1014_R interventie pe agresivitate.pdf

8/10/2019 1014_R interventie pe agresivitate.pdf

1/40

Campbell Systematic Reviews2006:6First published: 16 March, 2006Last updated: 16 March, 2006

The Effects of School-BasedSocial InformationProcessing Interventions on

Aggressive Behavior, Part II:Selected/Indicated Pull-OutPrograms

Sandra Jo Wilson, Mark W. Lipsey


2/40

Colophon

Title The effects of school-based social information processing interventions on

aggressive behavior, part II: Selected/Indicated Pull-out Programs

Institution The Campbell Collaboration

Authors Wilson, Sandra Jo

Lipsey, Mark W.

DOI 10.4073/csr.2006.6

No. of pages 37

Last updated 16 March, 2006

Citation Wilson SJ, Lipsey M. The effects of school-based social information

processing interventions on aggressive behavior, part II: Selected/Indicated

Pull-out Programs.

Campbell Systematic Reviews 2006:6

DOI: 10.4073/csr.2006.6

Copyright Wilson et al.

This is an open-access article distributed under the terms of the Creative

Commons Attribution License, which permits unrestricted use, distribution,

and reproduction in any medium, provided the original author and source are

credited.

Keywords

Contributions None stated.

Support/Funding The National Institute of Mental Health, USA

The National Institute of Justice, USA

William T. Grant Foundation, USA

Laboratory for Student Success, Center for Research in Human Development

and Education, Temple University USA

Potential Conflicts

of Interest

None.

Corresponding

author

Sandra Jo Wilson

Center for Evaluation Research and Methodology

Vanderbilt Institute for Public Policy Studies

Vanderbilt University


3/40

Campbell Systematic Reviews

Editors-in-Chief Mark W. Lipsey, Vanderbilt University, USA

Arild Bjrndal, Norwegian Knowledge Centre for the Health Services &

University of Oslo, Norway

Editors

Crime and Justice David B. Wilson, George Mason University, USA

Education Chad Nye, University of Central Florida, USA

Ralf Schlosser, Northeastern University, USA

Social Welfare Julia Littell, Bryn Mawr College, USA

Geraldine Macdonald, Queens University, UK & Cochrane Developmental,

Psychosocial and Learning Problems Group

Managing Editor Karianne Thune Hammerstrm, The Campbell Collaboration

Editorial Board Crime and Justice David Weisburd, Hebrew University, Israel & George Mason University, USA

Peter Grabosky, Australian National University, Australia

Education Carole Torgerson, University of York, UK

Social Welfare Aron Shlonsky, University of Toronto, Canada

Methods Therese Pigott, Loyola University, USA

Peter Tugwell, University of Ottawa, Canada

The Campbell Collaboration (C2) was founded on the principle that

systematic reviews on the effects of interventions will inform and help

improve policy and services. C2 offers editorial and methodological support to

review authors throughout the process of producing a systematic review. A

number of C2's editors, librarians, methodologists and external peer-

reviewers contribute.

The Campbell Collaboration

P.O. Box 7004 St. Olavs plass

0130 Oslo, Norway

www.campbellcollaboration.org


4/40

Selected/Indicated Social Information Processing Programs 1

The Effects of School-based Social Information Processing

Interventions on Aggressive Behavior:

Part II: Selected/Indicated Pull-out Programs

March 13, 2006__________

Reviewers

Sandra Jo Wilson and Mark W. Lipsey

Center for Evaluation Research and MethodologyVanderbilt Institute for Public Policy Studies

1207 18thAve. SouthNashville, TN 37212 USA

Tel: 615-343-7215Fax: 615-322-8081

Email: [email protected]


5/40


ContentsBackground for the Review.................................................................. 5

Social Information Processing................................................................ 5

Social Information Processing Programs ............................................... 6

What Social Information Processing Program are Not ........................... 7

Selected and Indicated Prevention ......................................................... 7

Prior Research on Social Skills Interventions.........................................8

Objective of the Review ...............................................................8

Methods of the Review ................................................................8

Criteria for Including Studies in the Review ...........................................8

Interventions...................................................................................8

Settings and Subjects....................................................................... 9

Outcomes ........................................................................................ 9

Study Design.................................................................................... 9

Search Strategy and Identification of Studies ......................................... 9

Selection of Studies ............................................................................... 11

Data Management and Extraction ........................................................ 12

Statistical Procedures........................................................................... 12

Findings.....................................................................................13

Description of Eligible Studies...............................................................13

Mean Effects of Universal Social Information Processing Programs..... 16

Analysis of Moderator Effects............................................................... 18

The Relationship of Method to Effect Size...................................... 18

The Relationship of Other Study Characteristics to Effect Size....... 19

Moderators of Observed Effects..................................................... 22

Conclusions .............................................................................. 23


6/40


List of Tables

Table 1: Characteristics of Studies............................................................. 14

Table 2: Zero-order Correlations between Study Method Characteristicsand Aggressive Behavior Effect Sizes ........................................................ 19

Table 3: Relationships between Study Characteristics and AggressiveBehavior Effect Sizes with Method Variables Controlled ........................... 21

Table 4: Regression Model for Effect Size Moderators for Selected andIndicated Social Information Processing Programs .................................. 22

Table A1: Method Variables by Study......................................................... 32

Table A2: General Characteristics and Subject Variables by Study ............ 34

Table A3: Treatment Characteristics by Study........................................... 36


7/40


List of Figures

Post-treatment Effect Sizes and Confidence Intervals for Aggressive andDisruptive Behavior Outcomes ..................................................................17


8/40


Background for the Review

While the primary role of schools is to provide academic instruction, they are also one ofthe primary institutions through which we socialize our children. One aspect of thissocializing role involves the prevention of aggressive or violent behavior. Over 75% ofU.S. schools use some sort of prevention curriculum to deal with behavior problems;and many schools use more than one prevention strategy (Gottfredson, Gottfredson,Czeh, Cantor, Crosse, & Hantman, 2000). Most school-based prevention programs areuniversal programs. That is, they are implemented on a school-wide basis or deliveredto entire classes of students regardless of the risk status of the student participants. In

addition to these universal efforts, schools often intervene with individual students whoare aggressive or violent or they target at-risk students for special prevention efforts.These types of interventions for specially selected students are called selected orindicated prevention programs (Mrazek & Haggerty, 1994).

Selected and indicated prevention involves targeting prevention efforts on particularstudents. Selected interventions are delivered to students who are specially selected fortreatment by virtue of the presence of some risk factor (such as activity level) that is

thought to be associated with later violent or aggressive behavior. Indicatedinterventions also involve targeting for certain students, but focus on children who arealready exhibiting the targeted behavior (e.g., aggression, violence). Most of theseprograms are delivered to the selected children outside of their regular classrooms (andmay use either group or individual formats).

There are many prevention strategies from which school administrators might choosefor at-risk or problem behavior students (see, for example, Gottfredson, et al., 2000).One set of overlapping strategies used in school settings focuses on students socialinformation processing difficulties. This review examines studies of the effectiveness ofprograms aimed at improving social information processing for reducing aggressivebehavior. The following section will briefly review the social information processingframework and describe the programs that fall under this framework.

Social Information Processing

The programs included in this systematic review all attempt to improve one or moreaspects of students social information processing. Under this intervention model, socialbehavior is the result of six interrelated steps: (1) encoding situational and internal cues,(2) interpretation of cues, (3) selecting or clarifying a goal, (4) generating or accessingpossible responses, (5) choosing a response, (6) and behavioral enactment (Dodge;1986; Crick & Dodge 1994) Negative social behavior such as aggression is thought to be


9/40


social information processing (Dodge, Pettit, McClaskey, & Brown, 1986; Kendall, 1995).To illustrate, deficits at the encoding or interpretation stage of processing may involve

misinterpreting as hostile the intent of others in neutral or ambiguous social situations.Hostile misattributions have been linked to aggressive responses (Crick & Dodge, 1994).And, aggressive children are more likely to make hostile attributions than their non-aggressive peers (Slaby & Guerra, 1988). Deficits at the goal selection or clarificationstage can result in the selection of antisocial rather than prosocial goals (Asher &Renshaw, 1981; Crick & Dodge, 1989). Children who have difficulty accessing orevaluating responses to social situations (Steps 4 and 5) tend to have fewer responsesfrom which to choose in social situations and may fail to evaluate the consequences of

particular behaviors (e.g., Mize & Cox, 1990; Spivack & Shure, 1974).

