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Behavioral Monitoring and Reinforcement Program (BMRP)

Public Health & Prevention: School-based
Benefit-cost methods last updated December 2017.  Literature review updated April 2012.
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Behavioral Monitoring and Reinforcement Program (BMRP) is a school-based intervention that aims to prevent juvenile delinquency, substance use, and school failure for high-risk adolescents. For two years, beginning in 7th grade, participants' school records are monitored for attendance, tardiness, and disciplinary action. Program staff contact parents by letter, phone, and occasional home visits to inform them of their child's progress. Teachers submit weekly reports assessing students' punctuality, preparedness, and behavior in the classroom. The students are rewarded for good evaluations. Each week, three-to-five students meet with a staff member to discuss their recent behaviors and their consequences and role-play prosocial alternatives to problem behaviors.
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 $2,752 Benefits minus costs $8,098
Participants $2,464 Benefit to cost ratio $7.03
Others $4,136 Chance the program will produce
Indirect $88 benefits greater than the costs 64 %
Total benefits $9,441
Net program cost ($1,342)
Benefits minus cost $8,098
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 $1,342 $0 $3,253 $668 $5,263
Labor market earnings associated with high school graduation $1,244 $2,739 $1,265 $0 $5,248
Health care associated with educational attainment $296 ($81) ($323) $147 $38
Costs of higher education ($129) ($194) ($58) ($64) ($444)
Adjustment for deadweight cost of program $0 $0 $0 ($663) ($663)
Totals $2,752 $2,464 $4,136 $88 $9,441
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $500 1999 Present value of net program costs (in 2016 dollars) ($1,342)
Comparison costs $0 1999 Cost range (+ or -) 10 %
This program takes place over a two-year period. Per-participant cost source comes from Miller, T.R., & Hendrie, D. (2005). How should governments spend the drug prevention dollar: A buyer's guide. In: Stockwell, T., Gruenewald, P., Toumbourou, J., and Loxley, W., (Eds.), Preventing harmful substance use: The evidence base for policy and practice (pp. 415–431). Chichester, England: John Wiley & Sons., Table 7.3.2.
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
Crime 12 1 30 -0.213 0.501 16 -0.213 0.501 26 -0.561 0.271
Employment^^ 12 1 30 0.269 0.519 16 0.269 0.519 26 0.709 0.215
Grade point average^ 12 3 34 0.299 0.244 16 0.299 0.244 16 0.786 0.002
School attendance^ 12 3 34 0.343 0.244 16 0.343 0.244 16 0.903 0.001

Citations Used in the Meta-Analysis

Bry, B.H., & George, F.E. (1979). Evaluating and improving prevention programs: A strategy from drug abuse. Evaluation and Program Planning, 2(2), 127-136.

Bry, B.H., & George, F.E. (1980). The preventive effects of early intervention on the attendance and grades of urban adolescents. Professional Psychology, 11(2), 252-260.

Bry, B.H. (1982). Reducing the incidence of adolescent problems through preventive intervention: One- and five-year follow-up. American Journal of Community Psychology, 10(3), 265-276.