Developing Evidence-based Practice 

Guidelines for Youth Programs

Technical Report on the Core Components of Interventions that 

Address Externalizing Behavior Problems
DEVELOPING EVIDENCE-BASED PRACTICE GUIDELINES FOR YOUTH PROGRAMS

Technical Report on the Core Components of Interventions that Address Externalizing Behavior Problems

August, 2020

Sandra Jo Wilson, Mark W. Lipsey, Ariel Aloe, and Sarah Sahni

Submitted to:

Sarah Oberlander and Cheri Hoffman

Office of the Assistant Secretary for Planning and Evaluation

U.S. Department of Health and Human Services

This document was prepared under contract number HHSP233201500069I Order No. HHSP23337013T from the U.S. 

Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation. Any statements

expressed are those of the authors and do not necessarily reflect the views of the Office of the Assistant Secretary for 

Planning and Evaluation, or the U.S. Department of Health and Human Services.

Project Director:

Sandra Jo Wilson

Abt Associates, Inc.

6130 Executive Blvd.

Rockville, MD, 20852

This report is in the public domain. Permission to cite is not necessary.

Suggested citation:

Wilson, S. J., Lipsey, M. W., Aloe, A., & Sahni, S. (2020). Developing evidence-based practice guidelines for youth 

programs: Technical report on the core components of interventions that address externalizing behavior problems. Office 

of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services.
 Technical Report  i 

TABLE OF CONTENTS 

Executive Summary...........................................................................................................................................................ii

1. Introduction.................................................................................................................................................................. 1

2. Characteristics of the Youth Programs ..................................................................................................................... 3

2.1 The Program Approaches .................................................................................................................................. 4

2.2 Other Program Features and Characteristics..................................................................................................... 6

2.3 Characteristics of Study Methodology................................................................................................................ 7

3. Effects of Youth Programs on Externalizing Behavior............................................................................................. 8

3.1 Interpreting the Effect Size Variability ................................................................................................................ 8

4. Analytic Approach to Identifying Core Components..............................................................................................10

4.1 Purpose............................................................................................................................................................10

4.2 Meta-regression ...............................................................................................................................................10

4.3 Stage 1 Analysis: General Core Components..................................................................................................10

4.4 Stage 2 Analysis: Specific Core Components..................................................................................................10

4.5 Sensitivity Analysis...........................................................................................................................................11

4.6 Limitations of the Analytic Approach ................................................................................................................11

5. Stage 1: General Core Components ........................................................................................................................12

6. Stage 2: Core Components for Different Program Approaches............................................................................14

6.1 Core Components for Family Relations and Parenting Skills Approaches......................................................16

6.2 Core Components for Relational Approaches..................................................................................................19

6.3 Core Components for Skill-building Approaches..............................................................................................22

6.4 Core Components for Behavior Management Approaches..............................................................................25

6.5 Core Components for Academic and Educational Approaches........................................................................28

7. Conclusions...............................................................................................................................................................31

Appendix A. The Meta-analytic Database ......................................................................................................................33

Appendix B. Analytic Methods........................................................................................................................................45

Appendix C. Analysis of the Influence of Method Variables ........................................................................................48

References Cited..............................................................................................................................................................55

References for the Studies in the Meta-analysis...........................................................................................................57

Table of Contents

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 Technical Report  i 

LIST OF EXHIBITS

Exhibit 1. Observed Variability in the Effect Size Distribution ......................................................................................... 9

Exhibit 2. Descriptive Statistics for General Core Components: All Programs (k=391) ................................................12

Exhibit 3. General Core Components (k=391)..............................................................................................................13

Exhibit 4. Mean Effect Sizes and Heterogeneity Statistics for the Program Approach Categories ...............................14

Exhibit 5. Mean Effect Sizes and Confidence Intervals for the Program Approach Categories ....................................15

Exhibit 6. Characteristics of Family Process and Parenting Skills Approaches (k=64).................................................16

Exhibit 7. Core Components for Family Process and Parenting Skills Approaches (k=64) ..........................................18

Exhibit 8. Characteristics of Relational Approaches (k=91)..........................................................................................19

Exhibit 9. Core Components for Relational Approaches (k=91)....................................................................................21

Exhibit 10. Characteristics of Skill-building Programs (k=121) .......................................................................................22

Exhibit 11. Core Components for Skill-building Approaches (k=121) .............................................................................24

Exhibit 12. Characteristics of Behavior Management Approaches (k=27)......................................................................25

Exhibit 13. Core Components for Behavior Management Approaches (k=27) ...............................................................27

Exhibit 14. Characteristics of Academic and Educational Approaches (k=75)................................................................28

Exhibit 15. Core Components for Academic and Educational Approaches (k=75).........................................................30

Exhibit 16. Summary of Analysis of Specific Core Components.....................................................................................31

Exhibit A1. The Seven Meta-analyses Included in the Database....................................................................................33

Exhibit A2. Selected Characteristics of the Studies Included in the Analysis (k=391).....................................................44

Exhibit C1. Study Methods and Research Procedures for All Studies (k=391) ...............................................................48

Exhibit C2. Method Variables Analysis for All Programs (k=391)....................................................................................49

Exhibit C3. Method Variables Analysis for Family Relations and Parenting Skills Approaches (k=64) ...........................50

Exhibit C4. Method Variables Analysis for Relational Approaches (k=91) ......................................................................51

Exhibit C5. Method Variables Analysis for Skill-building Approaches (k=121) ................................................................52

Exhibit C6. Method Variables Analysis for Behavior Management Approaches (k=27) ..................................................53

Exhibit C7. Method Variables Analysis for Academic and Educational Approaches (k=75)............................................54

List of Exhibits

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Back to Table of Contents Technical Report  ii

EXECUTIVE SUMMARY Executive Summary

This report describes and illustrates an approach to using evidence to improve the effectiveness of youth programs. The 

approach capitalizes on the fact that across the many program environments that offer youth programs (e.g., community, 

mental health, public health, child welfare settings, schools), there is a great deal of well-controlled research available. 

Further, there is considerable variability in effectiveness across programs that can be reliably predicted from information 

reported in the research. Our goal is to better understand the sources of that variability so that we can uncover the 

characteristics of effective programs and share guidelines about how to make them more effective with those who design, 

support, and implement such programs. Findings reported here will be used to inform evidence-based guidelines for 

improving practice.

Background

Our approach to evidence-based practice applies a way of thinking about evidence that differs from the traditional “model 

program” approach. This “core components” way of thinking considers both the programs themselves and aspects of the 

delivery format, dosage, implementation strategies, delivery personnel, and the like, that may also influence whether a 

program has positive impacts on youth outcomes. Drawing on a large meta-analytic database of research on youth 

programs, we identify a profile of program, participant, and implementation features that are empirically related to positive 

outcomes across the programs represented in the research. We call these program features core components, which we 

group into four domains of factors associated with: (1) program approach or content; (2) structure, format, and delivery of 

the program; (3) implementation strategies and problems; and (4) characteristics of the program participants.

In this report, we focus on a group of selected and indicated prevention programs for youth, all of which provide evidence 

of program effects on externalizing behavior problems. We group the prevention programs into the following categories 

based on their general approach to behavior change: 

• Family Relations and Parenting Skills

• Relational Approaches

• Skill-building

• Behavior Management

• Academic and Educational Interventions

Findings

Across the diverse prevention programs in the dataset, the overall average program effect on externalizing behavior is

positive, statistically significant, and represents meaningful effects on the externalizing behavior of the youth who 

participated in the programs ( = 0.32, p < .0001). This means that about 63% of youth participants in prevention 

programs exhibited better outcomes (less externalizing behavior problems) than the average comparison group 

participant. In addition, the five program approaches each exhibit statistically significant impacts on externalizing behavior

problems and each has sufficient variability to explore core components within the group. Our meta-regression analysis

focused on: (1) identifying general core components that apply across all programs in the dataset and (2) discovering core 

components that apply separately within each program approach.
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General Core Components 

We identified three general core components, all representing facets of implementation, which were associated with 

program effects across the full set of prevention programs. 

• Implementation quality

• Delivery complexity

• Provider training or supervision

Specific Core Components 

For four of the approaches, we identified specific core components in one or more of our core components domains that 

were meaningfully associated with program impacts on youth externalizing behavior. The evidence roadmap below 

summarizes the findings from our meta-regression analyses. Each of the factors in the roadmap will form the basis for a 

practice recommendation.
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1. INTRODUCTION 1 Introduction

Although the majority of young people in the United States are physically and emotionally healthy, regularly attend and 

progress through school, and choose to avoid drugs, alcohol, and other illegal behaviors, there are still large numbers of 

youth who struggle to stay on track. It is not surprising, then, that there is an extensive array of prevention programs that 

target youth risk behaviors and/or support positive youth development. Prevention programs that target youth violence, 

aggression, bullying, and other negative behaviors and those that support social and emotional learning, conflict 

resolution, and positive social behavior are available in most schools and communities in the U.S. Downward trends in 

school violence and victimization rates suggest that widespread programming efforts may be working, but there is still 

work to be done. For example, bullying is prevalent on school campuses and almost half of U.S. schools reported crimes 

to the police (Musu, Zhang, Wang, Zhang, & Oudekerk, 2019).

Over the last several decades we have seen a clear movement in many service environments (from juvenile justice to 

mental health to education) towards evidence-based practice as a way to improve on existing programming efforts (e.g., 

APA 2006; Kratochwill & Shernoff, 2003; Raines, 2008; Sacket, 1996; Schiele, Weist, Youngstrom, Stepahn, & Lever, 

2014). The most common approach to evidence-based practice focuses on identifying distinct model programs that have 

demonstrated positive impacts and then advocating that these programs be scaled up and delivered widely in the field. 

Such model programs usually have a brand name (e.g., Coping Power, Good Behavior Game), a manual, standardized 

models of service delivery, and, often, implementation supports. Model programs typically receive the “evidence-based” 

designation as a result of at least one rigorous study that demonstrates a statistically significant positive impact on an 

outcome of interest. Registries such as Blueprints for Healthy Youth Development (https://www.blueprintsprograms.org/), 

the What Works Clearinghouse (https://ies.ed.gov/ncee/wwc/), and Crime Solutions (https://www.crimesolutions.gov/) 

review the research on candidate programs and provide listings of those that meet their evidence standards. More 

recently, federal tiered evidence schemes and some federal grant funding have begun emphasizing the use of model 

programs (e.g., the Office of Adolescent Health’s Teen Pregnancy Prevention program, the Every Student Succeeds Act, 

the Department of Education’s Education Innovation and Research program).

Although the evidence behind model programs is often well-designed and well-conducted, there are several drawbacks to 

the focus on fully articulated program models: (1) generalizability may be questionable given that there are typically only a

few studies of a program that assess its impact; (2) local flexibility or adaptation may be limited because the program must 

be implemented with fidelity to the original model to achieve similar results; and (3) service providers or program staff may

be reluctant to drop their current practice to adopt something new due to cost, resistance to change, contractual 

obligations, local support for the current program, and the like. This latter point is critical. The model programs approach 

can be helpful for decision-makers who are considering adopting a new program (and look to evidence registries to select 

a well-supported model) or when selecting a program from among several options. But, evidence registries offer less 

help to agencies that are already providing programs and services and may be interested in using evidence to 

improve their current practices. 

Indeed, a large majority of programs in operation in the field are not model programs at all, but rather homegrown or 

locally developed programs or adaptations of model programs. In some cases, the proportion of model programs used in 

actual practice is estimated to be less than 10% (see Becker, Smith, Jensen-Doss, 2013; Garland et al., 2010 for mental 

health; and, Lipsey, 2018 for juvenile justice). All programs (whether model programs or homegrown) are comprised of a 

set of specific approaches and procedures. Examining the specific components that comprise a program—rather 

than the program as a whole—has the potential to identify components that are effective and inform 

programming for much greater numbers of youth than model- or registry-based approaches. 

This report describes the technical aspects of an alternative approach to using evidence to improve the effectiveness of 

youth programs. The approach is designed to provide evidence-based guidance and strategies for improving current 

practice and is intended to be broadly applicable across a range of settings and agencies. It capitalizes on the fact that 

across the many program environments that offer youth programs (e.g., community, mental health, public health, child 
Back to Table of Contents Technical Report  2 

welfare settings, schools), there is a great deal of well-controlled research available—some on model programs, but 

mostly on diverse locally-developed programs. 

This approach to evidence-based practice applies a different way of thinking about evidence—a way that considers both 

the programs themselves and aspects of the delivery format, dosage, implementation strategies, delivery personnel, and 

the like, that may also influence whether a program has positive impacts on youth outcomes. Drawing on a large metaanalytic database of research on youth programs, we identify a profile of program, participant, and implementation 

features that are empirically related to positive outcomes across the programs represented in the research. We call these 

program features core components. This report focuses on identifying core components for prevention programs that 

target youth externalizing behavior problems. In the next phase of this work, we will draw on the contributing research 

studies to flesh out full descriptions of the core components we identify, and use the results as the basis for practice 

guidelines that will allow agencies and providers to assess how well their services stack up against what the evidence 

says are effective practices and can inform providers’ efforts to improve services to align more closely with the evidence.

Rather than expecting practitioners to consider model program evidence that may be disconnected from their work 

context, the approach described here can provide a pathway for providers’ to reflect on their current efforts in light of core 

components. Doing so might, in turn, guide their decisions around which practices to keep, which to adopt, and which to 

target for improvement.

We illustrate this approach with a group of selected and indicated prevention programs for youth, all of which provide 

evidence of program effects on externalizing behavior problems. In the next section, we describe the meta-analytic 

database that serves as the evidence base and define the programs, participants, and implementation features included 

in the database. We then discuss the overall effectiveness of these youth programs for improving youth behavior as a 

lead-in to our analytic approach. Following that, we present the core components we identified from this meta-analysis. A 

series of appendices provides additional technical details about the meta-analytic database, our analytic approach, and 

sensitivity analyses.
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2. CHARACTERISTICS OF THE YOUTH PROGRAMS 

 

2 Characteristics of the Youth Programs

To identify core components, we use a group of youth programs from a large meta-analytic database that includes the 

results of hundreds of randomized and quasi-experimental studies of youth programs of relatively high quality. This 

database is a compilation of seven separate meta-analyses of youth programs conducted by two research teams (see 

Appendix A) developed with the goal of exploring the variability of intervention effects across studies of diverse programs 

for children and youth. The programs in the database are designed for children and youth and aim to have beneficial 

effects on many different outcome domains related to social and cognitive development, school performance, family and 

peer relations, antisocial behavior, and positive youth development generally. Within any of these domains, there is a 

great deal of variability in the effects of programs that can be reliably predicted from information reported in the studies. A 

better understanding of the sources of that variability could uncover the characteristics of effective programs, information 

that has the potential to be informative for those who design, support, and implement such programs about how to make 

them more effective. 

The process of identifying core components begins with selecting an outcome domain and then collecting any program 

that reports program impacts in that domain from the larger database. Working backwards from an outcome domain, 

rather than selecting a set of programs for analysis, means that we can focus on a variety of program approaches, 

providers, participants, implementation practices, and settings, whatever has the greatest potential to improve the 

outcome of interest. This focus on any actionable feature of a service environment that might improve a high-priority 

outcome is intended to inform guidelines that are maximally useful to a range of audiences.

We selected externalizing problem behavior as the outcome domain of interest. Externalizing problem behaviors are 

defined as negative behaviors such as aggression, acting out, hostility, bullying, disobedience, and the like that are 

enacted overtly in the external world.1 The negative behaviors assessed within this domain like acting out, aggression, 

and disciplinary actions can be extremely disruptive, are often correlated with other problem behaviors, and tend to have 

far-reaching consequences for children and youth. Programs that target externalizing behaviors are diverse and common 

in both school and community settings, so the audience for practice guidelines in this area may be large. 

From this larger database, we selected the 391 programs that report program impacts on externalizing problem behavior. 

The 391 programs consist of selected (i.e., strategies targeted toward at-risk subpopulations) or indicated (i.e., strategies 

for individuals considered to be at risk of problems) prevention programs in which the youth participants are at risk for or 

are already experiencing behavioral, academic, or family difficulties associated with externalizing behavior. The outcomes 

themselves are diverse; they index a variety of behaviors ranging from anger, disobedience, and disruptiveness to verbal 

and physical aggression. Most of the measures are collected via surveys or questionnaires reported by teachers, parents, 

or the children and youth themselves, but the database also includes measures taken from administrative records, such 

as school disciplinary actions. Appendix A includes additional descriptive detail about the outcomes and Appendix B 

provides information about how we selected and aggregated outcomes from the candidate studies. 

The record for each study we selected for analysis provides estimates of program impacts (i.e., effect sizes) for the major 

study outcomes, along with extensive descriptive details about each study’s program, providers, participants, and 

implementation activities. These descriptive data are our potential core components. 

1 Although delinquent behavior such as arrests, convictions, court contacts, and the like is included in the broad definition of externalizing problem 

behavior, it is considered a separate outcome in the meta-analytic database and is not included in the analyses reported here.
Back to Table of Contents Technical Report  4 

2.1 The Program Approaches

The prevention programs include school-based, community-based, and afterschool programs that employ a wide range of 

intervention strategies, including those that directly target youth behavior and emotions (e.g., social problem solving skills, 

anger management) and those focused on other targets such as parenting or academic difficulties that may also influence 

externalizing behavior. Using an inductive approach in which we carefully reviewed the descriptions of each program 

provided in the studies, we sorted the programs into six broad categories representing different program approaches, 

most with several subcategories. Although we have grouped programs into mutually exclusive categories, many programs 

are multi-dimensional and often include elements from more than one of our approach categories. We aimed to place 

each program in the approach category that best reflected its predominant content. To capture the multi-dimensionality of 

programs, our database also includes the configuration of individual elements that make up each program; we describe 

these elements in Appendix A. 

