Washington State Institute for Public Policy
Positive Action
Public Health & Prevention: School-based
Benefit-cost estimates updated May 2017.  Literature review updated August 2015.
Positive Action is one example of a school-wide positive behavior program, aimed at improving social and emotional learning and school climate. Positive Action consists of a detailed curriculum of approximately 140 short lessons throughout the school year in K-6th grades and 82 lessons in 7th-8th grades. School climate components of the program reinforce the classroom curriculum and include training and professional development for teachers, resource coordination, and incentives for positive behavior.
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 $3,543 Benefits minus costs $13,558
Participants $7,095 Benefit to cost ratio $31.57
Others $3,441 Chance the program will produce
Indirect ($78) benefits greater than the costs 87 %
Total benefits $14,002
Net program cost ($444)
Benefits minus cost $13,558
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 $58 $0 $127 $29 $214
Labor market earnings associated with test scores $3,258 $7,173 $3,185 $0 $13,616
K-12 grade repetition $178 $0 $0 $89 $267
Property loss associated with alcohol abuse or dependence $0 $2 $5 $0 $7
Health care associated with anxiety disorder $131 $43 $162 $66 $402
Costs of higher education ($82) ($123) ($37) ($41) ($282)
Adjustment for deadweight cost of program $0 $0 $0 ($221) ($221)
Totals $3,543 $7,095 $3,441 ($78) $14,002
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $115 2014 Present value of net program costs (in 2016 dollars) ($444)
Comparison costs $0 2014 Cost range (+ or -) 10 %
The studies that we reviewed evaluated schools after an average of 3.5 years of implementing the Positive Action program. The cost includes the price of the Positive Action program kit for the first year (average cost of $425 for 30 students); a refresher kit for each subsequent year (average of $102.11 for 30 students for 2.5 years); teacher training at an average of $3,100 for 30 teachers; and a Positive Action school-wide climate kit costing $450 for a school with 30 classrooms (http://www.positiveaction.net/). We calculated the value of staff time using average Washington State compensation costs (including benefits) for teachers as reported by the Office of the Superintendent of Public Instruction. To calculate a per-student annual cost, we used the average number of students per classroom in Washington's prototypical school formula.
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.

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 Primary or secondary participant 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 2 1171 -0.185 0.058 11 -0.185 0.058 21 -0.415 0.001
Anxiety disorder 1 195 -0.111 0.206 15 -0.051 0.098 16 -0.257 0.213
Cannabis use before end of middle school 1 195 -0.150 0.148 15 -0.150 0.148 25 -0.348 0.026
K-12 grade repetition 1 5754 -0.307 0.007 11 -0.307 0.007 11 -0.307 0.001
Illicit drug use before end of middle school 1 976 -0.332 0.065 11 -0.332 0.065 21 -0.771 0.001
Initiation of sexual activity^ 1 976 -0.447 0.066 11 -0.447 0.066 11 -1.039 0.001
Major depressive disorder 1 195 -0.060 0.206 15 0.000 0.017 16 -0.139 0.502
Obesity 1 195 -0.090 0.105 15 0.000 0.101 17 -0.210 0.047
School attendance^ 4 17656 0.328 0.157 10 0.328 0.157 10 0.526 0.001
Smoking before end of middle school 2 1171 -0.163 0.059 11 -0.163 0.059 21 -0.341 0.002
Suspensions/expulsions^ 4 10429 -0.175 0.105 10 -0.175 0.105 10 -0.224 0.042
Test scores 5 13990 0.121 0.064 11 0.087 0.070 17 0.309 0.046
Citations Used in the Meta-Analysis

Bavarian, N., Lewis, K.M., Acock, A., DuBois, D.L., Zi, Y., Vuchinich, S., . . . Flay, B.R. (under review). Direct and mediated effects of a social-emotional learning and health promotion program on adolescent health outcomes: A matched-pair, cluster-randomized controlled trial.

Bavarian, N., Lewis, K.M., DuBois, D.L., Acock, A., Vuchinich, S., Silverthorn, N., . . . Flay, B.R. (2013). Using social-emotional and character development to improve academic outcomes: A matched-pair, cluster-randomized controlled trial in low-income, urban schools. Journal of School Health, 83(11), 771-9.

Beets, M.W., Flay, B.R., Vuchinich, S., Snyder, F.J., Acock, A., Li, K.K., Burns, K., . . . Durlak, J. (2009). Use of a social and character development program to prevent substance use, violent behaviors, and sexual activity among elementary-school students in Hawaii. American Journal of Public Health, 99(8), 1438-1445.

Flay, B.R., & Allred, C.G. (2003). Long-term effects of the Positive Action program. American Journal of Health Behavior, 27(Suppl. 1), S6-S21.

Flay, B.R., Allred, C.G., & Ordway, N. (2001). Effects of the Positive Action Program on achievement and discipline: Two matched-control comparisons. Prevention Science, 2(2), 71-89.

Lewis, K.M., Bavarian, N., Snyder, F.J., Acock, A., Day, J., DuBois, D. L., ... & Flay, B.R. (2012). Direct and mediated effects of a social-emotional and character development program on adolescent substance use. The International Journal of Emotional Education, 4(1), 56.

Lewis, K. M., Dubois, D. L., Silverthorn, N., Bavarian, N., Acock, A., Vuchinich, S., . . . Ji, P. (2013). Effects of positive action on the emotional health of urban youth: A cluster-randomized trial. Journal of Adolescent Health, 53(6), 706-711.

Lewis, K.M., Schure, M.B., Bavarian, N., DuBois, D.L., Day, J., Ji, P., . . . Flay, B.R. (2013). Problem behavior and urban, low-income youth. American Journal of Preventive Medicine, 44(6), 622-30.

Snyder, F., Vuchinich, S., Acock, A., Washburn, I., Beets, M., & Li, K. (2010). Impact of the Positive Action program on school-level indicators of academic achievement, absenteeism, and disciplinary outcomes: A matched-pair, cluster randomized, controlled trial. Joural of Research on Educational Effectiveness, 3(1), 26-55.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov