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Relation of Measures of Executive Function toAggressive Behavior in ChildrenCynthia A. Riccio a , Lisa Lockwood Hewitt b & Jamilia J. Blake aa Department of Education Psychology, Texas A & M University, College Station, Texasb Fort Worth Independent School District, Fort Worth, TexasVersion of record first published: 04 Mar 2011.

To cite this article: Cynthia A. Riccio , Lisa Lockwood Hewitt & Jamilia J. Blake (2011): Relation of Measures of ExecutiveFunction to Aggressive Behavior in Children, Applied Neuropsychology: Adult, 18:1, 1-10

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Relation of Measures of Executive Function toAggressive Behavior in Children

Cynthia A. Riccio

Department of Education Psychology, Texas A & M University, College Station, Texas

Lisa Lockwood Hewitt

Fort Worth Independent School District, Fort Worth, Texas

Jamilia J. Blake

Department of Education Psychology, Texas A & M University, College Station, Texas

This study investigated the role of executive function in relation to aggression in a sam-ple of children (N¼ 93) aged 9 to 15 years. Based on parent ratings of aggression, thesample was divided into low- (n¼ 66) and high- (n¼ 27) aggression groups. Althoughthe groups did not differ significantly on laboratory measures of executive function,significant differences emerged on behavioral regulation and metacognition ratings byparents. Notably, a high level of behavioral dysregulation was predictive of placementin the high-aggression group; both good metacognitive skills and behavior regulationserved as significant predictors of prosocial and adaptive skills.

Key words: aggression, children, conduct, executive function, parent ratings

Problems of aggression, conduct problems, and anti-social behaviors are continuing concerns for society.Levels of youth violence, in the form of physical fight-ing, bullying, using weapons, making verbal threats,and engaging in impulsive forms of aggression, affectthe safety and well-being of all youth (Rappaport &Thomas, 2004). Behaviors associated with aggressionand conduct problems account for up to one-half ofreferrals to mental health professionals (Kazdin,Esveldt-Dawson, French, & Unis, 1987). Further, exter-nalizing and conduct problems are associated with peerrejection (Coie & Dodge, 1998), poor academic perform-ance and decreased motivation (Bergman &Magnusson,1997), as well as increased risk for school dropout(Ensminger & Slusarcick, 1992; Kokko, Tremblay,Lacourse, Nagin, & Vitaro, 2006). As such, aggression

and conduct problems constitute a significant concern;factors that contribute to or mediate aggression=conduct problems need to be better understood toinform prevention and intervention (Brody et al., 2004).

Multiple pathways and etiologies have been implicatedin the development of aggression, conduct problems, andother antisocial behavior, including biological or physio-logical explanations (e.g., Caspi et al., 2002; Halperinet al., 1997; McBurnett, Lahey, Rathouz, & Loeber,2000; Yehuda, Boisoneau, Lowy, & Giller, 1995), psycho-social explanations specific to home contexts (Loeber,Green, Keenant, & Lahey, 1995; Loeber, Wung, Keenant,& Giroux, 1993), parenting style (e.g., Patterson,DeBaryshe, & Ramsey, 1989), peer relationships (e.g.,Coie & Miller-Johnson, 2001; Thomas, Holzer, & Wall,2003), and social information processing or the socialcognition perspective of the individual (Dodge, Bates, &Petit, 1990; Slaby & Guerra, 1988).

Neuropsychological perspectives of aggression takebiological processes into account, particularly those

Address correspondence to Cynthia A. Riccio, Department of

Educational Psychology, Texas A & M University, TAMU MS4225,

College Station, TX 77843-4225. E-mail: criccio@tamu.edu

APPLIED NEUROPSYCHOLOGY, 18: 1–10, 2011

Copyright # Taylor & Francis Group, LLC

ISSN: 0908-4282 print=1532-4826 online

DOI: 10.1080/09084282.2010.525143

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cognitive processes that may affect information proces-sing and cognitive functioning. From a neuropsycholo-gical perspective, prefrontal dysfunction has beenassociated with antisocial behavior (Davidson, Jackson,& Kalin, 2000; Lapierre, Braun, & Hodgins, 1995).Others agree that individuals with damage to the pre-frontal cortex display ‘‘increased rates of aggressiveand antisocial behavior’’ (Brower & Price, 2001,p. 724); it has been shown that violent offenders demon-strate lower levels of prefrontal activity (Raine, 2002).Further, orbitofrontal damage is associated with socialdisinhibition, shallow affect, decreased empathy, impul-sivity, and antisocial behavior (Cummings, 1993;Grattan, Bloomer, Archambault, & Eslinger, 1994;Martzke, Swan, & Varney, 1991; Stuss, Gow, & Hether-ington, 1992). Conversely, it has been suggested thatappropriate functioning of the frontal lobes gives riseto appropriate social behavior, as well as inhibitionof maladaptive and aggressive behavior (Grigsby &Stevens, 2000).

Integrity of the frontal and prefrontal regions of thebrain is tapped traditionally by executive function tasks.Executive function has been conceptualized from a var-iety of contexts. At the most global level, executive func-tion is composed of those composite psychologicalprocesses necessary for problem solving (Zelazo, Carter,Reznick, & Frye, 1997) and self-regulation (Barkley,2000). Barkley (2000) asserted that executive functionsallow for the developmental shift from external controlsand cues to internal, mental representations and self-control of one’s behavior. Similarly, Denckla (1996)suggested that the development of executive function iswhat differentiates adults from children. Multiple beha-viors are believed to constitute executive function. Thosemost clearly linked to the risk and resiliency factorsof substance use and related disorders include theability to engage in independent, goal-focused behavior(Barkley, 2000; Lezak, 1995), the ability to carry out astrategic and sequential plan of action (Luria, 1966;Zelazo et al., 1997), the ability to plan and self-monitorone’s own behavior (Flavell, 1971; Zelazo et al., 1997),and the ability to inhibit a dominant response or shiftresponse sets (Barkley, 2000).

As part of executive function, self-regulation isintegral to the development of social and academiccompetence (Barkley, 1997; Eisenberg et al., 1997;Kochanska, Murray, & Coy, 1997; Kochanska, Murray,Jacques, Koenig, & Vandegeest, 1996; Kopp, 1989;Olson, 1989); deficits in self-regulation are associatedwith increased risk of aggression, impulsivity, and socialrejection (Calkins, 1994; Campbell, 1995; Hoaken,Shaughnessy, & Pihl, 2003; Olson & Hoza, 1993). Takentogether, impulsivity, low self-regulation, low futureorientation, poor problem-solving skills, poor self-awareness and metacognition, as well as the inability

to delay gratification are risk factors for aggressionand antisocial behavior in children.

EXECUTIVE FUNCTION AND AGGRESSION

Executive function measures have been found helpful inpredicting maladaptive functioning in adolescents. Inparticular, ‘‘the inability to strategically plan and regu-late behavior . . . to reciprocate appropriately . . . to resisttemptation, or to avoid breaking social norms . . . ’’emerge as important risk factors in adolescents (Clarke,Prior, & Kinsella, 2002, p. 792). More specifically, defi-cits in executive functioning are implicated in those indi-viduals who engage in aggressive and other antisocialbehavior (Coolidge, DeBoer, & Segal, 2004; Fishbein,2000; Paschall & Fishbein, 2002). For example, Dinnand Harris (2000) examined executive function in 12males with antisocial personality disorder, ages 19 yearsto 34 years in comparison to 10 male controls aged 21years to 41 years. Across multiple measures, the clinicalgroup demonstrated impairment on measures sensitiveto orbitofrontal dysfunction relative to the controls,specifically on the Stroop test and object alternation test(Dinn & Harris, 2000). In another study, Ready,Stierman, and Paulsen (2001) found that results of theFrontal Lobe Personality Scale (Grace, Stout, &Malloy, 1999) Disinhibition and Executive DysfunctionScales correlated moderately with aggression (r¼ .42and r¼ .32, respectively) as well as with risky behavior(r¼ .32 and r¼ .23, respectively). Other studies havealso indicated high rates of impaired inhibitory controlto be associated with conduct problems (Herba, Tranah,Rubia, & Yule, 2006).