Social Information Processing Programs

Some of the earliest programs designed to address social information processing deficitswere the social problem solving programs developed in the 1970s (e.g., DZurilla &Goldfried, 1971; Shure & Spivack, 1972; 1979). These programs were designed toimprove social behavior by teaching cognitively-based problem solving skills. For

example, theI Can Problem Solveprogram (Shure, 1992) involves teaching participantsa series of problem solving skills that includes perspective taking, alternative responsegeneration, consequential or means-ends thinking, and causal thinking.

In more recent years, many variations on this theme have been developed (Coleman,Wheeler, & Webber, 1993). Attribution retraining programs, such as HudleysBrainPower(Hudley, 1991) program, focus on the early stages of the social informationprocessing model and teach children to accurately detect intentionality, to make

nonhostile attributions when social encounters are ambiguous, and to generateappropriate behavioral responses to ambiguous negative situations. LochmansAngerCopingprogram (Lochman, Lampron, Burch, & Curry, 1985) includes a module thathelps children learn cognitive goal-setting skills, a social problem solving component,and a module on anger control (which focuses on the emotional aspects of socialinformation processing).

While these are examples of some typical social information processing programs, a

conceptual definition of the programs in general is necessary for conducting theproposed systematic review. This definition aids in identifying candidate programs forthe review and in coding the particular treatment components of each program. Forpurposes of this review, therefore, a social information processing program is one withthe following distinct characteristics:

1 The program involves training in one or more of the social information


10/40


What Social Information Processing Programs are Not

Another set of popular programming strategies also focuses on social competence. Theseprograms, often called by the generic term behavioral social skills, are distinct from thesocial information processing programs that are the focus of this review. Behavioralsocial skills curricula focus primarily on the social (or antisocial) behaviors themselves,rather than the underlying cognitive thought processes. These programs generally teachspecific skills such as making eye contact, smiling in context, paying compliments,communication skills, group entry skills, assertiveness, and the like (see Goldstein &Pentz, 1984 for a review).

In addition, there are other cognitively-oriented programs that do not specifically targetsocial information processing. For example, programs for children with attention oractivity level difficulties often involve teaching skills for cognitive impulse control.Similarly, there are cognitively oriented programs for dealing with stress, divorce,depression, etc. (e.g., Alpert-Gillis, Pedro-Carroll, & Cowen, 1987; Lewinsohn, Clarke,Hops, & Andrews, 1990). While these other cognitive programs focus on thinking skills,they do not have the focus on interpersonal relationships that is characteristic of social

information processing programs.

Selected and Indicated Prevention

Programs that address social information processing difficulties tend to be structuredand have detailed lesson plans, which make them attractive to schools. These programsare also easily delivered by teachers or school psychologists and can be used in differentformats (group or individual) and settings (classrooms or out-of-class school facilities).

Our original intent for this systematic review was to include all research studies of socialinformation processing programs delivered in school settings. As we began collectingthe relevant research literature, however, we discovered that the programs weredelivered using several different approaches to prevention. In particular, socialinformation processing programs are sometimes delivered universally to all studentsand, other times, only to specially selected at-risk or behavior problem students. That is,social information processing programs can be universal, selected, or indicated(Mrazek& Haggerty, 1994). Universal prevention interventions are delivered in classroom

settings to an entire classroom without regard to the risk level or degree of behaviorproblems among students in the classroom. Selected and indicated preventioninterventions target children who are exhibiting risk factors (such as anger orhyperactivity) or children who are already showing early signs of disorder (i.e., behaviorproblems). The studies of social information processing programs that focus onuniversal prevention of course tend to have different student subjects than studies of


11/40


might be associated with study outcomes, we elected to conduct two separate systematicreviews. The review presented here focuses solely on selected and indicated social

information processing programs delivered in school settings. A second review focuseson school-based universal social information processing programs (Wilson & Lipsey,forthcoming).

Prior Research on Social Skills Interventions

Several recent narrative reviews of social skills interventions are available (Clayton,Ballif-Spanvill, & Hunsaker, 2001; Howard, Flora, & Griffin, 1999; Moote, Smyth, &

Wodarski, 1999; Nangle, Erdley, Carpenter, & Newman, 2002) but these cover socialskills interventions quite broadly by including training in social skills, friendship makingskills, communication skills, and other such social behaviors without an explicit focus onaltering cognitive and social information processing deficits. A few narrative reviews ofprograms specific to social information processing have also been conducted (e.g.,Coleman, Wheeler, & Webber, 1993; Pellegrini & Urbain, 1985), but these are somewhatdated and also include programs delivered to clinical populations in non-school settings.Several meta-analysis of related interventions are available (e.g., Beelmann, Pfingsten, &

Lsel, 1994; Denham & Almeida, 1987; Lsel & Beelmann, 2003; Mytton, DiGuiseppi,Gough, Taylor, & Logan, 2002; Quinn, Kavale, Mathur, Rutherford, & Forness, 1999;Schneider & Byrne, 1985). Like the narrative reviews, but with the exception of Denhamand Almeida (1987), these syntheses focus on social competence programs in generaland thus include both social information processing and behavioral social skillsprograms. The Denham and Almeida meta-analysis focuses exclusively on interpersonalcognitive problem solving interventions, but is 15 years old and does not includeinternational studies.

Objective of the Review

This review examines the effects of school-based social information processinginterventions on the aggressive and disruptive behavior of school-age childrenspecifically targeted for attention because they are judged to be at risk for such behavior(selected) or already engaged in early versions of such behavior (indicated). Programeffects are examined overall and in relation to methodological and substantivedifferences across studies.

Methods of the Review

Criteria for Including Studies in the Review


12/40


or clarifying a goal, (4) generating or accessing possible responses, (5) choosing aresponse, (6) and behavioral enactment.

2.

Cognitive skills or thinking processes were emphasized rather than specificbehavioral skills.3. Structured tasks and activities were used to teach cognitive skills and their

application to actual social situations.

Settings and Subjects. The interventions had to be delivered to school-aged children (K-12 or equivalent ages in international settings) in regular school settings during schoolhours. Moreover, the intervention had to be delivered to children who were specially

selected for treatment by virtue of any risk factor linked to later antisocial behavior orfor evident behavior problems. Special education classroomsand alternative schoolswere eligible school settings, although classrooms in residential facilities (e.g.,psychiatric hospitals) were not. After-school programs were not eligible. Any qualifyingschool in any region or country was eligible.

Outcomes.The study reported intervention effects for at least one outcome variable,measured on children, representing aggressive behavior, broadly defined to include

violence, aggression, fighting, person crimes, disruptive behavior problems, acting out,conduct disorder, externalizing problems, and so forth.

Study Design.Only studies using a control group design were eligible. The interventionand control groups could be randomly or nonrandomly assigned but, if nonrandom,needed to be matched or provide evidence of initial equivalence on key demographicvariables and/or pretests. Control groups could represent placebo, wait-list, notreatment, or treatment as usual conditions. Studies without control or comparison

groups were not eligible. This included one-group pretest-posttest studies and studies inwhich a treatment condition was compared to another treatment condition.

