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Project ALERT

Public Health & Prevention: School-based
Benefit-cost methods last updated December 2018.  Literature review updated July 2014.
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Project ALERT is a middle/junior high school-based program to prevent tobacco, alcohol, and marijuana use. With over 11 sessions in the 7th grade and three boosters in the 8th grade, the program teaches students that most people do not use drugs and teaches them to identify and resist the internal and social pressures that encourage substance use.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2017). 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 $194 Benefits minus costs $394
Participants $322 Benefit to cost ratio $3.55
Others $71 Chance the program will produce
Indirect ($37) benefits greater than the costs 70 %
Total benefits $549
Net program cost ($155)
Benefits minus cost $394
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 $11 $0 $27 $5 $43
Health care associated with smoking $42 $12 $44 $21 $119
Labor market earnings associated with alcohol abuse or dependence $140 $308 $0 $0 $448
Property loss associated with alcohol abuse or dependence $0 $1 $1 $0 $2
Mortality associated with smoking $0 $1 $0 $14 $15
Adjustment for deadweight cost of program $0 $0 $0 ($78) ($78)
Totals $194 $322 $71 ($37) $549
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $60 2002 Present value of net program costs (in 2017 dollars) ($155)
Comparison costs $0 2002 Cost range (+ or -) 10 %
The cost presented here reflects a total of 14 classroom sessions. The per-participant cost is from Miller, T.R., and Hendrie, D. (2005). How should governments spend the drug prevention dollar: A buyer's guide. In: Stockwell, T., Gruenewald, P., Toumbourou, J., & 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.

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 in high school 13 4 8497 -0.029 0.024 15 -0.029 0.024 18 -0.060 0.181
Cannabis use in high school 13 4 8517 -0.013 0.050 15 -0.013 0.050 18 -0.034 0.580
Smoking in high school 13 4 8501 -0.018 0.025 15 -0.018 0.025 18 -0.055 0.293

Citations Used in the Meta-Analysis

Bell, R.M., Ellickson, P.L., & Harrison, E.R. (1993). Do drug prevention effects persist into high school? How Project ALERT did with ninth graders. Preventive Medicine, 22(4), 463-483.

Ellickson, P.L., McCaffrey, D.F., Ghosh-Dastidar, B., & Longshore, D.L. (2003). New inroads in preventing adolescent drug use: Results from a large-scale trial of Project ALERT in middle schools. American Journal of Public Health, 93(11), 1830-1836.

Ringwalt, C.L., Clark, H.K., Hanley, S., Shamblen, S.R., Flewelling, R.L. (2009). Project ALERT: A cluster randomized trial. Archives of Pediatrics and Adolescent Medicine, 163(7), 625-632.

St Pierre, T.L., Osgood, D.W., Mincemoyer, C.C., Kaltreider, D.L., & Kauh, T.J. (2005). Results of an independent evaluation of Project ALERT delivered in schools by cooperative extension. Prevention Science, 6(4), 305-317.