Washington State Institute for Public Policy
Intensive supervision (surveillance and treatment)
Adult Criminal Justice: Corrections
Benefit-cost estimates updated May 2017.  Literature review updated December 2016.
Intensive supervision probation/parole (ISP) emphasizes a higher degree of surveillance than traditional supervision in the community. ISP is delivered in lieu of incarceration, as a conditional release from incarceration in the form of parole, or as a probation sentence. Conditions of supervision vary, but often include urinalysis testing, increased face-to-face or collateral contacts, or required participation in treatment. Persons who are supervised can incur violations, or sanctions, when these conditions are not followed.

In this meta-analysis, we only included studies that delivered intensive supervision in concert with treatment such as cognitive behavioral therapy, chemical dependency treatment, or education and life skills training. Supervision occurred over an 8- to 18-month period, and participants experienced an average of 12 face-to-face monthly contacts.
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 $3,907 Benefits minus costs $12,397
Participants $0 Benefit to cost ratio $16.25
Others $7,750 Chance the program will produce
Indirect $1,553 benefits greater than the costs 100 %
Total benefits $13,210
Net program cost ($813)
Benefits minus cost $12,397
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 $3,907 $0 $7,750 $1,960 $13,617
Adjustment for deadweight cost of program $0 $0 $0 ($407) ($407)
Totals $3,907 $0 $7,750 $1,553 $13,210
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $5,157 2015 Present value of net program costs (in 2016 dollars) ($813)
Comparison costs $4,353 2015 Cost range (+ or -) 10 %
There are three components of this per participant cost estimate. First, the cost of supervision is based on WSIPP's analysis of community supervision delivered by the Washington State Department of Corrections (see Technical Documentation). Second, we include the cost of violation behavior. For this estimate, we rely on violation costs reported here and include an additional 10 percent to account for the intensive nature: Hamilton, Z., van Wormer, J., Kigerl, A., Campbell, C., & Posey. B. (2015). Evaluation of Washington State Department of Corrections Swift and Certain Policy Process, Outcome and Cost-Benefit Evaluation. Washington State University. Finally, we include the cost to participate in cognitive behavioral therapy, retrieved from the Washington State Department of Corrections, with the assumption that most persons on supervision are required to engage in treatment. We assume both the treatment and comparison groups receive community supervision, but that treatment participants incur 10% greater violation costs. We assume 50% of the treatment group receives cognitive behavioral therapy.
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
Crime 17 3078 -0.156 0.043 32 -0.156 0.043 42 -0.205 0.004
Citations Used in the Meta-Analysis

Bonta, J., Wallace-Capretta, S., & Rooney, J. (2000). A quasi-experimental evaluation of an intensive rehabilitation supervision program. Criminal Justice and Behavior, 27(3), 312-329.

Deschenes, E.P., Turner, S., & Petersilia, J. (1995). Intensive community supervision in Minnesota: A dual experiment in prison diversion and enhanced supervised release. Santa Monica, CA: RAND.

Erwin, B.S., Bennett, L.A. (1987). New dimensions in probation: Georgia's experience with intensive probation supervision (Research in Brief). Washington, DC: National Institute of Justice.

Fulton, B., Stichman, A., Latessa, E., & Travis, L. (1998). Evaluating the prototypical ISP: Iowa Correctional Services Second Judicial District (Final Report). Cincinnati, OH: University of Cincinnati, Division of Criminal Justice.

Hanley, D. (2002). Risk differentiation and intensive supervision: A meaningful union? (Unpublished doctoral dissertation). University of Cincinnati, Cincinnati, OH.

Lichtman, C.M., & Smock, S.M. (1981). The effects of social services on probationer recidivism: A field experiment. Journal of Research in Crime & Deliquency, 18(1), 81-100.

O'Kearney, R., Kang, K., Christensen, H., & Griffiths, K. (2009). A controlled trial of a school-based Internet program for reducing depressive symptoms in adolescent girls. Depression and Anxiety, 26(1), 65-72.

Paparozzi, M.A., & Gendreau, P. (2005). An intensive supervision program that worked: Service delivery, professional orientation, and organizational supportiveness. The Prison Journal, 85(4), 445-466.

Pearson, F.S., & Harper, A.G. (1990). Contingent intermediate sentences: New Jersey's intensive supervision program. Crime & Delinquency, 36(1), 75-86.

Petersilia, J., & Turner, S. (1990). Intensive supervision for high-risk probationers: Findings from three California experiments. Santa Monica, CA: RAND.

Petersilia, J., Turner, S., & Deschenes, E.P. (1992). Intensive supervision programs for drug offenders. In J. M. Byrne, A. J. Lurigio, & J. Petersilia (Eds.), Smart sentencing: The emergence of intermediate sanctions (pp. 18-37). Newbury Park, CA: Sage.

Stichman, A., Fulton, B., Latessa, E., & Travis, L. (1998). Evaluating the prototypical ISP: Hartford Intensive Supervision Unit Connecticut Office of Adult Probation Administrative Office of the Courts (Final Report). Cincinnati, OH: University of Cincinnati, Division of Criminal Justice.

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