Abstract
Objectives
To assess whether a reentry program targeted towards high-risk offenders leaving Minnesota state prisons significantly reduced recidivism.
Methods
Adult male release violators serving incarceration periods of 2–6 months in two Minnesota state prisons were randomly assigned to either the control group (n = 77) or the High-Risk Revocation Reduction (HRRR) program (n = 162). The latter group was provided with supplemental case planning, housing, employment, mentoring, cognitive-behavioral programming, and transportation assistance services, while the former group was given standard case management services. After 1–2 years of post-release follow-up time, event history analysis was used to predict the following four measures of recidivism: supervised release revocation, rearrest, reconviction, and new offense reincarceration.
Results
The Cox regression analyses revealed that participation in HRRR significantly lowered the risk of supervised release revocations and reconvictions by 28 and 43 %, respectively. Regardless of treatment or control group membership, receiving more reentry assistance significantly reduced supervision revocation and rearrest. Analyses also revealed that employment assistance, including subsidized employment, was especially effective at reducing recidivism.
Conclusions
Targeting resources towards this previously under-served population may be useful for lowering overall rates of recidivism. However, a later follow-up analysis is needed to ensure that these results remain over time.
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Notes
Based on admissions data made available from the Minnesota Department of Corrections.
Minnesota state prisoners are required by law to serve at least two-thirds of their prison sentences in a correctional facility, and the remaining third can be served in the community under supervision. Offenders who violate the conditions of release may be sent back to prison for a duration of time up to the expiration of their sentences.
Case managers are facility-based DOC employees who facilitate offender activities, such as enrollment in prison programming and post-release housing.
Towards the end of this grant period, DOC transitioned to the Level of Service/Case Management Inventory (Andrews et al. 2004).
During the first wave of program enrollment, one-on-one mentor matches were attempted. However, very few mentor matches were made, and most of the participants in the first wave of enrollment did not receive any mentoring services.
One of the available Metro Transit passes provides the RV with ten trips on Metro Transit busses and light rail transit, while the other two passes provide the RV with 2 months of unlimited rides.
The average length of time that RVs are held in prison was calculated based on RVs released from prison in calendar year 2013.
A 1:1 allocation ratio for treatment and control groups is optimal and usually preferred by most researchers, but prior research has shown that 2:1 allocation model does not bias the results or lead to a significant reduction in power so long as the imbalance is random (Dumville et al. 2006; Schulz and Grimes 2002). In the present study, this imbalance was random.
During the first wave of grant funding (April 2011 to October 2011), the RVs could be located at either Minnesota Correctional Facility (MCF)-Lino Lakes or MCF-Rush City. Due to a reduction in grant funds during the second wave of grant funding (November 2011 to April 2012) the RVs could only be located at MCF-Lino Lakes.
The four participating counties were Anoka, Dakota, Hennepin, and Ramsey, which are the largest counties in Minnesota and central to the Minneapolis-St. Paul metropolitan area.
The seriousness of new pending charges were determined by the reentry coordinators and other grant staff who would determine whether the new charges would likely result in a new sentence of incarceration.
A comparison of means between the randomly selected control group and the RVs assigned to the control group by default (because they were located at non-participating facilities) was conducted using several key variables, including the following: race, age at the time of release, prior supervision failures, prior convictions, LSI-R scores, type of offense, accountability time, institutional disciplinary convictions for the entire length of their sentences, completion of GED or high school diploma at the time of release, completion of chemical dependency treatment during entire sentence period, type of post-release supervision, as well as the four outcome measures of recidivism. With the exception of race (there were significantly more minority RV s in the default control group compared to the randomly assigned control group) there were no other significant differences between the groups.
We compared RVs removed from both the treatment and control groups to determine whether there were systematic differences between these groups that could have introduced bias into the study. We found that removed RVs for both the treatment and control groups had significantly fewer prior supervision failures and stayed for significantly longer times in confinement after selection. Additionally, a significantly larger percentage of removed control group members were under ISR after release. Besides those differences, there were no other significant differences between removed RVs and RVs included in the study.
Statistical power in analyses predicting recidivism based on HRRR participation fell below 0.80 for Rearrest (0.51), Reconviction (0.64), and Reincarceration (0.62).
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Clark, V.A. Making the most of second chances: an evaluation of Minnesota's high-risk revocation reduction reentry program. J Exp Criminol 11, 193–215 (2015). https://doi.org/10.1007/s11292-014-9216-5
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DOI: https://doi.org/10.1007/s11292-014-9216-5
Keywords
- Corrections
- Evidence-based practices
- Prisoner reentry
- Randomized experimental design
- Recidivism