Search Strategy for Identification of Studies

An attempt was made to identify and retrieve the entire population of empirical studiesthat met the eligibility criteria specified above, including both published andunpublished studies. Several sources were used to identify potentially eligible research

reports. First, a large database compiled at the Center for Evaluation Research andMethodology with NIMH grant funding (Lipsey, PI) was searched for eligibleinterventions. That database includes studies of early intervention programs targeting awide range of risk factors for antisocial behavior and includes many school-basedprograms.


13/40


The search strategy utilized three categories of search terms2derived from thecontrolled vocabulary used to index articles for each specific database. Wildcard

characters were used to identify variants of words (e.g., delinquen* to locate delinquent,delinquents, and delinquency). Within each category described below, search terms areconnected by the OR operator; the results for each of the three categories werecombined with the AND operator:

1. The population of interest: child, adolescent, childhood (MEDLINE); children,adolescents, preadolescents, students (ERIC); children, adolescents, students(PsychInfo), and children, adolescents, students (Sociological Abstracts);

2.

Risks or outcomes: social adjustment, interpersonal relations, social interaction,social isolation, aggression, juvenile delinquency, peer group, attention deficitand disruptive behavior disorders, hyperkinesis, cultural deprivation,interpersonal relations, social environment, social behavior, child behaviordisorders, social problems, antisocial personality disorder, conduct disorder,dangerous behavior, social alienation, conflict, hostility, violence, reactiveattachment disorders, impulsive behavior, problem solving (MEDLINE); socialenvironment, social integration, social adjustment, social attitudes, social

experience, social characteristics, attachment behavior, antisocial behavior,adjustment, aggression, delinquency, attention deficit disorders, hyperactivity, atrisk persons, high risk students, educationally disadvantaged, problem children,dropouts, social influences, behavior disorders, behavior problems, youthproblems, conflict, hostility, truancy, violence, peer relations, peer influences(ERIC); interpersonal influences, interpersonal interaction, social skills, socialdevelopment, social networks, acting out, adjustment disorders, aggressivebehavior, juvenile delinquency, predelinquent youth, attention deficit disorder,

hyperkinesis, at risk populations, runaway behavior, school dropouts,disadvantaged, social deprivation, cultural deprivation, peer relations, referencegroups, behavior disorders, behavior problems, antisocial behavior, conductdisorder, conflict, hostility, truancy, oppositional defiant disorder, impulsiveness,arguments (PsychInfo); adjustment, social dynamics, social participation, socialbehavior, social attitudes, social competence, social development, social learning,social isolation, juvenile delinquency, social background, disadvantaged, peerrelations, peer influence, behavior problems, interpersonal conflict, conflict,

violence, deviant behavior (Sociological Abstracts);3. Treatment/evaluations: social problem solving, social information processing,

counseling, intervention, prevention and control, preventive, therapy,psychotherapy, social control, behavior therapy, cognitive therapy, treatmentoutcome, program evaluation, behavioral assessment, randomized controlledtrials pilot projects clinical trial meta-analysis (MEDLINE); behavior change


14/40


early intervention, prevention, psychotherapeutic outcomes, therapy, training,social programs, compensatory education, treatment outcomes, program

evaluation, behavioral assessment, treatment effectiveness evaluation,educational program evaluation, meta-analysis (PsychInfo); behaviormodification, counseling, intervention, prevention, therapy, training, treatment,social programs, educational programs, treatment outcomes, evaluation,effectiveness, quantitative analysis.

Third, the bibliographies of previous meta-analyses and literature reviews (e.g., Denham& Almeida, 1987; Durlak, 1997) were inspected for studies that met the eligibility

criteria. In addition, the bibliographies of retrieved studies were themselves examinedfor potentially eligible research reports. Finally, follow-up searches on the first andsecond authors of all eligible studies and cited reference searches of eligible articles inthe Social Sciences Citation Index were conducted. We have found this forwardsearching technique to be more efficient and fruitful than conducting hand searches ofjournal issues.

Studies identified through our searches were retrieved from the library, obtained via

interlibrary loan, or requested directly from the author(s). In addition, we attempted tolocate and include any eligible studies published in non-English language sources thatwere missed by the search strategies described above by asking colleagues from bothinside and outside the U.S. to assist us with locating foreign-language studies.

Selection of Studies

Abstracts of the studies found through the search procedures were screened for

relevance. Documents that were not obviously ineligible or irrelevant (based on theabstract review) were retrieved from the Vanderbilt University Libraries, InterlibraryLoan, ERIC, University Microfilms, and government documents sources for finaleligibility screening. Final determination of eligibility for all studies irrespective ofsource was made from the full study report document(s) on the basis of detailedeligibility criteria. The abstract screening and eligibility determination were performedby the first author or a trained research assistant. Any ambiguities or questions abouteligibility were resolved through discussion by both authors.

Although some research suggests that two reviewers might increase accuracy inidentifying potentially eligible studies from abstracts obtained through bibliographicsearches (Edwards, et al., 2002), our experience is that most abstracts do not provideenough detail to allow reviewers to make reliable judgments about whether a studymeets the review criteria Thus we reviewed abstracts mainly to eliminate those clearly


15/40


Data Management and Extraction

The coding protocol used for this project allowed for coding a wide variety of studycharacteristics, as well as study results. The standardized mean difference effect sizestatistic (Cohen, 1988; Lipsey & Wilson, 2001) was used to record intervention effects.This effect size statistic is defined as the difference between the treatment and controlgroup means on an outcome variable divided by their pooled standard deviations. Whenmeans and standard deviations were not available, effect sizes were estimated from thestatistics that were reported using the procedures described in Lipsey and Wilson(2001). Typically, studies reported results on multiple outcome constructs (e.g.,

aggression, social skills, school achievement) and often included more than oneoperationalization of the same construct (e.g., parent and teacher reports of aggressivebehavior). For purposes of this systematic review, all effect sizes that assessed aggressiveor disruptive behavior outcomes that could be extracted from a study were coded.Procedures for maintaining statistical independence during analysis in cases of multipleeffect sizes will be discussed in the next section.

In addition to effect size values, information was coded for each study that describes the

methods and procedures, the intervention, and the subject samples. The itemsdescribing study methods and procedures include details of the design, measures, andattrition. Those coded to describe the subject samples include age, gender, ethnicity,socioeconomic status, and risk for later antisocial behavior. The interventions weredescribed by coding the details of specific program components; duration, intensity,setting, and format of the program; delivery personnel; and, other such characteristics.

All study coding was done on computer screens configured in FileMaker Pro for direct

entry into the database. All coding was completed either by the first author or by trainedresearch assistants. Any study coded by a research assistant was reviewed for accuracyby the first author. Any discrepancies or ambiguities in coding were resolved by the twoauthors.

Statistical Procedures

Effect sizes based on small samples are known to be biased; to adjust for this, all effect

sizes were multiplied by the small sample correction factor, 1 (3/4n-9), where nis thesample size for the study (Hedges & Olkin, 1985). Also, each effect size was weighted byits inverse variance in all computations so that its contribution was proportionate to itsreliability (Hedges & Olkin, 1985). Examination of the effect size distribution identifieda small number of outlier effect sizes with potential to distort the analysis; these wererecoded (i e Winsorized) to less extreme values (Hedges & Olkin 1985; Lipsey &


16/40


The intervention outcome of principal interest was aggressive and disruptive behavior,which involves a variety of negative interpersonal behaviors including fighting, hitting,

bullying, verbal conflict, disruptiveness, acting out and the like.4

The most common typeof measure was a teacher-report questionnaire, though many studies provided resultsfor more than one aggressive behavior outcome. To create sets of independent effect sizeestimates for analysis, only one effect size from each subject sample was used in anyanalysis. The procedures for selecting an independent set of effect sizes are describedbelow.

Finally, many studies provided data sufficient for calculating mean difference effect

sizes on the outcome variables measured at the pretest. In cases where pretest effectsizes were available, we adjusted the posttest effect sizes for pretest differences bysubtracting the pretest value from the posttest value. In the analyses presented below,we tested whether there were systematic differences between effect sizes that wereadjusted and those that were not by including dummy codes for adjustment in theanalyses.

Findings

Description of Eligible Studies

The search strategy identified 68 eligible reports, which reported the results of 47unique research studies. Some eligible studies were reported in multiple reports, whilesome reports presented results for multiple independent studies. In addition, when theresults of a study were reported for subgroups (e.g., male and female results werereported separately), we coded the two subgroups rather than the aggregate and treated

them as two studies. Table 1 summarizes the characteristics of the 47 selected andindicated social information processing programs included in this review. Coding detailsfor each of the 47 studies can be found in the Appendix.

Nearly 90 percent of the studies were conducted in the United States, and slightly overhalf were published in peer reviewed journals. Studies were published from the 1970s tothe present, with most programs in the 1980s and 1990s. As would be expected withpopulations at risk for aggressive behavior, the samples were predominantly male. Age

ranged from six to 16, with 45% of the samples in the nine to eleven year range. In theUnited States, nine to eleven year olds are typically in upper elementary school, betweenthe 4thand 6thgrades. Among the studies that reported the ethnicity for their subjectsamples, over half were comprised primarily of minority youth. Forty percent of thestudies were conducted with predominantly low income populations. In terms of therisk status of student participants 32% of the studies focused on selected groups and


17/40


Table 1: Characteristics of Studies (n=47)

Characteristic N % Characteristic N %

Publication Year Gender Mix1970s 3 6 No males (60%) 20 432000s 13 28 All males (>95%) 14 30

Form of Publication AgeUnpublished 21 45 6-8 years 10 21Published (peer review) 26 55 9-11 years 21 45

12-16 years 16 34Country of StudyUSA 41 87 Race/Ethnicity (Predominant)Canada 2 4 White 13 28Finland 1 2 Black 15 32

Australia 1 2 Hispanic 2 4Israel 1 2 Asian 1 2India 1 2 Mixed 2 4

Cannot tell 14 30Group Assignment

Random (individual) 35 74 Socioeconomic StatusRandom (group, class) 5 11 Predominantly low 19 40Non-random (individual) 4 9 Mixed, full range 6 13Non-random (group, class) 3 6 Predominantly middle 10 21

Cannot tell 12 26Pretest AdjustmentYes 41 87No 6 13 Risk for Antisocial behavior

General, very low risk 2 4Attrition At-risk, selected 15 32None 21 45 Antisocial, indicated 30 643-10% 11 23 11% 15 32 Role of evaluator

Delivered treatment 21 45Sample Size (tx + control) Supervised delivery 25 53Up to 30 19 40 Influential, but no delivery 1 231-60 19 4061-86 9 19 Routine Practice Program

Research program 41 87

Timing of Posttest Demonstration program 5 11Immediate post-tx 38 81 Routine practice program 1 22-52 weeks 9 19

Implementation ProblemsInformant Yes 9 11Teacher 34 72 None indicated 38 81Archival report 5 11


18/40


Table 1 (continued): Characteristics of Studies (n=47)

Characteristic N % Characteristic N %

Treatment Site Number of Sessions per WeekRegular education school 42 89 Less than weekly 2 4Special ed. school/class 5 11 Once per week 22 47

1-2x per week 2 4Delivery Personnel Twice per week 15 32Researcher 14 30 2-3x per week 1 2Researcher + school pers. 12 26 3x per week 2 4Non-research personnel 11 23 3-4x per week 1 2Graduate students 10 21 Daily (5x per week) 2 4

Treatment Elements*General cognitive-behavioral 13 28 Format*

Anger management 25 53 Group format 42 89Social problem solving 28 60 Individual format 7 10Perspective taking 12 26 *not mutually exclusiveBehavior modification 13 28*not mutually exclusive

Duration of Treatment

Up to 8 weeks 20 439-16 weeks 16 3417-34 weeks 8 171 school year or more 3 6

The majority (74%) of studies used random assignment of individual students to createtreatment and comparison groups. Eighty-seven percent of the studies presented pretestresults on the outcome variable, which allowed us to adjust for any pretest differences

between groups at the effect size level.5Overall, the average pretest effect size was notsignificantly different from zero, indicating the treatment and comparison groups hadequivalent levels of aggressive behavior before treatment began. In addition, therandom and nonrandom assignment studies were not significantly different at thepretest.

Only one program was coded as a routine practice program (administered by schoolpersonnel as an ongoing school program). The remaining programs were conducted

primarily for research or demonstration purposes. Correspondingly, the programevaluators/researchers tended to be involved in treatment delivery or supervision ofdelivery personnel. In 55% of the studies, the primary researcher developed the programunder study, while there were only 5 studies in which the program developer was notinvolved in the research project. For just over a third of the studies, program developerswere not involved but the primary researchers modified the program We believe this


19/40


program administration, there were few studies (9) in which implementation problemswere reported.

Programs were mainly conducted using group formats in regular schools, though sevenprograms were either solely one-on-one or included individual as well as group sessions.Five programs were conducted with special education students. Treatment durationranged from short programs of less than 8 weeks to those lasting one school year ormore. The majority of programs had sessions once or twice a week. Since students weretypically pulled out of their regular classrooms to meet for treatment, it is not surprisingthat most programs could only arrange sessions once or twice a week. A range of

delivery personnel was utilized, with most having some affiliation with the researchers.Finally, Table 1 shows the frequency of the different types of social informationprocessing interventions utilized. Most programs involved more than one aspect ofsocial information processing, and 13 also included a behavior modification component.

Mean Effects of Selected and Indicated Social Information ProcessingPrograms

The 47 eligible studies generated a total of 120 standardized mean difference effect sizeson aggressive or disruptive behavior; these effect sizes index the posttreatmentdifferences between the treatment and comparison groups. Most studies (32) generatedmore than one effect size (ranging from two to nine), while 15 studies provided only asingle effect size. The multiple measures of aggressive and disruptive behavior withinstudies were either different aspects of aggressive behavior (e.g., physical and non-physical aggression) or were the same type of aggressive behavior reported by differentinformants.

To create a set of independent effect sizes for analysis, a combination of procedures wasused. When studies reported results on different types of aggressive behavior, weselected the effect size(s) that most closely represented interpersonal physicalaggression and discarded the others. Next, we wanted to retain informant as a variablefor analysis, so did not elect to average across effect sizes from different informantswhen more than one was reported. If there was more than one effect size from the sameinformant or source, however, their mean value was used. Then, from the studies with

multiple effect sizes reported by different informants, one effect size was selected fromthe informant that was most frequently represented in the data. In this case, teacherswere the most common informants, followed by self-reports from the participantsthemselves. These procedures resulted in the 47 effect sizes that are the subject of thefollowing analyses.


20/40



21/40


Analysis of Moderator Effects

There was also significant variability across the different studies in the effect sizes. A testof the homogeneity of the effect sizes using the Q-statistic (Hedges & Olkin, 1985)showed more variability across studies than expected from subject-level sampling error(Q46=97, p


22/40


Table 2: Zero-order Correlations between Study Method Characteristics and Aggressiveand Disruptive Behavior Effect Sizes (n=47)

Method Variable Correlation pTeacher reported dependent variable (1) vs. other (0) -.12 .40Self-reported dependent variable (1) vs. other (0) .11 .45Timing of measurement, immediate (1) vs. later (0) -.05 .70Random assignment, individual (1) vs. other (0) -.02 .89Cluster random assignment (1) vs. other (0) .01 .92Non-random assignment (1) vs. other (0) .01 .94Pretest adjustment (1) vs. unadjusted (0) -.06 .67

Attrition (% loss) -.46 .00Number of ES aggregated .05 .71Note: weighted random effects analysis

There was only one significant relationship between any of the method characteristicsexamined and effect size. The relationship between attrition and study outcome waslarge, significant, and negative indicating that studies with greater attrition producedsmaller effect sizes. Most striking in this method analysis was the finding that there

were no differences between studies that used individual random assignment and thosethat assigned subjects to groups using a non-random method. Because of its significantinfluence, attrition was carried forward as a method control in all later analyses. Inaddition, the non-random assignment dummy code was carried forward to ensure thatany influence was made explicit; the teacher-report dummy code was also retainedbecause its relationship with effect size, though insignificant, was not trivial.6

The Relationship of Other Study Characteristics to Effect Size

With the influential method variables identified, we can turn to an analysis of theimportant substantive study characteristics. This analysis follows the same proceduredescribed above for the method variables, but with adjustments for the three carried-over method variables. A series of inverse-variance weighted random effects multipleregressions were conducted, with each including a single study characteristic and thefour method controls (Raudenbush, 1994). We elected to run each of these analysesseparately at first in order to identify the relationships between each study characteristic

and effect size, without the confounding influence of the other study characteristics.Table 3 presents the results of these regression analyses.

Only one variable shown in Table 3 had a significant relationship with study outcome,the type of school in which the program was conducted. However, there were severalother variables with non trivial relationships with effect size We will discuss each


23/40


In terms of student characteristics, only the risk status of the students showed arelationship with effect size greater than .10. As shown in Table 1, there are threecategories of student risk: low risk, selected, and indicated. Students in the selectedcategory were selected for programs because of some risk for later antisocial behavior,such as poor social skills, attention problems, and the like. Indicated students werealready exhibiting aggressive or disruptive behavior. Although the beta was notsignificant, students in the indicated group tended to show greater reductions inaggressive and disruptive behavior after treatment than did the lower risk students.There were no significant relationships between gender mix, age, or socioeconomicstatus and effect size.

Several characteristics of the treatment and its delivery circumstances had non-trivialrelationships with effect size in addition to the significant relationship between type ofschool and study outcome. Programs delivered in special education schools or those inwhich the subjects were pulled out of special education classrooms were not as effectiveas those in which subjects were pulled out of regular classrooms for treatment. Thestudents in the special education settings tended to have multiple problems, includingboth academic and behavioral difficulties. Although the higher risk children tended to

achieve greater benefits from treatment overall, the children in the special educationsettings did not. These children may be a particularly difficult group to work with.

The programs in which graduate students delivered treatment tended to be less effectivethan programs delivered by the researchers themselves or other non-research affiliateddelivery personnel (e.g., counselors, social workers, etc.), although the relationship wasnot statistically significant.

In terms of the amount and quality of treatment, longer programs and betterimplemented programs tended to be more effective than programs which were shorteror had implementation problems. In addition, the few programs with one-on-onesessions tended to be less effective than those that were delivered exclusively to groupsof students.

The final set of study characteristics we examined was a series of dummy codesrepresenting the most common modes of treatment used in social information

processing programs, anger control, social problem solving, perspective taking, andgeneral cognitive-behavioral and one dummy code representing the use of behavioralmodification in addition to the cognitively-oriented portion of the program. As isevident from Table 3, the different treatment modes did not tend to be associated withbetter or worse outcomes. All the different modes of treatment tended to producesimilar reductions in aggressive and disruptive behavior


24/40


Table 3: Relationships between Study Characteristics and Aggressive Behavior EffectSizes with Method Variables Controlled (n=47)

Study Characteristic (with method controls)General Study CharacteristicsYear of publication .15Published (1) vs. unpublished (0) .10USA (1) vs. all other countries (0) -.07

Student CharacteristicsStudent risk (1=low; 2=selected; 3=indicated) .12

Gender mix (% male) .09Age -.09Low SES (1) vs. mixed or middle (0) .07

Evaluator/Researcher Role in StudyRole of evaluator in treatment delivery (1=low; 4=high) -.06Demonstration program (1) vs routine practice (0) .07Program developer is PI (1) vs. developer not PI (0) .03

PI modified program (1) vs. unmodified (0) .07

Site and Delivery PersonnelSpecial placement (1) vs. regular school (0) -.24*Researcher provided treatment (1) vs. other provider (0) .04Graduate students provided treatment (1) vs. other (0) -.12Non-research delivery personnel (1) vs. research (0) .10

Amount and Quality of TreatmentDuration of treatment (weeks) .19Number of sessions per week -.01Implementation quality (no problems=1, problems=0) .15

Format of TreatmentTx has individual one-on-one component (yes=1; no=0) -.15

Treatment ElementsGeneral cognitive-behavioral component (1) vs. other (0) .03Anger management component (1) vs. other (0) .04Social problem solving component (1) vs. other (0) .01Perspective taking component (1) vs. other (0) -.05B h i difi ti t ( ) th ( )


25/40


Moderators of Observed Effects on Aggressive and Disruptive Behavior

The final stage of our analysis of important moderators of effect size involved examiningthe relative influence of some of the critical variables identified above. We performed aninverse-variance weighted random effects multiple regression analysis in which thethree method variables were entered along with all variables from Table 3 with betacoefficients greater than .10. The results of this analysis are shown in Table 4.

Only two variables were significant in the final model, attrition and the specialeducation school dummy variable. As in the earlier analyses, studies with greater

attrition tended to have significantly smaller effects and programs for special educationstudents were less effective. Publication year, publication status, student risk, andimplementation quality all had positive, though nonsignificant, relationships with effectsize, similar to the univariate model presented above. Programs with individualcomponents were somewhat less effective than those delivered exclusively to groups.

Table 4: Regression Model for Effect Size Moderators for Selected and Indicated SocialInformation Processing Programs (n=47)

Study Characteristic Method CharacteristicsTeacher reported DV (1) vs. other (0) -.01Attrition (%) -.57**Random assignment (1) vs. other (0) -.22

General Study CharacteristicsPublication year .26

Published (1) vs. unpublished (0) .11

Student CharacteristicsStudent risk (indicated=1; all other lower risk=0) .21

Special placementSpecial placement program (1) vs. regular school (0) -.30*

Format and Delivery PersonnelGraduate student providers (1) vs. other (0) .05Non-research provider (1) vs. research (0) .05Treatment has individual one-on-one component (1=yes; 0=no) -.17

A t d Q lit f T t t


26/40


Although the relationships in this analysis generally follow what we found in earlieranalyses, allowing the individual study characteristics to co-vary produced a fewchanges. Though not significant, the random assignment dummy code is moreinfluential in the full model. Studies which used individual random assignment tendedto produce smaller effects than those which used a non-random design. But, the dummycode for teacher reported outcome variables was less influential in this final model.

Conclusions

The objective of this systematic review was to examine the effects of school-based social

information processing interventions on the aggressive and disruptive behavior ofselected and indicated school-age children. We were able to locate 47 studies of socialinformation processing programs delivered to specially selected children in schoolsettings. Overall, we found a positive program effect. At-risk and behavior problemstudents who participated in social information processing programs showed lessaggressive and disruptive behavior after treatment than students who did not receive aprogram. The overall weighted mean effect size was .26, which was statisticallysignificant. Over 60% of the effect size values were positive.

There was significant heterogeneity in outcomes across the 47 studies we reviewed andour analyses of moderators produced some interesting findings. Only one methodvariable had an impact on study outcomesstudies with greater amounts of attritionbetween pretest and posttest tended to show smaller program impact than those withlittle attrition. There were no significant differences between experimental and quasi-experimental studies, although studies which used random assignment methods tendedto produce smaller effects than the non-random studies.

Social information processing programs for special education students weresignificantly less effective than those for regular education students, though overallgreater reductions in aggressive behavior were found for higher risk students. Studentswho have behavior problems likely have more potential for change than those who are atrisk but not yet exhibiting serious problems. However, children who have been placed inspecial schools or classrooms and then selected for special violence preventionprogramming on top of that may have such serious problems that short-term social

information processing programs are not likely to have a strong impact.

The different foci of social information processing programs did not appear to make adifference. Programs emphasizing anger control were no more effective than thoseemphasizing social problem solving or perspective taking.

S l d/I di d S i l I f i P i P


27/40


school grounds in the year prior to the survey. For 1995 and 1997, 15.5% and 14.8% ofstudents reported being in physical fights (Centers for Disease Control and Prevention,2002). If we use these figures to estimate that about 15% of untreated school childrenwill get into a fight during a school year, the overall effect size of .26 for selected andindicated social information processing programs translates into an eight percentagepoint reduction in fighting. That is, if 15% of selected or indicated students who receivedno social information processing training were getting into fights before intervention,only 7% of children in social information processing programs were getting into fights.The most effective programs produced larger effects than this and, thus, would reducerates of aggressive behavior even more. In addition, since many of the children in

selected or indicated programs were already exhibiting some problem behavior, it islikely that their baseline level of fighting behavior was higher than the general estimateof 15%. Thus, the reduction in aggressive behavior could possibly be greater.

Plans for Updating

The authors will take responsibility for updating this review to include new studiesreported subsequent to the initial review and earlier studies missed in the search that

are identified and located. These updates will be planned for approximately every threeyears.

Conflict of Interest

None.



28/40


References

Alpert-Gillis, L. J., Pedro-Carroll, J. L., & Cowen, E. L. (1987). The Children of DivorceIntervention Program: Development, implementation, and evaluation of a program for youngurban children.Journal of Consulting & Clinical Psychology, 57,583-589.

Asher, S. R., & Renshaw, P. D. (1981). Children without friends: Social knowledge and socialskills training. In S. R. Asher & J. M. Gottman (Eds.), The development of childrens

friendships(pp. 273-296). New York: Cambridge University Press.Beelmann, A., Pfingsten, U., & Lsel, F. (1994). Effects of training social competence in children:

A meta-analysis of recent evaluation studies.Journal of Clinical Child Psychology, 23,260-271.

Clayton, C. J., Ballif-Spanvill, B., & Hunsaker, M. D. (2001). Preventing violence and teachingpeace: A review of promising and effective antiviolence, conflict-resolution, and peaceprograms for elementary school children.Applied and Preventive Psychology, 10,1-35.

Cohen, J. (1988).Statistical power analysis for the behavioral sciences(2nd ed.). Hillsdale, NJ:Lawrence Erlbaum.

Coleman, M., Wheeler, L., & Webber, J. (1993). Research on interpersonal problem-solvingtraining: A review.Remedial and Special Education, 14, 25-37.

Crick, N. R., & Dodge, K. A. (1989). Childrens perceptions of peer entry and conflict situations:Social strategies, goals, and outcome expectations. In B. Schneider, J. Nadel, G. Attili, & R.

Weissberg (Eds.),Social competence in developmental perspective(pp. 396-399). New York:Kluwer.

Crick, N. R., & Dodge, K. A. (1994). A review and reformulation of social information-processingmechanisms in childrens social adjustment.Psychological Bulletin, 115,74-101.

Denham, S. A., & Almeida, M. C. (1987). Childrens social problem-solving skills, behavioraladjustment, and interventions: A meta-analysis evaluating theory and practice.Journal of

Applied Developmental Psychology, 8,391-409.DeVoe, J. F., Peter, K., Kaufman, P., Ruddy, S. A., Miller, A. K., Planty, M., Snyder, T. D., &

Rand, M. R. (2003).Indicators of school crime and safety: 2003(NCES 2004-004/NCJ201257). Washington, DC: US Departments of Education and Justice.Dodge, K. A. (1986). A social information processing model of social competence in children. In

M. Perlmutter (Ed.), The Minnesota Symposium on Child Psychology(Vol. 18, pp. 77-125).Hillsdale, NJ: Erlbaum.

Dodge, K. A., Pettit, G., McClaskey, C., & Brown, M. (1986). Social competence in children.Monograph of the Society for Research in Child Development, 51 (Serial No. 213).

Durlak, J. A. (1997). Primary prevention programs in schools.Advances in Clinical ChildPsychology, 19,283-318.

D'Zurilla, T. J., & Goldfried, M. R. (1971). Problem solving and behavior modification.Journalof Abnormal Psychology, 78,107-126.

Edwards, P., Clarke, M., DiGuiseppi, C., Pratap, S., Roberts, I., & Wentz, R. (2002).Identification of randomized controlled trials in systematic reviews: Accuracy and reliabilityof screening records.Statistics in Medicine, 21,1635-1640.

Garofalo, J., Siegel, L., & Laub, J. (1987). School-related victimizations among adolescents: An



29/40


215.Hudley, C. (1991). An attribution retraining program to reduce peer directed aggression among

African-American male elementary school students (Doctoral dissertation, University of

California, Los Angeles).Dissertation Abstracts International, 52/4-A, 1263-1264.(University Microfilms No. AAT91-28799)

Kanchur, S. P., et al. (1996). School associated violent deaths in the U. S., 1992 to 1994.Journalof the American Medical Association, 275,1729-1733.

Kendall, P. C. (1995). Cognitive-behavioral therapies with youth: Guiding theory, current status,and emerging developments.Journal of Consulting and Clinical Psychology, 61,235-247.

Lewinsohn, P. M., Clarke, G. N., Hops, H., & Andrews, J. (1990). Cognitive-behavioral treatmentfor depressed adolescents.Behavior Therapy, 21,385-401.

Lipsey, M. W., & Wilson, D. B. (2001).Practical meta-analysis, Thousand Oaks, CA: Sage.Lochman, J. E., Lampron, L. B., Burch, P. R., & Curry, J. F. (1985). Client characteristics

associated with behavior change for treated and untreated aggressive boys.Journal ofAbnormal Child Psychology, 13,527-538.

Lsel, F., & Beelmann, A. (2003). Effects of child skills training in preventing antisocialbehavior: A systematic review of randomized evaluations.Annals of the American Academyof Political and Social Science, 587,84-109.

Mize, J., & Cox, R. A. (1990). Social knowledge and social competence: Number and quality ofstrategies as predictors of peer behavior.Journal of Genetic Psychology, 151,117-127.

Moote, G. T., Smyth, N. J., & Wodarski, J. S. (1999). Social skills training with youth in schoolsettings: A review.Research on Social Work Practice, 9,427-465.

Mytton, J. A., DiGuiseppi, C., Gough, D. A., Taylor, R. S., & Logan, S. (2002). School-basedviolence prevention programs: Systematic review of secondary prevention trials.Archives ofPediatric and Adolescent Medicine, 156,752-762.

Nangle, D. W., Erdley, C. A., Carpenter, E. M., & Newman, J. E. (2002). Social skills training asa treatment for aggressive children and adolescents: A developmental-clinical integration.

Aggression and Violent Behavior, 7,169-199.Pellegrini, D. S. & Urbain, E. S. (1985). An evaluation of interpersonal cognitive problem solving

training with children.Journal of Child Psychology & Psychiatry & Allied Disciplines, 26,17-41.

Quinn, M. M., Kavale, K. A., Mathur, S. R., Rutherford, R. B., Jr., & Forness, S. R. A meta-analysis of social skill interventions for students with emotional or behavioral disorders.

Journal of Emotional and Behavioral Disorders, 7,54-64.Schneider, B. H., & Byrne, B. M. (1985). Childrens social skills training: A meta-analysis. In B.

H. Schneider, K. H. Rubin, & J. E. Ledingham (Eds.), Childrens peer relations: Issues inassessment and intervention(pp. 175-192). New York: Springer.

