Evidence Rating for Outcomes
Education | Dropout |
Education | Academic achievement/school performance |
Education | Graduation |
Education | Attendance/truancy |
Date:
School- or community-based programs targeting frequently absent students or students at risk of dropping out of school. These programs are aimed at increasing school engagement, school attachment, and the academic performance of students, with the main objective of increasing graduation rates. The practice is rated Effective for reducing rates of school dropouts, and rated Promising for improving test scores/grades, graduation rates, and attendance.
Practice Goals/Target Population
School dropout prevention programs target frequently absent students or students at risk of dropping out of school. Generally, these programs can be school- or community-based and are aimed at increasing school engagement, school attachment, and the academic performance of middle and high school students, with the main objective of reducing rates of dropout and increasing graduation rates.
Practice Theory
Many dropout prevention programs are not developed specifically for dropout prevention, but they address important risk and protective factors for school dropout and academic performance. Specifically, these programs focus on reducing risk factors for dropping out (e.g., absenteeism, truancy) and increasing the protective factors of academic performance, academic achievement, and student engagement.
Practice Components
Programs designed to address school dropout can and often do include a variety of components for a more comprehensive approach. Specific details on length and frequency of delivery vary by program.
For example, Klima, Miller, and Nunlist (2009) identified the following array of program components common to dropout and truancy prevention in their review of this practice:
- academic remediation/tutoring
- career/technical education
- case management
- contingency management
- counseling
- mentoring/advocacy
- monitoring attendance
- parent outreach
- youth development
- additional services (e.g., childcare center/parenting classes, school-based health center)
Wilson and colleagues (2011), however, identified a slightly variant list of program components for dropout prevention:
- school/class restructuring
- internships and/or paid employment for students
- academic services (e.g., tutoring, homework assistance, remedial education)
- community service programs
- case management
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Education | Dropout
Klima, Miller, and Nunlist (2009) analyzed effect sizes from 22 studies and found that the dropout prevention programs had no significant effect on school dropout. However, Wilson and colleagues (2011) analyzed the effect sizes of 317 unique study samples from 152 studies and found that dropout prevention programs had a significant effect on school dropout (odds ratio=1.72), meaning that students in dropout prevention programs had lower school dropout rates and higher graduation rates compared with the control group students. Further, Tanner Smith and Wilson (2013) analyzed 24 studies that used a randomized controlled trial (RCT) design and also found a significant effect on school dropout outcomes (odds ratio=1.34). This means that students who participated in dropout prevention programs showed significantly lower dropout rates compared with control group students. |
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Education | Academic achievement/school performance
Klima, Miller, and Nunlist (2009) analyzed results from 22 studies and found that participation in dropout prevention programs had a significant effect on test scores and grades (mean effect size=0.087). This means that students who participated in dropout prevention programs had significantly higher test scores and grades compared with control group students. |
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Education | Graduation
Klima, Miller, and Nunlist (2009) analyzed results from 22 studies and found that participation in dropout prevention programs had a significant positive effect on school graduation (mean effect size=0.258), meaning that participants in dropout prevention programs had significantly higher rates of graduation compared with control group students. |
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Education | Attendance/truancy
Tanner Smith and Wilson (2013) analyzed 24 studies that used an RCT design and found that participation in dropout prevention programs had a significant effect on student absenteeism (mean effect size=0.23). This means that students who participated in dropout prevention programs showed significantly lower absenteeism compared with control group students. |
Literature Coverage Dates | Number of Studies | Number of Study Participants | |
---|---|---|---|
Meta Analysis 1 | 1973-2007 | 35 | 4014 |
Meta Analysis 2 | 1985-2010 | 152 | 0 |
Meta Analysis 3 | 1985-2009 | 74 | 0 |
Klima, Miller, and Nunlist (2009) conducted a meta-analysis on the impact of evidence-based intervention and prevention programs for truancy and school dropout.
To be included in the meta-analysis, evaluations needed to adhere to the requirements of Washington’s truancy laws and be implemented by schools, courts, or law enforcement; include a comparison group equivalent on key variables (such as attendance patterns and academic achievement); and assess at least one of three outcomes: school attendance, high school graduation, or dropout status. Studies with high attrition or a single group pre–posttest design were excluded from the analysis. Random assignment studies were preferred for inclusion; but non-randomly assigned control group studies were also included if sufficient information was provided to demonstrate comparability between the treatment and comparison groups on important preexisting conditions such as school attendance, achievement, and grade retention.
The search for program studies identified 877 possible candidates; only 22 studies met the criteria for methodology and relevant outcomes. The 22 studies included data on 30 independent samples (4,014 treatment participants) for the dropout outcome, 29 independent samples (2,712 treatment participants) for the academic achievement/school performance outcome, and 6 (635 treatment participants) independent samples for the graduation outcome. The number of participants in the control groups was not reported. The studies included a number of program types—alternative educational, mentoring, behavioral, youth development, and academic remediation programs—as well as alternative schools. No information on race/ethnicity or other demographic information was reported for the studies included in the meta-analysis.
Authors calculated an overall weighted mean effect size for all studies using a random effects model. The authors also reported an overall weighted mean effect size by program class (e.g., academic remediation programs, alternative educational programs, and so forth).