Using parent reporting for neuropsychological func-tioning, Coolidge et al. (2004) found that children intheir bullying group demonstrated significantly moreproblems on scales of executive function deficits, as wellas on the General Neuropsychological Dysfunction andMild Neurocognitive Scales of the Coolidge Personalityand Neuropsychological Inventory for Children(Coolidge, 1998). Within the Executive Function Scale,children in the bully group had difficulties on all threesubscales (decision making, planning; metacognitivedysfunctions; and social misjudgments). In a longitudi-nal study, Giancola and Parker (2001) found that lowexecutive functioning and difficult temperament wereassociated with increased antisocial behavior, whichwas in turn related to increased substance use. Giancola(2000) proposed that executive function both mediatesand moderates the relationship between aggression andalcohol use. Giancola and Mezzich (2000), as well asGiancola, Roth, and Parrott (2006), further argued thatexecutive function mediates aggressive behavior, parti-cularly for those individuals with difficult temperament.

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Santor, Ingram, and Kusumaker (2003) concludedthat for those individuals with impaired executive func-tion, there was a greater likelihood of impulsive andaggressive responses to provocation. Aggressive indivi-duals have been found to have higher levels of impulsiv-ity and to evidence deficits in executive functiondomains even when the presence of another disorderhas been taken into consideration (e.g., Hoaken et al.,2003; Seguin, Boulerice, Harden, Tremblay, & Pihl,1999). Although deficits in executive function have beenidentified as risk factors for aggression and antisocialbehaviors, it is not clear if their effect is direct or ifthe deficits mediate other factors that lead to these samebehaviors (Brower & Price, 2001). Environmentalfactors, for example, likely interact with deficits in pre-cortical functioning to produce antisocial behavior(Raine, 2002). Genetic predisposition to aggression isalso considered a factor (see DiLalla, 2002, for areview).

PURPOSE OF THIS STUDY

Recently, the construct of executive function, includingthe higher-order cognitive processes involved in plan-ning and problem solving, has taken on more impor-tance in the clinical and research domains. There is agrowing body of literature about the relation betweenexecutive function and the occurrence of aggression inchildren and youth; however, new rating scales havebeen developed and have not been incorporated into thisresearch as yet. Further, less research has examinedexecutive function processes and adaptive (prosocial)behavior, despite potential links between the develop-ment of prosocial and antisocial behaviors (Caprara,Barbaranelli, & Pastorelli, 2001). The purpose of thisstudy was to investigate the linkage of executive func-tion to aggression and antisocial behavior to determinethe extent to which differing measures would be sensitiveto and predictive of inappropriate and antisocial beha-vior. In addition, relations of various measures of execu-tive function to adaptive (prosocial) behaviors wereinvestigated. Finally, a strength of the current studyis the incorporation of both traditional measures ofexecutive functioning and questionnaire-based measuresof executive function as recommended by others in thefield (Nigg, 2000).

METHOD

Participants

Participants were children (aged 9 to 15 years) who wereconsecutive referrals to the Memory, Attention, and

Planning Study. Data used in this analysis are part ofa larger, university-based research study in the South-western United States. The overall study was designedto investigate attention, memory, problem-solving, andplanning skills in children with and without attention-deficit hyperactivity disorder (ADHD). Participantswere recruited through the use of announcements dis-tributed in the local community to physicians, localschools, a community-based counseling center, on localbulletin boards, and in the local newspaper. Theannouncement indicated that the research study focusedon memory, attention, and planning=problem solving.Participation was voluntary with consent obtained fromthe parent and assent obtained from each participant.For inclusion in this study, children had to obtain anIQ greater than or equal to 80, and they had to speakand read English. Prior to the start of the project, pre-vious diagnosis of schizophrenia or history of severehead injury were established as exclusionary criteria.

The participants in this study included 93 childrenwho were a mean age of 11.74 years (SD¼ 2.07); agesranged from 9.0 years to 15.92 years. For the total sam-ple, 63 (67.74%) were male and 30 (32.36%) were female.Of these, 74 (79.57%) were White non-Hispanic, 11(11.83%) were African American, 7 (7.53%) were Hispa-nic English speaking, and 1 (1.08%) was Asian Ameri-can; ethnicity was based on parent report. Based ondiagnostic considerations, 41 (44.09%) met criteria forADHD, with twice as many meeting criteria for com-bined type as compared with predominantly inattentive.In addition, 26 (27.96%) met criteria for some otherdisorder but not ADHD (e.g., depression, learningdisability, some type of anxiety disorder), and 26(27.96%) did not meet criteria for any disorder. Fourof the participants did meet criteria for diagnosis ofoppositional defiant disorder, 3 in conjunction withADHD. Because of the limited number of individualswithin each diagnostic group, analyses were not conduc-ted by individual groups.

Information on parent educational level indicatesthat despite a range from seventh grade to medical=legaldegree (16þ years), for the majority of participants, atleast one parent had completed some college(M¼ 14.51 years of education; SD¼ 1.86). The averagecognitive ability of the sample was within the averagerange (Mean Full-Scale IQ¼ 102.19; SD¼ 12.45). Simi-larly, achievement of the sample was within the averagerange (Mean Total Achievement from the Woodcock-Johnson III¼ 98.95; SD¼ 14.10).

Based on parent ratings of aggression, the sample wassplit into two groups — high aggression (n¼ 27) and lowaggression (n¼ 66). Assignment into these groups wasbased on children’s score on the Aggression Scale ofthe Behavior Assessment System for Children (BASC;Reynolds & Kamphaus, 1992). On this measure, a

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T-score of 60 or above is at least one standard deviationabove the mean, corresponds to a percentile score of 86,and indicates ‘‘at-risk’’ or ‘‘clinically significant’’ levels.Demographics and descriptive data by the high- andlow-aggression groups are provided in Table 1 Groupsdiffered on parent educational level (p¼ .03) such thatthe highest grade completed by parents of children inthe high-aggression group was lower than that ofchildren in the low-aggression group. Similarly, groupsdiffered on Full-Scale IQ (p¼ .01) such that thehigh-aggression group obtained a lower Full-Scale IQscore than the low-aggression group. Notably, equalproportions of males and females were in the high-and low-aggression groups (35% and 34.8% female,respectively).

Procedures

All individuals participated in a comprehensive assess-ment including assessment of cognition, achievement,language, memory, executive function, attention, andbehavioral=emotional status in a clinic setting. Alicensed psychologist or advanced doctoral studentssupervised by a licensed psychologist administered all

measures consistent with standardization.Measures wereadministered in a random order. Test sessions varied inlength based on the individual being assessed. Parentsreceived a copy of the report of their child’s results.

Instruments

Wechsler Intelligence Scale for Children–ThirdEdition (WISC-III; Wechsler, 1991). The WISC-III isthe most frequently used measure of cognitive abilityfor child populations. All subtests required for compu-tation of the factor scores were administered. TheFull-Scale IQ was of interest here for exclusion anddescriptive purposes only.

Woodcock-Johnson Tests of Achievement–ThirdEdition (WJ-III; Woodcock, McGrew, & Mather,2001). The WJ-III is one of the most frequently usedmeasures of achievement in psychological practice.The standard battery of achievement tests was adminis-tered to all participants; the Total Achievement scoreresulting from the battery is reported here for descriptivepurposes only.

TABLE 1

Demographic Data for the Low-Aggression and High-Aggression Groups

Variable Low-Aggression Group (n¼ 66) High-Aggression Group (n¼ 27)

Gender

Male 43 20

Female 23 7

Ethnicity

White, non-Hispanic 51 23

Black 9 2

Hispanic 5 2

Asian American 1 0

Handedness

Right 57 25

Left 9 2

Diagnostic Status

No Diagnosis 25 1

ADHD 28 13

Other Psychiatric, but not ADHD 13 13

Ever Retained in Grade (Yes) 11 7

In Special Education (Yes) 3 3

Mean (SD) F p Eta2

Age (years) 11.68 (2.06) 11.88 (2.10) 0.182 .67 .002

Grade Level 5.78 (2.23) 5.86 (2.07) 0.114 .74 .001

Highest Grade Completed by Parent (number of years) 15.35 (2.36) 14.15 (2.18) 5.218 .025 .055

