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Cognitive-Behavioral Therapy As A Clinical Intervention for Childhood Disruptive Behaviours:
A Meta-Analysis

Bita Ghafoori Ph.D.
Assistant Clinical Professor and Director of Research
University of California San Francisco Fresno Medical Education Program
Psychiatry Residency Training Program
2615 East Clinton Avenue
Fresno, CA 93703-2286
(559) 225-6100 x5655
fax (559) 241-6494
Bita.Ghafoori@ucsfresno.edu

and Susan M. Tracz Ph.D.
Professor
California State University Fresno

All correspondence should be directed to Bita Ghafoori, Ph.D.

Abstract

A meta-analysis was conducted to evaluate the success of cognitive-behavioral therapy in reducing disruptive behaviors exhibited by school-age children. Twenty-seven articles employing cognitive-behavioral therapy and a teacher measure of disruptive behavior were critically analyzed. This meta-analysis of these studies revealed that children who received cognitive-behavioral therapy displayed fewer disruptive behavior problems than did children who did not receive a cognitive-behavioral intervention. Cognitive-behavioral therapy used in conjunction with teacher-implemented contingencies was not found to be more effective in reducing disruptive behavior than cognitive-behavioral therapy alone. Also, no global difference in disruptive behavior was found relative to treatment administered in a school setting as compared to other settings. A difference in level of disruptive behavior was found with respect to the following factors: socioeconomic status, ethnicity, and diagnosis.

 

Key words: therapy, aggressive behavior, school, children, treatment

 

School age children exhibiting significant behavioral problems are often a challenge for parents, teachers, and mental health clinicians. These students frequently engage in behavioral deviancy, including aggression, hyperactivity, acting-out behavior, lack of self-control, and inattention (Robinson, Smith, Miller, & Brownell, 1999). Parents and teachers often report behavioral problems as a major concern, and psychiatrists, psychologists or other mental health professionals are often called on to intervene with children who exhibit these problems (Goldstein & Braswell, 1994). Strategies are needed that can be incorporated efficiently into daily routines to reduce the negative effects of disruptive behavior (Robinson et al., 1999). The use of Cognitive-Behavioral Therapy (CBT) in the classroom represents a method for addressing the need to remediate behavioral excesses and deficits.

Recent treatment development efforts in the area of disruptive behavior disorders have begun to focus on CBT (Beck & Fernandez, 1998). Kendall and Hollon (1979) have offered the following definition of CBT: CBT is "a purposeful attempt to preserve the demonstrated effectiveness of behavior modification within a less doctrinaire context and to incorporate the cognitive activities of the client in the effort to produce therapeutic change" (p.1). CBT with children uses various forms of enactive, performance-based procedures as well as cognitive interventions to produce changes in thinking, feeling, and behavior (Kendall, 2000). CBT interventions recognize the complexities of the interactions among behavior, cognition, affect, social factors, and environmental conditions. The clinician utilizing CBT may fulfill the role of a diagnostician, consultant, or educator, and often functions as a "coach" providing short-term treatment to the child and/or family (Kendall, 2000). CBT interventions have the goal of mitigating aggression as well as other disruptive behavior problems by building appropriate social competencies in children before aggression becomes a deeply established method of problem solving.

Cognitive-behavioral procedures provide an empirically based collection of interventions to control disruptive behavior. The self-regulation of behavior is accomplished by providing young people with carefully planned experiences that help them develop more adaptive problem solving strategies. CBT strategies help provide youth with a cognitive framework to address a series of complex problems, including self-control difficulties, interpersonal problems, behavioral problems, and academic problems (Kendall, Reber, McLeer, Epps, & Ronan, 1990; Meichenbaum & Burland, 1979). Researchers have utilized particular CBT interventions such as social skills training, self-control/self-regulation approaches, relaxation training, cognitive-restructuring approaches, problem solving approaches, and cognitive modeling (Goldstein & Braswell, 1994) in the treatment of childhood disruptive behavior difficulties. These interventions focus on decreasing the social-cognitive deficits or distortions that children may possess to decrease disruptive behavior.

Cognitive behavioral techniques seem like a viable treatment approach for disruptive behavior problems in children; however, analysis of their actual efficacy is necessary. Some studies have found that CBT decreases disruptive behavior according to teacher reports (Bienert & Schneider, 1995; Kazdin, Bass, Siegel, & Thomas, 1989; Lochman & Lampron, 1986), while other studies have found that CBT has limited effects (Bloomquist, August, & Ostrander, 1991; Dubow, Huesmann, & Eron, 1987; Lochman, 1992). The present study assessed the effectiveness of CBT in decreasing teacher reports of disruptive behavior by conducting a meta-analysis of existing research.

