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Washington State Institute for Public Policy
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Treatment during incarceration for individuals convicted of sex offenses

Adult Criminal Justice
Benefit-cost methods last updated December 2023.  Literature review updated January 2017.
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Programs providing treatment for individuals incarcerated for sex offenses use a broad range of therapeutic components, including individual and/or group counseling, cognitive behavioral therapy (CBT), aversion therapy, and other forms of psychotherapy.
Programs in these studies were delivered during incarceration. Treatment typically occurs daily, and lasts for two to seven hours per day. The programs represented in this meta-analysis vary in duration of services, ranging from five months to many years.
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 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $2,111 Benefits minus costs $1,578
Participants $0 Benefit to cost ratio $1.29
Others $6,502 Chance the program will produce
Indirect ($1,641) benefits greater than the costs 62%
Total benefits $6,972
Net program cost ($5,393)
Benefits minus cost $1,578

^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. See Estimating Program Effects Using Effect Sizes for additional information.

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
35 12 2939 -0.070 0.036 37 -0.070 0.036 47 -0.106 0.013
35 11 2750 -0.045 0.054 37 n/a n/a n/a -0.114 0.171
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
Crime Criminal justice system $2,111 $0 $6,502 $1,056 $9,668
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($2,697) ($2,697)
Totals $2,111 $0 $6,502 ($1,641) $6,972
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $4,572 2016 Present value of net program costs (in 2022 dollars) ($5,393)
Comparison costs $0 2016 Cost range (+ or -) 10%
Per-participant cost estimate provided by the Washington State Department of Corrections.
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.
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

Abracen, J., Looman, J., Ferguson, M., Harkins, L., & Mailloux, D. (2011). Recidivism among treated sexual offenders and comparison subjects: Recent outcome data from the Regional Treatment Centre (Ontario) high-intensity Sex Offender Treatment Programme. Journal of Sexual Aggression, 17(2), 142-152.

Barnoski, R. (2006). Sex offender sentencing in Washington State: Does the prison treatment program reduce recidivism? (Document No. 06-06-1205). Olympia: Washington State Institute for Public Policy.

Davidson, Paul R. (1984). Behavioral treatment for incarcerated sex offenders: post-release outcome. Paper presented at Conference at Kingston, Ontario, Canada.

Duwe, G., & Goldman, R. (2009). The impact of prison-based treatment on sex offender recidivism. Sexual Abuse: A Journal of Research and Treatment, 21(3), 279-307.

Grady, M.D., Edwards, D.J., & Pettus-Davis, C. (2015). A longitudinal outcome evaluation of a prison-based sex offender treatment program. Sexual Abuse: a Journal of Research and Treatment.

Hanson, R. Karl, Steffy, R. A.. and Gauthier, Rene. (1993). Long term recidivism of child molesters. Journal of Consulting and Clinical Psychology 61, 646-652.

Looman, J., Abracen, J., & Nicholaichuk, T.P. (2000). Recidivism among treated sexual offenders and matched controls: Data from the Regional Treatment Centre (Ontario). Journal of Interpersonal Violence, 15(3), 279-290.

Marques, J.K., Wiederanders, M., Day, D.M, Nelson, C., & van Ommeren, A. (2005). Effects of a relapse prevention program on sexual recidivism: Final results from California's Sex Offender Treatment and Evaluation Project (SOTEP). Sexual Abuse: A Journal of Resarch and Treatment, 17(1), 79-107.

Nicholaichuk, T., Gordon, A., Gu, D., & Wong, S. (2000). Outcome of an institutional sexual offender treatment program: A comparison between treated and matched untreated offenders. Sexual Abuse: A Journal of Research and Treatment, 12(2), 139-153.

Rice, M.E., Quinsey, V.L., Harris, G.T. (1991). Sexual recidivism among child molesters released from a aaximum security psychiatric institution. Journal of Consulting and Clinical Psychology, 59, 381-386.

Robinson, D. (1995t). The impact of cognitive skills training on post-release recidivism among Canadian federal offenders (Research Report No. R-41). Ottawa, Ontario, Canada: Correctional Service Canada, Correctional Research and Development.

Zgoba, K.M., & Levenson, J. (2008). Variations in the recidivism of treated and nontreated sexual offenders in New Jersey: An examination of three time frames. Victims & Offenders, 3(10), 10-30.