Shure, M. B. (1992).I Can Problem Solve: An interpersonal cognitive problem-solvingprogram: Kindergarten and primary grades.Champaign, IL: Research Press.Shure, M. B., & Spivack, G. (1972). Means-ends thinking, adjustment, and social class among

elementary-school-aged children.Journal of Consulting and Clinical Psychology, 38,348-353.

Shure, M. B., & Spivack, G. (1979). Interpersonal cognitive problem solving and primaryi P i f h l d ki d hild J l f Cli i l Child



30/40


Studies Included in the Systematic Review

NOTE: Numbers in brackets at the end of each reference are study identification numbers. Citationswith the same number are part of the same study.

Arbuthnot, J. (1992). Sociomoral reasoning in behavior-disordered adolescents: Cognitive and behavioralchange. In J. McCord & R. E. Tremblay (Eds.),Preventing antisocial behavior: Interventions frombirth through adolescence.(pp. 283-310). New York: The Guilford Press. [463]

Arbuthnot, J., & Gordon, D. A. (1986). Behavioral and cognitive effects of a moral reasoning developmentintervention for high-risk behavior-disordered adolescents.Journal of Consulting and Clinical

Psychology, 54, 208-216. [463]Barkstrom, S. R. (1998).School-based intervention and adolescent aggression: A comparison of

behavioral social skills and social problem-solving approaches to modifying student behavior(Doctoral dissertation, State University of New York at Buffalo). Dissertation AbstractsInternational, 58/8-B, 4436. (University Microfilms No. AAT98-07274) [1956]

Binfet, J. T. (2001). The effect of reflective abstraction versus peer-focused discussions on the promotionof moral development and prosocial behavior: An intervention study(Doctoral dissertation, TheUniversity of British Columbia (Canada), 2000). Dissertation Abstracts International, 61(12-A),4670. (University Microfilms No. AAT NQ56506 ) [5090]

Bloomquist, M. L., August, G. J., & Ostrander, R. (1991). Effects of a school-based cognitive-behavioralintervention for ADHD children.Journal of Abnormal Child Psychology, 19, 591-604. [321]

Booth, B. A. (1995).A cognitively based anger control training program with aggressive adolescents inthe school setting(Doctoral dissertation, State University of New York, Albany, 1995). DissertationAbstracts International, 56/07-A, 2870. (University Microfilms No. AAT95-40344) [498]

Broota, A., & Sehgal, R. (2004). Management of conduct disorders through cognitive behaviouralintervention.Psychological Studies, 49, 69-72. [5061]

Burcham, B. G. (2002).Impact of school-based social problem-solving training on middle schoolstudents with disruptive behavior(Doctoral dissertation, University of Kentucky). Dissertation

Abstracts International, 63(2-A), 507. (University Microfilms No. 3042453) [5030]Burgher, B. M., III (1997). An analysis of predictors of response to preventive treatment for conduct

disorder(Doctoral dissertation, University of Houston, 1996). Dissertation Abstracts International,

DAI-B 58(03), 1521-1851. (University Microfilms No. AAT 9724393) [3798]Camp, B. W. (1980). Two psychoeducational treatment programs for young aggressive boys. In C. K.

Whalen & B. Henker (Eds.),Hyperactive children: The social ecology of identification andtreatment(pp. 191-219). New York: Academic Press. [1884]

Camp, B. W., Blom, G. F., Herbert, F., & Van Doornick, W. J. (1977). "Think Aloud": A program fordeveloping self-control in young aggressive boys.Journal of Abnormal Child Psychology, 5, 157-169. [476]

Coie, J. D., & Dodge, K. A. (1988). Multiple sources of data on social behavior and social status in theschool: A cross-age comparison. Child Development, 59, 815-829. [401; 460]

Coie, J. D., Dodge, K. A., & Coppotelli, H. (1982). Dimensions and types of social status: A cross-ageperspective.Developmental Psychology, 18, 557-570. [401; 460]Coie, J. D., Lochman, J. E., Terry, R., & Hyman, C. (1992). Predicting early adolescent disorder from

childhood aggression and peer rejection.Journal of Consulting & Clinical Psychology, 60, 783-792.[401; 460]

Coie, J. D., Rabiner, D. L., & Lochman, J. E. (1989). Promoting peer relations in a school setting. In L. A.Bond & B. E. Compas (Eds.), Primary prevention and promotion in the schools (pp. 207-234).


31/40



32/40

/ g g 9

Lochman, J. E., Lampron, L. B., Gemmer, T. C., & Harris, S. R. (1987). Anger coping intervention withaggressive children: A guide to implementation in school settings. In P. A. Keller, & S. R. Heyman(Eds.),Innovations in clinical practice: A source book (Vol. 6) (pp. 339-356). Sarasota, FL:

Professional Resource Exchange. [458]Lochman, J. E., Lampron, L. B., Gemmer, T. C., Harris, S. R., & Wyckoff, G. M. (1987). Teacherconsultation and cognitive behavioral interventions with aggressive boys. Paper presented at themeeting of the American Psychological Association Annual Convention. (ERIC DocumentReproduction Service No. 291044) [459]

Lochman, J. E., Lampron, L. B., Gemmer, T. C., Harris, S. R., & Wyckoff, G. M. (1989). Teacherconsultation and cognitive-behavioral interventions with aggressive boys.Psychology in the

Schools, 26, 179-188. [459]Lochman, J. E., & Wells, K. C. (2004). The Coping Power Program for preadolescent aggressive boys and

their parents: Outcome effects at the 1-year follow-up.Journal of Consulting and Clinical

Psychology, 72, 571-578. [5039]Lochman, J. E., & Wells, K. C. (2003). Effectiveness of the Coping Power Program and of classroom

intervention with aggressive children: Outcomes at a 1-year follow-up.Behavior Therapy, 34, 493-515. [5023]

Lochman, J. E., & Wells, K. C. (2002). Contextual social-cognitive mediators and child outcomes: A test ofthe theoretical model in the Coping Power program.Development and Psychopathology, 14, 945-967. [5039]

Lochman, J. E., & Wells, K. C. (2002). The Coping Power program at the middle-school transition:Universal and indicated prevention effects.Psychology of Addictive Behaviors, 16 (Suppl. 4), S40-

S54. [5023]Mannarino, A. P., Christy, M., Durlak, J. A., & Magnussen, M. G. (1982). Evaluation of social competencetraining in the schools.Journal of School Psychology, 20, 11-19. [224]

Milne, J., & Spence, S. H. (1987). Training social perception skills with primary school children: Acautionary note.Behavioural Psychotherapy, 15, 144-157. [2121]

Nelson, J. R., Dykeman, C., Powell, S., & Petty, D. (1996). The effects of a group counseling interventionon students with behavioral adjustment problems.Elementary School Guidance & Counseling, 31,21-33. [384]

Nickerson, K. F. (2004).Anger in adolescents: The effectiveness of a brief cognitive-behavioral angermanagement training program for reducing attitudinal and behavioral expressions of anger

(Doctoral dissertation, ). Dissertation Abstracts International, 65(1-B), 425. [5092]Omizo, M. M., Hershberger, J. M., & Omizo, S. A. (1988). Teaching children to cope with anger.

Elementary School Guidance & Counseling, 22, 241-245. [379]Pascucci, N. J. (1991). The efficacy of anger control training in reducing chronic aggressive behavior

among emotionally disturbed/learning-disabled African-American male preadolescents andadolescents(Doctoral dissertation, St. John's University, 1990). Dissertation AbstractsInternational, 51(11), 3678. (University Microfilms No. AAT 9109870) [5066]

Pepler, D., King, G., Craig, W., Byrd, B., & Bream, L. (1995). The development and evaluation of amultisystem social skills group training program for aggressive children. Child and Youth Care

Forum, 24, 297-313. [241]Pitkanen, L. (1974). The effect of simulation exercises on the control of aggressive behaviour in children.

