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Practice Profile

After-School Programs

Evidence Ratings for Outcomes:

Promising - One Meta-Analysis Attitudes & Beliefs - Child Self-Perceptions
Promising - One Meta-Analysis Education - School Bonding
Promising - One Meta-Analysis Mental Health & Behavioral Health - Social Behaviors
Promising - One Meta-Analysis Mental Health & Behavioral Health - Externalizing behavior
Promising - One Meta-Analysis Education - Academic achievement/school performance
Promising - One Meta-Analysis Education - Reading Achievement
Promising - One Meta-Analysis Education - Math Achievement
No Effects - One Meta-Analysis Education - Attendance/truancy
No Effects - One Meta-Analysis Drugs & Substance Abuse - Multiple substances
No Effects - One Meta-Analysis Crime & Delinquency - Multiple crime/offense types

Practice Description

Practice Goals
After-school programs (ASPs) were developed to decrease the amount of unsupervised time that youth have after school while their parents finish the work day. It is believed that these programs can provide youth with shelter from unsafe neighborhoods and decrease the amount of time they spend with delinquent youth in an unsupervised setting. Furthermore, these programs may contribute to an improvement in youth’s personal and social development and their school performance.

Overall, these programs aim to prevent youth from engaging in delinquent behavior that may occur without supervision, increase their academic achievement, and promote their personal and social growth (Taheri and Welsh 2016; Durlak, Weissberg, and Pachan 2010; Lauer et al. 2006).

Practice Components/Target Population
Although ASPs vary in terms of size, type, and specific focus, they all aim to increase the amount of time that youth are supervised, and they are all delivered to school-aged children. These programs can act as a source of formal supervision and as a place for youth to further develop academic skills, personal skills, and social skills. In terms of formal supervision, ASPs target the unstructured time that youth have after school, given that research has shown that this is often a time when youth engage in delinquent activities (Fox and Newman 1997; Durlak, Weissberg, and Pachan 2010). It is believed that by replacing this unstructured time with structured activities, ASPs limit opportunities to engage in delinquency while also promoting prosocial behaviors. For example, ASPs offer a range of structured activities, including homework assistance, academic tutoring, mentoring, job-skills training, social and cognitive skills development, and recreation-based activities.

Given that ASPs are designed to fill time with meaningful activities, they may also include the involvement of community members, families, and schools, all of which can work together to provide youth with prosocial activities and support (Taheri and Welsh 2016; Durlak, Weissberg, and Pachan 2010; Lauer et al. 2006).

Meta-Analysis Outcomes

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Promising - One Meta-Analysis Attitudes & Beliefs - Child Self-Perceptions
Durlak, Weissberg, and Pachan (2010) aggregated the effects from 23 studies and found that after-school programs had a statistically significant impact on child self-perceptions (standardized mean difference=0.34). Students that participated in after-school programs experienced a greater increase in their overall self-confidence and self-esteem than students that did not participate in after-school programs.
Promising - One Meta-Analysis Education - School Bonding
Durlak, Weissberg, and Pachan (2010) aggregated the effects from 28 studies and found that after-school programs had a small, yet statistically significant impact on school bonding (standardized mean difference=0.14). Students who participated in after-school programs exhibited greater increases in their positive feelings and attitudes toward school, compared to students that did not participate in after-school programs.
Promising - One Meta-Analysis Mental Health & Behavioral Health - Social Behaviors
Aggregating the results from 36 studies, Durlak, Weissberg, and Pachan (2010) found a small, yet statistically significant effect (standardized mean difference=0.19) for positive social behaviors. This result suggests that participants in after-school programs exhibited more positive interactions with others, compared with those who did not participate in such programs.
Promising - One Meta-Analysis Mental Health & Behavioral Health - Externalizing behavior
Durlak, Weissberg, and Pachan (2010) examined the results from 43 studies and found a small, yet statistically significant effect (standardized mean difference=0.19) for externalizing behaviors, suggesting that participants in after-school programs were less likely to exhibit problem behaviors than participants in the comparison conditions.
Promising - One Meta-Analysis Education - Academic achievement/school performance
Durlak, Weissberg, and Pachan (2010) examined the results of 25 studies and found a small, yet statistically significant effect (standardized mean difference=0.12), suggesting that students who participated in after-school programs received better grades compared to students who did not participate in the after-school programs.
Promising - One Meta-Analysis Education - Reading Achievement
Aggregating the results from 15 studies, Lauer and colleagues (2006) found a small, yet statistically significant effect (standardized mean difference=0.07) for reading achievement. This result suggests that participants in after-school programs exhibited a greater improvement in their reading achievement scores, compared with nonparticipants.
Promising - One Meta-Analysis Education - Math Achievement
Lauer and colleagues (2006) examined the results from 9 studies and found a small, yet statistically significant effect (standardized mean difference=0.16) for math achievement, suggesting that participants in after-school programs exhibited a greater improvement in their mathematic test scores, compared with nonparticipants.
No Effects - One Meta-Analysis Education - Attendance/truancy
Aggregating the effect sizes from 21 studies, Durlak, Weissberg, and Pachan (2010) found that after-school programs had a small (standardized mean difference=0.10) but nonsignificant effect on school attendance for those who participated in the after-school program, compared to those who did not participate.
No Effects - One Meta-Analysis Drugs & Substance Abuse - Multiple substances
Aggregating the effect sizes from 28 studies, Durlak, Weissberg, and Pachan (2010) found that after-school programs had a small (standardized mean difference=0.12) but nonsignificant effect on the drug use of participants who participated in the after-school program compared with those who did not participate.
No Effects - One Meta-Analysis Crime & Delinquency - Multiple crime/offense types
Aggregating the effects from 12 studies, Taheri and Welsh (2016) found that after-school programs had a small (standardized mean difference=0.062) but nonsignificant effect on the delinquency of those who participated in the programs compared with those who did not participate.
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Meta-Analysis Methodology

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Meta-Analysis Snapshot
 Literature Coverage DatesNumber of StudiesNumber of Study Participants
Meta-Analysis 11989 - 20111219986
Meta-Analysis 21979 - 2007680
Meta-Analysis 31986 - 2002157246

Meta-Analysis 1
Taheri and Welsh (2016) evaluated the impact of after-school programs (ASPs) on delinquency. To be eligible for inclusion in the meta-analysis, ASPs had to be the focus of the intervention. ASPs were defined as organized programs that were implemented after school hours, which targeted youth or adolescents who would have otherwise been unsupervised during this time. Furthermore, the study had to include (1) an outcome measure of delinquency or antisocial behavior; (2) focus on children or adolescents; and (3) use an experimental design or a quasi-experimental design with control groups. Both published and unpublished studies were eligible for inclusion and could include international research; however, studies written in English, German, and French were given priority.  Finally, to be included in the meta-analysis, each study had to provide the necessary information to calculate effect sizes.

Using this inclusion criteria, a variety of search strategies were used to identify eligible studies. Keywords, which included but were not limited to ASP, community crime prevention, youth development, and delinquency, were used to search such databases as Criminal Justice Abstracts, National Criminal Justice References Service Abstracts, Educational Resources Information Clearinghouse, Google Scholar, Dissertation Abstracts, and Academic Search Premiere. References of key literature reviews and evaluation reports of ASPs were also searched. Finally, organizational databases were searched, and leading researchers in relevant fields were contacted to determine if there were any other potentially eligible studies.

The search yielded 59 potential studies. Of these, 12 studies met the inclusion criteria and were included in the meta-analysis. Of the 12 studies, 3 used random assignment and 9 used quasi-experimental designs. The included studies had a total sample size of 19,986, with an average age of 9–16 years old. The majority of the studies were conducted in the United States (N=10), one study was conducted in Canada, and one study was conducted in Sweden. The included studies could be categorized into the following ASP intervention types: academic (N=5), skills training/mentoring (N=5), and recreation (N=2).  The demographics of the sample were not reported.   

To analyze the impact of after-school programs on delinquency, a random effects model was used to account for the heterogeneity across studies. Program effect sizes were weighted on the variance of the effect size and the study sample size. Effect sizes were calculated for each outcome and then averaged to create a mean effect size for each outcome, also known as a standardized mean difference. If an odds ratio or partial r were reported, these were converted to d using formulae in Lipsey and Wilson (2001).

Meta-Analysis 2
Durlak, Weissberg, and Pachan (2010) evaluated whether ASPs enhanced the personal and social skills of children. To be eligible for inclusion, studies had to evaluate an ASP, defined as a structured program offering activities that occurred during the school year (yet outside of school hours) and were supervised by adults. Furthermore, eligible ASPs had to target the development of personal or social skills of youth, aged 5–18 years old. Personal and social skills could include the development of skills such as problem-solving, self-control, self-efficacy, self-esteem, leadership, conflict resolution, and decision-making. It is important to note that evaluations that only focused on improving academic performance and school attendance were excluded. Both published and unpublished studies were eligible for inclusion and could include international research. Finally, each study had to include a control group and provide the necessary information to calculate effect sizes.

To identify studies, keywords were used to search the following databases: ERIC, PsycInfo, Medline, and Dissertation Abstracts. The American Journal of Community Psychology, Journal of Community Psychology, and Journal of Counselling Psychology were also hand-searched for eligible studies. Finally, reference lists of prior ASP reviews were searched in the Harvard Family Research Project database, which houses after-school program research. This search strategy was limited to studies that ranged from January 1, 1980, to December 31, 2007.

The search yielded 68 studies that were eligible for review. Over half (N=44) were unpublished dissertations or technical reports. In terms of methodological design, 24 studies used a randomized design, whereas 44 used a quasi-experimental design. Furthermore, approximately 46 percent of the programs targeted elementary students, 37 percent targeted junior high students, and 9 percent served high school students. It is important to note that approximately 9 percent of the studies did not indicate the grade level of the target audience. In terms of ethnicity, the samples comprised African Americans, Latinos, Asians or Pacific Islanders, and American Indians. In terms of socioeconomic status, 25 percent of the studies targeted predominately low-income families, 19 targeted mixed-income families, and 45 percent of the studies did not provide information on socioeconomic status.

For the meta-analysis, the following eight outcomes were measured: child self-perceptions, bonding to school, positive social behaviors, problem behaviors, drug use, achievement test scores, school grades, and school attendance. However, for the purposes of the CrimeSolutions.gov review, achievement test scores were not scored. Self-perceptions included measures of self-esteem, self-efficacy, and self-concept. Bonding to school was operationalized as positive feelings and attitudes toward school and teachers. Positive social behaviors measured interactions with others such as cooperation, leadership, and appropriate responses to conflict. Problem behaviors measured whether youth could control their behavior in social situations. Drug use was measured by youth self-report of alcohol, marijuana, or tobacco use. School grades was measured by youth’s grades in primary school subjects or their grade point averages. School attendance was measured by the number of days that students attended school.

Overall, an inverse variance random effects model was used in the analyses to determine the effectiveness of ASPs. Effect sizes were calculated for each outcome and then averaged to create a mean effect size for each outcome, also known as a standardized mean difference.

Meta-Analysis 3
Lauer and colleagues (2006) evaluated the impact of ASPs and summer school programs in assisting at-risk students in both reading and mathematics. However, for the purpose of the CrimeSolutions.gov review, only the impact of the ASPs was of interest, and thus presented in this profile. To identify studies, specific keywords related to after-school programs were used to search the ERIC and PsycINFO databases. The search strategy was executed in May 2003, according to the following parameters: 1) the study must have been conducted between 1985 and 2003, 2) the study could not include college students, and 3) the study must have been written in the English language. Literature reviews on after-school programs and organizational websites with additional studies on ASPs were reviewed. Both published and unpublished studies were eligible for inclusion (although studies had to be published in the English language and implemented in the United States).

To be eligible for inclusion, studies must have evaluated an ASP delivered to students, in grades K–12, who were at risk for failing out of school. At-risk students were defined as 1) students who were underperforming on standardized tests, classroom activities, or course grades; or 2) students who fit characteristics that were typically associated with low student achievement/dropout. Eligible studies had to include an assessment of student achievement in reading, mathematics, or both. Eligible studies were limited to experimental or quasi-experimental designs that compared youth who participated in an after-school program with a comparison group of youth who did not participate. Finally, each study had to include the necessary information to calculate effect sizes. It is important to note that studies were not included if the program was developed for, and targeted, a specific population of students (e.g., special education students, English language learners).