Full-Scale IQ 104.24 (13.08) 97.19 (9.21) 6.522 .012 .067

Total Achievement 99.55 (14.77) 97.42 (12.40) 0.421 .518 .005

BASC Parent-Rating Scale – Aggression 48.80 (7.75) 70.48 (9.69) 129.023 <.001 .586

BASC Parent-Rating Scale – Conduct Problems 50.64 (12.13) 70.30 (14.93) 43.863 <.001 .325

BASC Teacher-Rating Scale – Aggression (n¼ 65) 48.05 (6.37) 65.13 (12.07) 52.716 <.001 .456

BASC Teacher-Rating Scale – Conduct Problems (n¼ 65) 47.32 (8.90) 56.36 (12.52) 9.352 .003 .131

Note. ADHD¼ attention-deficit hyperactivity disorder; BASC¼Behavior Assessment System for Children.

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Behavior Assessment System for Children(Reynolds & Kamphaus, 1992). The BASC is a multi-component system for use with children and youth thatmeasures both problematic and adaptive behavior inchildren. Varying forms allow for input from parents,teachers, and the child (self-report). For purposes of thisstudy, the Parent-Rating Scale (PRS), and when feasible,the Teacher-Rating Scale (TRS), were completed for allparticipants. In many cases, either the parents did notconsent to teachers completing the forms, the teachersdid not return the forms, or the child was home-schooled;as a result, teacher data were only available for 65 parti-cipants. For this reason, the PRS, available for all parti-cipants, was used for group assignment. Results of theBASC PRS and TRS Aggression and Conduct ProblemsScales by group are provided in Table 1.

Children’s Memory Scale (CMS; Cohen, 1997). Allparticipants were administered the subtests of the CMSneeded for computation of the core scales. Minimalresearch is available on the CMS; however, validityand reliability evidence are adequate. The Attention=Concentration Scale was of interest for this study.

Wisconsin Card-Sorting Test (WCST; Heaton,1981, 1999; Heaton, Chelune, Talley, Kay, & Curtiss,1993). Manual card administration of the WCST withsix-category or 128-card limit was used in this study.Scoring was completed using the scoring program (Hea-ton et al., 1993) to ensure consistency. Variables of inter-est included Categories Obtained, Failure to MaintainSet, and Perseverative Responses based on extant litera-ture (e.g., Romine et al., 2004). Although this task hasbeen criticized by some for failing to differentiatebetween different underlying disorders (Zelazo et al.,1997), it is widely used and has merit as a measure ofseveral aspects of executive function.

Tower of London–Drexel Edition (TOLDX; Culbertson& Zillmer, 2000). All items were administered. Based onexisting research, number of items solved in the mini-mum number of moves (number correct), total numberof moves, initiation time, and rule violations were thevariables of interest.

Verbal fluency. Verbal fluency is considered a criti-cal measure of executive function (Denckla, 1996). TheF-A-S version of the task was used. The total numberof words generated was the variable of interest.

Trail-Making Test (TMT; Reitan & Wolfson,1985). Participants were administered both the TMT-A

and TMT-B. Time on TMT-A is generally considered anattentional baseline, while time on TMT-B was of inter-est as a measure of set shifting.

Conners’s Continuous Performance Test–II(Conners, 1995). The standard parameters were used;the examiner remained in the room during the taskadministration. Previous studies using continuous per-formance tests have yielded significant group differenceson omission errors and commission errors (e.g., Gansleret al., 1998; Seidman, Biederman, Weber, Hatch, & Far-aone, 1998; Walker, Shores, Trollor, Lee, & Sachdev,2000; Weyandt, Mitzlaff, & Thomas, 2002). Also basedon existing research (e.g., Holdnack, Moberg, Arnold,Gur, & Gur, 1995; Murphy, 2002; Seidman et al.,1998), hit reaction time, reflecting speed and mainte-nance of response, was of interest, as was variability ofresponding.

