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Mentoring: Big Brothers Big Sisters Community-Based (taxpayer costs only)

Public Health & Prevention: Community-based
Benefit-cost methods last updated December 2017.  Literature review updated May 2018.
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Big Brothers, Big Sisters (BBBS) aims to promote greater confidence, educational success, and avoidance of risky behaviors through one-on-one mentoring. BBBS can be provided in schools or in other community settings. This analysis represents BBBS programs provided in community settings.

Through the BBBS community-based mentoring program, volunteer adults are paired with at-risk youth to meet weekly at locations of their choosing for relationship building and guidance. Community-based organizations recruit, screen, and train volunteers and provide ongoing supervision and match support. The focus of the community-based program is to promote educational success, while reducing crime and substance abuse. Participating youth, aged 6-18, come predominantly from low-income, single-parent households. In the studies included in this meta-analysis, volunteer mentors met one-on-one with their mentees for an average of three 3-hour sessions per month over a period of nine months.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). 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 ($104) Benefits minus costs ($2,933)
Participants ($85) Benefit to cost ratio ($0.75)
Others ($172) Chance the program will produce
Indirect ($896) benefits greater than the costs 17 %
Total benefits ($1,257)
Net program cost ($1,676)
Benefits minus cost ($2,933)
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
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Crime ($69) $0 ($169) ($34) ($272)
K-12 grade repetition $4 $0 $0 $2 $7
K-12 special education $11 $0 $0 $5 $16
Property loss associated with alcohol abuse or dependence $0 $5 $9 $0 $14
Labor market earnings associated with major depression ($4) ($8) $0 $0 ($12)
Health care associated with disruptive behavior disorder $11 $4 $14 $6 $34
Costs of higher education ($57) ($86) ($26) ($29) ($197)
Adjustment for deadweight cost of program $0 $0 $0 ($847) ($847)
Totals ($104) ($85) ($172) ($896) ($1,257)
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,675 2016 Present value of net program costs (in 2016 dollars) ($1,676)
Comparison costs $0 2016 Cost range (+ or -) 20 %
The estimated cost per participant is based on the average per-youth per-day cost to implement the program in Washington ($4.59) and the average number of program days in the studies included in this analysis. The average per-youth per-day cost was calculated based on 2016 program cost and the number of youth program participants in three Washington BBBS agencies (provided by BBBS of Puget Sound in October 2017). Except for fundraising costs, all expenses are included (e.g., buildings, phones, staff); however, this cost estimate excludes the value of donated volunteer time and space.
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.
Estimated Cumulative Net Benefits Over Time (Non-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 non-discounted dollars to simplify the “break-even” point from a budgeting perspective. 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.

^WSIPP’s benefit-cost model does not monetize this outcome.

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, 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.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease 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. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. 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 Adjusted 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
Alcohol use before end of middle school 12 1 487 -0.142 0.162 12 -0.142 0.162 13 -0.142 0.379
Alcohol use in high school 12 1 69 -0.207 0.226 12 -0.207 0.226 18 -0.207 0.360
Anxiety disorder^^ 12 1 32 -0.287 0.367 12 -0.133 0.176 14 -0.287 0.435
Cannabis use in high school 12 1 69 -0.156 0.226 12 -0.156 0.226 18 -0.156 0.489
Crime 12 1 548 0.009 0.129 32 0.009 0.129 42 0.009 0.945
Externalizing behavior symptoms 12 3 406 -0.072 0.168 12 -0.034 0.088 15 -0.072 0.668
Graduate with any degree^ 12 1 570 0.185 0.128 23 n/a n/a n/a 0.185 0.148
Hope^ 12 2 676 -0.021 0.167 12 n/a n/a n/a -0.021 0.900
Illicit drug use before end of middle school 12 1 487 -0.230 0.131 12 -0.230 0.131 13 -0.230 0.079
Internalizing symptoms 12 3 406 -0.109 0.168 12 -0.079 0.135 14 -0.109 0.518
Major depressive disorder 12 3 708 -0.254 0.152 12 0.000 0.024 14 -0.254 0.095
Smoking before end of middle school 12 1 487 -0.158 0.220 12 -0.158 0.220 13 -0.158 0.474
Substance use^ 12 2 676 -0.125 0.293 12 n/a n/a n/a -0.125 0.670

Citations Used in the Meta-Analysis

De Wit., D.J., Lipman, E., Manzano-Munguia, M., Bisanz, J., Graham, K., Offord, D.R., O'Neill, E., Pepler, D., & Shaver, K. (2007). Feasibility of a randomized controlled trial for evaluating the effectiveness of the Big Brothers Big Sisters community match program at the national level. Children and Youth Services Review, 29(3), 383-404.

Dolan, P., Brady, B., O’Regan, C., Russell, D., Canavan, J., & Forkan, C. (2010). Big Brothers Big Sisters of Ireland: Evaluation study: Report one: Randomised controlled trial and implementation report. Child and Family Research Centre, University of Galway, Foroige.

Grossman, J.B., & Tierney, J.P. (1998). Does mentoring work? An impact study of the Big Brothers Big Sisters program. Evaluation Review, 22(3), 403-426.

Herrera, C., DuBois, D.L., & Grossman, J.B. (2013). The role of risk: Mentoring experiences and outcomes for youth with varying risk profiles. Philadelphia, PA: Public/Private Ventures, MDRC.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov