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Psychological Bulletin1995, Vol. 117, No. 3,450-468 Copyright 1995 by the American Psychological Association, Iical Association, Inc.0033-2909/95/$3.00

Effects of Psychotherapy With Children and Adolescents Revisited:A Meta-A nalysis of Treatment Outcome StudiesJohn R. Weisz

University of California, Los AngelesBahr Weiss

Vanderbilt UniversitySusan S. Han and Douglas A. GrangerUniversity of California, Los Angeles Todd MortonUniversity of North Carolina, Chapel Hill

A meta-analysis of child and adolescent psychotherapy outcome research tested previous findingsusing a new sample of 150 outcome studies and weighted least squares methods. The overall meaneffect of therapy wa s positive and highly significant. Effects were more positive fo r behavioral thanfor nonbehavioral treatments, and samples of adolescent girls showed better outcomes than otherAge X Gender groups. Paraprofessionals produced larger overall treatment effects than professionaltherapists or students, but professionals produced larger effects than paraprofessionals in treatingovercontrolled problems (e.g., anxiety and depression). Results supported the specificity of treat-ment effects: Outcomes were stronger for the particular problems targeted in treatment than fo rproblems not targeted. The findings shed new light on previous results and raise significant issues forfu ture study.

Over the past decade, applications of the technique knownasmeta-analysis (see Cooper & Hedges, 1994; Mann, 1990;Smith, Glass, & Mller, 1980) have enriched ou r understandingof the impact of psychotherapy with children and adolescents(herein referred to collectively as "children"). At least threegeneral meta-analyses encompassing diverse treatment methodsand diverse child problems have indicated that the overall im-pact of child psychotherapy is positive, with effect sizes averag-ing not far below Cohen's (1988) threshold of 0.80 for a "large"effect. Casey and Herman (1985 ) reported a mean effect size of0.71 for a collection of treatment outcome studieswith children12 years of age and younger (studies published from 1952-1983). Weisz, Weiss, Alicke, an d Klotz ( 1 9 8 7 ) reported a meaneffect size of 0.79 for a collection of studies with youth 4-18years old (studies published from 1958-1984). Kazdin, Bass,

John R. Weisz, Susan S. Han, and Douglas A. Granger, Departmentof Psychology, University of California, Los Angeles; Bahr Weiss, De-partment of Psychology and Human Development, Vanderbilt Univer-sity; Todd Morton, Department of Psychology, UniversityofNorth Car-olina, Chapel Hill.Th e work reported here was facilitated by National Institute of Men-tal Health (N IMH) Research Scientist Award K05 MH 01 1 6 1 , NIMHResearch Grant R01 MH49522, NIMH Grant 1-R18 SM50265, andSubstance Abuse and Mental Health Services Administration Grant 1-HD5 SM50265-02.W e are grateful to Danika Kauneckis and Julie Mosk for their helpwith various phases of the project. We also thank the outcome studyauthors who provided us with information needed to calculate effect-size values fo r this meta-analysis.

Correspondence concerning this article should be addressed to JohnR. Weisz, Department of Psychology, Franz Hall, University of Califor-nia, 405 Hilgard Avenue, Los Angeles, California 90024-1563. Elec-tronic mail may be sent via Internet to [email protected].

Ayers, and Rodgers (1990) assembled a collection of studiespublished between 1970 and 1988 focused on youth 4-18 yearsof age; mean effect sizes were 0.88 fo r treatment versus no-treat-ment comparisons and 0.77 for treatment versus active controlcomparisons. Combined, these three meta-analyses suggest thatpsychotherapy may have significant beneficial effects with chil-dren and adolescents (for a more detailed review of the meta-analytic procedures, findings, and implications, see Weisz &Weiss, 1993; Weisz, Weiss, & Donenberg, 1992).

In addition to generating overall estimates of therapyeffectiveness, meta-analyses can provide evidence on factorsthat may be related to psychotherapy outcome. For example,meta-analytic evidence has fueled a lively debate over whethertherapy outcomes differ as a function of the type of interventionused. Much of the adult therapy outcome literature has sug-gested that various forms of therapy work about equally well.One of the general conclusions reached by Smith et al. (1980)in their landmark meta-analysis was as follows:

Psychotherapy is beneficial, consistently so and in many ways. . . .Different types of psychotherapy (verbal or behavioral, psychody-namic, client-centered, or systematic desensitization) do not producedifferent types or degrees of benefit. . . .[It is]. . . clearly possiblethat all psychotherapies are equally effective, or nearly so; and thatthe lines drawn among psychotherapy schools are small distinctions,cherished by those who draw them, but all the same distinctions thatmake no important differences, (pp. 184, 186)

This conclusion has come to be called "the Dodo verdict" (i.e.,"Everybody has won and all must have prizes"; see Parloff,1984).The picture may be different in the area of child psychother-apy, but the evidence is somewhat mixed thus far. Casey andHerman (1985) initially found that behavioral methods yieldedsignificantly larger effect sizes than nonbehavioral methods;450


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CHILD AND ADOLESCENT PSYCHOTHERAPY EFFECTS 45 1however, when they excluded cases in which outcome measureswere "very similar to activities occurring during treatment" (p.391), the superiority of behavioral methods was reduced to astatistically marginal level (p = .06; R. J. Casey, personal com-munication, July 30, 1992). Weisz et al. (1987) also found ini-tially that, overall, behavioral treatmentsgenerated significantlylarger effects than nonbehavioral treatments. Weisz et al. theneliminated only those outcome assessments for which outcomemeasures were unnecessarily similar to treatment activities.The rationale was that, with some treatments, the most validtest of efficacy may require an outcome measure that resemblesthe treatment activity; for example, when one treats a child'sfear of dogs by graduated steps of approach, the most valid testof outcome is probably a behavioral test of the child's abilityto approach dogs (i.e., an outcome measure that is necessarilysimilar to the treatment activities). For other treatments, bycontrast, such resemblance is clearly unnecessary; for example,researchers who treat impulsivity through training on theMatching Familiar Figures Test (MFFT; see Kagan, 1965) andthen use the MFFT to assess treatment outcome are using anunnecessarily similar outcome measure; it is not necessary touse the MFFT asan outcome measure because the goal of train-ing is reduction of impulsivity, which can be measured in other,more ecologically valid ways than through readministration ofthe MFFT. After eliminating cases of unnecessary similarity,Weisz et al. (1987) found that behavioral therapies still gener-ated significantly more positive effects than nonbehavioral ap-proaches. Yet, meta-analytic findings on the relative effects ofbehavioral and nonbehavioral therapies remain a subject ofcontroversy (e.g., see Weiss &Weisz, in press).

It is important that this issue and other controversial issuesbe addressed through new meta-analyses as new outcome stud-ies are published. Given the inevitable variability of treatmenteffects across studies and the possibility of temporal shifts asmethods evolve, it is necessary to assess the replicability of keyfindings across successive samples of treatment studies. As pat-terns are replicated across multiple meta-analytic samples, theymay be accepted with increasing confidence. Of course, replica-tion of findings across overlapping samples of studies may notbe useful , because the overlap introduces a bias in favor of rep-lication. Accordingly, in the present meta-analysis, we includedonly studies that had not been included previously in the twomajor comparative meta-analyses of child-adolescent psycho-therapy research published thus far (i.e., Casey & Berman,1985; Weisz etal., 1987).

Beyond the question of therapy method effects, it was impor-tant to test whether psychotherapy effects differ with the age oftreated youngsters. Research on developmental differences incognitive and social capacities (see Piaget, 1970; Rice, 1984)and on developmental differences in conformity to social normsand responses to adult authority (see Kendall, Lerner, & Craig-head, 1984) suggests that, as children grow older, they may be-come less cooperative with adult therapists and less likely to ad-just their behavior to societal norms. On the other hand, thecognitive changes (e.g., development of abstract thinking andhypotheticodeductive reasoning) that accompany maturationmight also mean that, in contrast to children, adolescents betterunderstand the purpose of therapy and are better suited to theverbal give-and-take that accompanies many forms of therapy

( for thoughtful discussions of diverse developmental issues re-lated to child psychotherapy, see Holmbeck & Kendall, 1991;Shirk, 1988). However, the evidence on age and therapy out-come is mixed thus far. Casey and Berman (1985) found norelation between child age and study effect size, but Weisz et al.(1987) found a significant negative relation suggesting thatolder youth showed less positive changes in therapy than didtheir younger counterparts.Several other previous findings need to be tested for robust-ness through fur ther meta-analysis. Are girls more responsiveto therapy than boys?The evidence is mixed thus far. Casey andBerman (1985) found that studies involving predominantlygirls had better outcomes than studies involving mostly boys,but Weisz et al. (1987) found no significant relation betweenoutcome and child gender.Do therapy effects differ for differenttreated problems? Here, too, the evidence is mixed. Casey andBerman found a lower mean effect size for social adjustmentproblems than for phobias, somatic problems, or self-controlproblems, but Weisz et al. found no reliable differences amongsuch specific categories or between the broad categories of over-controlled (e.g., phobias and social withdrawal) and undercon-trolled (e.g., delinquency and noncompliance). Finally, meta-analytic comparisonscan help one learn whether treatment out-comes are related to therapist experience. Casey and Bermanfound no relationship. However, although Weisz et al. alsofound no overall relationship, they did find two potentially in-formative interactions. Age and effect size were uncorrelatedamong children who saw professional therapists, but graduatestudents and paraprofessional therapists (e.g., trained teachersand parents) produced better outcomes with younger childrenthan with older ones. In addition, professionals, students, andparaprofessionals did not differ in their success with undercon-trolled children, but as amount of training and experience in-creased, so did effectiveness with overcontrolled children. Fur-ther evidence is needed to test the robustness of such effects.A final substantive purpose of the current meta-analysis wasto address the theoretically and practically important questionof whether treatment effects with children are specific to theproblems being addressed in treatment. Focusing on therapywith adults, Frank (1973) and others (see Brown, 1987) haveargued that therapy has a variety of "nonspecific effects" (e.g.,increasing the client's hopes and expectations of relief, produc-ing cognitive and experiential learning, generating experiencesof success, and enhancing feelings of being understood). Suchspeculation has led some outcome researchers (e.g., Bowers &Clum, 1988; Horvath, 1987)to explore the specificity of effectsin psychotherapy (i.e., the extent to which an intervention'seffects are specific to the theoretically targeted symptom do-main vs. generalized across other symptom domains). Some(e.g., Horvath, 1988) have even taken the position that psycho-therapy effects are "artifactual" to the extent that the therapyinfluences theoretically off-target symptoms. In the presentstudy, weprovided what appears to be the first test of treatmentspecificity in a broad-based meta-analysis of child outcome re-search. We tested whether treatment effects were larger for thespecific target problems being addressed in therapy than fornontarget problems.

