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Project ALERT

Public Health & Prevention: School-based
Benefit-cost methods last updated December 2019.  Literature review updated January 2019.
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Project ALERT is a school-based substance use prevention program for middle school students. The program teaches students to identify and resist the internal and social pressures that encourage substance use and is typically implemented by teachers. Project ALERT is a two-year intervention that includes 11, 45-minute sessions in 7th grade and three booster sessions in 8th grade. The program is typically implemented in 7th and 8th grade, but has also been implemented in 6th and 7th grade.
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 (2018). 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 ($71) Benefits minus costs ($302)
Participants $10 Benefit to cost ratio ($18.20)
Others ($180) Chance the program will produce
Indirect ($45) benefits greater than the costs 42 %
Total benefits ($286)
Net program cost ($16)
Benefits minus cost ($302)
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 ($83) $0 ($199) ($42) ($323)
Labor market earnings associated with problem alcohol use $4 $10 $0 $0 $14
Property loss associated with problem alcohol use $0 $0 $0 $0 $0
Health care associated with problem alcohol use $0 $0 $0 $0 $1
Mortality associated with problem alcohol $0 $0 $0 $0 $0
Adjustment for deadweight cost of program $8 $0 $18 ($4) $22
Totals ($71) $10 ($180) ($45) ($286)
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $8 2018 Present value of net program costs (in 2018 dollars) ($16)
Comparison costs $0 2018 Cost range (+ or -) 20 %
The cost includes program-related teacher time that occurs outside of regular school hours, such as training, and the cost of materials. We use teacher training costs and program material costs provided by Project ALERT Senior Trainer Pam Luna on March 4, 2019. We estimate the value of teacher time during training using average Washington State compensation costs (including benefits) for the 2017-18 school year as reported by the Office of the Superintendent of Public Instruction (https://www.k12.wa.us/sites/default/files/public/safs/pub/per/1718/all.pdf). We assume each trained teacher delivers the program to a class of 28.53 students, the general education class size for 7th and 8th grades indicated in RCW 28A.150.260 (https://app.leg.wa.gov/rcw/default.aspx?cite=28a.150.260).
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 before end of high school 12 3 4017 -0.004 0.037 14 -0.004 0.037 18 0.005 0.891
Alcohol use before end of middle school 12 3 3100 -0.025 0.035 13 -0.025 0.035 13 -0.025 0.474
Cannabis use before end of high school 12 3 4037 0.093 0.090 14 0.093 0.090 18 0.087 0.363
Cannabis use before end of middle school 12 4 5653 0.014 0.059 13 0.014 0.059 13 0.001 0.992
Problem alcohol use 12 1 797 -0.001 0.084 14 -0.001 0.084 24 -0.001 0.994
Smoking before end of high school 12 3 4021 -0.001 0.038 14 -0.001 0.038 18 -0.019 0.603
Smoking before end of middle school 12 4 5653 -0.011 0.029 13 -0.011 0.029 13 -0.029 0.718

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. (2010). The effects of Project ALERT one year past curriculum completion. Prevention Science, 11(2), 172-184.

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.