Meta-analysis was selected as the means for analysis because it is an ideal method for summarizing results across a number of existing studies that have examined the effectiveness of CBT. Through meta-analysis, we attempted to answer the following questions: Is the overall effect of CBT positive according to the treatment outcome literature? Will teacher-implemented contingencies used in conjunction with CBT be more effective in reducing teacher reports of disruptive behavior than CBT alone? Will treatment administered in a school setting be more effective than treatment administered in other settings? Will lower socioeconomic status subjects exhibit decreased levels of disruptive behavior at posttreatment when compared to subjects of higher socioeconomic status? Will differences exist in level of disruptive behavior when comparing ethnicity of subjects? Will children diagnosed with Conduct Disorder exhibit decreased levels of disruptive behavior at posttreatment when compared to subjects with other diagnoses? A meta-analytic review of CBT studies analyzed the effect size obtained in the treatment outcome data reported in the study.

Methods

Characteristics of Reviewed Studies

This meta-analysis reviewed a number of research studies conducted with children who exhibit disruptive behavior. To be included in this review each study met the following criteria: (a) children included in the study were in the 5 to 13 year age range (elementary school age children); (b) the study was published between 1987 and 1997; (c) the study compared pretreatment and posttreatment conditions; (d) the study focused on decreasing a disruptive behavior identified as problematic; (e) the study included a teacher report measure of disruptive behavior as the dependent variable; (f) the treatment procedures were administered by a professional, paraprofessional, teacher, or parent; and (g) the study was written in English. This study did not include effect sizes calculated from follow-up data. These criteria resulted in 27 articles being identified, which were included in the present analysis. Studies included in the review are listed in Table 1.
Table 2 summarizes selected characteristics included in this analysis. These characteristics include socioeconomic status, ethnicity, and diagnosis.

Literature Search

Several approaches were utilized to identify relevant literature. A computer search on the PsychLit, Psychological Abstracts, and ERIC databases occurred using the following words: cognitive; behavior; cognitive behavior; child; therapy; classroom; elementary; school; junior high; disruptive; disruptive behavior; behavior problem; aggression; interventions; treatment meta analysis; and teacher. The resulting data were crossed with appropriate age group and topic constraints. The following journals for the appropriate time periods (1987 to 1997) were searched by hand because these journals seemed to have the majority of the relevant articles according to the previous search: Cognitive Therapy and Research, Journal of Consulting and Clinical Psychology, Journal of Abnormal Child Psychology, Journal of Clinical Child Psychology, Journal of School Psychology, Psychology in the Schools, and School Guidance and Counseling. The reference section of previous reviews, recent relevant publications, and articles identified in the computer and hand search were cross-referenced for articles that were included in the present analysis.


Coding

Variables included in this study were drawn from conclusions and recommendations derived from child therapy literature and meta-analyses of child and adolescent literature. Treatment and methodological variables in the present analysis included the following: how the treatment was measured, setting of treatment, type of treatment, effects of treatment, and effects of including a teacher-implemented contingency (Baer & Nietzel, 1991; Durlak, Fuhrman, & Lampron, 1991; Loeber, 1982; Schneider, 1992; Singh, Deitz, Epstein, & Singh, 1991; Verduyn et al., 1990; Weisz, Weiss, Alicke, & Klotz, 1987; Zaragoza, Vaughn, & McIntosh, 1991). Data relative to treatment setting were drawn directly from descriptive information reported by the respective study authors.

The client variables included in this study were socioeconomic status (SES), ethnicity, and diagnosis (if applicable). These variables are based on previous research (Baar & Nietzel, 1991; Durlak et al., 1991; Loeber, 1982; Schneider, 1992; Singh et al., 1991; Weisz et al., 1987; Zaragoza et al., 1991). Data relative to ethnicity, SES, and diagnosis were drawn from descriptive information reported by the respective study authors. Individuals were classified as belonging to a certain SES, ethnic, or diagnostic category based on the author's description or exceeding 70% of the total study population. Individuals were classified as belonging to a "mixed diagnosis" category if the respective study authors reported more than one diagnosis in their description.

The researcher coded all of the variables in this study. Ten articles were randomly chosen and coded independently by a second coder. This coder was a graduate student. The graduate student was trained by the researchers in the study on coding techniques, and was then given ten articles to code independently. The second coding was done to obtain interrater reliability of the coding. Total agreement or 100 percent interrater reliability was found.

Calculation of Effect Sizes

Effect sizes were calculated from the outcome statistics in each study using the DSTAT computer software package (Johnson, 1989). This software package utilizes the
following formula to obtain the effect size:

 

g = M2 - M1
S pooled

where g is the estimated effect size, M2 is the posttest mean for the treated group, M1 is the pretest mean for the same group before the treatment was administered, and S pooled refers to the pooled pretest/posttest standard deviation (Hedges 1982b; 1982c). An effect size was obtained by the above formula in order to compare behavior before and after cognitive behavioral treatment was implemented. When only the F or t statistics were provided in the articles being reviewed, a DSTAT formula to compute the effect size was utilized for decomposing the F or t . When chi-square values were provided, and the chi-square value was based on two groups, a direct conversion to an effect size was performed. In studies in which multiple outcome measures were reported, such as ratings from parents, teachers, and peers, the effect size was calculated from the teacher or paraprofessional group only. Also, if multiple treatments were compared in a study, the effect size was calculated separately for each treatment, resulting in multiple effect sizes from one study. The effect size is a reflection of the overall effectiveness of cognitive-behavioral treatment.
After each effect size g was calculated, mean weighted effect sizes (d) were computed using the sample size within the study as a weighting factor. The effect size can be interpreted as the change from pre- to posttest in standard deviation units. Interpretation in these units is standardized and avoids the problem of varying metrics based on different instruments. Probabilities for each weighted effect size (d) were also calculated. To aggregate results over studies, mean effect sizes are reported overall and by various moderator variables. These mean effect sizes are also associated with probability values.
To address the question of the efficacy of cognitive-behavioral therapy, an overall d was calculated on the overall effect size reflecting differences between pre- and post-cognitive-behavioral treatment to determine if this result was significant. Each of the individual and treatment variables was examined to identify if the variables were differentially related to the overall effect size. Categorical model testing was completed, and study qualities were utilized to account for variability in heterogeneous effect sizes. The QB statistic, a measure of between group homogeneity, was calculated in order to determine if the means of the classes tested significantly differed from one another. If the QB statistic is significant, it implies that the means of the classes tested are significantly different from one another.
Results
This study assessed the effectiveness of CBT in decreasing teacher reports of disruptive behavior by conducting a meta-analysis of existing research. The statistics in this analysis were utilized to estimate: (1) the overall effect of CBT; (2) the effect of teacher-implemented contingencies; (3) the effect of treatment setting; (4) the effect of SES; (5) the effect of ethnicity; and (6) the effect of diagnosis.
Data from each of the original 27 studies were critically analyzed and converted to an effect size if possible. Seven studies were omitted from the final analysis due to the data being insufficient in order to calculate an effect size. These 7 studies did not publish the appropriate statistical information necessary to calculate an effect size (examples include mean, standard deviation). Of the 20 studies included in the final review, effect sizes were calculated separately for the pretreatment/posttreatment difference for each outcome measure. All effect sizes were calculated immediately at posttreatment, and no follow-up data was included in the calculations. Each outcome measure was a standard measure that provided a teacher or paraprofessional rating of classroom disruptive behavior. The calculated effect size reflects overall pre-post improvement. This procedure produced 91 effect sizes. Three effect sizes were excluded from the final analysis because they were considered outliers in the list, leaving 88 effect sizes in the final analysis.
The overall mean effect size for all d values was .29. This indicates that children receiving cognitive-behavioral therapy displayed an approximately .3 standard deviation improvement in modifying disruptive behavior according to teacher and independent observer classroom reports. This study found that teacher implemented contingencies used in conjunction with CBT were not more effective in reducing disruptive behavior than CBT alone. A nonsignificant relationship (QB (1) = .25, p = .61) was found between teacher-implemented contingencies (d = .27) and non-teacher implemented contingencies (d = .30) for disruptive behavior. This study tested for the difference between treatments administered in a school setting (d=.30) versus a nonschool setting (d=.27). The setting of treatment was not found to be differentially related to treatment outcome (QB (1) = .17, p = .67). This meta-analysis tested for a difference between the low and low-middle Socioeconomic Status (SES) categories. The findings suggest that children classified as low SES (d = .50) showed significantly (QB (1) = 6.6, p = .01) greater changes in behavior than those children classified as low-middle SES (d = .21). A test of comparing children described as predominantly African American (d = .24), Caucasian (d = .36), mixed ethnicity (d = .10), or other (d = .27) suggests that children classified as being Caucasian showed significantly (QB (3) = 9.60 p = .02) greater improvements in behavior than children classified as mixed ethnicity. Finally, differences between children described as predominantly having no diagnosis (d=.29), ADD/ADHD (d=.31), conduct disorder (d=.43), or mixed diagnoses (d=.11) were calculated. The means of the four classes did significantly (QB (3) = 7.82, p = .04) differ. The findings suggest that children classified as having a diagnosis of conduct disorder (d = .43) showed significantly greater improvements in behavior than did children classified with mixed diagnoses (d = .11).