In addition to the substantive aims of the meta-analysis, wesought to address a little-noted but potentially critical statisti-


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452 WEISZ, WEISS, HAN, GRANGER, MORTONcal-analytic concern. Previous general meta-analysis of thechild outcome literature have used the unweighted least squares(ULS) general linear model analytic approach (which sub-sumes regression an d analysis of variance [ANOVA]) initiallyused by Smith et al. (1980 ).' For this approach to be preciselyvalid, several assumptions must be met, including the assum p-tion of homogeneity of variance. This means that (a) the vari-ance for the dependent variable for diiferent subgroups (e.g.,behavioral vs. nonbehavioral treatments) or within differentANOVA cells must be equivalent and (b) the variances of indi-vidual observations (i.e., in the case of meta-analysis, the indi-vidual effect sizes) must be equivalent acrossobservations.It may seem anomalousto refer to the variance of a singleobservation or, in the case of meta-analysis, the variance of asingle effect size. However, in meta-analysis, the variance of aneffect size (which refers to the reliability of that effect size) isdirectly computable and is, in part, a function of the samplesize of the study on which the effect size is based. Becausedifferent studies often have quite different sample sizes, it is un-likely that the homogeneity assumption is satisfied in mostmeta-analyses (Hedges & Olkin, 1985).To addressthis problem in the curre nt analyses, we analyzedou r data using the weighted least squaresgeneral linear modelsapproach described by Hedges and Olkin (1985; see alsoHedges, 1994), weighting effect sizes by the inverse of their vari-ance. One drawback of our using this approach exclusivelywould be that meaningful comparison of the present findingswith previous meta-analytic findings would be hampered; itwould be impossible to determinewhether differences betweenpresent an d previous findings resulted from substantive differ-ences in the relations among variables or from differences inanalytic methods. Consequently, to facilitate comparison withprevious findings, we report results fo r the current sample withboth the WLS method, which we believe generates the mostvalid results, and the ULS general linear model method,whichwe(Weiszetal . , 1987)ando thers (e .g . ,Casey&Berman ,1985)had used previously. To our knowledge, no su ch direct compar-ison has been made in previous meta-analyses.

MethodA s in our previous meta-analyses (Weiss & Weisz, 1990; Weiszet al.,

1987), wedefinedpsychotherapy as any intervention intended to allevi-ate psychological distress, reduce maladaptive behavior, or enhanceadaptive behavior through counseling, structured or unstructured in-teraction, a training program, or a predetermined treatment plan. W eexcluded treatments involving drugs, interventionsinvolving only read-in g (i.e., bibliotherapy), teaching or tutoring intended only to increaseknowledge of a specific subject, interventions involving only relocation(e.g., moving children to a foster home), an d exclusively preventive in -terventions intended to prevent problems in youngsters considered tobe at risk. W e included psychotherapy conducted by fully trained pro-fessionals, as well as psychotherapy conducted by therapists in training(e.g., clinical psychology and social work students and child psychiatryfellows) and by trained paraprofessionals (e.g., teachers an d parents).Different schools of thought differ on the issue of whether extensive pro-fessional training is required fo r effective intervention. Here we treatedthis issue as an empirical question (see later discussion).Literature Search

W e included only published psychotherapy outcome studies, relyingon the journal review process as one step of quality control. W e used

several approaches to identify relevant published studies (c f. Reed &Baxter, 1994; White, 1994). First, we conducted a computer search fo rth e period January 1983 through April 1993, using th e same 2 1 psycho-therapy-related ke y terms used in Weisz et al. ( 1 9 8 7 ) crossed with th esame age-group constraints and outcome-assessment constraints usedin that meta-analysis. Second, still focusing on the 1983-1993 time pe -riod, we also searched by hand, issue by issue, 30journals that hadproduced articles in our 1987 meta-analysis. Third, and finally, we re-viewed the list of studies included in previous meta-analyses conductedby Smith et al. ( 1 9 8 0 ) an d Kazdin et al. ( 1 9 9 0 ) to identify an y articlesfitting our criteria that might have been missed in the other tw o steps ofou r search an d that had not been included in the Casey an d Herman(1985) o r Weisz et al . (19 87) meta-analysis. We did not exclude studiesincluded in the Kazdin et al . (19 90) surveyan d meta-analysis becausewe wanted to include tests of the impact of such factors as treatmentmethod, treated problem, and therapist experience (tests that were nota focus of the Kazdin et al. report, which included only overall meaneffect size values).Design and Reporting Requirements

To be included, a study had to include a comparison of a treatedgroup with an untreated or attention control group. W e excluded stud-ie s reporting only follow-up data (i.e., with no immediate posttreat-m e n t data). W e excluded single-subject or within-subject designs. Suchstudies generate an unusual form of effect size (e.g., one based on intra-part ic ipant variance, which i s not comparable to conventional variancestatistics) and, thus, do not appear to warrant equal weighting withstudies that include independent treatment and control groups.Outcome Studies Generated by the Search

These several steps produced a pool of 15 0 studies2 (marked with anasterisk in the References) involving 2 44 different treatment groups.The studies had been published between 1967 and 1993. Across the 150studies, the mean age of the children ranged from 1.5 to 17.6 years (M= 10.50, SD = 3.52). Because the concept of "psychotherapy" withchi ldren 1.5 years old may seem implausible, we should note that stud-ie s focusing on very young children involved parent-training interven-tions focused on such early adjustment problems as f requent waking atnight .Coding of th e Studies

We coded studies for sample, therapy method, and design features,with parts of our coding system patterned after Casey and Berman(1985) and most of the system matching that used by Weisz et al.( 1 9 8 7 ) ; this overlap facilitated comparison with previous f indings.Effect-size calculation an d coding of the studies were carried ou t inde-pendent ly to avoid contamination. After training in the use of the cod-ing system, four coders (i.e., four of the authors [two graduate students,on e postdoctoral fellow, and one faculty member]) independently

1 One exception to this generalization was a meta-analysis by Durlak,Fuhrman, and Lampman ( 1 9 9 1 ) , which focused on the effects of cog-nitive-behavioral interventions with children. Durlak et al. used aweighted least squares (WLS) group partitioning approach described byHedges and Olkin ( 1 9 8 5 ) .2 Two of these studies were reported in a single article by Edleson andRose (1982). Also, two Strayhorn and Weidman (1989, 1991) articlesare reports of an original treatment study and its follow-up findings,respectively; thus, the two reports were coded as a single outcome studyin our database.


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CHILD AND ADOLESCENT PSYCHOTHERAPY EFFECTS 45 3Table 1Mean E f f e c t Size and Significance Value (Versus 0)for Each Type of Therapy

Weighted leastsquaresTreatment type

BehavioralOperantPhysical reinforcementConsultation in operant methodsSocial/verbal reinforcementSelf-reinforcementCombined physical/verbal reinfMultiple operant methodsRespondentSystematic desensitizationRelaxation (n o hierarchy)Multiple respondentBiofeedbackModelingLive nonpeer modelNonl ive peer modelNonlive nonpeer modelSocial skillsCognitive/cognitive behavioraltherapyParent train ingMultiple behavioralBehavioral, not otherwise specifiedNonbehavioralClient centeredInsight orientedDiscuss ion groupNonbehavioral , not otherwise specifiedMixed

19719523252312233312

1101

233836353276910220

Effect size0.540.85,1.671.591.241.290.850.060.45*1.860.410.420.200.40,,,:0.230.340.850.28C0.57b0.49*0.610.330.300.110.300.400.460.63

P.0000.0000.0000.0000.0000.0000.0000.1554.3611.0026.0250.0023.0000.0000.0000.1507.0000.4218.0072.0009.0000

Unweighted leastsquaresEffect size

0.761.69a2.432.171.183.571.380.060.70b1.340.720.540.120.73ab0.240.790.870.37b0.67b0.56b0.860.380.350.150.310.480.380.55

P.0000.0086. 1119.3312.0616.0005.0022.0959.3564.1018.1905.0095.0000.0000.0015.0486.0001.0884.0547.0122.0002

Note, Tier 2 therapy types (e.g., operant an d respondent) differed significantly for the behavioral categories(p < .01 for both the weighted and unweighted least squares methods) but not for the nonbehavioral cate-gories. Those Tier 2 behavioral categories that share a subscript did not differ significantly. For this table, asfor results reported in the text, effect sizes were computed by collapsing up to the level of analysis (i.e., eachstudy provided, at most, one effect size for each therapy category). However, in this table, sample sizes werecomputed without collapsing so as to provide information on the number of different treatment groups inour sample (i.e., the column labeled n shows number of treatment groups). Reinf = reinforcement.

coded 20% of the sample of studies. Mean interrater agreement (kappa)across pairs ofcoders isreported later fo r the various parts of the system.Therapy methods. The three-tiered system shown in Table 1 wasused in classifying therapy methods. Tier 1 included the broad catego-ries behavioral an d nonbehavioral ( m e a n K = .83). Tier 2 included sub-categories within each Tier 1 category (e.g., operant an d client centered;

K =.75). Tier3 included finer grained descriptors applicable only to thebehavioral methods (e.g., relaxation only vs . extinction only [within theTier 2 respondent category]; < c = .70). W e also coded each treatment aseither group or individually administered ( K = .88).Target problems. Problems targeted by the treatment in the variousstudies were coded by means of the two-tiered system shown in Table2. First, problems were grouped into either one of the two broadbandcategories most often identified in factor analyses of child behaviorproblems (e.g., se e Achenbach & Edelbrock, 1978) overcontrolled(e.g., social withdrawal) and undercontrolled (e.g., aggression)or another category ( K = .95). Tier 2 included descriptive subcategories (e.g.,delinquency, depression, an d social relations) within each Tier 1 cate-gory (K = .79).

Outcome measures. Following Casey an d Berman (1985) , wecoded whether outcome measures were similar to treatment activities ( K

= .79). As noted earlier (and see detailed rationale in Weisz et al,,1987), we used an additional step of coding fo r outcome measures thatwere rated as similar to treatment activities; such measures were codedfor whether the similarity was necessary (given the treatment goals) orunnecessary for a valid assessment ( K = .60).Following Casey and Berman ( 1 9 8 5 ) , we also coded outcome mea-

sures into source and domain/type. Source of outcome measure in-cluded such categories as observers, therapists, parents, an d partici-pants ' own performance ( K = .88). Domain included such content cate-gories as fear-anxiety, aggression, an d social adjustment (K = .87),grouped into broadband overcontrolled and undercontrolled catego-ries. It may be useful to clarify th e distinction between problem typeand domain, both of which involved the same overcontrolled and un-dercontrolled broadband categories as well as the same Tier 2 codes.Problem type categories were used to classify the problems that werethe target of the treatment intervention in a study, whereas domain cat-egories were used to classify each of the individual outcome measuresused in a study.

