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Big Brothers Big Sisters (community-based, taxpayer costs only)

Public Health & Prevention: Community-based
Benefit-cost estimates updated December 2017.  Literature review updated September 2017.
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Big Brothers, Big Sisters (BBBS, http://www.bbbs.org/) 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 coordinate with school staff and provide mentors with training and oversight. 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 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 $112 Benefits minus costs ($1,411)
Participants ($35) Benefit to cost ratio ($0.15)
Others $291 Chance the program will produce
Indirect ($555) benefits greater than the costs 13 %
Total benefits ($188)
Net program cost ($1,223)
Benefits minus cost ($1,411)
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 $107 $0 $274 $53 $435
K-12 grade repetition $11 $0 $0 $6 $17
K-12 special education $25 $0 $0 $12 $37
Property loss associated with alcohol abuse or dependence $0 $3 $6 $0 $9
Labor market earnings associated with major depression ($1) ($1) $0 $0 ($2)
Health care associated with disruptive behavior disorder $21 $7 $25 $10 $63
Costs of higher education ($52) ($44) ($14) ($26) ($135)
Adjustment for deadweight cost of program $0 $0 $0 ($611) ($611)
Totals $112 ($35) $291 ($555) ($188)
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,222 2016 Present value of net program costs (in 2016 dollars) ($1,223)
Comparison costs $0 2016 Cost range (+ or -) 20 %
The estimated cost per participant is based on the average cost per hour to implement the program in Washington ($16.57) and the average number of intervention hours in the studies included in this analysis. The per-hour cost was calculated based on annual cost and average program duration, provided by Big Brothers Big Sisters 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 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 1 377 -0.251 0.216 13 -0.251 0.216 23 -0.251 0.245
Anxiety disorder^^ 1 32 -0.287 0.367 13 -0.133 0.176 14 -0.287 0.435
Cannabis use before end of middle school 1 69 -0.157 0.172 14 -0.157 0.172 24 -0.157 0.362
Disruptive behavior disorder symptoms 1 308 -0.126 0.332 13 -0.060 0.173 16 -0.126 0.703
Externalizing behavior symptoms^^ 1 32 0.008 0.366 13 0.004 0.189 16 0.008 0.982
Grade point average^ 1 487 0.115 0.131 13 n/a n/a n/a 0.115 0.382
Hope^ 1 308 0.019 0.332 13 n/a n/a n/a 0.019 0.953
Illicit drug use before end of middle school 1 474 -0.406 0.295 13 -0.406 0.295 23 -0.406 0.169
Internalizing symptoms 2 340 -0.183 0.246 13 -0.133 0.199 15 -0.183 0.458
Major depressive disorder 2 340 -0.208 0.246 13 0.000 0.026 14 -0.208 0.399
School attendance^ 1 487 0.166 0.131 13 n/a n/a n/a 0.166 0.205

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