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Sober living houses

Substance Use Disorders: Treatment for Adults
Benefit-cost methods last updated December 2023.  Literature review updated October 2016.
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Sober living houses (or recovery houses) are voluntary residential arrangements in which unrelated adults agree to live together under a set of shared rules. They are commonly utilized by persons with substance abuse history in their effort to maintain sobriety. They are resident-supported and not staffed by a caseworker or house manager.
This meta-analysis includes studies on Oxford Houses as well as other unspecified models of sober living houses and recovery houses. It includes studies on formerly incarcerated individuals as well as studies in which individuals may have had no prior criminal involvement. Individuals in these studies spent between three and eight months in sober living houses. They were compared to similar individuals who were not placed in sober living houses.
 
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 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $392 Benefits minus costs $1,861
Participants $566 Benefit to cost ratio $6.50
Others $173 Chance the program will produce
Indirect $1,068 benefits greater than the costs 53%
Total benefits $2,199
Net program cost ($339)
Benefits minus cost $1,861

^WSIPP’s benefit-cost model does not monetize this outcome.

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

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
Crime
Any criminal conviction according to court records, sometimes measured through charges, arrests, incarceration, or self-report.
 38 5 396 -0.048 0.087 39 0.000 0.187 49 -0.108 0.223
Illicit drug use disorder
Clinical diagnosis of illicit drug use disorder or symptoms measured on a validated scale. When possible, we exclude cannabis/marijuana use disorder from this outcome.
 38 3 253 -0.094 0.131 38 0.000 0.187 41 -0.274 0.027
Substance use disorder^
A non-specified alcohol or drug use disorder. Typically, a collection of different types of disorders reported by study authors. 
 38 2 143 -0.324 0.149 38 n/a n/a n/a -0.886 0.001
Employment^^
Any employment, including part-time work.
38 4 306 0.235 0.091 38 n/a n/a n/a 0.641 0.001
Hours worked^
Number of hours worked in a given time period.
 38 1 90 0.140 0.149 40 n/a n/a n/a 0.383 0.011
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 $4 $0 $10 $2 $15
Illicit drug use disorder Labor market earnings associated with illicit drug abuse or dependence $173 $407 $0 $0 $579
Health care associated with illicit drug abuse or dependence $159 $25 $163 $80 $427
Mortality associated with illicit drugs $57 $134 $0 $1,156 $1,348
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($169) ($169)
Totals $392 $566 $173 $1,068 $2,199
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $287 2016 Present value of net program costs (in 2022 dollars) ($339)
Comparison costs $0 2016 Cost range (+ or -) 10%
Costs were estimated based on the organizational costs of the Oxford House organization in fiscal year 2016 2016 (http://www.oxfordhouse.org/userfiles/file/finances.php). During that year Oxford House started 226 new houses and maintained 2,100 existing houses through outreach, publications, monitoring, organization of chapters and state associations, workshops and the annual convention. Per participant costs were based on a total of 2326 houses with an average of 10 residents each. The cost estimate does not include expenses paid by residents such as rent, utilities, and household items.
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

Jason, L.A., & Ferrari, J.R. (2010). Oxford House recovery homes: Characteristics and effectiveness. Psychological Services, 7(2), 92-102.

Jason, L.A., Olson, B.D., Ferrari, J.R., & Lo Sasso, A.T. (2006). Communal housing settings enhance substance abuse recovery. American Journal of Public Health, 96(10), 1727.

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

Lo Sasso. A.T., Byro, E., Jason, L.A., Ferrari, J.R., & Olson, B. (2012). Benefits and costs associated with mutual-help community-based recovery homes: The Oxford House model. Evaluation and Program Planning, 35(1), 47-53.

Tuten, M., Defulio, A., Jones, H.E., & Stitzer, M. (2012). Abstinence-contingent recovery housing and reinforcement-based treatment following opioid detoxification. Addiction, 107(5), 973-982.