The six program approaches are:

Family Relations and Parenting Skills (72 studies). Programs in this group aim to increase desirable 

positive behaviors and decrease undesirable negative behaviors among youth by improving parentchild relationships and/or promoting positive parenting behaviors. Family relations and parenting skills 

approaches are intended to change youth behavior primarily by enhancing or improving parental or 

family influences on youth. This group of approaches includes three variations in our database:

• Approaches with a family focus. Parent(s) and children receive services in these programs, with 

perhaps others as well (e.g., teachers); parent(s) and children may receive services together or 

separately. Content focuses on family functioning and parent-child relationships, but parenting 

skills may also be covered.

• Approaches focused on parent training. Parent(s) receive services with child not involved or only 

minimally involved; others (e.g., teachers) may also be involved. Content focuses primarily on 

parenting skills and behaviors.

• Approaches with a child coping focus. Children (and perhaps others, e.g., teachers) receive 

services, but not parents. Content focuses on strategies for supporting children coping with 

family issues, such as divorce. 

Relational Approaches (91 studies). Programs in this group aim to influence desirable positive and 

undesirable negative behaviors and their precursors (e.g., attitudes, motivation, insight, perceptions, 

and behavioral intentions) via positive and supportive relationships with others, including mentors or 

counselors, and possibly also with peers involved in the same program. There are two variations of 

relational approaches in our database:

• Relatively open-ended or eclectic counseling/mentoring. Programs do not clearly follow a 

particular therapeutic orientation or process; content is often tailored to the needs of individual 

youth. 

• Counseling/mentoring with a particular therapeutic orientation. Programs generally have a 

structure, guiding principles or goals, or issue that colors the process.
Back to Table of Contents Technical Report  5 

Skill-building (121 studies). Programs in this group aim to enhance youth interpersonal skills, improve 

youth responses to challenging interpersonal interactions with peers, teachers, and other adult 

authority figures, and train youth to manage social interactions and/or their internal affective/executive 

processes and responses in ways that reduce the potential for conflict and externalizing behavior. 

Most programs involve training as well as the opportunity to practice learned skills. There are three 

variations in the database:

• Approaches that emphasize both interpersonal skills and affective/executive processes or 

responses. Programs include interpersonal skills elements such as learning social problem 

solving steps or identifying and diagnosing emotions or conflict situations and elements focused 

on controlling or managing affective/executive responses such as anger and impulsivity. 

• Approaches that emphasize mainly interpersonal skills. Programs focus largely on social 

problem solving training and identifying and diagnosing emotions or conflict situations.

• Approaches that emphasize mainly affective/executive processes or responses. Programs focus 

mainly on training that addresses affective/executive processes or responses including anger, 

impulsivity, and the like that may inhibit or prevent positive social interactions.

Behavior Management (27 studies). Programs in this group aim to shape or modify problem behavior 

and precursor/risk behaviors via manipulation of rewards and punishments. Programs employ a variety 

of mechanisms including incentives, disincentives, and behavioral contracting to modify problem 

behavior directly or modify the precursor behaviors that are risk factors for problem behavior.

Academic and Educational Interventions (75 studies). Programs in this group aim to improve school 

performance, school engagement, and academically-oriented behavior. Academic performance is a 

risk factor for externalizing behavior, which can manifest in school settings. Although not generally the 

primary focus, programs with an academic or educational focus may provide collateral benefits on 

youth behavior by promoting positive youth development in general. Many programs in this group also 

include elements focused on behavior. There are three variations in the database:

• Programs that focus on changing the school environment or structure. Programs include 

alternative schools, schools-within-schools, career academies, and the like. Many programs 

involve smaller class sizes, personalized interactions with teachers, and additional academic 

and behavioral supports for youth.

• Tutoring and remedial academic programs without a vocational component. Programs focus 

largely on academic supports for youth, often with goals of improved attendance and high school 

completion, though they may include other support services such as counseling.

• Tutoring and remedial academic programs with an employment or vocational component. 

Programs in this group also provide academic supports, but focus mainly on career awareness 

and development. Programs may include vocational- or career-oriented courses, internships or 

other employment experiences, and community or volunteer service.

Deterrence (5 studies). Programs in this group aim to change behavior via sanctions, intensive oversight or monitoring, 

consequences, or punishment. Manipulation of punishments or negative consequences, or illustrating potential negative 

consequences, is expected to modify behavior directly. Programs may include prosocial or positive youth development 

aspects, but the primary focus is on deterrence.

The deterrence approaches and the child-coping programs (within Family Relations and Parenting Skills Approaches) 

were dropped from the analyses because so few programs were included in these categories (n=13 total). Thus, five 

approach categories were carried through our analyses.
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2.2 Other Program Features and Characteristics 

The prevention programs in the database also vary in their staffing, configurations, resources, and program length, among 

other features. We have grouped these potential core components into four domains: program content, program structure, 

implementation strategies and outcomes, and participant characteristics. Details about the studies included in the metaanalytic database, the protocol for coding the potential core components, and descriptive statistics for program content, 

structure, and implementation for all 391 programs are included in Appendix A. 

• Program content

− Program approach. Each program was coded into one of the five program approach categories we described 

above.

− Program content elements. The content of each intervention was additionally described with a series of nonmutually exclusive elements. 

• Program structure 

− Program setting

 Location: rural, suburban, urban, mixed. 

Country, region of US

 Service delivery setting: classroom, school, 

afterschool, community 

− Delivery format: individual, group, classroom

− Program standardization

 Program protocol: has manual, program guide

 Lesson plans: specified number of sessions 

and session content vs. less structured

− Delivery complexity: counts of formats, provider 

types, and settings

− Program dosage

 Duration in weeks from beginning to end

 Frequency of sessions per week

− Program personnel

 Delivery personnel: researcher, specialist, 

teacher, layperson, etc.

• Implementation strategies and problems

− Provider training: training indicated or not

− Provider supervision: evidence of supervision, 

consultation, or coaching of providers during the 

intervention

− Implementation problems: whether implementation 

difficulties reported or not

• Participant characteristics (see Box on the right)

− Gender mix: male proportion of participant sample

− Average age of participant sample

− Age range of participant sample

− Predominant race/ethnicity of sample

− Socioeconomic status

− Presenting problem: Externalizing, internalizing, peer, family, school, etc.
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2.3 Characteristics of Study Methodology 

In addition to the program and participant features, the meta-analytic database also includes details about the methods 

and research practices used in each study. These variables are not themselves potential core components that might 

inform practice because they do not represent substantive features of the program or its participants and are not 

actionable in practice settings. However, study methods and research practices are associated with program impacts in 

ways that may obscure statistical relationships that might be important for understanding program effects. For example, 

imagine that we observe smaller effects from research studies in which comparison groups receive some minimal level of 

service than from studies in which comparison groups receive no services at all. It makes sense that studies in which 

comparison groups receive more services might appear to have smaller impacts, but the contrast between intervention 

and comparison groups is not an actionable feature of a typical service environment. Thus, our analyses must address the 

influence of research methods, so that we can identify the actionable core components without them being obscured by 

methods. We conduct these analyses as sensitivity analyses and present the results in Appendix C. 
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3. EFFECTS OF YOUTH PROGRAMS ON EXTERNALIZING BEHAVIOR

 

3 Effects of Youth Programs on

Externalizing Behavior

Before we identify the profile of core components associated with positive program impacts, we first look at the overall

effects of youth programs on externalizing behavior problems and the distribution of those effects. Across the 391 

programs in the dataset, the overall average program effect on externalizing behavior is positive, statistically significant, 

and represents meaningful effects on externalizing behavior among youth who participated in the programs ( = 0.32, p 

< .0001). Expressed in percentage terms, this average effect size of 0.32 means that about 63% of youth participants in 

prevention programs exhibited better outcomes (less externalizing behavior) than the average comparison group 

participant.

In the results below, we will use a threshold of .10 effect size units as an indicator of a relatively meaningful difference,

rather than relying solely on statistical significance. The random effects models we use in all analyses are conservative. If

we focus only on statistical significance from such models, we may overlook findings that are substantively meaningful.

There is no standard way of judging whether an effect size difference is substantively important. It can depend on the 

particular context or on nature of the outcome (e.g., small changes may be meaningful for some outcomes, but larger

changes may be required for others to be considered meaningful) and also depends on the overall distribution of effects.

We selected the .10 threshold because it represents about a third of the mean effect size or an approximately 4 

percentage point difference in externalizing behavior. That is, subtracting or adding .10 from our mean effect size of 0.32 

translates into a range of 59%-66% of program participants exhibiting less externalizing behavior than the average 

comparison group participant. This may seem small, but taken in the context of the number of school children who are 

victims of bullying, for example, we think a 4% change could represent a visible impact on a school climate. More 

important for our purposes than the average treatment effect, however, is the considerable variability we observe in the 

effect sizes across studies.

3.1 Interpreting the Effect Size Variability

In the random effects meta-analysis models we use throughout this report, we use several indicators to provide different 

perspectives on the variability or heterogeneity in the effect sizes (Borenstein, Hedges, Higgins, & Rothstein, 2009). For 

the 391 programs we analyze here, there is a great deal of heterogeneity (Q = 2506, p <.05; I2

=83.08%; τ

2

=.26). The Q 

statistic is an index for the total amount of study-to-study variation observed. A statistically significant Q indicates that 

there is more study-to-study variation than can be explained by within-study sampling error. The I2 statistic is derived from 

the Q and reflects the proportion of the total effect size variation that represents the between-study portion. I2 values 

greater than 50% are generally considered to indicate sufficient effect size variability to warrant exploration of study 

characteristics associated with larger or smaller effects. The τ

2 statistic is a direct estimate of the between-study variance. 

The square root of τ

2 is often used to describe the range of the between-study effects. For example, for a mean effect size 

of 0.32 and a τ of .51 (the square root of our τ

2 of .26), we can expect that about 95% of the distribution of between-study 

effects will fall between -0.68 and 1.32 (i.e., 0.32 +/- 1.96*τ), a rather large range.
Back to Table of Contents Technical Report  9 

To further illustrate this variability, Exhibit 1 shows the distribution of observed effect sizes across the 391 programs. 

Some programs were not especially effective; programs clustering around zero are those in which there were no or very 

small differences between the intervention groups and the comparison groups after intervention. Programs on the left side 

of the graph are those in which comparison groups exhibited greater reductions in behavior problems than intervention 

groups. Programs on the left side of the distribution might give us some clues about practices to avoid. Fortunately, most 

programs (72%) showed positive effects and many of these represent meaningful levels of behavior change. For example, 

the median effect size of 0.26 translates to a 10 percentage point improvement in externalizing behavior. This variability 

motivates and provides the ideal circumstance for us to identify the factors that characterize the most effective programs 

in this distribution. Our next step is to identify those factors.

Exhibit 1. Observed Variability in the Effect Size Distribution
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4. ANALYTIC APPROACH TO IDENTIFYING EFFECTIVENESS FACTORS 4 Analytic Approach to Identifying Core 

Components

4.1 Purpose

We noted above that the meta-analytic database contains descriptive detail about the programs and participants involved 

in the research, which we categorized into four broad domains: program content, program structure, implementation 

strategies and problems, and participant characteristics. This information, along with the observed variability in program 

impacts, is what permits us to identify core components across the range of studies reporting outcomes on externalizing 

behavior. 

4.2 Meta-regression

Specifically, we use a form of regression analysis tailored to meta-analytic data to identify the profile of program, 

participant, and implementation features that are empirically related to the effect sizes for externalizing outcomes across 

the diverse program implementations represented in the studies in this body of research. This analysis estimates the 

relative contribution of each potential core component for predicting the largest program impacts. 

As with any multiple regression analysis, correlated independent variables (or moderators) can obscure the relationship of 

any one independent variable with the outcome. That is, many of the potential core components in the meta-analytic 

database are not just related to program effectiveness; they are also related to each other. For example, academicallyfocused programs tend to be longer than skills-based approaches; when both program approach and program duration 

are included in an analysis and we see a large relationship between, for example, duration and program effectiveness, we 

do not know whether it is the longer duration that produced the impact, the academic programs (which happen to be 

longer), or some combination of the two. Many of the potential core components do co-occur in the programs in the 

database. Our analytic strategy is, therefore, designed to isolate the independent influence of each potential core 

component as much as possible. For the analysis, we sought to select variables that were not strongly correlated with 

each other and, when possible, we grouped related variables together in composites. In addition, we performed some 

analyses separately for the five program approach categories to better isolate the core components that might interact 

with the approach categories if all programs were analyzed together. 

Further, we hypothesized that, given the diversity of programs and settings in the database, there might be core 

components that are unique to certain program approaches as well as core components that might be more generally 

associated with positive effects across programs. We, therefore, performed the analyses to identify the core components

in two stages. 

4.3 Stage 1 Analysis: General Core Components

In the first stage, we identified core components that should be important for any program – we call these general core 

components. We selected options for this first phase from the implementation strategies and problems domain because 

we expected these features to apply broadly across different types of programs and settings even if, for example, different 

program approaches were more or less likely to experience implementation problems or were more or less complex. 

4.4 Stage 2 Analysis: Specific Core Components

In the second stage of our analysis, we turned our focus to core components that might be important only for certain 

program approaches (e.g., program duration may be important for some program approaches but not others, or may not 

vary at all for some). We call these specific core components. For this stage, we focused on potential core components in 

the other three domains of program and participant features captured in the meta-analytic database: program content, 

program structure, and participant characteristics. We performed these analyses separately for each of the five approach 

categories. Separating programs in this way helps us better disentangle the core components that are related to each 
Back to Table of Contents Technical Report  11

other. This separation also means that the practice guidelines we develop from the analysis may need to be tailored to the 

approach categories so that practitioners can more easily find guidance that is relevant for the kinds of programs they 

implement.

4.5 Sensitivity Analysis

Once we identified the specific core components for each of the five program approach categories, we double checked 

the general core components to be sure that those relationships held for each of them. We suspected that, because of 

variations across the approaches in the correlations between general and specific core components, these relationships 

might not always hold when we subset the data and add additional variables. In the results, we point out places where this 

occurs. In the final stage of our analysis, we explore whether any methodological confounds exist and whether these 

confounds might offer alternative explanations for the substantive findings. These analyses are presented in Appendix C.

Additional technical details about our analytic approach, including our procedures for weighting, estimating models, 

handling missing data, and the process for selecting core components, are presented in Appendix B.

4.6 Limitations of the Analytic Approach

All of the analyses we report in this paper are exploratory and correlational. Even though individual impact estimates from 

the studies, especially those that use randomized designs, are causal estimates, findings from meta-regression analyses 

are not. Our analyses examine the empirical relationships between potential core components and observed findings, but 

that does not mean that a particular variable or core component directly caused the findings we observe. That is, any 

core component we identify should not be thought of as having a direct causal impact on externalizing behavior, 

but rather as a factor that practitioners should consider. This is not specifically a limitation of the analytic approach, 

but it is important to communicate this complexity. In addition, although we present significance tests for our findings, we 

are more interested in the magnitude of the regression coefficients than in their statistical significance. The random effects 

models we use to estimate our models are rather conservative (as is appropriate for a diverse dataset like ours), but that 

means that we are less likely to find statistical significance, even when the relationships are substantively meaningful. Our 

analyses are intended identify the features that characterize the most effective programs as a way to inform practice, not 

to make causal statements about the effects of any particular variable or set of variables.
Back to Table of Contents Technical Report  12

5. STAGE 1: GENERAL EFFECTIVENESS FACTORS 5 Stage 1: General Core Components

We selected four potential core components from the implementation strategies and problems domain for the first stage 

analysis: implementation quality, delivery complexity, provider training, and provider supervision. Descriptive statistics for 

these variables are shown in Exhibit 2 along with their correlations with effect size. 

Implementation quality was analyzed as a binary variable, with a 1 indicating that the study authors explicitly mentioned 

problems or implied that there were problems with implementation. There was considerable variability across programs in 

what (and how much) studies reported about program implementation. For instance, some studies simply stated that 

programs experienced problems with implementation, but provided no additional information on specific types of 

problems. More commonly, studies reported difficulties related to staffing or funding, intervention group participants 

receiving less intervention contact than intended, or intervention group participants not receiving the entire intervention. A 

substantial number of studies did not mention implementation at all (56%); these cases are included in the reference 

category. Few studies explicitly stated that they had no problems with implementation (5%). 

Delivery complexity was a composite variable created from a principal components factor analysis of three variables: 

number of different implementation settings (e.g., classroom, home, playground), number of different types of delivery 

personnel (e.g., teachers, laypeople, program specialists), and number of different formats (e.g., group, one-on-one). See 

Appendix B for the factor analysis results. Provider training prior to delivery of the program being delivered and provider 

supervision during program delivery were coded as binary variables, with a 1 indicating the presence of training or 

supervision, respectively. For analysis, the provider training and provider supervision variables were combined in a single 

variable that indicates whether provider training or provider supervision or both were mentioned in a study.

