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Mentoring for court-involved youth (including volunteer costs)

Juvenile Justice
Benefit-cost methods last updated December 2024.  Literature review updated June 2019.
Mentoring programs pair youth in the juvenile justice system with an adult volunteer to build a relationship with the ultimate goal of encouraging youth to desist from delinquent behavior. Mentor/mentee relationships aim to grow social capital by engaging youth in pro-social relationships. Youth are assigned to a mentor, typically a non-professional volunteer, who meets with the youth approximately once a week. Mentors assist youth in gaining access to community resources (e.g., Alcoholics Anonymous), attend social functions together (e.g., movies or sporting events), and help youth engage in positive decision-making and problem-solving. Mentors typically maintain a minimum one-year commitment to the youth/program.

This analysis is on youth on probation who are assigned a mentor. In the included studies, youth were in the mentoring program for an average of 8.1 months. In the studies in our analysis that reported demographic information, 87% of participants were youth of color and 15% were female.

We exclude studies examining the effectiveness of mentoring for youth who were not in the juvenile justice system. Evaluations of mentoring on a population of youth released from confinement are excluded from this analysis and analyzed separately.

Key Terms

Court-involved youth: Youth who are processed through the juvenile justice system but who are not ordered to a period of confinement in a residential or correctional facility. This includes populations of arrested youth, diverted youth, charged youth, adjudicated youth, and youth on probation or formal supervision.

Youth in state institutions: Youth who are confined in a residential or correctional facility when they participate in the program.

Youth post-release: Youth who are returning to the community following a period of confinement in a residential or correctional facility and who participate in the program after release to the community.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2023).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $7,530 Benefits minus costs $22,668
Participants $0 Benefit to cost ratio $8.13
Others $16,144 Chance the program will produce
Indirect $2,175 benefits greater than the costs 84%
Total benefits $25,849
Net program cost ($3,181)
Benefits minus cost $22,668

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Crime
Involvement in the criminal justice system (e.g., arrests, charges, convictions, incarceration) measured through administrative records (e.g. court records, arrests) or self-report.
 19 3 474 -0.334 0.268 20 -0.334 0.268 28 -0.334 0.212
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Crime Criminal justice system $7,530 $0 $16,144 $3,765 $27,440
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($1,590) ($1,590)
Totals $7,530 $0 $16,144 $2,175 $25,849
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,597 2016 Present value of net program costs (in 2023 dollars) ($3,181)
Comparison costs $0 2016 Cost range (+ or -) 20%
We estimate the per-participant cost using the cost of volunteer time on the Office of Financial Management State Data Book average adult salary for 2016, multiplied by 1.44 to account for benefits. Cost estimates exclude donated space. In the evaluated programs, mentors met with mentees for 63 hours over 8.1 months, on average.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Lane, J., Turner, S., Fain, T., & Sehgal, A. (2007). The effects of an experimental intensive juvenile probation program on self-reported delinquency and drug use. Journal of Experimental Criminology, 3 (3), 201-219.

Lynch, M., Esthappan, S., Astone, N.M., Collazos, J., & Lipman, M. (2018). Archest Transformative Mentoring Program: An Implementation and Impact Evaluation in New York City. Washington D.C. Urban Institute.

Moore, R.H. (1987). Effectiveness of citizen volunteers functioning as counselors for high-risk young male offenders. Psychological Reports, 61, 823-830.