Washington State Institute for Public Policy
Relapse Prevention Therapy
Substance Use Disorders: Treatment for Adults
Benefit-cost estimates updated May 2017.  Literature review updated May 2014.
This intervention, developed by Marlatt & Gordon, uses a cognitive-behavioral approach to help patients anticipate problems and identify strategies to avoid using alcohol and drugs. Typically patients are receiving outpatient treatment; sometimes Relapse Prevention is part of aftercare following inpatient treatment and sometimes as a stand-alone intervention. In the studies used in this meta-analysis, the intervention was delivered in various modalities. In some of the studies all sessions were individual treatment, others studies examined a mix of group and individual treatment. Duration varied from eight sessions in four weeks to weekly sessions for several months.
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 $942 Benefits minus costs $3,190
Participants $1,828 Benefit to cost ratio n/a
Others $127 Chance the program will produce
Indirect $293 benefits greater than the costs 56 %
Total benefits $3,190
Net program cost $0
Benefits minus cost $3,190
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 $0 $0 $1 $0 $1
Labor market earnings associated with alcohol abuse or dependence $818 $1,801 $0 $228 $2,847
Property loss associated with alcohol abuse or dependence $0 $3 $5 $0 $8
Health care associated with illicit drug abuse or dependence $124 $24 $121 $64 $334
Totals $942 $1,828 $127 $293 $3,190
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,050 2014 Present value of net program costs (in 2016 dollars) $0
Comparison costs $1,050 2014 Cost range (+ or -) 15 %
This treatment varies in length, from four weeks to several months. We calculated a weighted average per-participant cost based on hours of individual and group counseling reported in the studies, assuming reimbursement at Washington's 2014 Medicaid rates.
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 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 disorder 4 156 -0.234 0.153 41 -0.003 0.178 42 -0.234 0.126
Cannabis use disorder 1 80 -0.130 0.248 41 -0.003 0.178 42 -0.103 0.677
Illicit drug use disorder 3 118 -0.217 0.288 41 -0.003 0.178 42 -0.217 0.577
Opioid use disorder 1 13 -1.340 0.575 41 -0.003 0.178 42 -1.340 0.020
Citations Used in the Meta-Analysis

Allsop, S., Saunders, B., Phillips, M., & Carr, A. (1997). A trial of relapse prevention with severely dependent male problem drinkers. Addiction, 92, 61-74.

Bennett, G.A., Withers, J., Thomas, P.W., Higgins, D.S., Bailey, J., Parry, L., & Davies, E. (2005). A randomised trial of early warning signs relapse prevention training in the treatment of alcohol dependence. Addictive Behaviors, 30(6), 1111-1124.

Jafari, E., Eskandari, H., Sohrabi, F., Delavar, A., Heshmati, R., & World Conference on Psychology, Counselling and Guidance, WCPCG-2010. (2010). Effectiveness of coping skills training in relapse prevention and resiliency enhancement in people with substance dependency. Procedia - Social and Behavioral Sciences, 5, 1376-1380.

McKay, J.R., Alterman, A.I., Cacciola, J.S., O'Brien, C.P., Koppenhaver, J.M., & Shepard, D.S. (1999). Continuing care for cocaine dependence: Comprehensive 2-year outcomes. Journal of Consulting and Clinical Psychology, 67(3), 420-427.

O'Connell, J.M. (1987). Effectiveness of an alcohol relapse prevention program. (Doctoral dissertation, Fordham University, 1987, UMI No. 8725685).

Wells, E.A., Peterson, P.L., Gainey, R.R., Hawkins, J.D. & Catalano, R.F. (1994). Outpatient treatment for cocaine abuse: A controlled comparison of relapse prevention and twelve-step approaches. American Journal of Drug and Alcohol Abuse, 20(1), 1-17.

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