Exhibit 2. Descriptive Statistics for General Core Components: All Programs (k=391)

Frequency (%) Mean (sd) Range (Mode)

Correlation with 

Effect Size

Implementation Quality

Explicit or suggested problems 153 (39%) -0.14

No problems or no mention of problems 239 (61%)

Delivery Complexity

Number of different settings 1.50 (0.86) 1-6 (1)

Number of different delivery personnel 1.75 (1.00) 1-5 (1)

Number of different formats 1.82 (1.10) 1-8 (1)

Delivery complexity factor 0.00 (1.00) -0.26

Provider Training

No 181 (46%)

Yes 210 (54%) 0.19

Provider Supervision

No 230 (59%)

Yes 161 (41%) 0.02

Provider Training or Supervision

No 163 (42%)

Yes 228 (58%) 0.09

The results of the analysis of the general core components with all of them included in a meta-regression model predicting 

effect sizes are shown in Exhibit 3. Implementation problems and delivery complexity were associated with smaller 

program impacts. Provider training or supervision was associated with larger program impacts. The coefficients in 
Back to Table of Contents Technical Report  13

the regression model represent the amount of change on the dependent variable (the effect size) associated with a one 

unit change on the core component. For example, studies for which provider training or supervision was reported show, 

on average, effects 0.12 effect size units larger than studies that did not report training or supervision. Although the 

general core components account for significant variability in the distribution of effects (the Q-test for the model is 

statistically significant), the significant Q-residual and large I2 and τ

2 values indicate that substantial effect size differences 

among programs remain that are not accounted for by the three general core components. 

Exhibit 3. General Core Components (k=391)

General Core Components b (se)a

Intercept 0.31 (0.05) ***

Implementation: Explicit or suggested problems -0.12 (0.06) †

Delivery complexity -0.11 (0.03) ***

Provider training or supervision 0.12 (0.06) * 

Model Statistics

Q-model 26.10 ***

Q-residual 2289.87 ***

τ2 0.24

I

2 81.65%

R2 8.22%

a Unstandardized regression coefficients (b) and standard errors from inverse variance weighted random effects 

meta-regression analyses using REML estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

The implementation problems variable provides a direct assessment of the relationship of implementation quality with 

program effects. The variability in the type of problems experienced and the varied level of detail with which it is reported

makes it difficult to derive specific guidance directly from the studies in the database. Our single implementation problems 

variable did not focus solely on fidelity. That is, we recorded any mentioned issues with implementation, including 

attendance at sessions by participants, provider turnover, fidelity to a manual or guidelines, incomplete service delivery, 

number of sessions delivered, and the like as an implementation problem. Although the quality and quantity of information 

reported about implementation varies across the studies in the database, it is clear that implementation matters. 

We interpret the delivery complexity factor as more of an implementation issue than an indication that multi-faceted or 

multicomponent programs are less effective. In fact, there was a small non-significant interaction between implementation 

and delivery complexity suggesting that programs with high delivery complexity that did not have explicit implementation 

problems performed slightly better than less complex programs without explicit implementation problems. In terms of 

practice implications, we think this finding suggests that it is critical for program implementers to consider delivery 

complexity in their particular setting and context and pay special attention to ensuring that program organizers have the 

support and infrastructure required to implement complex programs should they wish to do so. 

Finally, programs for which provider training or supervision were mentioned exhibit better outcomes than those for which 

supervision and training were not. Training can improve the quality of program delivery, but building capacity in service 

providers is likely to yield other implementation-related benefits as well, including supporting staff retention and building a 

cohesive service environment. We will see below that training and supervision appear to be less critical for some program

approaches with explicit lesson plans or manuals, but that does not negate its potential to further improve the quality of 

service delivery.

In the next section, we separate the programs into the five approach categories and explore the core components that are 

important for each category. These, along with the general core components we have explored here, serve as the basis 

for the practice guidelines we will develop in the next phase of this work. 
Back to Table of Contents Technical Report  14

6. STAGE 2: EFFECTIVENESS FACTORS FOR DIFFERENT PROGRAM APPROACHES 6 Stage 2: Core Components for Different 

Program Approaches

For the second phase of our analysis, we separated the diverse programs that aim to reduce externalizing behaviors into 

the five program approach categories with sufficient evidence to analyze. We hypothesized that programs characterized 

by different approaches to changing behavior might exhibit different configurations of core components. In addition, we 

expect that practice guidelines might be more useful for practitioners if they are focused separately on the five program 

approaches.

Exhibit 4 shows the mean effect sizes and heterogeneity statistics for the five program approach groups. All five of the 

broad program approaches have statistically significant impacts on externalizing behavior problems. In addition, each has 

sufficient variability to explore core components within the group, as evidenced by the statistically significant Q-statistics, 

and large I2 and τ

2 values. 

Exhibit 4. Mean Effect Sizes and Heterogeneity Statistics for the Program Approach Categories

k 

Mean Effect 

Size se LCI UCI τ2 I

2 Q 

Family Relations and Parenting Skills 64 .52* 0.07 0.38 0.66 .19 78.61 392*

Approaches with a family focus 30 .53* 0.10 0.32 0.73 .29 85.26 297* 

Approaches focused on parent training 34 .52* 0.10 0.32 0.72 .08 58.48 76* 

Relational Approaches 91 .30* 0.06 0.18 0.42 .28 80.60 357*

Open-ended or eclectic approaches 47 .39* 0.08 0.22 0.55 .22 79.79 183* 

Approaches with a therapeutic orientation 44 .20* 0.09 0.03 0.38 .35 79.76 173*

Skill-building 121 .32* 0.05 0.22 0.43 .18 66.50 369*

Interpersonal skills + affective/executive responses 45 .31* 0.09 0.13 0.48 .10 55.29 98* 

Interpersonal skills 46 .37* 0.09 0.19 0.55 .33 78.13 221*

Affective/executive responses 30 .28* 0.11 0.06 0.51 .08 38.73 46* 

Behavior Management 27 .58* 0.12 0.35 0.81 .19 67.89 794*

Academic and Educational Approaches 75 .18* 0.06 0.06 0.30 .29 91.26 702*

School environment or structure 21 .21 0.12 -0.02 0.44 .42 94.22 314* 

Tutoring or academic support 37 .21* 0.09 0.03 0.39 .35 89.43 330*

Career or employment focus 17 .11 0.13 -0.14 0.36 .05 75.38 56* 

Note. k = number of studies contributing to the mean effect size estimate; se = standard error of the estimate; LCI and UCI are the lower and upper 95% confidence interval boundaries; 

τ2 is an estimate of the between-studies variance; I2 is the proportion of between-studies variance to the total variance; Q is an index of the total amount of study-to-study variation.

*p<.05

Across the five approaches, the confidence intervals overlap for all approaches except academic and educational 

approaches (Exhibit 5). Academic and educational approaches are effective, as evidenced by the positive, statistically 

significant mean effect, but are less effective overall than family relations and parenting skills approaches and behavior 

management approaches. In addition, the approach sub-categories within each of the main approach groups also tend to 

exhibit similar impacts on average, in spite of the conceptual differences between them. 

The differences in the magnitude of the average effects across the five approach groups are large enough that they might 

obscure the relationships of other core components to the outcomes. Thus, there are both practical reasons (i.e., practice 

guidelines might be more useful if separated by program approach) and empirical reasons (i.e., differences in average 

effects between programs might obscure the relationships of moderators to the outcome) to explore the core components

separately for each program approach.
Back to Table of Contents Technical Report  15

Exhibit 5. Mean Effect Sizes and Confidence Intervals for the Program Approach Categories

For each program approach group, we began our exploratory analysis by examining the descriptive statistics for the 

potential core components in three domains: program content, program structure, and participant characteristics. The 

specific configurations of core components were tailored to the individual approach categories because not all features 

were present or had sufficient variability within a category. 

• Program content: approach sub-category and the most common content elements in the approach category

• Program structure: duration of intervention and frequency of treatment; individualized vs. group; classroom-based, 

pullout, community-based; delivery personnel; use of lesson plans

• Participant characteristics: age, presenting problem, gender and race/ethnicity mix, and SES

We selected potential core components from the set of available variables using several strategies. First, we examined 

the bivariate relationships of each potential core component with effect size; those with near zero relationships were not 

explored further. In addition, we used a form of random forests analysis tailored to meta-analytic data to assist with 

variable selection. Random forests analysis is a technique for variable selection that helps identify potentially influential

variables for analysis while taking into consideration the interrelationships and interactions among those variables 

(Hapfelmeier & Ulm, 2013; van Lissa, 2018). Variables correlated with effect size that were not highly skewed (i.e., only a 

small number of programs in the group exhibited that feature) were entered into a random forests analysis. Those that 

were identified as important in that analysis were explored in our meta-regression models. To arrive at the final metaregression models, we removed variables selectively from the meta-regression models that did not have meaningful 

independent relationships with the effect sizes. As we mentioned above, we chose .10 effect size units as the threshold 

for a meaningful difference. Thus, binary core components were considered to have a meaningful relationship with effect 

sizes if their independent contribution to predicting effect sizes (the regression coefficients, or bs, in the models) was 0.10 

or larger. We also used the .10 threshold for core components indexed on a standard scale (i.e., with a mean of zero and 

a standard deviation of 1) such as delivery complexity. The .10 threshold was also considered meaningful when 

associated with a 1 point change on the three potential core components that were ordinal (program frequency, gender 

mix, and SES). Two potential core components were scaled continuously, program duration and average age of the 

sample. For these variables, if a 10 week change on duration or 3 year change on age was associated with +/- .10 in the 

effect size, the variable was considered meaningful. These values represent approximately half of a standard deviation for 

each variable. More details about the specifics of our analysis are included in Appendix B.
Back to Table of Contents Technical Report  16

6.1 Core Components for Family Relations and Parenting Skills 

Approaches

The key features of the family relations and parenting skills approaches are shown in Exhibit 6 along with the 

correlations between selected features and effect sizes. Programs in this group averaged about 15 weeks in 

duration, typically offering sessions once a week. Most programs were community-based (rather than 

school-based). Specialist staff (e.g., social workers, clinicians) were the most common delivery personnel 

after researchers and all other types of personnel. Content elements were varied, with many focused on family relations or 

parenting, as expected. A non-trivial number of programs also included content for youth, including personal development 

and interpersonal or social skills.

Exhibit 6. Characteristics of Family Process and Parenting Skills Approaches (k=64)

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Implementation Quality Approach Subcategory

Explicit or suggested problems 28 (44%) -0.05 Family focus 30 0.21

No problems or no mention of problems 36 (56%) Parent training focus 34

Delivery Complexity Content Elements

Number of different settings 1.9 (1.1) -0.17 Relaxation skills training 2

Number of different delivery personnel 1.8 (0.9) -0.07 Appropriate classroom behavior 3

Number of different formats 1.5 (0.9) -0.20 Problem solving sequence 8

Delivery complexity factor 0.05 (1.0) -0.19 Empathy 1

Provider Training or Supervision Attribution retraining 7

Yes 49 (77%) 0.11 Moral development training 0

Dosage Self-statements to inhibit impulsiveness or 

promote positive behavior

1 

Duration (weeks) 15.1 (13.6) -0.20 Interpersonal, social skills 16 -0.20

Frequency (sessions/week) -0.04 Conflict resolution 3 

Less than weekly 7 (11%) Assertive communication skills 0 

1x/week 38 (59%) Personal development 14 0.39

More than 1x/week 18 (30%) Identifying, understanding feelings 4 

Setting Trusting relationship with caring adult

Classroom-based 7 (11%) -0.22 General personal or social support 1 

School-based pullout 2 (3%) 0.25 Behavioral coping skills for anger/aggression 2 

Community-based 55 (86%) 0.08 Problem solving sequence for 

anger/aggression

2 

Delivery Personnel Attribution retraining for anger/aggression 0 

Researcher 21 (33%) 0.09 Self-statements to inhibit anger/aggression 0 

Specialist staff 23 (36%) -0.13 Angry behavior cycle 0 

Laypersons, mixed personnel types, and 

others

20 (31%) Parent skills training 53 -0.03

Format Parent functioning 17 0.13

Group of parents/families 25 (39%) 0.08 Social support, building support network 8 

One-on-one 21 (33%) 0.04 Family communication skills 37 0.27

All other formats 18 (28%) Engagement with child’s school 7 
Back to Table of Contents Technical Report  17

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Lesson Plans Information provision for families 0 

Yes 40 (63%) 0.29 Academic, educational 7 

Participant Characteristics School structure 0 

Presenting Problem=behavior 38 (59%) -0.16 Service learning 1 

Age 9.4 (4.1) 0.10 Self-sufficiency skills

Gender mix -0.08 Health education and promotion 1 

No males (<5%) 1 (2%) Provide basic needs 3 

Some males (<50%) 9 (14%) Recreational 5 

50-60% male 11 (17%) Employment, vocational

Mostly males (>60%) 35 (55%) Case management, service brokerage 2 

All males (>95%) 8 (13%) Parenting skills for youth 1 

Predominant race/ethnicity Unspecified 1 

White 44 (69%) -0.08 Violence and drug use education 3 

Black 6 (9%)

Hispanic 5 (8%)

Other minority 1 (2%)

Mixed, none > 60% 8 (13%)

SES -0.02

Low 29 (45%)

Middle 22 (34%)

Upper middle 13 (20%)

Note. k=number of studies. The correlations shown in the table are bivariate inverse variance weighted correlations between the potential core component and the effect size. For binary 

variables (e.g., implementation quality) the correlation is reported for only one direction. For categorical variables, the correlations reported are for the category shown with all other 

values on the variable in the reference category. The correlations are reported only for variables or categories within categorical variables with at least 10 cases in the category.

We present three core components meta-regression models for the family process and parenting skills approaches in 

Exhibit 7. Model 1 shows the specific core components associated with the programs in this category. Model 2 adds the 

general core components so we can explore whether the relationships of the general factors with program impacts hold 

when the specific core components are included. The third model shows only the general factors to explore whether the 

general factors apply within the subset of family process and parenting skills approaches. These latter two models are 

reported mainly to address questions about the robustness of the findings. If we see differences in the relationships of the 

general core components to outcomes when they are considered alongside the specific core components or when they 

are considered within the program approach subgroups, this may be a sign of a confound. 

Recall that potential core components were considered for inclusion based on their relationships with effect size (see 

Appendix C) and were retained in Model 1 if the coefficients met our threshold for meaningful differences. Five specific 

core components were independently associated with effective family process and parenting skills approaches based on 

the thresholds for meaningful relationships we discussed earlier. Although none of the potential core components were 

statistically significant, the magnitude of their relationships with the effect sizes suggests that a change on the core 

component is associated with a meaningful difference on the outcome. Family relations and parenting skills programs 

in which services were delivered in one-on-one formats tended to show more positive outcomes than those with 

group formats. Programs that were lesson-plan-based also showed larger impacts than programs that were less 

structured. Two specific content elements were associated with program impacts: family communication skills and 

personal development elements were both associated with larger average impacts. Finally, family process and 

parenting skills approaches were slightly more effective with younger children.
Back to Table of Contents Technical Report  18

Exhibit 7. Core Components for Family Process and Parenting Skills Approaches (k=64)

Model 1 Model 2 Model 3

Specific Core Components b (se) b (se) b (se)

Intercept 0.51 (0.24) * 0.62 (0.19) ** 0.62 (0.15) ***

Delivery format: one-on-one 0.11 (0.16) 0.13 (0.18)

Lesson-plan-based program 0.19 (0.15) 0.20 (0.18)

Age of sample -0.03 (0.02) -0.02 (0.02)

Content element: Family communication skills 0.12 (0.14) 0.11 (0.15)

Content element: Personal development 0.15 (0.17) 0.16 (0.18)

General Core Components

Implementation: Explicit or suggested problems -0.10 (0.14) -0.11 (0.14)

Delivery complexity 0.01 (0.08) -0.05 (0.07)

Provider training or supervision -0.11 (0.17) -0.05 (0.16)

Model Statistics

Q-model 5.70 6.45 1.76

Q-residual 295.64 *** 290.54 *** 368.60 ***

τ2 0.18 0.20 0.20

I

2 76.86% 77.09% 78.17%

R2 3.48% 0.00% 0.00%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

Model 2 indicates that the relationship of delivery complexity with program impacts within this approach group is 

somewhat attenuated from what we observed in the analysis of all programs combined. We think this may be due to the 

fact that a large number of programs in this group are lesson-plan-based, which may protect against difficulties in 

implementation associated with high delivery complexity. In addition, the relationship between complexity and provider 

training or supervision for this group of approaches results in neither variable having a strong independent relationship 

with effect size in Model 3, although both variables have non-trivial univariate relationships (see Exhibit 6).

Across all the models for the family process and parenting skills approaches, the Q-model values are not statistically 

significant and the percent of variance accounted for by the models (R2

) is small. This means that, although the core 

components do have meaningful relationships with the effect sizes, differences among the programs remain that are not 

accounted for by the core components we have to work with. Since the models give a somewhat less than full accounting 

of the possible sources of differential effects for programs in this approach category, the resulting practice guidelines may

have correspondingly less potential influence for guiding program improvements. That is, there may be other unknown 

factors associated with beneficial (or even harmful) outcomes that could potentially overshadow the factors in the models. 
Back to Table of Contents Technical Report  19

6.2 Core Components for Relational Approaches

The key features of the relational approaches are shown in Exhibit 8. Programs in this group are almost twice 

as long in duration on average as those in the previous group of family relations and parenting skills 

approaches. All settings (in-class, at school but in pull-out format, and in community) are about equally 

 epresented, in contrast to the previous group which contained primarily community-based programs. A 

quarter of the programs delivered services primarily in a one-on-one format. The youth participants were also 

considerably older than those in the previous group (13 years for this approach category vs. 9 years across all programs). 

Interpersonal, social skills and personal development were common content elements, as were academic or educational 

elements, service learning, and parenting skills for youth. There is a small group of programs in this approach category 

focused on teen pregnancy prevention that included service learning and parenting skills for the youth participants, which 

explains the prevalence of these latter two elements in this group. 

Exhibit 8. Characteristics of Relational Approaches (k=91)

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Implementation Quality Approach Subcategory

Explicit or suggested problems 24 (26%) -0.09 Open-ended or eclectic 47 0.01

No problems or no mention of problems 67 (74%) Particular orientation or structure 44

Delivery Complexity Content Elements

Number of different formats 1.7 (0.6) -0.19 Relaxation skills training 0 

Number of different provider types 1.4 (0.8) -0.11 Appropriate classroom behavior 12 0.15

Number of different settings 1.6 (0.8) -0.17 Problem solving sequence 2 

Delivery complexity -0.11 (0.7) -0.21 Empathy 0 

Provider Training or Supervision Attribution retraining 3 

Yes 37 (41%) 0.22 Moral development training 0 

Dosage Self-statements to inhibit impulsiveness or 

promote positive behavior

1 

Duration (weeks) 28.3 (21.2) -0.28 Interpersonal, social skills 51 -0.04

Frequency (sessions/week) -0.12 Conflict resolution 2 

Less than weekly 9 (10%) Assertive communication skills 0 

1x/week 32 (35%) Personal development 65 -0.00

2x/week 36 (40%) Identifying, understanding feelings 10 0.09

More than 2x/week 13 (15%) Trusting relationship with caring adult 18 -0.15

Setting General personal or social support 7 

In-class 31 (34%) -0.25 Behavioral coping skills for anger/aggression 0 

Pullout 34 (37%) 0.27 Problem solving sequence for anger/aggression 2 

Community 26 (29%) -0.02 Attribution retraining for anger/aggression 0 

Delivery Personnel Self-statements to inhibit anger/aggression 0 

Researcher 19 (21%) 0.18 Angry behavior cycle 2 

Specialist staff 25 (28%) -0.12 Parent skills training 6 

Laypersons 31 (34%) -0.08 Parent functioning 1 

All others 16 (17%) Social support, building support network 2 

Format Family communication skills 5 

One-on-one (vs. group) 23 (25%) 0.21 Engagement with child’s school 5 

Lesson Plans or Content Focused Information provision for families 2 

Yes 6 (7%) Academic, educational 20 -0.17
Back to Table of Contents Technical Report  20

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Participant Characteristics School structure 0 

Presenting Problem=behavior 29 (32%) 0.30 Service learning 23 -0.19

Age 13.4 (3.2) -0.13 Self-sufficiency skills 0 

Gender mix 0.23 Health education and promotion 2 

No males (<5%) 5 (6%) Provide basic needs 1 

Some males (<50%) 24 (26%) Recreational 12 0.09

50-60% male 15 (17%) Employment, vocational 3 

Mostly males (>60%) 23 (25%) Case management, service brokerage 8 

All males (>95%) 24 (26%) Parenting skills for youth 22 -0.20

Predominant race/ethnicity Unspecified 1 

White 35 (39%) 0.20 Violence and drug use education 6 

Black 28 (31%)

Hispanic 10 (11%)

Other minority 0 (0%)

Mixed, none > 60% 18 (20%)

SES 0.06

Low 52 (57%)

Mid 29 (32%)

High 10 (11%)

Note. k=number of studies. The correlations shown in the table are bivariate inverse variance weighted correlations between the potential core component and the effect size. For binary 

variables (e.g., implementation quality) the correlation is reported for only one direction. For categorical variables, the correlations reported are for the category shown with all other 

values on the variable in the reference category. The correlations are reported only for variables or categories within categorical variables with at least 10 cases in the category.

Exhibit 9 shows meta-regression Model 1 with specific core components; Models 2 and 3 explore the general core 

components for this approach category. The analysis identified five core components for the relational approaches. Oneon-one formatted programs were associated with better outcomes than group-based formats. Programs 

delivered in schools for which participants were pulled out of class for services were also associated with better 

outcomes than programs delivered in class or in community settings. Two content elements were associated with 

program impacts. The set of programs with a service learning component were less effective overall than the other 

relational approaches without this component. Programs that included any content element relating to 

interpersonal skills exhibited better outcomes than relational approaches that did not include these elements.

One participant characteristic was associated with better outcomes; programs in which the youth participants were 

selected as a result of behavioral issues performed better than programs in which the youth were selected as a result of 

other risk factors, which included academic difficulties, mental health issues, family conflict, or multiple risk factors. Youth 

with behavior problems may have more room for improvement on the measures of externalizing behavior that serve as 

our outcomes than youth experiencing other kinds of difficulties. Practically, a finding like this is not intended to suggest 

that programs should focus solely on youth experiencing behavior problems. Rather, program personnel may have a 

better sense of what impacts they can expect when serving youth with academic versus behavioral difficulties, for 

example, knowing that impacts on externalizing behavior with youth who present with issues other than behavior 

problems tend to be smaller or they may consider programming with a different focus.
Back to Table of Contents Technical Report  21

Exhibit 9. Core Components for Relational Approaches (k=91)

Model 1 Model 2 Model 3

Specific Core Components b (se) b (se) b (se)

Intercept -0.18 (0.20) -0.04 (0.20) 0.25 (0.09) **

Delivery format: one-on-one 0.24 (0.14) † 0.35 (0.15) * 

Delivery setting: pullout 0.26 (0.14) † 0.24 (0.15)

Presenting problem: behavior 0.43 (0.13) ** 0.50 (0.14) ***

Content element: Service learning -0.14 (0.17) -0.23 (0.17)

Content element: Any interpersonal skills element 0.26 (0.17) 0.24 (0.17)

General Core Components

Implementation: Explicit or suggested problems -0.29 (0.14) * -0.07 (0.15)

Delivery complexity -0.08 (0.09) -0.14 (0.10)

Provider training or supervision -0.16 (0.14) 0.14 (0.14)

Model Statistics

Q-model 26.66 *** 33.87 *** 4.58

Q-residual 271.66 *** 257.49 *** 332.03 ***

τ2 0.21 0.20 0.27

I

2 74.70% 72.92% 79.17%

R2 26.22% 29.28% 3.62%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

Model 3 in Exhibit 9 shows the relationships between the general core components and program effects for the relational 

approaches; these relationships are similar to those we found for the full set of 391 programs (Exhibit 3). However, Model 

2 suggests that some of the general and specific core components may be confounded in this approach category. The 

provider training and supervision variable is nearly redundant with the pull-out delivery setting variable (r=.50). The 

negative coefficient we see for provider training or supervision is thus driven primarily by the small number of programs

with training or supervision that are not pullout programs (k=14). We do not interpret this finding to suggest that training 

and supervision are not important for classroom-based or community-based programs; rather, it is difficult to tease out the 

complex interrelationships among core components when particular combinations of factors are not evenly represented 

across the dataset.

The Q for Model 1 is statistically significant and the variables in the model account for about a quarter of the observed 

variability in program effects across studies. Thus, the configuration of core components for the relational approaches 

have potential to guide practice towards better outcomes. Although rather substantial variability remains, as suggested by 

the large I2 value, the fact that features of the programs that we can identify in the research might be influential enough to 

effect practice is encouraging. 
Back to Table of Contents Technical Report  22

6.3 Core Components for Skill-building Approaches

The key features of the 121 studies of skill-building approaches are shown in Exhibit 10. Like the relational 

approaches, skill-building approaches are delivered across classroom, pull-out, and community settings, but 

the skill-building approaches tend to be shorter than the relational approaches. The one-on-one format is 

also less common in this category. We see teachers as delivery personnel in a number of cases. Delivery 

complexity is lower than the average across all of the programs, but many programs have multiple content elements.

Exhibit 10. Characteristics of Skill-building Programs (k=121)

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Implementation Quality Approach Subcategory

Explicit or suggested problems 42 (35%) -0.33 Interpersonal + affective/executive 45 -0.09

No problems or no mention of problems 79 (65%) Interpersonal 46 0.09

Delivery Complexity Affective/executive 30 0.01

Number of different formats 1.4 (0.9) -0.24 Content Elements

Number of different provider types 1.5 (0.8) -0.18 Relaxation skills training 14 0.03

Number of different settings 1.3 (0.8) -0.26 Appropriate classroom behavior 12 0.04

Delivery complexity -0.40 (0.9) -0.26 Problem solving sequence 50 0.14

Provider Training or Supervision Empathy 20 -0.03

Yes 69 (57%) 0.14 Attribution retraining 13 -0.00

Dosage Moral development training 2 

Duration (weeks) 14.8 (16.1) -0.13 Self-statements to inhibit impulsiveness or 

promote positive behavior

9 

Frequency (sessions/week) 0.13 Interpersonal, social skills 51 0.01

Less than weekly 9 (7%) Conflict resolution 18 0.21

1x/week 45 (37%) Assertive communication skills 17 0.04

1-2x/week 12 (10%) Personal development 39 0.07

2x/week 31 (26%) Identifying, understanding feelings 32 0.05

More than 2x/week 24 (20%) Trusting relationship with caring adult 3 

Setting General personal or social support 1 

In-class 36 (30%) -0.10 Behavioral coping skills for anger/aggression 13 -0.03

Pullout 67 (55%) 0.19 Problem solving sequence for 

anger/aggression

32 -0.02

Community 18 (15%) -0.11 Attribution retraining for anger/aggression 3 

Delivery Personnel Self-statements to inhibit anger/aggression 31 0.04

Researcher 45 (38%) -0.12 Angry behavior cycle 26 0.06

Specialist staff 23 (19%) 0.20 Parent skills training 13 -0.24

Teachers 22 (18%) 0.02 Parent functioning 1 

All others 31 (25%) Social support 2 

Format Family communication skills 10 -0.25

One-on-one (vs. group) 11 (9%) 0.14 Engagement with child’s school 5 

Lesson Plans or Content Focused Information provision for families 4 

Yes 83 (69%) 0.24 Academic, educational 6 
Back to Table of Contents Technical Report  23

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Participant Characteristics School structure 1

Presenting Problem=behavior 73 (60%) -0.01 Service learning 0 

Age 10.8 (3.1) 0.28 Self-sufficiency skills 0

Gender mix 0.13 Health education and promotion 0 

No males (<5%) 3 (3%) Provide basic needs 1 

Some males (<50%) 10 (8%) Recreational 3 

50-60% male 28 (23%) Employment, vocational 1 

Mostly males (>60%) 51 (42%) Case management, service brokerage 1 

All males (>95%) 29 (24%) Parenting skills for youth 0 

Predominant race/ethnicity Unspecified 0 

White 53 (44%) -0.02 Violence and drug use education 2 

Black 40 (33%)

Hispanic 7 (6%)

Other minority 2 (2%)

Mixed, none > 60% 19 (16%)

SES 0.13

Low 56 (46%)

Mid 32 (26%)

High 33 (27%)

Note. k=number of studies. The correlations shown in the table are bivariate inverse variance weighted correlations between the potential core component and the effect size. For binary 

variables (e.g., implementation quality) the correlation is reported for only one direction. For categorical variables, the correlations reported are for the category shown with all other 

values on the variable in the reference category. The correlations are reported only for variables or categories within categorical variables with at least 10 cases in the category.

The three meta-regression models for the skill-building approaches are shown in Exhibit 11. Four specific core 

components were identified. Delivery by specialist staff was associated with larger impacts than delivery by other 

types of personnel. In addition, programs that were lesson-plan based were associated with better outcomes 

than those that were less structured. Many skill-building approaches included multiple skills-based elements, including 

interpersonal skills, skills for identifying and understanding emotions, skills for managing anger or impulsiveness, and 

problem solving skills. Among these elements, programs that included conflict resolution skills among their mix of 

elements were particularly effective. Programs that also included a family or parenting element were less 

effective. 
Back to Table of Contents Technical Report  24

Exhibit 11. Core Components for Skill-building Approaches (k=121)

Model 1 Model 2 Model 3

Specific Core Components b (se) b (se) b (se)

Intercept 0.14 (0.09) 0.12 (0.10) 0.32 (0.09) ***

Delivery by specialist staff (vs. all others) 0.51 (0.12) *** 0.46 (0.12) ***

Lesson-plan program 0.13 (0.10) 0.13 (0.10)

Content element: Conflict resolution skills 0.26 (0.12) * 0.29 (0.12) * 

Content element: Any family/parenting element -0.41 (0.14) ** -0.11 (0.19)

General Core Components

Implementation: Explicit or suggested problems -0.25 (0.10) * -0.30 (0.10) **

Program complexity score -0.09 (0.06) -0.06 (0.05)

Provider training or supervision 0.07 (0.09) 0.15 (0.10)

Model Statistics

Q-model 27.28 *** 39.85 *** 14.62 **

Q-residual 261.51 *** 237.72 *** 316.23 ***

τ2 0.13 0.11 0.16

I

2 56.33% 52.62% 61.53%

R2 30.50% 36.95% 12.94%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

The findings shown in Models 2 and 3 in Exhibit 11 for the general core components are consistent with the findings for 

the general core components when tested across all programs in the dataset. The implementation problems factor is 

particularly important for the skill-building approaches, which may require more careful attention to fidelity than other types 

of approaches.

The fit statistics for Models 1 and 2 indicate that the configurations of core components identified from the research 

account for significant between-study differences. Comparing the τ

2 and I2 values from the models in Exhibit 11 to the null 

model for skill-building approaches shown in Exhibit 4, we see that our core components substantially reduce the 

variability in the distribution. Practice guidelines developed from these findings, thus, have potential to result in positive 

changes in youth outcomes. 
Back to Table of Contents Technical Report  25

6.4 Core Components for Behavior Management Approaches

The key characteristics of the 27 studies of behavior management approaches are shown in Exhibit 12. 

Behavior management programs averaged about 23 weeks in duration, many taking place over the course of 

an elementary school semester about once or twice a week. The majority of behavior management 

programs were delivered in classroom settings and about half were administered one-on-one. In spite of the 

heterogeneity in the effect sizes, the relatively small number of programs in this approach category limits our ability to 

explore potential core components for this group of programs. 

Exhibit 12. Characteristics of Behavior Management Approaches (k=27)

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Implementation Quality Content Elements

Explicit or suggested problems 12 (44%) -0.15 Relaxation skills training 0 

No problems or no mention of problems 15 (56%) Appropriate classroom behavior 21 0.07

Delivery Complexity Problem solving sequence 0 

Number of different formats 1.6 (0.8) -0.11 Empathy 0 

Number of different provider types 2.1 (1.2) -0.10 Attribution retraining 0 

Number of different settings 1.2 (0.6) 0.09 Moral development training 0 

Delivery complexity -0.10 (0.8) -0.08 Self-statements to inhibit impulsiveness or 

promote positive behavior

5 

Provider Training or Supervision Interpersonal, social skills 4 

Yes 20 (74%) 0.20 Conflict resolution 0 

Dosage Assertive communication skills 0 

Duration (weeks) 23.3 (32.5) -0.19 Personal development 6 

Frequency (sessions per week) -0.07 Identifying, understanding feelings 0 

Less than weekly 9 (7%) Trusting relationship with caring adult 0 

1x/week 45 (37%) General personal or social support 1 

1-2x/week 12 (10%) Behavioral coping skills for anger/aggression 0 

2x/week 31 (26%) Problem solving sequence for 

anger/aggression

0 

More than 2x/week 24 (20%) Attribution retraining for anger/aggression 0 

Setting Self-statements to inhibit anger/aggression 1 

In-class 19 (70%) -0.17 Angry behavior cycle 0 

Pullout 4 (15%) Parent skills training 5 

Community 4 (15%) Parent functioning 0 

Delivery Personnel Social support, building support network 0

Researcher 2 (7%) Family communication skills 0 

Specialist staff 6 (22%) Engagement with child’s school 0 

Teachers 11 (41%) -0.04 Information provision for families 0 

All others 8 (30%) Academic, educational 8 

Format School structure 0 

One-on-one (vs. group) 14 (52%) 0.33 Service learning 0 

Lesson Plans or Content Focused Self-sufficiency skills 0 

Yes 1 (4%) Health education and promotion 0 
Back to Table of Contents Technical Report  26

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Participant Characteristics Provide basic needs 0

Presenting Problem=behavior 11 (41%) 0.21 Recreational 1 

Age 9.9 (3.0) 0.01 Employment, vocational 0

Gender mix 0.11 Case management, service brokerage 0 

No males (<5%) 1 (4%) Parenting skills for youth 0 

Some males (<50%) 3 (11%) Unspecified 0 

50-60% male 3 (11%) Violence and drug use education 0 

Mostly males (>60%) 18 (67%)

All males (>95%) 2 (7%)

Predominant race/ethnicity

White 10 (37%) -0.06

Black 10 (37%)

Hispanic 2 (7%)

Other minority 1 (4%)

Mixed, none > 60% 4 (15%)

SES 0.13

Low 15 (56%)

Mid 7 (26%)

High 5 (19%)

Note. k=number of studies. The correlations shown in the table are bivariate inverse variance weighted correlations between the potential core component and the effect size. For binary 

variables (e.g., implementation quality) the correlation is reported for only one direction. For categorical variables, the correlations reported are for the category shown with all other 

values on the variable in the reference category. The correlations are reported only for variables or categories within categorical variables with at least 10 cases in the category.