Discussion

The results of the present meta-analysis study found that cognitive-behavioral therapy is an effective form of treatment for school-age children with disruptive behavior. This study found that overall, cognitive-behavioral interventions were associated with improvements in behavior of approximately .3 standard deviations compared to pretreatment. Although the effect size from pre- to post-treatment is relatively small, it is arguable that any reduction in disruptive behavior is clinically meaningful. These results are consistent with other meta-analytic reviews in this area. For example, Baer and Nietzel (1991) in their meta-analytic review of cognitive and behavioral treatment of impulsivity in children, found that cognitive and behavioral interventions are associated with improvements in impulsivity of approximately one-third to three-quarters of a standard deviation relative to untreated or placebo controls. Dush, Hirt, and Shroeder (1989), in their meta-analysis of self-statement modification in children, reported that the children improved by one-third of a standard deviation compared to control groups. Zaragoza et al. (1991) conducted a meta-analytic review examining social skills interventions and their effectiveness on students with behavior problems. The authors found that social skills interventions led to changes in self, teacher, and parent perceptions. The aforementioned meta-analytic reviews indicate that CBT is an effective intervention for decreasing disruptive behavior. Moreover, Zaragoza et al. (1991) stated that parents and teachers frequently perceive that the child's behavior problems decreased following intervention. The results of the present study seem to support this assumption. According to this analysis, teachers do seem to indicate that children who participate in CBT intervention programs display fewer disruptive behaviors.
The present review failed to find a difference between studies that utilize teacher-implemented contingencies in conjunction with CBT versus studies utilizing CBT alone.

Mathur and Rutherford (1991), in their review of peer mediated interventions promoting social skills of children and youth with behavioral disorders, found that teacher prompts have played an important role in effective peer-mediated interventions. The finding from our study is contrary to the literature published in this area, and several possibilities are likely explanations for these results. First, it is possible that the particular type of CBT intervention was not appropriately suited for the classroom; therefore, this would decrease the chance teacher-implemented contingencies would be effective. Second, it is possible that the particular CBT intervention or the teacher-implemented contingency were not age-appropriate for the subject. A previous meta-analytic review of cognitive-behavioral therapy for maladaptive children (Durlak et. al., 1991) suggested that subject's age may be an important factor relative to efficacy of treatment. A third possible explanation for the results found may be that the teachers were not properly trained to administer the particular CBT intervention in the classroom. Finally, it is possible that teacher bias may exist and may influence successful implementation of therapeutic techniques in the classroom.
The results from this study raise several questions. How do teachers successfully reinforce therapeutic gains obtained by children who have received CBT? Do teacher perceptions of the child influence their ability to successfully implement interventions? These questions remain unanswered and would appear to be areas for future research inquiry.

The findings from this study suggest that the subjects in this review did not show gains in terms of treatment efficacy relative to the setting of treatment. The data from the teacher ratings indicated that this variable did not significantly affect disruptive behavior. Treatment administered in a school was not found to be significantly different from treatment administered in a hospital, an outpatient treatment facility, or other settings. A possible explanation for this finding may be that the children generalized the CBT intervention, making the particular environment in which they were taught certain skills to modify their behavior irrelevant. Increased attention is needed by future researchers to further test this variable.
Client populations described as lower SES demonstrated more improvement at the end of treatment than did those considered lower-middle SES. This finding is particularly important considering that disruptive behavior in youth has traditionally been more common in lower socioeconomic groups (Carson, Butcher, & Coleman, 1988). Conditions such as an environment characterized by the breakdown of social norms and regulations, disorganization of the subjects' social milieu, and undesirable peer and family models are often associated with the stress of poverty and may produce inadequate conscience development, lack of concern for others, and destructive or overt aggressive behavior (Carson et al., 1988). Traditional psychotherapeutic approaches have not proven to be effective in treating childhood disruptive behavior disorders in families of low SES. The findings from this meta-analysis indicate that CBT may be a promising treatment approach for lower income populations. This finding suggests that children from lower income level homes respond well to the cognitive structuring and organization that cognitive behavioral interventions offer. In Hoag and Burlingame's (1997) review of client variables in child and adolescent group treatment, middle class populations seemed to show greater improvement than did lower class ones. This finding is contrary to the findings of the present study. The differential effectiveness of treatment to various income populations warrants further investigation of this client variable in order to understand why lower income SES students seem to respond better to CBT interventions.