The Behavior-Rating Inventory of Executive Func-tion (BRIEF; Gioia, Isquith, Guy, & Kenworthy,2000). BRIEF is a measure designed to assess beha-viors related to executive function across home andschool environments. It consists of a questionnaire com-pleted by parents or teachers to reflect the frequencywith which a child aged 5 to 18 years exhibits certainbehaviors. The BRIEF yields eight specific scales andtwo global scales. For this study, the two global scales,Metacognitive Index and Behavioral Self-Regulation,were of interest. In standardization of the BRIEF, sig-nificant differences were found between results fromthe parent and teacher scales; the test authors postulatedthat this difference was due to the distinct environmentsof home and school. In this study, both parent andteacher reports were examined.

RESULTS

Data Preparation and Screening

Because multivariate techniques assume multivariatenormal distributions and would be sensitive to extremeoutliers, the procedures used by Kline (1998) were usedfor data trimming=screening. For each variable, anyobservations with values that exceeded three standarddeviations from the mean were set to values that werethree standard deviations from the mean. This is a fairlyconservative trimming procedure that retains extremevariations but limits adverse effects on the distributionor undue influence on the covariances. Of the variablesof interest, this trimming procedure only affected threescores of 18 variables across 93 cases (0.002%). Toensure univariate normality, skewness and kurtosis for

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each variable were calculated. Absolute values of theunivariate skew indexes greater than 3.0 were consideredas extremely skewed; absolute values of the univariatekurtosis index greater than 8.0 were considered asindicating extreme kurtosis (Kline, 1998). Based onthese criteria, all variables met assumptions with amaximum absolute value of 1.92 for skewness and 3.69for kurtosis.

Group Comparison

The high- and low-aggression groups were compared ona number of variables believed to reflect attention, plan-ning, and problem solving as described earlier usingmultivariate analysis of variance. Wilks’s Lambda wassignificant (F(1, 92)¼ 2.85, p¼ .001). Group data andunivariate results are presented in Table 2. Results indi-cated that groups differed significantly only on theParent BRIEF Metacognitive Index and BehavioralRegulation Index. No significant group differencesemerged on variables derived from the CMS, WCST,TMT, Verbal Fluency, or TOLDX.

Logistic Regression Analysis

Logistic regression analysis was conducted to examinewhether executive function predicted the likelihood thatchildren would engage in low or high levels ofaggression. High- and low-aggression groups wererecoded to represent binary outcomes, with the low-aggression group coded as 0 and high-aggression groupcoded as 1. A direct logistic regression was conductedin which eight executive function predictors measuring

attention, planning, and problem solving were enteredsimultaneously into the model.

To determine whether the predictors as a whole con-tributed to the prediction of children’s aggression level,a likelihood ratio test comparing the constant-onlymodel to the full model was conducted. The likelihoodratio test was statistically significant, v2(8)¼ 41.76,p¼ .000, indicating that the combined predictors dis-tinguished between children with low and high levelsof aggression. The overall success rate for executivefunctioning variables in predicting classification of chil-dren into low- and high-aggressive groups was 84.9%.Specifically, executive functioning correctly predicted93.9% of low-aggressive children and 63% of high-aggressive children. These results suggest that as a wholeexecutive functioning reliably predicts aggression levelin children; however, an examination of Wald statisticsfor individual predictors revealed that only BehavioralSelf-Regulation reliably predicted children’s level ofaggression, v2(1)¼ 13.90, p¼ .000. Results suggest thatchildren who exhibit elevated levels of behavioral dysre-gulation are more likely to exhibit high levels ofaggression. Specifically, the odds of exhibiting highlevels of aggression are 14% greater among childrenwho have difficulty regulating their behavior as com-pared with children who are able to self-regulate.Regression coefficients and odds ratios are presentedin Table 3.