The core components meta-regression analysis for behavior management approaches shown in Exhibit 13 indicates that 

one-on-one formatted programs performed better than programs delivered in group settings. Behavior 

management approaches are often tailored to individual youth participants so it is not surprising that the one-on-one 

format is more effective than the other formats. The findings from Models 2 and 3, although not universally consistent with 

the overall analysis, do not call into question the importance of our general core components. Behavior management 

approaches exhibited lower than average delivery complexity, which may explain the small coefficient for this variable in 

Models 2 and 3.
Back to Table of Contents Technical Report  27

Exhibit 13. Core Components for Behavior Management Approaches (k=27)

Model 1 Model 2 Model 3

Specific Core Components b (se) b (se) b (se)

Intercept 0.46 (0.13)*** 0.40 (0.27) 0.49 (0.25) †

One-on-one format 0.31 (0.22) 0.29 (0.28)

General Core Components

Implementation: Explicit or suggested problems -0.02 (0.27) -0.16 (0.23)

Program complexity score 0.05 (0.16) 0.00 (0.16)

Provider training or supervision 0.12 (0.31) 0.21 (0.29)

Model Statistics

Q-model 2.06 1.94 0.86

Q-residual 66.14 *** 62.19 *** 67.00 ***

τ2 0.17 0.21 0.27

I

2 64.12% 66.66% 90.45%

R2 9.71% 0.00% 6.00%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

Overall, the models for the behavior management approaches do not account for significant between-study variability. 

Other than one-on-one format, no other specific core component we identified in the source studies explained a 

meaningful degree of between-study differences, leaving rather substantial unexplained variability for such a small group 

of programs. Practice guidelines derived from these findings may have less potential to influence youth outcomes than 

those derived from models that more reliably account for observed differences between studies. However, the large mean 

effect size for this approach category ( = 0.58, p < .0001) indicates that behavior management approaches can produce 

meaningful changes in behavior. The difficulty is more that it is not clear how to improve on behavior management 

approaches, other than considering individualized or one-on-one delivery.
Back to Table of Contents Technical Report  28

6.5 Core Components for Academic and Educational Approaches

The characteristics of the final group of programs, the academic and educational approaches, are shown 

in Exhibit 14. The programs in this group differ from the other four groups in several ways. Academic and 

educational approaches are considerably longer than the other approaches and services are provided 

more frequently. Many of the school structure programs, for example, operate five days a week. As 

expected, many programs are delivered in class settings by teachers. Youth participants are older than 

for the other programs. Most programs in this approach group are focused on youth with academic 

difficulties rather than youth with behavior problems, though behavior problems are clearly a concern for these 

interventions as evidenced by the inclusion of externalizing outcome measures in the studies.

Exhibit 14. Characteristics of Academic and Educational Approaches (k=75)

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Implementation Quality Approach Subcategory

Explicit or suggested problems 43 (57%) -0.00 School structure 21 0.05

No problems or no mention of 

problems

32 (43%) Tutoring academic supports 37 -0.02

Delivery Complexity Career, vocational focus 17 -0.03

Number of different formats 2.6 (1.3) -0.16 Content Elements

Number of different provider types 2.2 (1.1) -0.13 Relaxation skills training 1 

Number of different settings 1.8 (0.9) -0.18 Appropriate classroom behavior 11 0.17

Delivery complexity 0.7 (1.2) -0.20 Problem solving sequence 2 

Provider Supervision or Training Empathy 0 

Yes 42 (56%) -0.03 Attribution retraining 2 

Dosage Moral development training 0 

Duration (weeks) 37.2 (27.5) -0.10 Self-statements to inhibit impulsiveness or 

promote positive behavior

1 

Frequency (sessions per week) 0.04 Interpersonal, social skills 13 0.12

Less than weekly 8 (11%) Conflict resolution 7 

1x/week 4 (5%) Assertive communication skills 2

2-4x/week 13 (17%) Personal development 38 0.002

More than 2x/week 50 (67%) Identifying, understanding feelings 2 

Setting Trusting relationship with caring adult 12 -0.12

In-class 51 (68%) 0.07 General personal or social support 18 -0.20

Pullout 7 (9%) Behavioral coping skills for anger/aggression 0 

Community 17 (23%) Problem solving sequence for anger/aggression 0 

Delivery Personnel Attribution retraining for anger/aggression 0 

Researcher 6 (8%) Self-statements to inhibit anger/aggression 0 

Specialist staff 10 (13%) Angry behavior cycle 1 

Teachers 44 (59%) 0.14 Parent skills training 6 

All others 15 (20%) Parent functioning 2

Lesson Plans or Content Focused Social support 1 

Lesson plans 4 (5%) Family communication skills 2 

Content focused 20 (27%) Engagement with child’s school 26 -0.21

Structural 31 (41%) 0.02 Information provision for families 3 

Combination 20 (27%) Academic, educational 57 0.08
Back to Table of Contents Technical Report  29

Frequency 

(%)

Mean (sd)

Correlation 

with Effect 

Size Frequency

Correlation 

with Effect 

Size

Participant Characteristics School structure 20 0.01

Presenting Problem=behavior 7 (9%) Service learning 8 

Age 13.4 (3.4) -0.05 Self-sufficiency skills 2 

Gender mix -0.10 Health education and promotion 5

No males (<5%) 1 (1%) Provide basic needs 2 

Some males (<50%) 12 (16%) Recreational 17 -0.05

50-60% male 26 (35%) Employment, vocational 27 0.05 

Mostly males (>60%) 28 (37%) Case management, service brokerage 17 -0.06

All males (>95%) 8 (11%) Parenting skills for youth 1 

Predominant race/ethnicity Unspecified 3 

White 22 (29%) -0.04 Violence and drug use education 3 

Black 29 (39%)

Hispanic 8 (11%)

Other minority

Mixed, none > 60% 16 (21%)

SES -0.03

Low 45 (60%)

Mid 21 (28%)

High 9 (12%)

Note. k=number of studies. The correlations shown in the table are bivariate inverse variance weighted correlations between the potential core component and the effect size. For binary 

variables (e.g., implementation quality) the correlation is reported for only one direction. For categorical variables, the correlations reported are for the category shown with all other 

values on the variable in the reference category. The correlations are reported only for variables or categories within categorical variables with at least 10 cases in the category.

Exhibit 15 presents the results of the core components meta-regression analysis for the academic and educational 

approaches. Unlike the other approaches, delivery personnel, setting, and format were not associated with more or less 

effective programs in this category. For the academic and educational approaches, different types of content were 

associated with program impacts on externalizing behavior problems. Among the approach subcategories, programs 

focused on school structure were associated with more positive outcomes than programs focused on tutoring 

and academic supports or career and vocational topics. In addition, programs with an appropriate classroom

behavior element exhibited more positive outcomes than programs that did not incorporate this element.

Programs with appropriate classrooms behavior elements included content on teaching the youth participants classroom

rules, when it is appropriate to raise your hand, to take turns speaking, to pay attention to instructors, and how to

contribute to an orderly classroom environment (i.e., not creating distractions). It is not surprising that academicallyfocused programs with an added behavior element might have stronger influences on externalizing behaviors than those

without such elements. Programs with more of a mentoring (trusting relationship with caring adult) or general

personal or social support focus were generally less effective for reducing behavior problems that programs

without these elements. 
Back to Table of Contents Technical Report  30

Exhibit 15. Core Components for Academic and Educational Approaches (k=75)

Model 1 Model 2 Model 3

Specific Core Components b (se) b (se) b (se)

Intercept 0.21 (0.09) * 0.30 (0.12) ** 0.32 (0.11) **

Subcategory: School structure (vs. tutoring and vocational approaches) 0.18 (0.16) 0.22 (0.16)

Content element: Appropriate classroom behavior 0.25 (0.19) 0.21 (0.19)

Content element: Trusting relationship w/ caring adult -0.15 (0.18) -0.08 (0.18)

Content element: General personal or social support -0.32 (0.17) † -0.32 (0.18) †

General Core Components

Implementation: Explicit or suggested problems -0.30 (0.16) † -0.25 (0.16)

Delivery complexity -0.08 (0.06) -0.13 (0.06) * 

Provider training or supervision 0.03 (0.14) 0.05 (0.14)

Model Statistics

Q-model 8.13 † 12.83 † 6.71 †

Q-residual 644.19 *** 617.37 *** 659.78 ***

τ2 0.27 0.27 0.28

I

2 90.57% 90.17% 90.69%

R2 5.60% 6.93% 4.00%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001

Models 2 and 3 show the findings for the general core components for the academic and educational approaches. The 

relationships of these general factors to the outcomes parallel the overall findings for the general factors. Academically 

focused programs are generally longer and more complex than average. Implementation may be particularly important for 

these types of programs to achieve the expected outcomes.

The overall model fit for the academic-educational approaches is moderate. The Q-model statistics and proportion of 

variance accounted for by the models indicate that there may be other, unknown factors associated with positive program 

effects in addition to the program characteristics identified in our models. Although the models provide some clues to 

factors that are meaningfully associated with more effective programs (e.g., appropriate classroom behavior elements, 

implementation quality), the variability unaccounted for by the models could be predictable from characteristics that are 

unknown or unreported in the research and these unknown factors could overshadow those we identified here.
Back to Table of Contents Technical Report  31

7. CONCLUSIONS 7 Conclusions

Overall, our analysis identified a range of actionable core components in the research on youth programs. Across all 

programs, three general core components were observed:

• Implementation quality: Explicit mention or suggestion of implementation problems was associated with smaller 

program impacts. 

• Delivery complexity: Programs delivered with multiple formats (e.g., with both group and individual components), 

in multiple settings (e.g., during and after school), and/or that employed multiple different types of personnel (e.g., 

teachers and social workers) tended to have smaller program impacts. 

• Provider training or supervision: Explicit mention of provider training or supervision was associated with larger 

program impacts

In addition, across the five approaches to behavior change, a number of specific core components were identified, as 

summarized in Exhibit 16. 

Exhibit 16. Summary of Analysis of Specific Core Components

Program Content Program Structure

Participant 

Characteristics

Overall 

Model Fit

Family 

Relations and 

Parenting 

Skills

Programs that included family communication 

skills or personal development elements 

exhibited larger program impacts. 

One-on-one formatted programs 

and those with lesson plans 

exhibited larger program impacts. 

Programs with younger 

children exhibited larger 

program impacts. 

Weak

Relational 

Approaches

Programs that included interpersonal skills 

elements exhibited larger program impacts.

Programs that included service learning 

elements tended to have smaller program 

impacts. 

One-on-one formatted programs 

and those based in schools with 

pullout formats evidenced larger 

program impacts.

Programs serving youth 

with behavior problems 

exhibited larger 

program impacts.

Strong

Skill-Building Programs that included conflict resolution skills 

elements exhibited larger program impacts. 

Programs that included any family/parenting 

element exhibited smaller program impacts. 

Programs that had lesson-plans 

and used specialist delivery 

personnel exhibited larger 

program impacts. 

Strong

Behavior 

Management

One-on-one formatted programs 

exhibited larger program impacts.

Weak

AcademicEducational

Programs that focused on changing the school 

environment or structure exhibited larger 

program impacts than those focused primarily 

on academic or vocational content. 

Programs that included appropriate classroom 

behavior elements exhibited larger program 

impacts. 

Programs that included trusting relationship or 

general personal support elements exhibited 

smaller program impacts. 

Moderate

The general core components and the specific core components for relational approaches and skill-building approaches 

explain meaningful differences in program impacts and, thus, have the strongest potential to inform practice guidelines. 

For academic-educational approaches, the core components we identified resulted in an overall model with a moderate fit 

to the data. For academic-educational approaches, then, the corresponding practice guidelines may have less potential 

influence on youth outcomes because other factors not present in our dataset may also be associated with effective 
Back to Table of Contents Technical Report  32

programs. In contrast, the models for family relations and parenting skills approaches and behavior management 

approaches, though they point to particular factors associated with more effective programs, did not account for significant 

variability in program effects. There may be other factors associated with larger or smaller impacts that could potentially 

overshadow the factors identified in our models. For these approaches, more work is needed to have a stronger claim on 

the core components that might be influential enough to improve youth outcomes.

The weak model fits that we observe for family relations and parenting skills approaches and behavior management 

approaches means that we are less confident about the practices we might recommend that could improve outcomes for 

service providers implementing such approaches. However, these two approach categories had the largest average 

impacts on youth behavior outcomes across all the approach categories. Thus, just because the model results suggest 

that there may be other factors that are more predictive of larger impacts than the core components we identified for these 

approaches, both approaches have good potential to improve youth outcomes. This is particularly true for the behavior 

management approaches, which because of their relatively low delivery complexity, may be recommended as a standalone strategy. 

The findings and the meta-regression analyses we use to produce them are correlational and it would be incorrect to draw 

causal conclusions from this work. We also note that there is a limited range of and, especially, detail about potential core 

components available from the contributing studies. We extracted from the studies and explored in our analyses a number 

of variables, but large proportions of the differences in effectiveness we see between studies is left unexplained. Future 

studies and, we hope, better reporting of key program and implementation features may further improve our ability to 

identify more features associated with positive effects. Indeed, the ultimate test of the validity of results such as these is 

not the statistical relationships we observe among the source studies, but demonstrations in the field that programs with 

the identified core components do in fact have better outcomes.

The next step for this work involves more fully developing each of the core components we identified here into actionable 

practice guidelines. This will include delving into the research studies themselves, as well as the literature on 

implementation strategies, to identify practical examples and tips for how to put something in to practice. 
Back to Table of Contents Technical Report  33

APPENDIX A. THE META-ANALYTIC DATABASE Appendix A. The Meta-Analytic Database

This paper makes use of a large meta-analytic database developed by Sandra Wilson of Abt Associates and her former 

colleague, Mark Lipsey of Vanderbilt University, which houses the results of hundreds of studies of youth programs. This 

database is a compilation of seven separate meta-analyses of youth programs conducted by two teams (Lipsey/Wilson 

and Joseph Durlak). This appendix provides details about the meta-analytic database and its development. 

The research captured in the database represents a range of program environments and age ranges and includes only 

RCTs or quasi-experiments of relatively high quality. Each study provides estimates of program impacts (i.e., effect sizes) 

for the major study outcomes, along with descriptive details about each study’s program, providers, participants, and 

implementation activities. Many of the studies in the database provide information about the programs, providers, and 

implementation activities that serve as our potential core components. Some studies provide extensive detail, while for 

others reporting is somewhat limited. To maximize the utility of our approach, it would be desirable to have more 

information reported about the features that serve as our potential core components than we typically find in the research. 

But, within the limits of what is reported, the common coding scheme we developed to collate the seven meta-analyses 

attempts to capture as much detail as possible about the wide range of topics that might inform our work. Exhibit A1

describes the range of programs and outcomes included in the database and the year of publication for the most recent 

studies in each. For the analyses reported in this report, we selected studies from any of the seven meta-analyses 

involving selected or indicated prevention programs that reported program impacts on externalizing problem behavior.

Exhibit A1. The Seven Meta-analyses Included in the Database

Meta-analysis Studies Included Primary Outcomes

Most 

Recent 

Studies

After-school programs (Durlak, 

Weissberg, & Pachan, 2010)

68 studies of after-school 

programs for youth age 5-18

Social-emotional skills, self-esteem, conduct 

problems/externalizing, academic performance, school 

attendance and engagement, and substance use

2007

School-based social and emotional 

learning programs (Durlak, 

Weissberg, Dymnicki, Taylor, & 

Schellinger, 2011)

213 studies of universal schoolbased programs for youth age 5-

18 targeting social-emotional 

learning

Social-emotional skills, positive social behavior, conduct 

problems/externalizing, internalizing problems, academic 

performance, self-esteem, and school attitudes

2007

School-based prevention programs 

for acting out problems (Payton, et 

al., 2008)

38 studies of school-based 

prevention programs for acting 

out problems for at-risk children 

in grades K-6 

Positive social behavior and conduct 

problems/externalizing

2007

Parent and family programs for 

improving child mental health 

outcomes (Durlak, 2007)

57 studies of programs 

intervening with parents or 

family to influence outcomes for 

school-aged children (age 5-18)

Positive social behavior, family relations, conduct 

problems/externalizing, and emotional 

distress/internalizing problems

2007

Interventions for juvenile offenders

(Lipsey, 1992; Lipsey, 2009)

583 studies of interventions for 

juvenile offenders age 12-21

All the studies have delinquency outcomes; other 

outcomes include social-emotional skills, self-esteem, 

peer and family relations, emotional distress/internalizing 

problems, school attendance, school dropout, school 

performance, and conduct problems

2007

Early interventions targeting risk for 

antisocial behavior (Wilson, Lipsey, 

& Derzon, 2003; Wilson & Lipsey, 

2007)

456 studies of interventions for 

youth under age 18 focused on 

antisocial behavior and risk for 

antisocial behavior

All the studies have conduct problem outcomes; other 

outcomes include social-emotional skills, peer relations, 

self-esteem, self-control, internalizing, and academic 

performance

2004

School dropout prevention programs

(Wilson, Tanner-Smith, Lipsey, 

Steinka-Fry, & Morrison, 2011) 

317 studies of school dropout 

prevention programs

All have school dropout or graduation outcomes; other 

outcomes include attendance, academic performance, 

school attachment, and conduct problems/externalizing

2009
Back to Table of Contents Technical Report  34

Coded Variables in the Meta-analytic Database

The two research teams (Lipsey/Wilson and Durlak) that created the seven meta-analytic databases collaborated and 

built from each other’s work over time. Thus, the databases had many similar coding items to begin with, but they were 

not identical. To create the combined database, Wilson and Lipsey built on and adapted the original coding to produce a 

uniform set of coded items across the combined database. The database includes many variables, not all of which were 

used in the analysis. This section shows the coding items as they are coded in the database for all of the variables used in 

the analyses reported in this paper in the program structure, implementation strategies and outcomes, and participant 

characteristics domains. We also show the coding items for the methodological characteristics. The items in the program 

content domain are included in the next section. In most cases, variables were combined or recoded for analysis.

Program Structure

Duration of treatment. Approximate (or exact) number of weeks that subjects received treatment, from first treatment 

event to last excluding follow-ups designated as such. Divide days by 7; multiply months by 4.3. Code 999 if cannot tell. 

Estimate for this item if necessary, and if you can come up with a reasonable order of magnitude number.

Approximate (or exact) frequency of contact between participants and provider or program activity. This refers only to the 

elements of treatment that are different from what the comparison group receives. 

1. Less than weekly

2. Once a week

3. 1-2 times a week

4. 2 times a week

5. 2-3 times a week

6. 3 times a week

7. 3-4 times a week

8. 4 times a week

9. Daily contact (not 24 hours of contact per day but some treatment during each day, perhaps excluding weekends, 

e.g., as in a school-based program that occurs every school day)

10. Continuous (e.g. residential living)

99. Cannot tell

Primary location of the program. Where does the service delivery take place?

1. School

2. Not school

3. Institution (i.e., residential)

4. Alternative school (must be clearly specified as “alternative” school)

Specific Site Detail. Where was the intervention delivered? Think about the actual treatment events and where they 

occurred. Check all that apply.

School Sites

1. Regular Classroom (interventions delivered during regularly scheduled classes AND in the children’s regular 

classroom)

2. Special Class (e.g., children in treatment are in a classroom-type setting that is different from a typical classroom, 

although it may be the subjects’ usual classroom – includes such settings as special education classrooms, 

alternative schools, etc.) 

3. Entire School; Systemic (this would include interventions like metal detectors and other environmental changes that 

presumably affect the whole school)

4. Resource Room, School Counselor’s Office, or other similar setting that is NOT the children’s regular classroom; 

the idea here is that children are removed from class for treatment

5. School Playground

6. School Site, cannot tell which of the above
Back to Table of Contents Technical Report  35

7. After School: treatment delivered at school facility, but not during regular school hours

Non-school Sites

8. Outpatient, Non-residential, Private office, clinic, center (e.g., YMCA, university, therapist’s office; medical facility)

9. Outpatient, Non-residential, Public office, clinic, center (e.g., probation department, public mental health clinic, 

community or neighborhood center)

10. Home (Treatment delivered in the subject’s home)

11. Religious institution (not parochial school)

12. Park, playground, wilderness area, etc.

13. Work site (e.g., community service, trash collection on roadside, etc.)

14. Universal (e.g., media intervention)

Institutional, Residential

15. Institution, residential (hospital, mental health facility, non-juvenile justice)

16. Public institution, residential (juvenile justice auspices)

17. Other

Focal Intervention Site. From the list above, select the focal intervention site. When there is more than one intervention 

site, the focal site is the site where the bulk of the intervention was delivered (i.e., where the participants spent the most 

time receiving direct services). If you cannot tell which of multiple sites is focal, flag the study for discussion so that 

decision rules can be made moving forward.

Who delivered the intervention? The items in this section refer to the delivery personnel regardless of whether they work 

at the host organization, the instigating organization, or elsewhere, i.e., the individuals who have direct contact with the 

children served by the program (or parents for parent training interventions). From the following list, check all that apply 

and, in the last item in the sequence, identify the primary or “focal” service provider.

People who work for the researcher/evaluator:

1. Researcher/author only

2. Graduate or undergraduate students

3. Laypersons

4. Specially trained teachers (teachers who are trained specifically to deliver the intervention AND who are not the 

students’ regular teacher)

5. Other: ____________________

People who don't work for researcher:

6. Regular teachers

7. School staff

8. Laypersons, volunteers

9. Psychiatrist, psychologist

10. Social worker, caseworker, school counselor, vocational counselor

11. Police or probation officer

12. Parents

13. Peers

14. Self-directed

15. Other: ______________

Who delivered the intervention? From the list above, select the focal provider. For interventions with more than one 

service provider, the focal provider is the individual who had the most contact with the participating youth (or parents for 

parent-oriented programs). If you cannot tell which of multiple delivery personnel types is focal or the multiple types of 

personnel appear equal, flag the study for discussion so that decision rules can be made moving forward.
Back to Table of Contents Technical Report  36

Delivery Timing. When was the intervention delivered?

1. During regular school hours (does not have to be a school setting)

2. After school

3. Evenings and/or weekends

4. Institutional or residential program

5. Other

9. No information provided

Primary format of treatment sessions. The primary emphasis of this question is on who was present with the treated 

individuals during treatment sessions. Check all that apply.

1. Subject alone (self-administered treatment, e.g., bibliotherapy; nobody else is present but the subject)

2. Subject and provider, one on one

3. Group of subjects with provider, not a classroom setting (e.g., group therapy session)

4. Student group, classroom setting

5. Parents only with provider, child not present

6. Group of parents with provider, children not present

7. Parents alone (self-directed)

8. Child and parent(s) together with provider

9. Group of families (parents and children) with provider

10. Child and parent(s), no provider

11. Treatment professionals, teachers, school staff only; children not present

12. Service (e.g., peer mediation, volunteering)

13. Systemic program; no format (e.g., media interventions, school-wide reforms that don’t involve direct services to any 

students or influential others)

Primary format of treatment sessions. Select one focal format from the list above. If the intervention involves multiple 

formats, select as focal the one that involved the most amount of time. If there are multiple formats with equal time or you 

cannot determine the focal format, flag the study for discussion.

Implementation Strategies and Problems 

Did the provider or treatment personnel receive special training in this specific program, intervention, or therapy prior to 

the beginning of the intervention? 

1. Yes

2. No

9. No information provided

Is there evidence of ongoing supervision, consultation, coaching, booster sessions, debriefing, or other forms of support 

during the intervention for the treatment providers delivering the intervention? This would include provision of feedback to 

providers based on observations by the research team. 

1. Yes

2. No

9. No information provided
Back to Table of Contents Technical Report  37

Based on specific data or author discussion, was there a drop or reduction in the desired level of implementation that was 

achieved? Did the authors discuss any problems in implementation that might have been caused by such things as high 

dropouts, erratic attendance, treatment not delivered as intended, staff turnover or burnout, staff caseloads, administrative 

issues, wide differences between settings or individual providers, etc.? 

1. Yes, implementation problems were evident (describe below)

2. Possible problems (describe below)

3. No, implemented as intended (must have a clear statement)

4. Level of implementation not reported

Participant Characteristics

Presenting problem. Identify the primary presenting problem of the participants upon entering the program.

1. None. General population sample, no indication that participants entered the program because of a specific issue or 

problem.

Problems or negative behaviors in participating child/youth

2. Externalizing problems: violence/aggression

3. Delinquency, police contact

4. Externalizing problems: noncompliance/behavior problem

5. Externalizing problems: bullying

6. Externalizing problems: anger management

25. Externalizing problems: ADD, ADHD, Attention problems or similar

7. Externalizing problem: combination of above (or cannot tell specifics)

8. Internalizing problems: depression or anxiety

9. Internalizing problems, other (e.g., fears, somatic problems)

10. Internalizing: combination (or cannot tell specifics)

11. Externalizing and internalizing difficulties combined

Family relationships

12. Parental attachment/bonding or parenting practices

13. General family relationships, family functioning

14. Other family

Peer relationships

15. Friendships, interactions

16. Peer rejection or dislike (or isolation, neglect)

Academic performance

17. Academic achievement

18. Study skills (including attending behavior) 

19. Behavioral school adjustment (attendance, tardiness)

20. Other academic

Other

21. Physical health

22. Drug use/misuse

23. Other: ______________________

24. Multiple problems spanning above categories: ___________________

Gender mix of youth in this group.

1. no males (<5%)

2. some males (<50%)
Back to Table of Contents Technical Report  38

3. 50% to 60% male or estimated 50%-50% split for intact groups such as classrooms or schools where you might 

expect the gender distribution to be approximately equal

4. mostly males (>60%)

5. all males (>95%)

9. cannot tell

Predominant ethnicity (60% or more) of the subjects in this group.

1. Anglo

2. Black

3. Hispanic

4. Other Minority

5. Mixed, none more than 60% or cannot estimate percent

9. Cannot Tell

Socioeconomic status: __________________

Describe any details provided in the study report about the participants’ socioeconomic status. This might include 

statements about a “white middle class community” and the like, or may involve explicit scoring of parents’ occupations. 

You should copy or closely paraphrase the information directly from the study reports.

Participant age. Record any age-related information provided about the sample.

Enter the average age of the sample using number of years.

Enter the average grade level of the sample.

Enter the lowest age using number of years.

Enter the highest age using number of years.

AND

Enter the lowest grade level.

Enter the highest grade level.

Grade level. 

1. Elementary

2. Middle

3. High School

4. Mixed grade levels

9. Cannot tell

Methodological Characteristics

Unit of group assignment. The unit on which assignment to groups was based.

1. Individual (i.e., some children assigned to treatment group, some to comparison group)

2. Group (i.e., whole classrooms, schools, therapy groups, sites, residential facilities assigned to treatment and 

comparison groups)

3. Program area, regions, school districts, counties, etc. (i.e., region assigned as an intact unit)

9. No information provided

Method of group assignment. How participants/units were assigned to groups. This item focuses on the initial method of 

assignment to groups, regardless of subsequent degradations due to attrition, refusal, etc. prior to treatment onset. These 

latter problems are coded elsewhere.
Back to Table of Contents Technical Report  39

Random or near-random: 

1. Randomly after matching, yoking, stratification, blocking, etc. The entire sample is matched or blocked first, then 

assigned to treatment and comparison groups within pairs or blocks. This does not refer to blocking after treatment 

for the data analysis.

2. Randomly without matching, etc. This also includes cases when every other person goes to the control group.

3. Regression discontinuity design: quantitative cutting point defines groups on some continuum (this is rare). 

4. Wait list control or other quasi-random procedure presumed to produce comparable groups (no obvious 

differences). This applies to groups which have individuals apparently randomly assigned by some naturally 

occurring process, e.g. first person to walk in the door. The key here is that the procedure used to select groups 

doesn’t involve individual characteristics of persons so that the groups generated should be essentially equivalent.

Non-random, but matched: Matching refers to the process by which comparison groups are generated by identifying 

individuals or groups that are comparable to the treatment group using various characteristics of the treatment group. 

Matching can be done individually, e.g., by selecting a control subject for each intervention subject who is the same age, 

gender, and so forth, or on a group basis, e.g., by selecting comparison schools that have the same demographic makeup 

and academic profile of treatment schools.

5. Matched ONLY on pretest measures of some or all variables used later as outcome measures. 

6. Matched on pretest measures AND other personal characteristics, such as demographics.

7. Matched ONLY on demographics: big sociological variables like age, sex, ethnicity, SES.

Nonrandom, no matching prior to treatment but descriptive data, etc. regarding the nature of the group differences: 

8. Non-random, not matched, but pretreatment equivalence information is available.

9. No information provided

Control or Comparison Condition. What do subjects in the control or comparison group receive?

1. “Straw man” alternate program or treatment, diluted version, less extensive program, etc., not expected to be 

effective but used as contrast for treatment group of primary interest. If the alternate treatment is not minimal and 

could realistically be expected to be effective, it is not a control condition and should be classified as a focal 

treatment instead.

2. Placebo (or attention) treatment. Group gets some attention or sham treatment (e.g., watching Wild Kingdom videos 

while treatment group gets therapy).

3. Treatment as usual. Group gets “usual” handling instead of some special treatment.

4. No treatment. Group gets no treatment at all.

Context of comparison group. Are comparison group participants in the same institutional context as the intervention 

participants? For example, if treatment kids are pulled out of class, are control kids also pulled out for, e.g., an attention 

placebo condition, or do they remain in their usual classrooms? If intervention subjects are institutionalized, are the 

comparison subjects in the same or similar institution?

1. Yes

2. No

9. No information provided
Back to Table of Contents Technical Report  40

Program Content Elements 

The following section shows the full coding scheme for content elements. Elements were coded as present/absent for 

each program and are not mutually exclusive. An intervention element is defined as a discrete, reliably identifiable 

technique or strategy, which (a) is used as part of a larger intervention or prevention program, (b) is intended to influence

the behavior or well-being of a service recipient, and (c) cannot be further subdivided without being rendered inert. Both 

content and process elements were recorded for each intervention.

Behavioral 

Relaxation skills training. For example, meditation, breathing exercises, imaging peaceful scenes. 

Appropriate classroom behavior. For example, learning when it is appropriate to raise your hand, take turns speaking, paying attention to 

instructors, how to contribute to an orderly classroom environment (i.e., not creating distractions). 

Cognitive/cognitive restructuring

Problem-solving sequence: identify problem, think of alternatives, consequences, monitor outcomes. Not anger related.

Empathy. Activities focused on perspective taking and empathy. Children are taught to think about how other people would feel in a given 

situation. 

Attribution retraining/Cognitive coping skills for stress. For example, children experiencing divorce (understanding that the divorce is not 

their fault). Attribution re-training for internal attributions of success and failure, understanding that there are both healthy and unhealthy 

attributions. Note: Rational Emotive Therapy/Rational Emotive education would be coded here, characterized by a model for changing irrational 

beliefs into rational ones (i.e., changing the way someone responds to stress or an unpleasant event by changing their thoughts about that 

event).

Moral development training/moral dilemmas 

Self-statements to inhibit impulsive behaviors or promote positive behaviors (not anger related) self-instruction and self-talk can all be 

coded here.

Interpersonal/social skills/personal development

Interpersonal social skills: friendship, peer group interaction skills, affiliation with prosocial peers, prosocial skills, family relationships, general 

communication and active listening skills.

Conflict resolution, social or collaborative problem-solving skills (how to solve problem together with peers)

Note: “Social problem-solving” is often used to describe a cognitive problem solving process. If so, code under cognitive rather than 

interpersonal. 

Assertive communication skills, how to resist peer pressure. Includes assertiveness without aggression

Personal/individual development: self-concept, self-confidence, values clarification/”life creed,” goal-setting/future orientation, decision-making 

skills. Including investment and engagement in school. 

Identifying, understanding, and communicating feelings and emotions. However, identifying feelings and emotions as the first step of 

cognitive problem solving sequence should be coded as cognitive-problem solving sequence. This can include drawing attention to feelings, but 

attribution –retraining program should not be coded here.

Trusting relationship with a caring adult. Often found with mentoring programs and youth development programs.

General personal or social support. e.g., peer support groups or discussion groups where no specific skills are taught, or individual counseling 

(by licensed professional) where no specific skills are taught. 

Anger management

Behavioral coping skills for anger/aggression: includes behavioral impulse control (overt motor responses e.g., placing fist over mouth, hands 

tucked under arms) and distraction techniques (e.g., push-ups, timeouts, walking around) 

Problem-solving sequence for managing anger/aggression (identify problem, think of alternatives, consequences, monitor outcomes) 

Attribution training or retraining: learning to recognize accidental causes in interactions with peers to minimize aggressive responses. 

Self-statements to inhibit anger or aggressive behavior, self-instruction and self-talk can all be coded here.

Angry behavior cycle/provocation cycle. Identify cues/triggers for angry behavior- your own or others. Emphasis on understanding triggers 

and possibly physical response. If there is focus on alternative responses, you may also consider coding as behavioral coping skills for 

anger/aggression.
Back to Table of Contents Technical Report  41

Content for caregivers and families 

Parenting skills (e.g., positive discipline skills, communicating with child)

Parent functioning and well-being (e.g., coping with stress, self-care)

Social support; skills for building support network

Family communication skills, family problem-solving skills, family interactions. 

Engagement/communication with child’s school

Information provision for families. Education on child development, health information (sex education, ADHD) etc.

Other content categories

Academic/educational. Includes the following types of programs (provided for reference, but are not sub-elements to code).

• Tutoring; homework assistance; test-taking skills; study skills

• Academic monitoring. Includes attendance, homework, performance monitoring.

• Field trips in educational context.

• Remedial education

• GED preparation

• College focused (e.g., academic advising, summer/weekend programs, application assistance)

School structure. Class or grade reorganization, small class size, alternative school, school-level policies. This content element may not have an 

associated process element.

Service learning. Engaging in community service projects or volunteer roles to benefit community or school. This content element may not have an 

associated process element.

Self-sufficiency skills. Daily living and personal management (distinct from social skills).

Health education and promotion. Personal hygiene, nutrition, STIs, etc.

Provide basic needs. Medical and dental exams, screenings, etc.

Recreational. Sports/athletics, games, field trips (other than educational), adventure-based activities, summer camps, arts & crafts, music, general 

recreation, etc. This can be coded with process unspecified if little information is provided. If it’s used as a strategy for keeping participants engaged, 

can code process element as other engagement strategies.

Employment/vocational/job readiness. Supervised work programs, job placement, career counseling, job or vocational training.

Case management or service brokerage. Includes assessment of need and referral provided by an agency, individualized treatment plans, and 

case management services when all participants are receiving different customized services. This content element may not have an associated 

process element.

Parenting skills for youth. Parenting skills that are taught to youth (could be teen parents or youth that are not currently parenting).

Content unspecified. Use for process elements with no clear content (for data management purposes). 

Violence and Drug Use Education. Drug and substance use education, education on gang involvement and consequences of violent and criminal 

behavior. Includes field trips to prisons and ride-alongs with police members.
Back to Table of Contents Technical Report  42

Process Elements

For each content element, we also recorded any process elements, which are the active techniques or mechanisms 

through which a service provider delivers content elements and supports the behavior change process. The process 

elements were not used in the analysis, but may be used in the practice guidelines to provide additional guidance on how 

to implement a practice.

Access/Retention/Engagement Strategies: Any strategy designed to support or encourage participation in, or with, a practitioner, program or 

service. 