Therapist training. Weclassified therapists as to their level of pro-fessional training (K = .87). In our system, therapists were classified asprofessionals if they held a doctoral degree in medicine and had com-


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45 4 WEISZ, WEISS, HAN, GRANGER, MORTONTable 2Mean E f f e c t Size an d Significance Valu e (Versus 0)for Each Type of Target Problem

Target problemWeighted least squaresEffect size p

Unweighted leastsquaresEffect size p

UndercontrolledDelinquencyNoncomplianceSelf-controlAggressionMultiple undercontrolledOvercontrolledPhobias/anxietySocial withdrawa lDepressionMultiple overcontrolledSomatic (headaches)OtherAcademicLow sociometric/peer acceptanceSocial relationsPersonalityAdditional "other" problemsMultiple other

5974181 119401646

113554115

1223

0.520.65a0.39at>0.44a0.32 b0.490.520.600.660.640.390.370.561.31a0.47b0.56b0.680.47

.00000.00000.04721.00002.00403.00000.00000.00000.00243.00011.00009.00000.00000.00000.00071.00000.00000

0.620.420.420.870.340.670.690.570 . 7 10.670.400.860.810.221.031 . 1 20.531 . 1 80.66

.00000.00691.05794.02053.00802.00374.00000.00106.15998.01076.01034.00000.02506.08014.04571.00343.01972.00037

Note. Differences among Tier 2 problem type categories (e.g., self-control and aggression) were signific antonly with the weighted least squares method and only for two of the three broadband categories: undercon-trolled (p < .05) and other (p < .001). Within each of those broadband categories, the Tier 2 categories thatshare a subscript did not d i f f e r significantly from one another. Note that academic problems were no tincluded in weighted least s quares analyses (see text fo r rationale) and that the Additional "other" problemsand Multiple other categories were no t included in two-way comparisons because they were too heteroge-nous to be meaningful.

pleted psychiatric training or if they had completed a terminal doctor-ate or master's degree in psychology, education, or social work; theywere classified as graduate /professional students if they were workingtoward professional credentials in psychiatry or toward advanced de-grees in psychology, education, or social work; and they were classifiedasparaprofessionals(e.g., parents and teachers) if they lacked graduatetraining related to mental health but had been trained specifically toadminister the therapy. For a group to be categorized at one of thesethree levels, at least two thirds of the therapists had to fit the level.Clinical versus analog samples. W e also coded studies forwhether th e samples were clinical (i.e., th e youngsters were actuallyclinic referred or otherwise would have received t reatment regardlessof th e s tudy) or analog (i.e., th e youngsters were recruited for thestudy an d might no t have received treatment had it not been for thestudy;K = .89).

ResultsOverview of Data-Analytic Procedures

Before we report results, several data-analytic issues need tobe considered.Confounding of independent variables. A common problemin meta-analysis is that independent variables (e.g., therapymethod and target problem) tend to be correlated (e.g., seeGlass &Kliegl, 1983; Mntz, 1983). For example, because cer-tain therapy methods tend to be used with certain target prob-lems (e.g., behavioral methods with phobias), there is a naturalconfounding of therapy type and problem type. Here we used

an approach intended to address confounding while avoidingundue risk of either Type I or Type II error. Avoiding Type IIerror is especially important in meta-analyses given their poten-tial heuristic,hypothesis-generating value.

In an initial wave of analysis, we conducted planned tests fo-cused on five variablesof primary interest: therapy type, targetproblem type, child age, child gender,and therapist training. Foreach variable, we first tested the simple main effect. Then wetested the robustness of the main effect using general linearmodels procedures to control statistically for the effects of eachof the other four variables (see Appelbaum & Cramer, 1974);we covaried these variables individually in separate analyses,rather than simultaneously, to reduce the risk of capitalizing onchance. Finally, we tested each main effect for whether it wasqualified by two-way or three-way interactions involvingany ofthe other four variables (cf. Hedges, 1994).

Effect-size computation. As in our 1987 meta-analysis, wecalculated effect sizes by dividing each study's posttherapytreatment group versus control group mean difference by thestandard deviation of the control group. When means or stan-dard deviations were not reported in the published article, weattempted to contact the author(s) to obtain the missing infor-mation. In those cases in which such efforts were unsuccessful,we used the procedures recommended by Smith et al. (1980) toderive effect-size values from inferential statistics such as t or Fvalues; for reports of "nonsignificant" effects unaccompaniedby any statistic, we followed the conservative procedure of esti-


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CHILD AND ADOLESCENT PSYCHOTHERAPY EFFECTS 455mating the effect size at 0.00. In calculating effect-size values,some meta-analysts (e.g., Casey & Herman, 1985; Hedges,1982) favor dividing by the pooled standard deviation of treat-ment and control groups, but others (e.g., Smith et al., 1980)believe that pooling is inappropriate because one effect of treat-ment may be to make variability greater in the treatment groupthan in the control group. Our previous analyses (see Weiss &Weisz, 1990) support the latter position. Nonetheless, for com-parison purposes, we considered computing effect-size valuestwice in the present meta-analysis, once based on the pooledstandard deviation and once based on the control group stan-dard deviation. Before we could do this, it was necessary to testwhether treatment and control group variances differed signifi-cantly. We found that, for the present sample of studies averagedwithin study, treatment and control group variances were reli-ably different (mean z = 0.23, N=79,p< .05) and, thus, thatuse of the pooled standard deviation was not appropriate. Ac-cordingly, in calculatingeffect-size values for the present sampleof studies, we divided by the unpooled control group standarddeviation. Throughout our calculations, we consistentlycol-lapsed across outcome measures and treatment groups up to thelevel of analysis. For example, we collapsed across treatmentgroups except when we tested the effects of therapy type.