Regression Analyses

It was further predicted that children who were rated ashaving impaired behavioral regulation would evidence

TABLE 2

Executive Function Tasks (MANOVA)

Variable Low Aggression (n¼ 66) High Aggression (n¼ 27) F p Eta2

CMS Attention=Concentration 96.52 (15.15) 94.56 (14.30) 0.33 .57 .004

WCST Perseverative Errors 109.08 (16.46) 106.26 (15.08) 0.59 .44 .006

WCST Categories Obtained 102.74 (15.59) 103.16 (13.86) 0.02 .90 <.001

WCST Failure to Maintain 103.74 (13.23) 99.78 (13.86) 1.68 .20 .018

TOLDX Initiation Time 97.00 (10.82) 95.78 (11.32) 0.24 .63 .003

TOLDX Moves 96.55 (14.33) 95.78 (14.02) 0.06 .81 .001

TOLDX Correct 97.36 (12.82) 93.19 (10.56) 2.24 .14 .024

TOLDX Rule Violations 84.85 (19.69) 82.67 (22.25) 0.22 .64 .002

TMT-A Time 17.06 (7.59) 15.04 (5.76) 1.55 .22 .017

TMT-B Time 40.65 (18.42) 35.78 (19.93) 1.28 .26 .014

Verbal Fluency 26.62 (9.90) 24.37 (8.72) 1.06 .31 .011

CCPT Omission Errors 51.16 (9.39) 52.97 (13.82) 0.53 .47 .006

CCPT Commission Errors 49.53 (11.31) 47.26 (12.29) 0.73 .39 .008

CCPT Hit Reaction Time 50.49 (11.34) 53.31 (11.30) 1.18 .28 .013

CCPT Variability 52.63 (9.01) 54.87 (12.29) 0.95 .33 .010

BRIEF Behavioral Regulation Index 54.61 (12.38) 74.56 (13.20) 47.90 <.001 .345

BRIEF Metacognitive Index 60.18 (12.46) 70.59 (8.64) 15.72 <.001 .147

Note. BRIEF¼Behavior-Rating Inventory of Executive Function (parent version); CCPT¼Conners’s Continuous Performance Test–II;

CMS¼Children’s Memory Scale; TMT¼Trail-Making Test; TOLDX¼Tower of London–Drexel Edition; WCST¼Wisconsin Card-Sorting Test.

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lower levels of prosocial and adaptive behavior, whilechildren rated as having better metacognitive abilities(higher scores on the Metacognitive Scale) would evi-dence higher (better) levels of prosocial and adaptivebehavior. It was anticipated that these patterns wouldbe evident in both home and school settings. Multipleregression, with the two BRIEF scales, was used todetermine the extent to which these scales predictedadaptive skills as rated by the parent (see Table 4).The adjusted R2 yielded was .47 (p< .001). BothBehavioral Regulation (p¼ .001) and Metacognition(p¼ .005) emerged as significant predictors of parent-rated adaptive skills. Multiple regression, with the twoBRIEF scales, was used to determine the extent to whichthese scales predicted adaptive skills as rated by the

teacher (see Table 5). The adjusted R2 yielded was .22(p< .001). Metacognition emerged as the significant pre-dictor of teacher-rated adaptive skills.

DISCUSSION

The current study comes from a larger study designed toexamine aspects of executive function in depth. The datacontained in this article are specific to the relationbetween executive function and aggressive and antisocialbehavior in children and youth. Executive function wasassessed through various laboratory measures tradition-ally used to assess executive function, as well as by par-ent ratings on a recently developed rating scale ofexecutive functions. Not surprisingly, given the frequentfindings that laboratory results do not often match withdata obtained from raters (Gioia, Isquith, & Kenealy,2008; Matier-Sharma, Perachio, Newcorn, Sharma, &Halperin, 1995; Price, Joschko, & Kerns, 2003; Vriezen& Pigott, 2002; Wood & Liosi, 2006), traditional labora-tory measures did not significantly predict whether achild exhibited low or high levels of aggression. Thesedifferences may be related to the distinction now beingmade between cognitive, or ‘‘cool,’’ aspects and thoseinvolving more affective, or ‘‘hot,’’ aspects of executivefunction (Zelazo & Muller, 2002). In particular, the lab-oratory measures may be tapping the cognitive aspects,while the rating scales may be more sensitive to theaffective aspects. Alternatively, the differences mayreflect the structured and short nature of most of thesetasks in contrast to everyday contexts. These resultsfurther underscore the need for multimethod and multi-source assessment that considers how the child behavesin the real-world setting. In effect, not obtaining mea-sures of everyday functioning could result in a failureto identify a problem that exists in real-world settings.Finally, the small sample size of the high-aggressiongroup may have contributed to the finding of nodifference.

