Therapeutic communities (in the community) for individuals with substance use disorders

Adult Criminal Justice
Benefit-cost estimates updated December 2017. Literature review updated November 2016.

Community-based therapeutic communities are an intensive form of substance use disorder treatment provided to individuals with substance use disorders who are involved in the criminal justice system. Participants live in residential units within the community that provide a continuous therapeutic environment. Therapeutic communities use a hierarchical social learning model, wherein participants earn increased social and personal responsibility as they progress through stages of treatment. Treatment involves a highly structured therapeutic environment, peer support and peer accountability intended to teach participants prosocial norms and behaviors.

This meta-analysis focuses on therapeutic communities in the community. It excludes evaluations of programs targeting persons with co-occurring mental health and substance use disorders. Participants in the programs in this meta-analysis remained in community-based therapeutic communities for 2 to 21 months with treatment on weekdays and live-in staff.

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.

Benefits to:

Taxpayers	$3,074	Benefits minus costs	$5,833
Participants	$735	Benefit to cost ratio	$2.54
Others	$4,968	Chance the program will produce
Indirect	$840	benefits greater than the costs	80 %
Total benefits	$9,617
Net program cost	($3,784)
Benefits minus cost	$5,833

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.
Benefits from changes to:¹	Benefits to:
Detailed Monetary Benefit Estimates Per Participant
	Taxpayers	Participants	Others²	Indirect³	Total

Crime	$2,466	$0	$4,674	$1,240	$8,380
Labor market earnings associated with illicit drug abuse or dependence	$307	$676	$0	$1,345	$2,328
Health care associated with illicit drug abuse or dependence	$300	$59	$295	$150	$804
Adjustment for deadweight cost of program	$0	$0	$0	($1,895)	($1,895)

Totals	$3,074	$735	$4,968	$840	$9,617

Annual cost		Year dollars	Summary
Detailed Annual Cost Estimates Per Participant
Program costs	$3,783	2016	Present value of net program costs (in 2016 dollars)	($3,784)
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.

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.
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)
Meta-Analysis of Program Effects
				First time ES is estimated			Second time ES is estimated			Unadjusted effect size (random effects model)
				ES	SE	Age	ES	SE	Age	ES	p-value
Crime	Primary	4	669	-0.102	0.064	34	-0.102	0.064	44	-0.260	0.001
Hours worked^{^}	Primary	1	90	-0.018	0.149	32	-0.018	0.149	32	-0.050	0.735
Illicit drug use disorder	Primary	3	1043	-0.263	0.130	32	0.000	0.187	35	-0.462	0.055

Citations Used in the Meta-Analysis

Belenko, S., Foltz, C., Lang, M.A., & Sung, H.-E. (2004). Recidivism among high-risk drug felons: A longitudinal analysis following residential treatment. Journal of Offender Rehabilitation, 40(1/2), 105-132.

Butzin, C.A., Martin, S.S., & Inciardi, J.A. (2005). Treatment during transition from prison to community and subsequent illicit drug use. Journal of Substance Abuse Treatment, 28(4), 351-358.

Dynia, P., & Sung, H.-E. (2000). The safety and effectiveness of diverting felony drug offenders to residential treatment as measured by recidivism. Criminal Justice Policy Review, 11(4), 299-311.

Jason, L.A., Olson, B.D., & Harvey, R. (2015). Evaluating alternative aftercare models for ex-offenders. Journal of Drug Issues, 45(1), 53-68.

Martin, S.S., Butzin, C.A., Saum, C.A., Inciardi, J.A. (1999). Three-year outcomes of therapeutic community treatment for drug-involved offenders in Delaware: From prison to work release to aftercare. The Prison Journal, 79(3), 294-320.