As noted earlier, we analyzed our data using two different ap-proaches to permit comparisons between previous and presentresults unconfounded with analytic differences. The primaryanalyses involved the WLS approach, with each effect sizeweighted by the inverse of its variance (Hedges, 1994; Hedges &Olkin, 1985); this adjusted for heterogeneity of variance acrossindividual observations. In the WLS analyses, we did not in-clude academic outcomes (e.g., school grades), and we droppedoutliers (i.e., effect sizes lying beyond the first gap of at leastone standard deviation between adjacent effect-size values in apositive or negative direction; Bollen, 1989).3 We dropped aca-demic outcomes because so many factors (e.g., intelligence)other than psychopathology could be responsible for poor aca-demic performance that it seemed inappropriate to base tests ofpsychotherapy eff icacy on such outcomes. We dropped outliersso that our results would fairly represent the large majority ofthe data. Our secondary analyses, included for comparisonpurposes only, used the ULS approach (with academicout-comes and outliers included) used in previous meta-analysesconducted by Casey and Berman (1985), Kazdin et al. (1990),Smith et al. (1980), and Weiszet al. (1987).Overall Mean E f f e c t Size: WLS and ULS Findings

When we used the WLS method of analysis, with one effectsize per study, the mean effect size across the 15 0 studies was0.54 (significantly different from 0), X2( 1, N = 150) = 404.65,p < .000001. When we used the ULS method, again with oneeffect size per study, the mean effect size was 0.71 (significantlydifferent from 0), t( 149) = 9.49, p < .000001. The latter meanwas comparable to the ULS-derived means reported in earlierchild meta-analyses conducted by Casey and Berman (1985; Meffect size = 0.71), Weisz et al. (1987; M effect size = 0.79),and Kazdin et al. (1990; Meffect size = 0.88for treatment vs.nontreatment comparisons, and M effect size = 0.77 for treat-ment vs. active control groups). As the WLS and ULS figures

illustrate, one effect of the WLS adjustment is that it often pro-duces lower mean effect-size values when one averages acrossmultiple studies; larger effect-size values tend to have smallerweights because they usually involve smaller sample sizes andlarger variances than do smaller effect-size values.Therapy Type: Behavioral Versus NonbehavioralInterventions

Primary analysis with WLS. The mean effect size with theWLS method was higher for behavioral therapies than for non-behavioral therapies (effect-size means: 0.54 vs. 0.30), x2(l,N- 149) = 9.96, p < .005. The difference remained significantwhen we controlled for age, gender, and therapist training andwas marginally significant (p < .10) when we controlled forproblem type. This main effect of therapy type supports the hy-pothesis that behavioral treatments are more effective than non-behavioral treatments. However, it is possible that the effects ofbehavioral treatments are less enduring than those of nonbe-havioral treatments. If this were the case, the apparent superi-ority of behavioral treatments would be significantly qualified.W e tested this possibility by comparing the difference betweenposttreatment and follow-up effect sizes for behavioral versusnonbehavioral treatments. The test wasnonsignificant, indicat-ing that behavioral and nonbehavioral methods did not differ inthe durability of their effects.All two-way interactions between therapy type and the otherfour variables were nonsignificant. However, the Therapy TypeX Child Age XTherapist Training interaction was significant,X 2 ( 1, N = 99) = 9.49, p < .01. Of the component two-way in-teractions, only two were significant. First, among paraprofes-sional therapists only, therapy type and child age interacted (p< .005), indicating that paraprofessionals treating children(but not adolescents) produced a larger mean effect size withbehavioral than with nonbehavioral therapies (means: 1.2 vs.0.46, p < .005) and that paraprofessionals using behavioral (butnot nonbehavioral) methods produced larger effect sizes withchildren than with adolescents (means: 1.20vs. 0.03,p children***Female >male******

Paraprofessional >professional >student***

UL SBehavioral >nonbehavioral**

Female > male*

Paraprofessional >professional =student**

Significant after controlW LS

Problem typeChild ageChild genderTherapisttrainingChild gender8Therapy type3Problem typeChild genderTherapy type3Problem typeChild ageTherapisttrainingTherapy type3Problem typeaChild ageChild gender

ULSProblem typeChild ageChild gender"Therapistt raining

Therapy type aTherapisttrain ing

Therapy typeProblem typeChild age

Significant interaction withW LS

Therapist training******Child gender*****Therapist training****Child age*****Therapist training***

Problem type******Child age****Child gender***

ULS

Child gender*Therapisttraining***Problem type*Therapisttraining*

Child age***Child gender*

Note. Listings in the column labeled Significant after control indicate that th e main effect shown at left remained significant when th e variablelisted in the colu mn was controlled. WLS = weighted least squares; ULS = unw eighted least squares.a Main effect became marginal (p < . 10) when variable wa s controlled.*p


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460 WE ISZ, WEISS , HAN, GRANG ER, MORTONparison; thus, fo r these last two analyses, we report only W LSfindings. In the first such analysis, we assessed whether year ofpublication was related to effect size, to test wh ether such a re-lationship might explain differences between the present find-ings and those of Weisz et al. ( 1 9 8 7 ) . Accordingly, we dividedth e studies into pre-1985 (n = 60) and 1986-1993 ( = 91)subsets (1985 was the cutoff date for the sample of studies in -cluded in Weisz et al., 1987 ). In our prima ry analysis, using theW LS method, the main effect fo r year was nonsignificant; alsononsignificant were the interactions between year an d therapytype, problem type, and therapist training, indicating that therelation between those variables and therapy outcome had notchanged appreciably over time. However, there were significantinteractions with age, x 2 ( l , W = 147) = 5.34, p< .05, an d gen-der, x 2 ( 1, N = 12 2) = 7 .21 , p < .01. Th e effect of year wa snonsignificant fo r children bu t significant fo r adolescents (p N = 101)= 8.40,p


