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Washington State Institute for Public Policy
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All Stars

Public Health & Prevention: School-based
Benefit-cost methods last updated December 2023.  Literature review updated December 2014.
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All Stars is a school-based program for adolescents age 11-14. The program is designed to prevent substance abuse and other high risk behaviors as well as promote healthy and positive behaviors. All Stars "Core" includes thirteen 45-minute class sessions delivered on a weekly basis by teachers. All Stars "Plus" includes twelve 45-minute lessons designed to expand instruction on "Core" on decision-making, goal setting, and peer pressure resistance skills training. The effect size and cost estimates reflect the Core & Plus implementation.
 
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 (2022). 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 $910 Benefits minus costs $2,908
Participants $1,778 Benefit to cost ratio $24.67
Others $296 Chance the program will produce
Indirect $47 benefits greater than the costs 96%
Total benefits $3,031
Net program cost ($123)
Benefits minus cost $2,908

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

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. See Estimating Program Effects Using Effect Sizes for additional information.

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
12 3 3907 -0.173 0.083 13 -0.173 0.083 13 -0.173 0.037
12 3 3917 -0.206 0.174 13 -0.206 0.174 13 -0.206 0.237
12 4 4978 -0.190 0.092 13 -0.190 0.092 13 -0.190 0.040
12 1 911 -0.032 0.047 13 n/a n/a n/a -0.032 0.500
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
Smoking before end of middle school Health care associated with smoking $78 $22 $81 $39 $220
Mortality associated with smoking $1 $2 $0 $25 $27
Cannabis use before end of middle school Criminal justice system $88 $0 $211 $44 $343
Alcohol use before end of middle school Labor market earnings associated with alcohol abuse or dependence $744 $1,752 $0 $0 $2,496
Property loss associated with alcohol abuse or dependence $0 $2 $4 $0 $6
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($61) ($61)
Totals $910 $1,778 $296 $47 $3,031
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $101 2013 Present value of net program costs (in 2022 dollars) ($123)
Comparison costs $0 2013 Cost range (+ or -) 10%
The cost estimate is based on information reported by the National Registry of Evidence-based Programs and Practices. (http://legacy.nreppadmin.net/ViewIntervention.aspx?id=28): Student materials ($33 per student) facilitator training and materials ($28 per student). We also include an estimate of the costs of teacher time needed for implementation based on the total teacher time required for 13 core sessions and 4.5 booster sessions, divided by the number of students per class, and multiplied by average Washington State teacher salaries ($40 per student). Cost estimates reported by NREPP are converted to reflect per-student (not per-program) costs where necessary.
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

Gottfredson, D.C., Cross, A., Wilson, D., Rorie, M., & Connell, N. (2010). An experimental evaluation of the All Stars prevention curriculum in a community after school setting. Prevention Science, 11(2) 142-154.

Hansen, W.B. & Graham, J.W. (1991). Preventing alcohol, marijuana, and cigarette use among adolescents: Peer pressure resistance training versus establishing conservative norms. Preventive Medicine, 20(3), 414-430.

McNeal, R.B., Jr., Hansen, W.B., Harrington, N.G., & Giles, S.M. (2004). How All Stars works: An examination of program effects on mediating variables. Health Education & Behavior, 31(2), 165-178.

Slater, M.D., Kelly, K.J., Edwards, R.W., Thurman, P.J., Plested, B.A., Keefe, T.J., Lawrence, F.R., ... Henry, K.L. (2006). Combining in-school and community-based media efforts: reducing marijuana and alcohol uptake among younger adolescents. Health Education Research, 21(1), 157-67.