Engagement-Behavioral strategies targeting engagement or retention. For example, rewards for adhering to group rules or attending 

sessions. Includes both positive and negative reinforcements.

Removing barriers to participation, e.g., providing childcare, transportation support, meals during sessions.

Reminders to attend meetings or sessions

Other engagement strategies to engage or motivate participants (non-behavioral). 

Instructional or Pedagogical Strategies: Instructional or pedagogical techniques are process elements through which information is imparted 

and skills are built. The recipients of the information may be passive or active participants in the instructional activities.

Lecture, seminar, instruction (live or not live). Instruction can be delivered to individuals, may be academic tutoring or the material 

delivered is the same for all participants. This is distinct from an individualized therapeutic approach.

Group discussion/interaction – peer, family, or other

Modeling (live)

Modeling (or video)

Role play, behavioral rehearsal and feedback, trying new skills

Experiential learning. Development of knowledge, skills, or values from direct experiences or “hands on” learning (e.g. 

apprenticeship/internships)

Self-evaluation/reflection/self-monitoring. The process of reflecting on content learned on one’s own, may include journaling, logs, and 

diaries. If reflection occurs during group discussion, code as group discussion. This should not be used when there is self-monitoring as part 

of the problem sequence, self-statements, role play, or modeling. 

Self-directed learning. Content is delivered via a self-directed format (e.g. a workbook sent home, online/computer sessions where the 

content is taught through the software, not by a person). Self-directed activities to reinforce content learned previously should be code as 

homework.

Behavioral Strategies

Behavior modification – positive reinforcement. Techniques that reward (e.g., token economy, stickers, small toys) for desirable 

behaviors targeted by the intervention. Note: some token economies might combine positive reinforcement w/ negative punishment. 

Behavior modification – negative or positive punishment. Techniques that discourage undesirable behavior by taking away something 

valued or adding a negative consequence. (e.g., time out, grounding, detention, adding more rules & restrictions, extra chores or homework, 

reprimanding)

Counseling Strategies. These should be therapeutic relationships (with licensed/trained professional not layperson or peer)

Reality therapy. Specific type of therapy that emphasizes changing behavior rather than feelings; and focuses on the present and future, 

while avoiding discussing past events.

Individual counseling, e.g., cognitive behavioral therapy, psychotherapy (other than reality therapy) for youth or parents. 

Motivational interviewing. A goal-oriented, client-centered counseling style for eliciting behavior change by helping clients to explore and 

resolve ambivalence.

Group counseling, group therapy for peer groups, parent groups, and groups of families (multi-family).

Family counseling (individual families) 

Mediation. Counselor mediates/arbitrates between parties in conflict.

Support groups for youth or parents/caregivers (can be facilitated by layperson)

Mentor provided for youth (adult layperson)
Back to Table of Contents Technical Report  43

Peer-Driven Strategies

Peer mediation - recipient of services

Peer mediation - serving as mediator

Peer mentoring/counseling - recipient of services. Format can be with individuals or group. Includes peer facilitators.

Peer mentoring/counseling - serving as mentor/counselor to an individual or group. Includes peer facilitators.

Peer tutoring/education – serving as tutor or educator of academic and other content. 

Positive Peer Culture (specific approach where youth assume responsibility for helping one another and hold each other accountable)

Peer tutoring/education – recipient of peer educator of academic and other content

Supporting Change: Refers to elements that support child or parental behavior change.

Homework. Tasks given to client(s) to complete outside of session(s) to improve treatment adherence or reinforce/facilitate new knowledge 

or skills that are consistent with the intervention.

Referrals to other services

Program Integration. Efforts by the program to reinforce content in other spheres of the child’s life with the goal of this continuing on after 

the intervention. E.g., communication, conferences, or trainings with a parent/school staff to integrate content from the intervention in home 

or school life. 

Process unspecified. Use for process elements with no clear content (for data management purposes). 
Back to Table of Contents Technical Report  44

Exhibit A2. Selected Characteristics of the Studies Included in the Analysis (k=391)

Frequency 

(%)

Mean (sd) Frequency

Program Dosage Content Elements

Duration (weeks) 22.76 (22.64) Relaxation skills training 17

Frequency (sessions per week) Appropriate classroom behavior 59

Less than weekly 34 (9%) Problem solving sequence 69

1x/week 130 (33% Empathy 21

1-2x/week 21 (5%) Attribution retraining 32

2x/week 79 (20%) Moral development training 2 

2-3x/week 11 (3%) Self-statements to inhibit impulsiveness or promote positive behavior 19

3x/week 8 (2%) Interpersonal, social skills 137

3-4x/week 9 (2%) Conflict resolution 30

4x/week 10 (3%) Assertive communication skills 23

Daily (5x/week) 89 (23%) Personal development 168

Program Complexity Identifying, understanding feelings 53

Number of Different Formats 1.8 (1.1) Trusting relationship with caring adult 34

Number of Different Provider Types 1.7 (1.0) General personal or social support 33

Number of Different Settings 1.5 (0.9) Behavioral coping skills for anger/aggression 15

Program Setting Problem solving sequence – anger 38

In-class 144 (37%) Attribution retraining for anger/aggression 3 

School, pull-out 121 (31%) Self-statements to inhibit anger/aggression 32

Community 126 (32%) Angry behavior cycle 31

Delivery Personnel Parent skills training 84

Researcher 94 (24%) Parent functioning 21

Specialist staff 88 (23%) Social support, building support network 13

Teachers 79 (20%) Family communication skills 54

Laypersons, paraprofessionals 43 (11%) Engagement with child’s school 43

All others 87 (22%) Information provision for families 18

Implementation Problems Academic, educational 99

Explicit or suggested problems 152 (39%) School structure 21

No problems or none mentioned 239 (61%) Service learning 33

Provider Training or Supervision Self-sufficiency skills 2 

Neither training or supervision 163 (42%) Health education and promotion 8 

Either training or supervision 228 (58%) Provide basic needs 7 

Recreational 40

Employment, vocational 32

Case management, service brokerage 30

Parenting skills for youth 24

Unspecified content 5 

Violence and drug use education 17
Back to Table of Contents Technical Report  45

APPENDIX B. ANALYTIC METHODS Appendix B. Analytic Methods

This paper focuses on the externalizing behavior outcomes in the larger database. These outcomes were recorded from 

the research studies as standardized mean difference effect size statistics (d) calculated as the post-intervention

differences in externalizing outcomes between the intervention and control groups, divided by the pooled standard 

deviation of the groups. Cox transformations were applied to effect sizes based on dichotomous outcomes as outlined by 

Sánchez-Meca and colleagues (2003). All effect sizes were multiplied by the small sample correction factor (Hedges, 

1981), 1 – (3/4n-9), where n is the total sample size for the study, and each was weighted by its inverse variance in all 

computations. The inverse variance weights were computed using the subject-level sample size for each effect size. 

Because many of the studies used groups (e.g., classrooms, schools) as the unit of assignment to intervention and control 

conditions, they involved a design effect associated with the clustering of students within classrooms or schools that 

reduces the effective sample size. We calculated the total cluster-adjusted sample size using an intra-cluster correlation 

coefficient (ρ) of 0.1 (Borenstein et al., 2009).

Examination of the effect size distribution identified a small number of outliers with potential to distort the analysis; these 

were Winsorized to less extreme values using Tukey’s inner fences. In addition, several studies had unusually large 

samples. Because the inverse variance weights chiefly reflect sample size, those few studies would dominate any 

analysis in which they were included. Therefore, the extreme tail of the sample size distribution was Winsorized using the 

Tukey fences for skewed distributions. 

Many studies provided data sufficient for calculating mean difference effect sizes on the outcome variables at the pretest. 

In such cases, we adjusted the posttest effect sizes by subtracting the pretest effect size value. Indicator variables were 

tested in the methods analysis shown below to determine if there were systematic differences between effect sizes that 

were adjusted in this way and those that were not.

Effect Size Selection and Aggregation

One effect size estimate was used in the analyses for each study. Studies often reported multiple effect sizes in the 

externalizing behavior domain. These multiples came in several forms. In some cases, studies reported effect sizes for 

more than one type of externalizing behavior (aggression, acting out, school disciplinaries). In other cases, studies 

reported the same type of externalizing behavior outcome but from different informants (e.g., parents, teachers, etc.). The 

multiple effect sizes differed enough within study that averaging or selecting one would be likely to produce different 

overall results. We, therefore, organized the effect sizes from studies with multiple effect sizes into conceptually and 

empirically similar groups by type of externalizing behavior and informant. For example, effect sizes recorded as 

externalizing behavior, problem behavior, aggressive behavior, verbal aggression, disruptive behavior, and the like 

showed little empirical differentiation and were conceptually similar. The school disciplinary and conduct categories were 

more distinct from the above cluster of externalizing behavior types. There were fewer within-study multiples in this group 

of effect sizes so we have limited information about their empirical similarity; these were, thus, grouped on conceptual 

grounds. Among the informants, there was little empirical differentiation among informant categories of subject selfreports, parent reports, teacher reports, school records, peer reports, and researcher/interviewer reports. All of these 

informants were grouped together based on their empirical similarity. Observations were the only informant source that 

showed some empirical distinction, though data were limited for this assessment. 

With the objective of using as many of the effect sizes as possible, once these conceptual/empirical groupings were 

created, we aggregated the effect sizes within these groups. When effect sizes from more than one of these 

conceptual/empirical groups were available within a study, we selected the aggregate from the most common 

externalizing behavior type and informant type. Indicators for these aggregations and selections were tested in the 

methods analysis reported below.
Back to Table of Contents Technical Report  46

Missing Data

Some studies were missing data on the method, participant, or program variables used in our analysis. Most variables 

had fewer than 10% of cases missing. To permit us to use the full sample of studies in our analysis, we imputed missing 

values for moderators with the ‘Amelia’ package (Honaker et al., 2011) in R (3.5.1). We produced 20 imputations with this 

method. All analyses reported in this paper were run on the 20 imputed datasets and aggregated. Degrees of freedom 

and standard errors were adjusted to account for the uncertainty introduced by the imputation process per Barnard and 

Rubin (1999).

Selection and Recoding of Moderators

For analysis, most moderators were recoded into dummy codes or variables with fewer categories. The descriptive 

statistics for variables used in the analysis are presented as appropriate. We selected moderators based on the 

magnitude of their bivariate correlations with effect size. When multiple moderators that were conceptually similar were 

available, we either created composite variables or selected the moderator that had the strongest relationship with effect 

size. 

The meta-analytic database includes a large number of potential core components, many more than we could explore in a 

single analysis. To select moderators for analysis, we used a combination of strategies. First, we examined the bivariate 

correlations of each moderator with the effect sizes as well as the intercorrelations among the moderators. For those 

variables with correlations larger than r=.10 that had sufficient variability (i.e., moderators for which only a few studies had 

the feature were not explored), we performed a form of random forest analysis designed for meta-analytic data 

(Hapfelmeier & Ulm, 2013; van Lissa, 2018). Random forest analysis is a method for selecting moderators for regression 

analysis using machine learning techniques; this technique explores the strength of the relationships of each potential 

moderator with the effect sizes while taking into consideration the relationships of each moderator with the others. One 

result of a random forest analysis is a variable importance plot that identifies the moderators’ association with the effect 

sizes while taking into account the intercorrelations. Potential core components that were identified as important in the 

random forest analysis were entered into meta-regression models.

Rather than relying on statistical significance, which we felt would cause us to overlook substantively meaningful 

relationships, moderators were retained in the final meta-regression models based on a threshold of .10 effect size units. 

Binary core components were considered to have a meaningful relationship with effect sizes if their independent 

contribution to predicting effect sizes (the regression coefficients, or bs, in the models) was 0.10 or larger. We also used 

the .10 threshold for core components indexed on a standard scale (i.e., with a mean of zero and a standard deviation of 

1) such as delivery complexity. The .10 threshold was also considered meaningful when associated with a 1 point change 

on the three potential core components that were ordinal (program frequency, gender mix, and SES). Two potential core 

components were scaled continuously, program duration and average age of the sample. For these variables, if a 10 

week change on duration or 3 year change on age was associated with +/- .10 in the effect size, the variable was 

considered meaningful. These values represent approximately half of a standard deviation for each variable.

Delivery Complexity Factor Analysis 

The delivery complexity variable that appears in the universal core components models is a principal components factor 

computed from three variables: counts of different implementation settings (e.g., classroom, home, playground), different 

types of delivery personnel (e.g., teachers, laypeople, program specialists), and different program formats (e.g., group, 

one-on-one). Principal components analysis was used because we were interested in computing composite scores for the 

meta-regression analysis. A single factor was produced with an eigen value of 1.8 and which explained 60% of the 

variance. Factor loadings for settings, personnel, and formats were .79, .63, and .88, respectively.
Back to Table of Contents Technical Report  47

Data Analysis

All analyses were inverse variance weighted using random effects statistical models that incorporate both within-study 

and between-study sampling variance estimates into the study level weights. The between studies variance component 

(τ

2

) was estimated using restricted maximum likelihood. Random effects weighted mean effect sizes were calculated for 

all studies using 95% confidence intervals. Estimates of Cochrane’s Q, I2

, and τ

2 were used to assess heterogeneity in the 

effect sizes. The regression analyses reported in this paper were performed using the ‘metafor’ package in R 

(Viechtbauer, 2010).
Back to Table of Contents Technical Report  48

APPENDIX Appendix C. Analysis of the Influence of Metho C. ANALYSIS OF THE INFLUENCE OF METHOD VARIABLES d 

Variables

The meta-analytic database includes a wide range of variables relating to study methods and research procedures, some 

of which are associated with effect sizes. These variables cannot serve as potential core components but must be 

addressed in the analysis to ensure that the substantive relationships we explored earlier aren’t overly attenuated or 

obscured by the influence of the method variables. Descriptive statistics for the major method variables in the dataset are 

presented in Exhibit C1.

Exhibit C1. Study Methods and Research Procedures for All Studies (k=391)

Frequency (%) Mean (sd) Range

Correlation with 

Effect Size

Research Design

Individual random assignment 200 (51%) 0.07

Cluster random assignment 38 (10%)

Quasi-experimental design 153 (39%)

Features of Average Effect

Total sample size (Winsorized) 78 (90) 16-491 -0.20

N of Effect Sizes Aggregated 2.1 (1.7) 1-11 0.08

N of Effect Sizes in Aggregate Adjusted for Pretest 1.6 (1.8) 0-11 0.13

N of Effect Sizes in Aggregate Derived from Binary Data 0.2 (0.5) 0-4 -0.13

Type of Externalizing Behavior Measured

Externalizing 306 (78%) 0.22

School disciplinaries, suspensions 85 (22%)

Comparison Group Level of Service

No service 75 (19%) 0.06

Usual service 261 (67%)

Minimal service 55 (14%)

We estimated two models that included methods variables for the full sample of 391 programs. The first includes only the 

method variables and the second includes the method variables plus the universal core components. These results are 

shown in Exhibit C2. Using our threshold of .10 effect size units, we see that several method characteristics are 

associated with effect sizes. Studies in which comparison group participants received less service (i.e., the contrast 

between the amount of services received by the intervention and comparison group participants was larger) exhibited 

larger impacts, as would be expected. In addition, the type of externalizing behavior was also associated with effect sizes, 

with externalizing behavior measures producing larger effect sizes than measures of school disciplinaries or suspensions.

Although the method variables account for a significant portion of effect size variability, Model 2 indicates that the 

relationships of the universal core components to effect sizes are consistent with the overall model even when 

methodological variables are taken into account.
Back to Table of Contents Technical Report  49

Exhibit C2. Method Variables Analysis for All Programs (k=391)

Model 1 Model 2

Method Variables b se b se

Intercept - 0.18 0.15 -0.14 0.14

Design: Individual random assignment 0.003 0.06 0.01 0.06

Comparison group level of service (higher scores=less service) 0.16 0.06 ** 0.15 0.05 **

Intervention and comparison group same context 0.04 0.06 0.03 0.06

Type of externalizing behavior: externalizing 0.27 0.08 *** 0.19 0.08 * 

N of Effect Sizes Aggregated -0.01 0.03 0.03 0.03

N of Effect Sizes in Aggregate Adjusted for Pretest 0.002 0.03 -0.03 0.03

N of Effect Sizes in Aggregate Derived from Binary Data -0.07 0.06 -0.07 0.06

General Core Components

Implementation: Explicit or suggested problems -0.12 0.06 * 

Delivery complexity -0.10 0.03 **

Provider training or supervision 0.06 0.06

Model Statistics

Q-model 27.07 *** 46.56 ***

Q-residual 2341.91 *** 2186.66 ***

τ2 .25 .23

I

2 81.84% 80.79%

R2 5.86% 11.12%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  50

How Method Variables Affect the Substantive Analyses

We now present a series of regression models in which we explore the method variables for each program approach 

category. The purpose of this exercise is to examine whether including method variables in the models leads us to doubt 

the relationships we see between our core components and program impacts. In each exhibit, Model 1 shows the method 

variables alone. Model 2 adds the specific core components for each approach. With the exception of the family relations 

and parenting skills approaches, adding the method variables to the specific core components for each approach does not 

appreciably change the independent relationships of our core components to the effect sizes. The fact that the method 

variables do not contradict our findings gives us confidence that the relationships of the core components to program 

impacts are robust. For the family relations and parenting skills approaches, the method variables appear to be 

confounded with the specific core components, which does suggest that our core components may have less potential to 

influence youth outcomes than those for the other approaches. More work on these approaches to identify factors that do 

predict positive outcomes is suggested.

Exhibit C3. Method Variables Analysis for Family Relations and Parenting Skills Approaches (k=64)

Model 1 Model 2

Method Variables b se b se

Intercept 0.32 0.38 0.44 0.50

Design: Individual random assignment -0.12 0.16 -0.14 0.16

Comparison group level of service (higher scores=less service) 0.14 0.11 0.17 0.12

Intervention and comparison group same context -0.13 0.15 -0.11 0.15

Type of externalizing behavior: externalizing -0.15 0.31 -0.27 0.32

N of Effect Sizes Aggregated 0.02 0.06 0.03 0.07

N of Effect Sizes in Aggregate Adjusted for Pretest 0.03 0.06 0.01 0.07

N of Effect Sizes in Aggregate Derived from Binary Data 0.33 0.52 0.35 0.54

Specific Core Components

Delivery format: one-on-one 0.07 0.18

Lesson-plan-based program 0.07 0.18

Age of sample 0.25 0.18

Content element: Family communication skills 0.15 0.15

Content element: Personal development -0.03 0.02

Model Statistics

Q-model 5.76 10.29

Q-residual 349.04 *** 250.34 ***

τ2 .20 .19

I

2 77.65% 75.65%

R2 0.00% 0.00%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

† p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  51

Exhibit C4. Method Variables Analysis for Relational Approaches (k=91)

Model 1 Model 2

Method Variables b se b se

Intercept 0.26 0.37 -0.25 0.57

Design: Individual random assignment -0.01 0.14 0.00 0.14

Comparison group level of service (higher scores=less service) 0.08 0.15 0.15 0.17

Intervention and comparison group same context -0.06 0.15 -0.01 0.16

Type of externalizing behavior: externalizing 0.35 0.15 * 0.22 0.17

N of Effect Sizes Aggregated -0.13 0.07 -0.16 0.08 * 

N of Effect Sizes in Aggregate Adjusted for Pretest 0.03 0.07 0.06 0.08

N of Effect Sizes in Aggregate Derived from Binary Data -0.32 0.13 * -0.11 0.16

Specific Core Components

Delivery format: one-on-one 0.22 0.16

Delivery setting: pullout 0.18 0.17

Presenting problem: behavior 0.43 0.14 **

Content element: Service learning -0.04 0.24

Content element: Any interpersonal skills element 0.14 0.20

Model Statistics

Q-model 22.59 ** 36.57 ***

Q-residual 278.85 *** 240.73 ***

τ2 .23 .20

I

2 75.30% 72.68%

R2 20.05% 27.66%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  52

Exhibit C5. Method Variables Analysis for Skill-building Approaches (k=121)

Model 1 Model 2

Method Variables b se b se

Intercept 0.07 0.30 -0.34 0.27

Design: Individual random assignment 0.11 0.11 0.15 0.10

Comparison group level of service (higher scores=less service) 0.24 0.10 * 0.29 0.09 **

Intervention and comparison group same context 0.04 0.12 0.13 0.11

Type of externalizing behavior: externalizing -0.23 0.22 -0.24 0.19

N of Effect Sizes Aggregated -0.05 0.06 0.02 0.06

N of Effect Sizes in Aggregate Adjusted for Pretest 0.03 0.07 -0.03 0.06

N of Effect Sizes in Aggregate Derived from Binary Data 0.14 0.11 0.12 0.10

Specific Core Components

Delivery by specialist staff (vs. all others) 0.54 0.12 ***

Lesson-plan program 0.19 0.10 * 

Content element: Conflict resolution skills 0.20 0.12

Content element: Any family/parenting element -0.48 0.14 ***

Model Statistics

Q-model 10.51 47.19 ***

Q-residual 330.31 *** 216.23 ***

τ2 .17 .10

I

2 63.34% 49.50%

R2 4.64% 43.13%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  53

Exhibit C6. Method Variables Analysis for Behavior Management Approaches (k=27)

Model 1 Model 2

Method Variables b se b se

Intercept 0.67 0.94 0.94 1.00

Design: Individual random assignment -0.21 0.26 -0.25 0.27

Comparison group level of service (higher scores=less service) -0.19 0.38 -0.27 0.39

Intervention and comparison group same context 0.42 0.27 0.34 0.29

Type of externalizing behavior: externalizing 0.24 0.33 0.12 0.36

N of Effect Sizes Aggregated 0.11 0.43 0.03 0.44

N of Effect Sizes in Aggregate Adjusted for Pretest -0.12 0.42 -0.04 0.43

N of Effect Sizes in Aggregate Derived from Binary Data -0.40 0.47 -0.39 0.47

Specific Core Components

One-on-one format 0.24 0.29

Model Statistics

Q-model 4.78 5.44

Q-residual 55.57 *** 52.67 ***

τ2 .21 .21

I

2 67.74% 67.72%

R2 0.00% 0.00%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

 † p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  54

Exhibit C7. Method Variables Analysis for Academic and Educational Approaches (k=75)

Model 1 Model 2

Method Variables b se b se

Intercept -0.30 0.46 -0.45 0.50

Design: Individual random assignment -0.06 0.17 0.01 0.18

Comparison group level of service (higher scores=less service) 0.15 0.17 0.22 0.17

Intervention and comparison group same context 0.16 0.17 0.14 0.17

Type of externalizing behavior: externalizing 0.28 0.16 † 0.25 0.17

N of Effect Sizes Aggregated 0.04 0.12 0.06 0.12

N of Effect Sizes in Aggregate Adjusted for Pretest -0.05 0.12 -0.05 0.12

N of Effect Sizes in Aggregate Derived from Binary Data -0.06 0.12 -0.02 0.13

Specific Core Components

Subcategory: School structure (vs. tutoring and vocational approaches) 0.18 0.18

Content element: Appropriate classroom behavior 0.22 0.21

Content element: Trusting relationship w/ caring adult -0.23 0.21

Content element: General personal or social support -0.32 0.18

Model Statistics 

Q-model 4.62 12.63

Q-residual 659.47 *** 585.35 ***

τ2 .31 .29

I

2 91.24% 90.48%

R2 0.00% 0.64%

Note. The table reports unstandardized regression coefficients (b) and standard errors (se) from inverse variance weighted random effects meta-regression analyses using REML 

estimation.

† p<.10, * p<.05, ** p<.01, *** p<.001
Back to Table of Contents Technical Report  55

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REFERENCES FOR THE STUDIES IN THE META-ANALYSIS

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References for the Studies in the Meta-Analysis
Back to Table of Contents Technical Report  58

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50157 Brown, E. A. (1998). The effects of a parent education training program on the classroom behavior of 

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Vacc, N. A. (1968). A study of emotionally disturbed children in regular and special classes. Exceptional 

Children, 35(3), 197-204.

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Exceptional Children, 39, 15-23.

51233 Valentine, J., Griffith, J., Ruthazer, R., Gottlieb, B., & Keel, S. (1998). Strengthening causal inference in 

adolescent drug prevention studies: Methods and findings from a controlled study of the Urban Youth 

Connection program. Drugs & Society, 12(1-2), 127-145.

51242 Verduyn, C. M., Lord, W., & Forrest, G. C. (1990). Social skills training in schools: An evaluation study.

Journal of Adolescence, 13, 3-16.

51243 Vernot, G. G. (1975). A study of the effectiveness of group counseling using a human relations treatment 

program with disruptive tenth grade boys (Doctoral dissertation). Available from ProQuest 

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51248 Vostanis, P. & Harrington, R. (1994). Cognitive-behavioural treatment of depressive disorder in child 

psychiatric patients- Rationale and description of a treatment package. European Child and 

Adolescent Psychiatry, 3(2), 111-123.

Vostanis, P., Feehan, C., & Grattan, E. (1998). Two-year outcome of children treated for depression. 

European Child & Adolescent Psychiatry, 7(1), 12-18.

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depression: Lessons from a controlled trial. Clinical Child Psychology and Psychiatry, 1(2), 199-212.

51249 Vreeland, A. D. (1982). Evaluation of Face-to-Face: A juvenile aversion program (Doctoral dissertation). 

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51253 Walker, H. M., Kavanagh, K., Stiller, B., Golly, A., Severson, H. H., & Feil, E. G. (1998). First step to 

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51256 Walker, H. M., Retana, G. F., & Gersten, R. (1988). Replication of the CLASS program in Costa Rica: 

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51258 Wallace, Glen K. (1968). A cooperative program for the alleviation of juvenile behavior problems, Final 

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51262 Warner, R. W., Jr. (1971). Alienated students: Six months after receiving behavioral group counseling. 

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51264 Wax, M. L. (1977). The effects of symbolic restitution of presence of victim on delinquent shoplifters

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51270 Webster-Stratton, C. (1984). Randomized trial of two parent-training programs for families with conductdisordered children. Journal of Consulting and Clinical Psychology, 52(4), 666-678.

51271 Webster-Stratton, C. (1990). Enhancing the effectiveness of self-administered videotape parent training 

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51272 Webster-Stratton, C. (1992). Individually administered videotape parent training: "Who benefits?" 

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51273 Webster-Stratton, C., & Hammond, M. (1997). Treating children with early-onset conduct problems: A 

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51274 Webster-Stratton, C. (1990). Long-term follow-up of families with young conduct problem children: From 

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51276 Weeks, S. Z. (1986). The effects of Sierra II, an adventure probation program, upon selected behavioral 

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51278 Schweinhart, L. J., Weikart, D. P., & Larner, M. B. (1986). Consequences of three preschool curriculum 

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51279 Weinrott, M. R. (1979). The utility of tracking child behavior. Journal of Abnormal Child Psychology, 7(3), 

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51281 Weinstein, R. S., Soulé, C. R., Collins, F., Cone, J., Mehlhorn, M., & Simontacchi, K. (1991). Expectations 

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51284 Weiss, B., Catron, T., & Harris, V. (2000). A 2-year follow-up of the effectiveness of traditional child 

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51284 Weiss, B., Catron, T., Harris, V., & Phung, T. M. (1999). The effectiveness of traditional child 

psychotherapy. Journal of Consulting and Clinical Psychology, 67(1), 82-94.

51290 Flaherty, L. T., & Weist, M. D. (1999). School-based mental health services: The Baltimore models. 

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51294 Westover, S. R. (1991). An evaluation of a parenting program designed to facilitate children's post-divorce 

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51296 White, G. (1996). A two year comparative study of participants and nonparticipants in a peer mediation 

program at model school (Doctoral dissertation). Available from ProQuest Dissertations and Theses. 

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51302 Wiener, J., & Harris, P. J. (1997). Evaluation of an individualized, context-based social skills training 

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53.

51303 Wiggins, M., Bonell, C., Burchett, H., Sawtell, M., Austerberry, H., Allen, A., & Strange, V. (2008). Young 

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51314 Wisser, R.E. (1971). A comparison of the effects of three types of counseling upon the adjustment of fifth 

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51315 Cohen, H. L., Filipczak, J., Boren, J., Goding, I., Storm, R., Bishop, R. M., & Breiling, J. (1974). Academic 

and social behavior change in a public school setting. PICA final report: Project year four. Silver 

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evaluating a model. Corrective and Social Psychiatry and Journal of Behavior Technology Methods 

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Filipczak, J., Archer, M. B., Neale, M. S., & Winett, R. A. (1979). Issues in multivariate assessment of a 

large-scale behavioral program. Journal of Applied Behavior Analysis, 12, 593-613.

Filipczak, J., Archer, M., & Friedman, R. M. (1980). In-school social skills training: Use with disruptive 

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Filipczak, J., Friedman, R. M., & Reese, S. C. (1979). PREP: Educational programming to prevent 

juvenile problems. In J. S. Stumphauzer (Ed.), Progress in behavior therapy with delinquents (pp. 

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Filipczak, J., Storm, R., & Brieling, J. (1973). Programming for disruptive and low achieving students: An 

experimental in-school alternative. The Journal of the International Association of Pupil Personnel 

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Friedman, R. M., Filipczak, J., & Fiordaliso, R. (1977). Within-school generalization of the Preparation 

through Responsive Educational Programs (PREP) academic project. Behavior Therapy, 8, 986-995.

51315 Wodarski, J. S., Filipczak, J., McCombs, D., Koustenis, G., & Rusilko, S. (1979). Follow-up on behavioral 

intervention with troublesome adolescents. Journal of Behavior Therapy and Experimental Psychiatry, 

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51316 Wolchik, S. A., West, S. G., Westover, S., Sandler, I. N., Martin, A., Lustig, J., . . . Fisher, J. (1993). The 

Children of Divorce Parenting Intervention: Outcome evaluation of an empirically based program. 

American Journal of Community Psychology, 21(3), 293-331.

51317 Wolchik, S. A., West, S. G., Sandler, I. N., Tein, J-Y, Coatsworth, D., Lengua, L., . . . Griffin, W. A. (2000). 

An experimental evaluation of theory-based mother and mother-child programs for children of divorce. 

Journal of Consulting and Clinical Psychology, 68(5), 843-856.

51325 Yu, P., Harris, G. E., Solovitz, B. L., & Franklin, J. L. (1986). A social problem-solving intervention for 

children at high risk for later psychopathology. Journal of Clinical Child Psychology, 15(1), 30-40.

51326 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 preadolescent children (Doctoral dissertation). Available from ProQuest Dissertations and Theses. 

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51327 Zelie, K., Stone, C. I., & Lehr, E. (1980). Cognitive-behavioral intervention in school discipline: A 

preliminary study. Personnel and Guidance Journal, 59, 80-83.

51329 Berrueta-Clement, J. R., Schweinhart, L. J., Barnett, W. S., & Weikart, D. P. (1987). The effects of early 

educational intervention on crime and delinquency in adolescence and early adulthood. In J. D. 

Burchard & S. N. Burchard (Eds.), Prevention of delinquent behavior: Primary prevention of 

psychopathology (Vol. 10) (pp. 220-240). Newbury Park, CA: Sage Publications.

Berrueta-Clement, J. R., Schweinhart, L. J., Barnett, W. S., Epstein, A. S., & Weikart, D. P. (1984). 

Changed lives: The effects of the Perry Preschool Program on youths through age 19 (Vol. 8). 

Ypsilanti, MI: The High/Scope Press.

Farnworth, M., Schweinhart, L. J., & Berrueta-Clement, J. R. (1985). Preschool intervention, school 

success and delinquency in a high-risk sample of youth. American Educational Research Journal, 

22(3), 445-464.

Schweinhart, L. J. & Weikart, D. P. (1980). Young children grow up: The effects of the Perry Preschool 

program on youths through age 15 (Monograph, No.7). Ypsilanti, MI: High/Scope Educational 

Research Foundation.

Schweinhart, L. J., & Weikart, D. B. (1988). The High/Scope Perry Preschool Program. In R. H. Price, E. 

L. Cowen, R. P. Lorion, & J. Ramos-McKay (Eds.), 14 ounces of prevention: A casebook for 

practitioners (pp. 53-65). Washington, DC: American Psychological Association.

Schweinhart, L. J., & Weikart, D. P. (1983). The effects of the Perry Preschool Program on youths 

through age 15: A summary. In The Consortium for Longitudinal Studies (Ed.), As the twig is bent: 

Lasting effects of preschool programs (pp. 71-101). Hillsdale, NJ: Lawrence Erlbaum Associates.

Schweinhart, L. J., & Weikart, D. P. (1989). The High/Scope Perry Preschool study: Implications for early 

childhood care and education. Prevention in Human Services, 7(1), 109-132.

Schweinhart, L. J., & Weikart, D. P. (1991). Response to "beyond IQ in preschool programs." Intelligence, 

15, 313-315.
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Schweinhart, L. J., Berrueta-Clement, J. R., Barnett, W. S., Epstein, A. S., & Weikart, D. P. (1985). 

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Gullotta (Eds.), Issues in children's and families' lives: Primary prevention works (1st ed.) (pp. 146-

166). Thousand Oaks, CA: Sage Publications.

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and longitudinal results through fourth grade. (Monograph, No.3). Ypsilanti, MI: High/Scope 

Educational Research Foundation.

Weikart, D. P., Deloria, D., Lawser, S. & Wiegerink, R. (1970). Longitudinal results of the Ypsilanti Perry 

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Zigler, E., & Weikart, D. P. (1993). Reply to Spitz's comments. American Psychologist, 48(8), 915-916.

51330 Human Services Research Institute. (2001). Evaluation of First Step to Success: Final report executive 

summary. Tualatin, OR: Human Services Research Institute.

Walker, H. M., Golly, A., McLane, J. Z., & Kimmich, M. (2005). The Oregon First Step to Success 

replication initiative: Statewide results of an evaluation of the program's impact. Journal of Emotional 

and Behavioral Disorders, 13(3), 163-172.

51333 August, G. J., Braswell, L., & Thuras, P. (1998). Diagnostic stability of ADHD in a community sample of 

school-aged children screened for disruptive behavior. Journal of Abnormal Child Psychology, 26(5), 

345-356.

51333 August, G. J., Realmuto, G. M., Crosby, R. D., & MacDonald, A. W., III. (1995). Community-based 

multiple-gate screening of children at risk for conduct disorder. Journal of Abnormal Child Psychology, 

23(4), 521-544.

August, G. J., Realmuto, G. M., MacDonald, A. W., III, Nugent, S. M., & Crosby, R. (1996). Prevalence of 

ADHD and comorbid disorders among elementary school children screened for disruptive behavior.

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prevention for children with disruptive behavior: Initial outcomes. Journal of Abnormal Child 

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51334 Voelm, C. E. (1984). The efficacy of teaching rational emotive education to acting-out and socially 

withdrawn adolescents (Doctoral dissertation). Available from ProQuest Dissertations and Theses. 

(AAT 8402501 )