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CHILD AND ADOLESCENT PSYCHOTHERAPY EFFECTS 461child psychotherapy research but may instead reflect a generaltendency for treatment effects to be inversely related to samplesize. Robinson, Herman, and Neimeyer (1990) reported thiseffect in their review of depression treatment research, suggest-ing that it may result from publication bias in favor of statisti-cally significant treatment effects. That is, when sample sizesare small, only large effects will be statistically significant andthus likely to be published.The adult outcome literature has provided some support for"the Dodo verdict," the notion that different approaches totherapy are about equally effective. The present findings do notsupport such a conclusion with respect to treatment of children.W e found that behavioral methods were associated with moresubstantial therapy effects than nonbehavioral methods, andthis pattern held up when we controlled for outcome measuresthat were unnecessarily similar to treatment activities. The pat-tern also held up when we controlled for treated problem, ther-apist training, and child age and gender, and the main effect ofbehavioral versus nonbehavioral methods was not qualified byinteractions with any of those four variables. Superior effects ofbehavioral over nonbehavioral interventions were also reportedin earlier child meta-analyses conducted by Casey and Berman(1985; but see qualifications in the introduction and in Weisz &Weiss, 1993)and Weisz et al. (1987). Because none of the 150studies in the present meta-analysis was included in either theCasey and Berman (1985) or Weisz et al. (1987) analysis, thepresent findings must be seen as rather strong independent evi-dence of the replicability of this "non-Dodo verdict." On theother hand, only about 10% of the treatment groups in our sam-ple involved nonbehavioral interventions; in the fu ture , it willbe important for researchers to expand the base of evidence onthe effects of the nonbehavioral interventions that are widelyused in clinical practice but rarely evaluated for their efficacy incontrolled studies.

In addition, we must stress that even highly significant behav-ioral-nonbehavioral differences in outcome may ultimatelyprove to have artifactual explanations. Previous analyses withpredominantly adult samples have shown a significant relationbetween investigator allegianceor expectancies as to whichtherapy method will be more successfuland outcome whendifferent therapeutic methods are being compared (see Ber-man, Mller,& Massman, 1985; Robinson et al., 1990; Smith etal., 1980). Such findings do not clearly answer the question ofwhether investigator expectancy causesor results f romfindings of behavioral-nonbehavioral comparisons or whetherboth processes are operative. Certainly, investigators' expectan-cies regarding the relative effectiveness of treatments do not de-velop in a vacuum but are likely to be based on their past expe-rience and on the results of previous studies, their own as well asothers. This fact makes it diff icult to "control for" investigatorexpectancies statistically (e.g., by testing for behavioral vs. non-behavioral outcome differences with investigator expectanciescovaried).

To illustrate the problem, we offer an analogy. Suppose thatsurgeons over the years have used either Surgical Method A orSurgical Method B to address a particular type ofheart ailment.Over these years, increasing evidence has indicated that MethodA produces superior survival rates. Suppose, further, that a re-viewer conducts a statistical analysis "controlling for" the ten-

dency of surgeons in comparative studies to believe that A ismore effective than B, and the reviewer finds that, with that be-lief "controlled," there is no remaining reliable difference be-tween Methods A and B. Would this really mean that A is nomore effective than B? No. It would mean only that the beliefthat A is more effective than B corresponds so closely to theevidence that A is more effective than Bthat controlling for thebelief also controls for the evidence. In such a case, applyingstatistical control could be a disservice to the field.In our view, the potential role of investigator expectancies orallegiance has been highlighted sufficiently in previous correla-tional research that it warrants attention in fu ture research. Butthe only fair way we knowto study the role of such expectanciesis experimentally,by judicious assignment of therapists to con-ditions. For example, outcome researchers who wish to com-pare behavioral and nonbehavioral methods might use factorialdesigns in which therapy methods are crossed with therapist ori-entation (behavioral vs. nonbehavioral). We suspect that theresults of such research would contribute more to understand-in g than a proliferation of difficult-to-interpret correlationalanalyses.In contrast to our therapy type findings, we found no evidencethat therapists had different levels of success with overcontrolledproblems than with undercontrolled problems. The same findingwa s obtained in the only other meta-analysis to address this ques-tion (Weisz et al., 1987). Evidence from follow-up research cer-tainly indicates that undercontrolled problems show greater sta-bility and poorer long-term prognosis than do overcontrolledproblems (e.g., see Esser, Schmidt, &Woerner, 1990; Offord et al.,1992; Robins & Price, 19 9 1) . Such findings, however, concern thetemporal course ofproblems independent of therapeutic interven-tion. What our findings suggest is that when natural time course isheld constant through the use of treatment-control comparisons,therapy may not be reliably less effective with undercontrolledproblems than with overcontrolled problems.Although the general type of child problem being treated didnot relate to magnitude of treatment outcome, some of ourfindings suggested that other child characteristics might. Treat-ment outcomes were better for adolescents than for children.This finding cannot be considered robust, however; the maineffect became nonsignificant when we controlled for therapisttraining. Moreover, Casey and Berman (1985) found no rela-tion between age and therapy outcome, and Weisz et al. ( 1 9 8 7 )found larger effect sizes for children than for adolescents (i.e.,precisely the opposite of the present finding). Some light wasshed on this puzzling array of findings by the significant interac-tion between age and year of publication found in our primary,WLS analysis: The mean effect size for adolescents was signifi-cantly greater in studies published between 1986 and 1993 thanin pre-1986 studies. This suggests that changes in the age effectfrom earlier to later meta-analyses may reflect improvements inthe efficacy of interventions for adolescents.In comparison with our age effects, the effects of child genderwere more consistent with previous findings. In the presentsample of studies, therapy had more beneficial effects in sam-ples with female majorities than in male-majority samples. Animportant qualification must be added: In the present analysis,the gender effect was highly significant among adolescents butnot significant among children, and adolescents showed more