The fact that some of the children in both groupswere diagnosed with disorders believed to include someexecutive function deficits may have contributed furtherto the lack of significant differences as well. Notably, theParent BRIEF Behavioral Self-Regulation Index signifi-cantly predicted membership in the high-aggressiongroup. With increased emphasis on positive behaviorsand resiliency, regression analyses also were conductedwith parent- and teacher-reported adaptive skills as thedependent variable. For adaptive skills (e.g., leadership,social skills), both behavioral regulation and metacogni-tion were predictors for parent-rated adaptive skills;only metacognition predicted teacher-adaptive skills.These findings will need to be replicated with a largersample.

TABLE 3

Executive Function Predicting Aggression Level (Logistic

Regression)

Variables b Wald v2 test OR 95% CI

CCPT Hit Reaction

Time

�.01 0.05 0.99 0.94, 1.05

Verbal Fluency �.01 0.02 0.99 0.92, 1.07

TMT-A Time �.03 0.27 0.97 0.87, 1.08

TMT-B Time �.02 1.87 0.98 0.94, 1.01

TOLDX correct SS �.03 0.79 0.97 0.91, 1.03

WCST Failure to

Maintain

�.02 1.02 0.98 0.94, 1.02

BRIEF Behavioral

Regulation Index

.13�� 13.90 1.14 1.07, 1.22

BRIEF Metacognitive

Index

�.03 0.50 0.97 0.90, 1.05

Constant �.89 0.04 0.41

Note. BRIEF¼Behavior-Rating Inventory of Executive Function

(parent version); CCPT¼Conners’s Continuous Performance Test–

II; OR¼odds ratio; TMT¼Trail-Making Test; TOLDX¼Tower of

London–Drexel Edition; WCST¼Wisconsin Card-Sorting Test.��p< .001.

TABLE 4

Regression for Parent-Rated Adaptive Behavior

B SE B b

BRIEF Behavioral Regulation �.259 .079 �.394

BRIEF Metacognition �.282 .099 �.342

Note. R2¼ .48; Adjusted R2¼ .47; BRIEF¼Behavior-Rating

Inventory of Executive Function.

TABLE 5

Regression for Teacher-Rated Adaptive Behavior

B SE B b

BRIEF Behavioral Regulation �.046 .135 �.062

BRIEF Metacognition �.386 .157 �.448

Note. R2¼ .25; Adjusted R2¼ .22; BRIEF¼Behavior-Rating

Inventory of Executive Function.

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There is a growing body of literature that suggests asignificant association between deficits in those cognitiveprocesses often referred to as executive functions andaggressive or antisocial behavior (Giancola, 2000;Moffitt, 1993; Morgan & Lilienfeld, 2000). Under-standing the relationship between social informationprocessing and executive cognitive functions with mala-daptive behaviors associated with aggression andconduct problems can be helpful in the design of preven-tion and intervention programs. As with the existingliterature, the results of this study support continuedinvestigation into those cognitive (executive) processesthat may underlie maladaptive behaviors, such asaggression and antisocial behaviors, as well as adaptivebehaviors. A larger-scale study with longitudinal com-ponents to address developmental trajectories andchanges in skill levels across the life span is needed.Clearly, some of the measures traditionally used in neu-ropsychological assessment may not be as sensitive tosubtle deficits, and future studies need to incorporatemultiple perspectives and multiple methods. Alternatemeasures of problem solving and planning, strategyuse, and consideration of future consequences may beneeded to best identify those deficient cognitive pro-cesses that lead to increased risk. Once identified, target-ing these Origins and outcomes of individual differencesin emotion deficient processes may provide a frameworkfor intervention and prevention programming.

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