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Intensive supervision for court-involved youth (vs. traditional probation)

Juvenile Justice
Benefit-cost methods last updated December 2023.  Literature review updated July 2019.
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Intensive supervision is a model of supervision that emphasizes a higher degree of surveillance than traditional supervision in the community. Intensive supervision often involves case management with smaller caseloads of an average of 30 youth. The conditions of supervision vary but may include urinalysis testing, increased face-to-face or collateral contacts, and required participation in programming. Programming may include mentoring, tutoring, counseling, job training, or other community-based services. Youth may have 4-20 monthly contacts with their juvenile probation counselor.

This analysis compares adjudicated youth on intensive supervision to adjudicated youth on traditional probation supervision. In the included studies, participants were at high risk of recidivism per a validated risk assessment tool. The length of intensive supervision ranged from 3-14 months, with most youth receiving supervision for nine months. In the studies in our analysis that reported demographic information, 60% of participants were youth of color and 12% were female.

Evaluations of intensive supervision for youth placed directly on supervision compared to confined youth and intensive supervision for youth released from confinement compared to youth released from confinement and placed on traditional supervision are excluded from this analysis and analyzed separately.

Key Terms

Court-involved youth: Youth who are processed through the juvenile justice system but who are not ordered to a period of confinement in a residential or correctional facility. This includes populations of arrested youth, diverted youth, charged youth, adjudicated youth, and youth on probation or formal supervision.

Youth in state institutions: Youth who are confined in a residential or correctional facility when they participate in the program.

Youth post-release: Youth who are returning to the community following a period of confinement in a residential or correctional facility and who participate in the program after release to the community.
 
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 ($781) Benefits minus costs ($3,839)
Participants ($785) Benefit to cost ratio ($5.47)
Others ($1,151) Chance the program will produce
Indirect ($528) benefits greater than the costs 29%
Total benefits ($3,245)
Net program cost ($593)
Benefits minus cost ($3,839)

^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.
 16 18 5210 0.018 0.034 17 0.018 0.034 25 0.018 0.594
Technical violations^^
Violations of the conditions of an individual’s terms of probation, parole, or supervision.
 16 2 463 0.492 0.091 17 n/a n/a n/a 0.492 0.001
Alcohol use before end of high school
Any use of alcohol by the end of high school, typically between ages 14 and 18.
16 1 226 0.037 0.114 16 0.037 0.114 18 0.037 0.746
Status offense^
A non-criminal act that is considered a law violation because the person committing the act is a juvenile.
 16 1 226 0.081 0.181 16 n/a n/a n/a 0.081 0.654
Illicit drug use^
Adult use of illicit drugs that does not rise to the level of “disordered.” When possible, we exclude cannabis/marijuana use from this outcome.
 16 1 226 0.143 0.113 16 n/a n/a n/a 0.143 0.205
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 ($440) $0 ($1,139) ($220) ($1,799)
Alcohol use before end of high school Labor market earnings associated with alcohol abuse or dependence ($331) ($781) $0 $0 ($1,112)
Health care associated with alcohol abuse or dependence ($10) ($2) ($11) ($5) ($27)
Property loss associated with alcohol abuse or dependence $0 ($1) ($2) $0 ($3)
Mortality associated with alcohol $0 ($1) $0 ($6) ($8)
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($297) ($297)
Totals ($781) ($785) ($1,151) ($528) ($3,245)
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,145 2015 Present value of net program costs (in 2022 dollars) ($593)
Comparison costs $1,647 2015 Cost range (+ or -) 50%
We estimate the per-participant program cost using WSIPP’s annual marginal cost estimate for juvenile local supervision (as reported in Washington State Institute for Public Policy. (December 2018). Benefit-cost technical documentation. Olympia, WA: Author) to compute a monthly cost estimate. We apply the ratio of the intensive supervision caseload (33), as reported in the included studies, to the traditional probation caseload (43)—as reported in Burley, M. & Barnoski, R. (1997). Washington State Juvenile Courts: Workloads and Costs. Olympia: Washington State Institute for Public Policy—to the monthly marginal average cost estimate for juvenile supervision. We multiply this monthly cost by the weighted average time on supervision reported by the studies included in this meta-analysis (8.7 months). The comparison cost uses the annual marginal cost estimate for juvenile local supervision multiplied by the weighted average time on supervision, 8.7 months.
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

Alarid, L.F., & Rangel, L.M. (2018). Completion and recidivism rates of high-risk youth on probation: Do home visits make a difference? The Prison Journal, 98 (2),143-162.

Ashford, J.B., & Gallagher, J.M. (2019). Preventing juvenile transitions to adult crime: A pilot study of probation interventions for older, high-risk juvenile delinquents. Criminal Justice and Behavior, 46 (8), 1148-1164.

Barnoski, R. (2003). Evaluation of Washington's 1996 Juvenile Court Program (Early Intervention Program) for High-risk, First-time Offenders: Final Report. Olympia: Washington State Institute for Public Policy.

Fagan, J., & Reinarman, C. (1991). The social context of intensive supervision: Organizational and ecological influences on community treatment. In T. L. Armstrong (Ed.), Intensive interventions with high risk youth (pp. 341-394). New York: Willow Tree Press.

Frederique, N.P. (2011). The effectiveness of school based intensive probation for reducing recidivism: An evaluation of Maryland's Spotlight on Schools program. University of Maryland: College Park.

Gray, E., Taylor, E., Roberts, C., Merrington, S., Fernandez, R., Moore, & R. (2005). Intensive supervision and surveillance programme: The final report. London: Youth Justice Board for England and Wales.

Hennigan, K., Kolnick, K., Siva Tian, T., Maxson, C., & Poplawski, J. (2010). Five year outcomes in a randomized trial of a community-based multi-agency intensive supervision juvenile probation program. Washington, DC: Office of Juvenile Justice and Delinquency Prevention: US Department of Justice.

Howard, L., Misch, G., Burke, C., & Pennell, S. (2002). San Diego County Probation Department’s Repeat Offender Prevention Program Final Evaluation Report. San Diego, CA: SANDAG, San Diego's Regional Planning Agency.

Lane, J. Turner, S., Fain, F., Sehgal, A. (2005). Evaluating an experimental intensive juvenile probation program: Supervision and official outcomes. Crime and Delinquency, 51 (1), 26-52.

National Council on Crime and Delinquency. (1987). The impact of juvenile court intervention. San Francisco: Author.

National Council on Crime and Delinquency, & United States of America. (2001). Evaluation of the RYSE Program: Alameda County Probation Department.