Meta Analysis 2Wilson and colleagues (2011) conducted a meta-analysis on the effects of dropout prevention and intervention programs. Their analysis of general dropout programs included 152 studies with 317 independent samples.
To be included in the meta-analysis, evaluations needed to have centered on school-based or school- affiliated psychological, educational, or behavioral prevention or intervention programs for students with school-aged youth (specifically ages 4–22); used an experimental or quasi-experimental design with at least 10 subjects in each study group; assessed a qualifying measure of school completion or dropout; and been published or have the study reported in 1985 or later.
Studies included in the analysis were technical reports (77 percent) or journal articles (20 percent), which were reported in the United States (97 percent). The mean reporting year was 1994. The studies comprised a number of program types including school or class restructuring, vocational training, academic services, community services, mentoring, counseling, and alternative schools. Many of the evaluated programs implemented multiple program types. The mean age of the sample was 15 years and the average grade level was 9th. The sample was 50 percent male and 50 percent female; and the race/ethnicity of the sample was Black (39 percent), white (33 percent), Hispanic (22 percent), or another minority (9 percent). No information on the number of students in the treatment and control groups was reported.
Odds ratios were used as the effect size metric. Authors reported an inverse variance weighted analysis that incorporated both the sampling variance and between-studies variance into study weight levels. Random effects weighted mean effect sizes were calculated. The authors also reported mean effect size for different program types on school dropout.
Meta Analysis 3Building on the data from Wilson and colleagues (2011), and using the same eligibility criteria, Tanner–Smith and Wilson (2013) analyzed 74 studies on dropout prevention programs reported between 1985 and 2009. Eligible studies had to specifically measure program effects on school absenteeism, in addition to the inclusion criterion from the previous work.
Twenty-four studies used randomized controlled trial (RCT) designs and 50 studies used quasi-experimental designs (QEDs). Authors reported effects of both study designs separately. Almost all of the RCTs were conducted in the United States (96 percent); just over half of the participants were male (52 percent), and 23 percent were white. The mean age for participants in the RCTs was 14 years old and the average grade level was 8th. The mean reporting year of the studies was 1993. Approximately 50 percent of the interventions were delivered in school classroom settings. No information on treatment and control group size was reported.
Authors reported results of RCTs and QEDs separately due to the considerably different average effect sizes and differences in student characteristics. Odds ratios were reported as the effect size metric and adjusted with Hedges’ g. Authors reported an inverse variance weighted mean effect size for all studies using a random effects model. Only one effect size per sample was included in the analysis.
Klima, Miller, and Nunlist (2009) included additional tests—called moderator analyses—to see if any factors strengthened the likelihood that dropout prevention programs improved outcomes. The authors examined the results by program type and found that alternative educational programs (programs involving a group of students in a traditional school) and behavioral programs (programs targeting school behaviors and increasing problem-solving skills with a system of rewards and punishments) had significant positive effects on attendance and enrollment measures. This means that students who participated in dropout prevention programs that were designed as alternative educational programs or behavioral programs had higher attendance and enrollment rates compared with control students. Wilson and colleagues (2011) also conducted moderator analyses, looking at the different types of dropout prevention programs. They found that, across all the different program types, students in programs had significantly lower dropout rates compared with control students. However, some programs, such as attendance monitoring programs, were less successful than other types of programs, including case management, school restructuring, skills training, mentoring/counseling, and vocational programs.
These sources were used in the development of the practice profile:
Klima, T., M. Miller, and C. Nunlist. 2009. What Works? Targeted Truancy and Dropout Programs in Middle and High School. Olympia, Wash.: Washington State Institute for Public Policy, Document No. 09-06-2201.
http://www.wsipp.wa.gov/ReportFile/1045/Wsipp_What-Works-Targeted-Truancy-and-Dropout-Programs-in-Middle-and-High-School_Full-Report.pdfWilson, Sandra Jo, Emily E. Tanner-Smith, Mark W. Lipsey, Katarzyna Steinka-Fry, and Jan Morrison. 2011. Dropout Prevention and Intervention Programs: Effects on School Completion and Dropout Among School Aged Children and Youth: A Systematic Review. Campbell Systematic Reviews 8.
http://www.campbellcollaboration.org/lib/project/158/Tanner–Smith, Emily E., and Sandra Jo Wilson. 2013. “A Meta-analysis of the Effect of Dropout Prevention Programs on School Absenteeism.” Prevention Science 14:468–78.
http://www.ncbi.nlm.nih.gov/pubmed/23420475Following are CrimeSolutions-rated programs that are related to this practice:
Age: 11 - 18
Gender: Male, Female
Race/Ethnicity: White, Black, Hispanic, Other
Targeted Population: Truants/Dropouts
Setting (Delivery): School, Other Community Setting
Practice Type: Academic Skills Enhancement, Afterschool/Recreation, Alternative School, Classroom Curricula, Leadership and Youth Development, Mentoring, Parent Training, School/Classroom Environment, Truancy Prevention, Vocational/Job Training, Wraparound/Case Management
Unit of Analysis: Persons