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462 W E I S Z , WEISS, HAN, GRANGER, MORTONpositive treatment effects than children bu t only in female sam-ples. Thus, overall, psychotherapy showed more beneficialeffects fo r adolescent female samples than for any other Age XGender group. Weisz et al. ( 1 9 8 7 ) did not find the gender maineffect found here. In this connection, note that ou r analyses ofyear-of-publication effects showed that only in studies publishedsince th e 1985 cutoff for the Weisz et al . (1987) sample weregirls and adolescents found to be more effectively treated thanboys and children. This suggests that secular trends in therapyeffects as a function of gender and age may help to explain th edifference between th e present findings and those of Weisz et al.( 1 9 8 7 ) . Several writers (e.g., Lamb, 1986; Ponton, 1993) haveargued that adolescent girls are particularly sophisticated in theus e of interpersonal relationships fo r self-discovery an d changeand that these skills may facilitate use of the therapeutic rela-tionship to achieve treatment gains. This goodness of fit, alongwith th e fact that therapists ar e more often female than male,may enhance the impact of treatment for adolescent girls. Onthe other hand, it is not clear why such an enhancing effectmight only be seen in post-1985 studies. It is possible that, sincethe mid-1980s, interventions have become especially sensitiveto the characteristicsor treatment needs of adolescent girls, butwe have no well-informed opinion as to what specific changesmay have been relevant.

D o more fully trained clinicians produce th e most beneficialtherapy effects? Possibly, but our evidence does not supportsuch a conclusion. Instead, we found that paraprofessionals(typically parents or teachers trained in specific interventionmethods) generated larger treatment effects than either studenttherapists or fully trained professionals; moreover, students an dprofessionals did not differ reliably (this main effect of therapisttraining w as reduced to marginal significance when w e con-trolled fo r therapy type and for problem type). Such findingsare consistent with a growing body of related evidence on inter-vention effects with children and adults (see Christensen & Ja-cobson, 1994). W e must emphasize, however, that th e beneficialeffects produced by paraprofessionals an d students in thesestudies followed training an d supervision provided by profes-sionals who had, in most cases, designed the procedures. Fur-thermore, the procedures used may often have been fitted to thet raining level of therapists; for example, children an d proce-dures assigned to paraprofessionals and students were quitepossibly those thought especially appropriate for therapists withlittle previous training. And, conversely, professionals may bemore likely to take on the more difficult, intractable cases.

Thus, the main effect examined here is certainly not a defin-itive test of the value of professional training. Moreover, we didfind a Training X Problem Type interaction echoing on e foundin the Weisz et al. ( 1 9 8 7 ) meta-analysis and pointing to a possi-bl e benefi t of training: Professional therapists were no moreeffective than others when treating undercontrolled problems,but professionals produced larger effects than students (p


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CHILD AND ADOLESCENT PSYCHOTHERAPY EFFECTS 463ing in direction across meta-analyses). Our evidence suggests thatsome of the changes in findings (e.g., in gender and age effects) mayreflect changesover time in the results of treatment studies; meta-analytic findings changeover time because a moving target isbeingtracked. In addition, howevei; some of the shifts in findings almostcertainly reflect the fact that each individualmeta-analysis capturesonly part of the picture. Thus, it is important that one attend tothe cumulative record of successive meta-analyses and regard eachindividual meta-analytic finding as preliminary until it has beenreplicated.As the cumulative record of successive meta-analyses istracked, it should also be recognized that the findings of mostsuch analyses may be most fairly interpreted as evidence on thestate of knowledge about laboratory-based intervention. Rela-tively few of the studies included in most meta-analyses pertainto psychotherapy as it is practiced in most child and adolescentclinical settings, and the findings may thus reveal little aboutthe effectiveness of most clinic-based interventions (see Weisz,Donenberg, Han, &Kauneckis, in press; Weisz &Weiss, 1993).Clearly, research of the type reviewed here needs to be comple-mented by research on the impact of intervention with clinic-referred children in service-oriented treatment settings (seeWeisz, Donenberg, Han, & Weiss, in press).

Within their proper interpretive context, however, the presentfindings add substantially to what previous evidence has shownabout therapy outcome with young people. Particularly impor-tant are our findings that (a) psychotherapy effects were bene-ficial but weaker than had been thought previously; (b) effectsdiffered as a funct ion of methods of intervention, with behav-ioral methods showing markedly stronger effects than nonbe-havioral approaches; (c) outcomes were related to the interac-tion of child age and gender, with treatment effects particularlypositive for adolescent girls; (d) degree of improvementwas afunction of the interaction of domain and source of outcomeassessment, with improvement in overcontrolled versus under-controlled behavior depending on the source of information onerelies on (e.g., peers vs. parents vs. teachers); and (e) treatmenthad its strongest effects on the problems targeted in treatment.Continued inquiry will be needed to identify the best analyticmethods for estimating effects , to fill out the picture of therapyoutcomes across a broad age range, and to sharpen the under-standing of factors that can undermine or enhance interventioneffects. .

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