Scandinavian Journal of Psychology, 15, 169-177. [5043]Rahill, S. A. (2002).A comparison of the effectiveness of story-based and skill-based social competence

programs on the development of social problem solving and peer relationship skills of childrenwith emotional disabilities(Doctoral dissertation, University of Maryland, College Park).Dissertation Abstracts International 63(6-A) 2135 (University Microfilms No 3055612) [5000]



33/40

Scheckner, S. B., & Rollin, S. A. (2003). An elementary school violence prevention program.Journal ofSchool Violence, 2(4), 3-42. [5098]

Sharp, S. R. (2004).Effectiveness of an anger management training program based on rational emotive

behavior theory (REBT) for middle school students with behavior problems(Doctoral dissertation,University of Tennessee, 2003). Dissertation Abstracts International, 64(10-A), 3595. [5083]Shechtman, Z. (2000). An innovative intervention for treatment of child and adolescent aggression: An

outcome study.Psychology in the Schools, 37, 157-167. [5053]Stainback, G. J. (1986).Effects of cognitive self-instruction in the increase of anger control for verbally

aggressive children(Doctoral dissertation, North Carolina State University, 1986). DissertationAbstracts International, 47/5-B, 2187-2188. (University Microfilms No. AAT86-13117) [2052]

Sukhodolsky, D. G., Solomon, R. M., & Perine, J. (2000). Cognitive-behavioral, anger-control interventionfor elementary school children: A treatment outcome study.Journal of Child and Adolescent GroupTherapy, 10, 159-170. [1998]

Teglasi, H., & Rothman, L. (2001). STORIES: A classroom-based program to reduce aggressive behavior.Journal of School Psychology, 39, 71-94. [5064]

Vickery, S. A. (1982).Stress inoculation for anger control in children(Doctoral dissertation, University ofSouth Carolina, 1981). Dissertation Abstracts International, 42(12), 4945. (University MicrofilmsNo. AAT 8212268 ) [5026]

Voelm, C. E. (1984). The efficacy of teaching rational emotive education to acting-out and sociallywithdrawn adolescents(Doctoral dissertation, California School of Professional Psychology,Fresno, 1983). Dissertation Abstracts International, 44(12), 3947. (University Microfilms No. AAT8402501 ) [5049]

Zashin, M. (1981).Prosocial behavior training programs: Modeling, role-playing, and training in verbal self-instruction as techniques for teaching prosocial behaviors to groups of behaviorally disturbed pre-adolescent children(Doctoral dissertation, University of Texas at Austin, 1981). Dissertation AbstractsInternational, 42/3-B, 1199. (University Microfilms No. AAT81-19403) [3352]



34/40

Appendix

Tables of Coded Variables by Study


35/40



36/40

Table A1 (continued): Method Variables by StudyAuthor(s) & Year Random Informant/Source Pretest % Attrition # items ES # ES

Assignment of DV Adjustment in DV Estimated Aggregated

Rascucci, 1991 No archive Yes None > 5 items No 1Rosengren, 1987 No self-report Yes > 10% > 5 items No 1Schechtman, 2000 Yes teacher report Yes 3-10% > 5 items No 2Scheckner & Rollin, 2003 Yes teacher report No 3-10% > 5 items No 1Sharp, 2004 No archive No > 10% 2-5 items No 1Stainback, 1986 Yes teacher report Yes None > 5 items No 1Sukhodolsky, et al., 2000 Yes teacher report No None > 5 items No 1Teglasi & Rothman Yes teacher report No 3-10% > 5 items No 1

Vickery, 1982 Yes observation Yes None > 5 items No 1Voelm, 1984 Yes teacher report Yes > 10% > 5 items Yes 2

Zashin, 1981 No teacher report Yes 3-10% > 5 items No 2


37/40



38/40

Table A2 (continued): General Characteristics and Subject Variables by StudyAuthor(s) & Year Country Published? Subject Risk % male Age Low SES?Stainback, 1986 USA No at-risk 60-90% male 13.5 NoSukhodolsky, et al., 2000 USA Yes at-risk all male 10 NoTeglasi & Rothman USA Yes at-risk 60-90% male 9.5 YesVickery, 1982 USA No indicated 60-90% male 9 NoVoelm, 1984 USA No indicated 60-90% male 14 NoZashin, 1981 USA No at-risk 60-90% male 9.19 No



39/40

Table A3: Treatment Characteristics by StudyAuthor(s) & Year Type of school/class Delivery personnel Individual Duration Implementation

Component (weeks) Problems?

Arbuthnot & Gordon, 1986 Regular Researcher No 18 NoBarkstrom, 1998 Regular Researcher No 9 NoBinfet, 2001 Regular Researcher No 10 NoBloomquist, et al., 1991 Regular Mixed (research affiliated) No 10 NoBooth, 1995 Regular Mixed (research affiliated) No 12 YesBroota & Sehgal, 2004 Regular Researcher No 8 NoBurcham, 2002 Regular Mixed (research affiliated) No 30 NoBurgher, 1997 Regular Researcher Yes 16 YesCamp, 1980 Regular Svc. Professional No 8 NoCamp, et al., 1977 Regular Svc. Professional Yes 6 NoCollier, 2002 Regular Researcher No 8 NoDeffenbacher, et al., 1996 Regular Mixed (research affiliated) No 9 NoEdelson & Rose, 1981 (Study 1) Regular Grad student No 6 NoEdelson & Rose, 1981 (Study 2) Regular Grad student No 8 YesFlores de Apodaca, 1979 Regular Svc. Professional No 14 YesHudley, 1991 Regular Researcher No 6 NoHughes, Grossman, & Hart, 1993 Regular Grad student No 10 NoKahl, 1984 (Boys) Regular Svc. Professional No 23 NoKahl, 1984 (Girls) Regular Svc. Professional No 23 No

Larkin, 1999 Regular Researcher No 8 NoLarson, J., 1991 Special Researcher No 5 YesLarson, K., 1989 Regular Grad student No 50 NoLochman & Wells, 2002 Regular Mixed (research affiliated) Yes 68 YesLochman & Wells, 2004 Regular Mixed (research affiliated) No 60 NoLochman, et al., 1985 Regular Svc. Professional No 12 NoLochman, et al., 1989 Regular Svc. Professional No 18 NoLochman, et al., 1993 (Aggressive sample) Regular Grad student Yes 17 NoLochman, et al., 1993 (Rejected sample) Regular Grad student Yes 17 NoMannarino, et al., 1982 Regular Grad student No 14 NoMilne & Spence, 1987 Regular Researcher No 5 NoNelson, et al., 1996 Regular Svc. Professional No 8 NoNickerson, 2004 Regular Svc. Professional No 4 NoOmizo, Hershberger, & Omizo, 1988 Regular Researcher No 10 NoPepler, et al., 1995 Regular Svc. Professional No 15 YesPitkanen, 1974 Regular Grad student No 4 NoRahill, 2002 Special Mixed (research affiliated) No 25 No

continued



40/40

Table A3 (continued): Treatment Characteristics by StudyAuthor(s) & Year Type of school/class Delivery personnel Individual Duration Implementation

Component (weeks) Problems?Rascucci, 1991 Special Researcher No 5 YesRosengren, 1987 Regular Mixed (research affiliated) No 5 NoSchechtman, 2000 Special Grad student Yes 10 NoScheckner & Rollin, 2003 Regular Svc. Professional Yes 8 NoSharp, 2004 Regular Researcher No 6 NoStainback, 1986 Regular Mixed (research affiliated) No 4 NoSukhodolsky, et al., 2000 Regular Researcher No 10 NoTeglasi & Rothman Regular Researcher No 15 No

Vickery, 1982 Regular Researcher No 3 NoVoelm, 1984 Regular Researcher No 10 YesZashin, 1981 Special Grad student No 5 No