instances). In addition to age and source of information, other foci for future research on moderator variables are the wide range of personal, social, and contextual factors that might buffer or exacerbate relations of proactive and reactive aggression to maladjustment. One readily available example is gender, as few studies have tested whether the links between different functions of aggression and maladjustment differ among boys and girls. In short, there is an important need for future primary research investigating the correlates of proactive and reactive aggression, and we hope that this review systematically highlights the areas in which further research is needed. It also merits mention that the correlations reviewed in this paper are concurrent, thus inferences regarding directions of effects cannot be made. Although some of the studies included in our review also present longitudinal data (Atkins et al., 2002; Brendgen et al., 2001; Camodeca et al., 2002; Dodge

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et al., 1990, 1997; Frick et al., 2003; Poulin & Boivin, 1999, 2000; Prinstein & Cillessen, 2003; Pulkkinen, 1996; Strassberg et al., 1994; Vitaro et al., 1998, 2002), there are several limitations to this body of research. First, because of the scarcity of longitudinal research, each adjustment correlate that we have considered here is generally examined in only one or two longitudinal studies (if at all), making it difficult to draw conclusions regarding the reliability or magnitude of these longitudinal findings. Relatedly, the existing longitudinal studies vary considerably in terms of ages and time spans under investigation, as well as in their operationalization of constructs, thus drawing into question the extent to which these findings are due to idiosyncrasies of their methodologies. An important methodological limitation that should be corrected in future research is the fact that few of these longitudinal studies adequately control for initial levels of the hypothesized dependent variables, thus precluding conclusions that one variable predicts change in the other over time (rather than just being correlated across the time span under study; for exceptions see Poulin & Boivin, 1999; Prinstein & Cillessen, 2003). Finally, we were not able to locate even one study that tested both directions of effects between these functions of aggression and maladjustment (i.e., whether the correlate predicts change in the functions of aggression and whether the functions of aggression predict change in the correlates). These limitations suggest the need for well-designed longitudinal research (and where possible, experimental research, such as intervention studies aimed at the hypothesized cause) to address questions of temporal precedence in the relations of proactive and reactive aggression to the adjustment correlates examined in the current meta-analysis. These limitations also suggest the ambiguity in directions of effects among the correlations between proactive and reactive aggression and the indexes of maladjustment that were identified in the current meta-analysis.

Conclusions Despite these limitations, this meta-analytic review synthesizes the available empirical data to provide new insight into the relations of proactive and reactive functions of aggression to psychosocial adjustment. The results of this quantitative review indicate that both proactive and reactive aggression are associated with maladjustment, but that reactive aggression is more strongly related to internalizing problems, ED/ADHD-type symptoms, low social preference, peer rejection, and peer victimization than is proactive aggression. This differential relation is not large (and hence, not usually detectable within individual studies) due to the large intercorrelation between proactive and reactive aggression. However, we suspect that the high correlation present in the current literature does not represent the true relation between these constructs. Instead, further research using observational or decomposition techniques (Little et al., 2003) may yield greater differences in these relations than those found in this review. Further research using a wider span of age ranges may also confirm our mixed findings that studies with older samples tended to find smaller relations of proactive and reactive aggression with maladjustment, and studies assessing these functions via multiple sources of information may clarify whether differences in these relations depend on method of assessing aggression. We believe that these recommendations, as well as those described above, will

further illuminate the utility of the proactive versus reactive aggression distinction in future research.

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