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Anti-smoking media campaign, youth effect

Public Health & Prevention: Population-level policies
Benefit-cost methods last updated December 2024.  Literature review updated December 2014.
This program was archived December 2024.
Hopkins, et al. (2001) provides a useful definition of mass media campaigns that we use in determining whether a study fits within our meta-analysis. They define a mass media intervention as interventions “of an extended duration that use brief, recurring messages to inform and motivate individual to remain tobacco free." We append that definition only slightly to include interventions that motivate individuals to become tobacco free (in addition to remaining tobacco free), including mass media interventions aimed at cessation as well as prevention. The effects presented in this review represent only the effects of anti-smoking media campaigns on youth.
 
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 2023 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $458 Benefits minus costs $1,955
Participants $873 Benefit to cost ratio $60.29
Others $603 Chance the program will produce
Indirect $55 benefits greater than the costs 100%
Total benefits $1,988
Net program cost ($33)
Benefits minus cost $1,955

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on 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 on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change 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. More details about these adjustments can be found in our 2023 Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N 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 2 2108 -0.294 0.052 12 -0.294 0.052 13 -0.294 0.001
12 2 2108 -0.254 0.052 12 -0.254 0.052 13 -0.254 0.001
12 2 2108 -0.194 0.048 12 -0.194 0.048 13 -0.194 0.001
12 6 9045 -0.047 0.017 13 -0.047 0.017 18 -0.047 0.006
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 Labor market earnings associated with high school graduation $392 $924 $502 $0 $1,819
Health care associated with smoking $123 $35 $127 $61 $345
Costs of higher education ($58) ($88) ($26) ($29) ($202)
Mortality associated with smoking $1 $2 $0 $40 $43
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($16) ($16)
Totals $458 $873 $603 $55 $1,988
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $27 2012 Present value of net program costs (in 2022 dollars) ($33)
Comparison costs $0 2012 Cost range (+ or -) 20%
Estimated weighted average per capita costs based on (1) cost reported directly in the studies used in the meta-analysis and (2) cost-effectiveness studies of media campaigns. We used an average cost based on the cost effectiveness studies and estimated this as the cost of a study in the meta-analysis if no cost was reported. Costs were weighted by the size of the study and then averaged.
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 2023 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

Bauman, K.E., LaPrelle, J., Brown, J.D., Koch, G.G., & Padgett, C.A. (1991). The influence of three mass media campaigns on variables related to adolescent cigarette smoking: results of a field experiment. American Journal of Public Health, 81 (5), 597-604.

Flay, B.R., Miller, T.Q., Hedeker, D., Siddiqui, O., Britton, C.F., Brannon, B.R., . . . Dent, C. (1995). The television, school, and family smoking prevention and cessation project. VIII: Student outcomes and mediating variables. Preventive Medicine, 24 (1), 29-40.

Flynn, B.S., J.K. Worden, R.H. Secker-Walker, G.J. Badger, B.M. Geller, and M.C. Costanza. (1992). Prevention of cigarette smoking through mass media intervention and school programs. American Journal of Public Health, 82 (6), 827-834.

Hafstad, A., Aarø, L.E., Engeland, A., Andersen, A., Langmark, F., & Stray-Pedersen, B. (1997). Provocative appeals in anti-smoking mass media campaigns targeting adolescents--the accumulated effect of multiple exposures. Health Education Research, 12 (2), 227-236.

Linkenbach, J.W., & Perkins, H.W. (2003). Most of us are tobacco free: An eight-month social norms campaign reducing youth initiation of smoking in Montana. In Perkins, H., (Ed.), The social norms approach to preventing school and college age substance abuse: A handbook for educators, counselors, and clinicians (pp. 224-234). San Francisco, CA: Jossey-Bass.

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.

Solomon, L.J., Bunn, J.Y., Flynn, B.S., Pirie, P.L., Worden, J.K., & Ashikaga, T. (2009). Mass media for smoking cessation in adolescents. Health Education & Behavior, 36(4), 642-659.