This meta-analysis found that Caucasian children seemed to benefit more from CBT interventions than did children classified as mixed ethnicity. One possible explanation for this finding may be that CBT intervention approaches are culturally biased toward a Caucasian population and may be a better match for a dominant Caucasian culture. Cognitive-behavioral therapy originated within Western culture and seems to be oriented toward Western or individualistic types of cultures. A second possible explanation for this finding may be associated with the degree of similarity of the ethnicity of the therapist to the ethnicity of the subject. Previous research demonstrates that a high degree of match between the subject and therapist's ethnicity is correlated with more effective therapy outcomes (Carson et al., 1988). A third possible explanation for this finding may be that there were more Caucasian therapists than therapists from other ethnic backgrounds. The literature regarding cognitive behavioral treatment and ethnic variables as a focus is essentially silent. The results from this review further indicate that more research is needed in this arena.
The results from this study indicated that CBT interventions were more effective with children classified as having conduct disorder. Conduct disorder is the mental health disorder most closely associated with adolescent antisocial behavior and is the most common childhood diagnosis in both clinical and hospital settings (Kirk, Wakefield, Hsieh, & Pottick, 1999). The social and economic impact of conduct disorder is tremendous. Conduct disorder has far-reaching effects into other systems, such as families, schools, law-enforcement agencies, juvenile offender programs, mental health agencies, as well as other social systems and society in general. The findings from this study support the notion that interventions based upon CBT principles may be an effective treatment approach for this devastating mental disorder. It is not surprising that CBT is effective in the treatment of conduct disorder. Cognitive-behavioral therapy approaches are designed to alter the maladaptive cognitions of the child and, in the process, change the maladaptive affect and overtly dysfunctional behaviors of the child diagnosed with conduct disorder. The findings of this study are in line with other studies, which promote the CBT approach as a micro-intervention strategy in helping children with conduct disorder (Alexander & Curtis, 1995; Kendall, 1993).

Several limitations exist in this study. First, this study analyzed the influence of SES, ethnicity, and diagnosis, but failed to analyze other variables that may influence outcome. Future research needs to identify these and other subject, treatment, and methodological variables influencing outcome. Future research may want to identify why lower SES, Caucasian, and children having been diagnosed with a conduct disorder seem to benefit more from CBT and what factors may be involved with this. Another limitation to this study involves the reliability and validity of the instruments utilized in the outcome measures. It was beyond the scope of this study to assess reliability and validity of the instruments in each outcome measure, but future research may want to code for this.

This study calls to the literature for more outcome research on cognitive-behavioral interventions. Although the literature purports that school age children are thought to benefit from cognitive behavioral types of interventions, it is surprising that so few evaluative studies have been conducted to assess the outcome of CBT programs over the decade, 1987 to 1997, that this review examined. This meta-analysis only produced 88 usable effect sizes, indicating a need for more outcome studies analyzing the effectiveness of CBT interventions with children.
Cognitive-behavioral therapy techniques are a popular treatment approach for children exhibiting disruptive and aggressive behavior. The extent to which these procedures, used alone or within in a multi component treatment framework, modify aggressive and disruptive behavior is still somewhat ambiguous. This meta-analysis demonstrated that children receiving cognitive-behavioral interventions exhibited fewer disruptive behavior problems at posttreatment according to classroom measures of disruptive behavior. It also showed that children who are Caucasian, from a lower socioeconomic status home, and diagnosed with conduct disorder seem to show the greatest benefit from CBT interventions.

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*Winer-Elkin, J. I., Weissberg, R. P., & Cowen, E. L. (1988). Evaluation of a planned
short-term intervention for schoolchildren with focal adjustment problems.
Journal of Clinical Child Psychology, 17(2), 106-115.
Zaragoza, N., Vaughn, S., & McIntosh, R., (1991). Social skills interventions and
children with behavior problems: A review. Behavioral Disorders, 16, 260-275.

* indicates studies included in the meta-analysis

 

Table 1. Selected Study Characteristics

Study No./ Citation Number of d's d p N
1. Bienert & Schneider (1995) 0      
2. Bierman, Miller, & Stabb (1987) 0      
3. Bloomquist, August, & Ostrander (1991) 10 (2 excluded)

0.13
-0.10
0.80
0.55
0.66
0.22
0.84

.68
.78
.01
.12
.04
.52
.02

20
16
20
16
20
16
20
4. Dishion & Andrews (1995) 3 -0.13
0.19
.0.06
.61
.48
.82
30
27
28
5. Dubow, Heuesman, & Eron (1987) 0      
6. Guevremont & Foster (1993) 6

0.39
-0.59
-0.43
-0.71
0.81
1.29

.15
.03
.11
.01
.00
.00
28
28
28
28
28
28
7. Horn, Ialongo, Greenberg, Packard,
& Smith-Winberry (1990)
0      
8. Horn, Ialongo, Popovich, & Peradotto (1987) 8 0.55
0.58
0.42
0.74
0.28
0.43
0.40
0.52
.17
.15
.29
.07
.50
.30
.34
.21
12
12
12
12
11
11
11
11
9. Hudley & Graham (1993) 18  0.11
-0.06
0.21
0.00
0.18
0.47
-0.13
-0.20
0.28
0.19
-0.04
0.18
0.27
-0.04
0.33
0.00
-0.42
 .83
.91
.67
1.00
.72
.35
.79
.68
.57
.71
.94
.74
.61
.41
.53
1.00
.43
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
10. Kazdin, Bass, Siegel, & Thomas (1989) 2 -0.49
1.13
0.99
.36
.02
.04

6
10
10

11. Kazdin & Crowley (1997) 6 (1 excluded) 0.53
0.35
0.47
1.26
1.32

.03
.15
.05
.00
.00

34
34
34
32
32

12. Kazdin, Esveldt-Dawson, French, 2
& Unis (1987)
2 0.66
-0.42
0.00
0.00
120
120
13. Kendall, Reber, McLeer, Epps,& Ronan (1990) 1 1.11 .00 17
14. Lochman (1992) 7 0.21
0.71
-0.61
-0.71
0.53
0.57
0.35
0.42
0.01
0.02
0.01
0.046
0.03
0.28
29
29
29
29
29
29
29
15. Lochman, Coie, Underwood, & Terry (1993) 0      
16. Lochman & Lampron (1988) 1 0.95 .06 9
17. Lochman & Lampron (1989) 0
18. McGillivray, Cummins, & Prior (1988) 4

-0.02
0.33
0.18
0.50

0.96
0.38
0.67
0.23
13
13
11
11
19. Omizo, Hershberger, & Omizo (1988) 2 0.41
0.55
.39
.25
9
9
20. Phillips, Schwean, & Saklofske (1987) 2 1.06
0.83
0.1
0.4
12
12
21. Prinz, Blechman, & Dumas (1994) 4 1.12
0.64
1.42
1.27
0.0
0.01
0.00
0.00
165
31
18
12
22. Schneider (1991) 8 -0.56
-1.06
0.53
-0.53
0.05
-0.47
-0.27
-.07
0.01
0.02
0.02
0.02
0.84
0.4
0.24
0.77
42
42
42
42
38
38
38
38
23. Tremblay, McCord, Boileau, Charlebois,Gagnon, Le Blanc, & Larivee (1991) 3 0.86
0.22
0.20
.01
0.47
.50
21
21
21
24. Tremblay, Pagani-Kurtz, Masse, Vitaro,& Pihl (1995) 2 0.42
0.42
0.08
0.07
35
35
25. Verduyn, Lord, & Forrest (1990) 0
26. Vitaro & Tremblay (1994) 1 0.30 .18 39

27. Winer-Elkin, Weissberg, & Cowen (1988)
0.48 .15 17
OVERALL: 1 0.29 .00 88

 

Table 2: Selected Characteristics Included in the Meta-Analysis

Characteristics Number of studies %
Ethnicity (predominantly)
African American 3 11
Caucasian 7 26
Not specified 11 41
Mixed 6 22
Socioeconomic status
Lower/social assistance 5 19
Lower middle 6 22
Not specified 16 59
Diagnosis (predominantly)
Normal/no diagnosis 19 70
ADD/ADHD 3 11
Conduct disorder 3 11
Mixed diagnosis 1 4
Other diagnosis 1 4

 

First Published July 2004


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