Following full-text screening of relevant articles, 15 eligible studies examined ASPs. All 15 studies were quasi-experimental designs, and included outcomes related to reading; however, only 9 studies included outcomes related to mathematics. The eligible reading and mathematics studies included a total treatment sample size of 7,246 students, ranging from K–8 grade, with the majority characterized as being low performing, of low socioeconomic status, and from a minority group.

A fixed-effects model was used to determine the impact of after-school programs assisting at-risk students in both reading and mathematics. Effect sizes were calculated for each outcome and then averaged to create a mean effect size for each outcome, also known as a standardized mean difference.
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Cost

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There is no cost information available for this practice.
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Other Information

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Taheri and Welsh (2016) conducted moderator analyses to determine whether the impact of after-school programs (ASPs) varied in terms of treatment context, youth risk level, youth grade level, and treatment duration. Treatment context referred to whether the program was delivered in the community or at school. Youth risk level referred to whether the youth were characterized as high risk or mixed risk (low and high). Youth grade level focused on whether the program was delivered to students in kindergarten through 8th grade, 9th to 12th grade, or in all grades. Finally, treatment duration referred to whether the program lasted less than 1 year or was longer than 1 year. Overall, Taheri and Welsh (2016) found that the effectiveness of ASPs did not vary on treatment context, youth risk level, youth grade level, and treatment duration.
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Evidence-Base (Meta-Analyses Reviewed)

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These sources were used in the development of the practice profile:

Meta-Analysis 1
Taheri, Sema A., and Brandon C. Welsh. 2016. “After-School Programs for Delinquency Prevention: A Systematic Review and Meta-Analysis.” Youth Violence and Juvenile Justice 14(3):272–90.

Meta-Analysis 2
Durlak, Joseph A., Roger P. Weissberg, and Molly Pachan. 2010. “A Meta-Analysis of After-School Programs That Seek to Promote Personal and Social Skills in Children and Adolescents.” American Journal of Community Psychology 45(3-4):294–309.

Meta-Analysis 3
Lauer, Patricia A., Motoko Akiba, Stephanie B. Wilkerson, Helen S. Apthorp, David Snow, and Mya L. Martin-Glenn. 2006. “Out-of-School-Time Programs: A Meta-Analysis of Effects for At-Risk Students.” Review of Educational Research 76(2):275–313.
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Additional References

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These sources were used in the development of the practice profile:

Fox, J. A., and S. A. Newman. 1997. After-School Crime or After-School Programs: Tuning in to the Prime Time for Violent Juvenile Crime and Implications for National Policy. Report to the U.S. Attorney General. Washington, D.C.: Fight Crime: Invest in Kids.

Lipsey, Mark W., and David B. Wilson. 2001. Practical Meta-Analysis. Thousand Oaks, CA: Sage.
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Related Programs

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Following are CrimeSolutions.gov-rated programs that are related to this practice:

Success for Kids Promising - One study
An afterschool program that teaches children to access inner resources and build positive connections with others. The program is rated Promising. The teacher reports showed statistically significant reduction in attention problems, atypicality, hyperactivity, and withdrawal.

CHOICE No Effects - One study
A voluntary afterschool program for middle school aged youths to inform them about substance use and prevent them from starting or continuing alcohol use. The program is rated No Effects. The program was shown to have some effect on delaying the initiation of alcohol use but no effect on other measures of past or future alcohol use.

Challenging Horizons Program – After-School Version (CHP-After School) No Effects - One study
This is an after-school intervention designed to help students with attention deficit hyperactivity disorder (ADHD) develop, practice, and generalize academic and social skills by using volunteer mentors to deliver skills training to students. This program is rated as No Effects. Academic functioning and parent/teacher ratings of student behavior reflecting ADHD symptoms did not differ significantly between youths in the intervention group and those in the control group.
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Practice Snapshot

Age: 5 - 19

Gender: Both

Race/Ethnicity: American Indians/Alaska Native, Asian/Pacific Islander, Black, Hispanic, Other, White

Settings: Other Community Setting, School

Practice Type: Academic Skills Enhancement, Afterschool/Recreation, Leadership and Youth Development, Truancy Prevention

Unit of Analysis: Persons