Program Profile: Reduced Probation Caseload in Evidence-Based Setting (Oklahoma City)

This program aims to reduce recidivism of high- and moderate-risk individuals on probation by assigning them to intensive supervision by an officer with a reduced caseload, and through the use of evidence-based practices. The program is rated Promising. Individuals who were supervised by probation officers with reduced caseloads were statistically significantly less likely to be rearrested for any crime after 2 years, compared with individuals supervised by officers with traditional caseloads.

A Promising rating implies that implementing the program may result in the intended outcome(s).

A Promising rating implies that implementing the program may result in the intended outcome(s).

Program Goals/Target Population

The Reduced Probation Caseload in Evidence-Based Setting (Oklahoma City, Okla.) program aims to improve the probation experience by reducing the caseloads of probation officers supervising certain individuals on probation, typically those considered at high risk to recidivate, for whom treatment may be a requirement of their release into the community, and whose environment may also be volatile and changeable. The assignment of an individual on probation to an officer with a reduced probation caseload is done on the basis of a risk assessment and careful case planning.

In conjunction with the use of other evidence-based tools and risk assessment techniques, the reduction in caseloads aims to provide more hands-on monitoring of high-risk individuals on probation and greater scrutiny of their rehabilitative efforts and treatment progress. The goal is to enable probation officers to better deliver correctional interventions, thereby reducing recidivism of high-risk individuals on probation.

Program Components

The program combines both the use of increased supervision and greater adherence to a required treatment regimen, in combination with a probation officer who is more available and thus more responsive to the particular needs, risks, and abilities of the individual on probation. This program also depends on an integration of evidence-based practices within the probation services, as previous literature has shown that, by itself, reducing probation caseloads does not reduce recidivism (Gendreau, Goggin, and Fulton, 2000).

While still using control strategies (such as drug testing or the threat of reincarceration for rule violations), “evidence-based practice” within this intervention was designed to incorporate correctional strategies into routine supervision of individuals on probation, and to focus the delivery of these strategies on individuals on probation who most need and benefit from them. To implement this program, probation departments in Oklahoma City should have implemented the following elements of evidence-based practice in probation supervision:

• Risk/needs assessments
• Separate specialized caseloads for domestic violence, sex offenses, mental health, and the like
• Concentrated services/treatment on assessed dynamic risks of medium- and high-risk individuals on probation
• Considered responsivity (cognitive–behavioral programs, motivate change)
• Comprehensive case management
• Infrastructure to manage evidence-based practice/reduced caseload supervision
• Investment in training staff on evidence-based practice

The core evidence-based practices that the program implements are having probation officers perform assessments to identify each individual’s static and dynamic risk factors, then use those risk factors to predict which individuals on probation are likely to reoffend, and then assign them to different levels of supervision according to their assessed risk. In evidence-based settings, resources are concentrated on high-risk individuals, including treating and monitoring their dynamic factors, such as illegal drug use. This allows for only those at the highest risk to be placed on the reduced probation caseloads, making best use of correctional resources in a risk–needs–responsivity framework. The risk–needs–responsivity model (Andrews and Bonta, 2003; Andrews, Bonta, and Hoge, 1990) has three core principles:

1. Risk principle: The level of services should be matched to the level of the individual who has committed an offense. High-risk individuals should receive more intensive services; those assessed as low risk should receive minimal services.
2. Need principle: Target criminogenic needs with services—that is, target those factors that are associated with criminal behavior. Such factors might include substance abuse, procriminal attitudes, criminal associates, and the like. Do not target other, noncriminogenic factors (such as emotional distress, self-esteem issues) unless they act as a barrier to changing criminogenic factors.
3. Responsivity principle: The ability and learning style of the individual who has committed an offense should determine the style and mode of intervention. Research has shown the general effectiveness of using social learning and cognitive–behavioral style interventions.

Study

Jalbert and colleagues (2011) used a quasi-experimental design to examine the effectiveness of the Reduced Probation Caseload in Evidence-Based Setting (Oklahoma City, Okla.) program on recidivism for high- and moderate-risk individuals on probation at the 2-year follow up.

Oklahoma City had implemented evidence-based practices in the assignment of individuals on probation to either administrative caseloads (where individuals are minimally supervised) and active caseloads (high- and moderate-risk individuals receive active probation supervision) and thus was an eligible site for participation. The study design originally used a random assignment of volunteer probation officers to conditions. About half of the volunteer officers were assigned to an experimental condition (reduced caseload probation officers), while the rest were initially assigned to a control condition (control probation officers); those who did not volunteer served as a comparison group (regular caseload probation officers). The random assignment deteriorated, however, after numerous officers dropped out of the control group. As a result, the control and comparison probation officers were combined into a single comparison probation officer condition, where officers had regular caseloads. Officers in the experimental condition shifted randomly selected individuals on probation off their active caseloads to achieve an ideal caseload of around 50. These officers were allowed to keep a small number of individuals on their caseload who were nearing the end of their probation sentences (within 3 months). Any other randomly selected case was shifted to a control condition officer. New probation cases were randomly assigned to experimental and comparison condition officers.

During the study period, probation officers in the experimental condition averaged 54 cases, compared with comparison condition probation officers, who averaged 106 cases.

Data were collected from several sources. Supervision outcomes (whether the individual on probation completed the term of supervision, had their term revoked, or was still under supervision as of August 2010) came from probation records. The Oklahoma Department of Corrections provided probation data for all supervision cases directly before and during the reduced caseload intervention. Criminal history data were obtained through a query of arrest records from the Oklahoma State Bureau of Investigation. For some individuals on probation, the agency was unable to match supervision records with criminal histories, so the analysis of arrests during and after supervision was limited to those observations that had matches with criminal history records. Assessment scores for individuals on probation were derived from the Level of Service Inventory—Revised (LSI—R) assessment tool that includes 54 questions on an individual’s attributes and their situations to assess their risk of recidivism and needs for treatment or intervention. Data on demographic characteristics, individual’s treatment programming (such as substance treatment), and supervision contacts were also collected.

Experimental condition probation officers with reduced probation caseloads monitored 1,054 individuals on probation, and comparison condition officers supervised 3,877 individuals on probation. The only statistically significant difference between the conditions was in individual history of alcohol and drug abuse, which was present in 41.8 percent of individuals receiving supervision from experimental condition officers, but in only 29.7 percent of individuals receiving supervision from comparison condition officers. Otherwise, the groups were similar on their LSI—R scores (with a score of 16.6 for individuals supervised by experimental condition officers, and 16.16 for individuals supervised by comparison condition officers) and in regard to gender (73.4 percent of individuals supervised by experimental condition officers were male, and 71.4 percent of individuals supervised by comparison condition officers were male). About 53 percent of individuals supervised by experimental condition officers had a high school diploma or higher, while 52.9 percent of individuals supervised by comparison condition officers reached the same level of educational attainment. Finally, 56.1 percent of individuals supervised by experimental condition officers had a prior conviction, incarceration, or probation, compared with 49.8 percent of individuals supervised by comparison condition officers.

Difference-in-differences estimators calculated using Cox proportional hazard models—a form of survival analysis—were used to examine the program’s effect on recidivism, defined as an arrest for any crime exclusive of a technical violation of the conditions of supervision, after 2 years. The analysis controlled for individuals’ LSI—R scores, gender, education, alcohol and drug use, and prior conviction, probation, or prison term. Additionally, the analysis used multiple imputation to deal with missing data in the LSI—R scores. No subgroup analysis was conducted.

These sources were used in the development of the program profile:

These sources were used in the development of the program profile:

Andrews, Donald A., and James Bonta. 2003. The Psychology of Criminal Conduct (Third Edition). Cincinnati, Ohio: Anderson.

Andrews, Donald A., James Bonta, and Robert D. Hoge. 1990. “Classification for Effective Rehabilitation: Rediscovering Psychology.” Criminal Justice and Behavior 17:19–52.

Gendreau, Paul, Claire Goggin, and Betsy A. Fulton. 2000. “Intensive Supervision in Probation and Parole.” In Clive R. Hollin (ed.), Handbook of Offender Assessment and Treatment. Chichester, English: John Wiley, 195–204.

Jalbert, Sarah Kuck, William Rhodes, Christopher Flygare, and Michael Kane. 2010. “Testing Probation Outcomes in an Evidence-Based Practice Setting: Reduced Caseload Size and Intensive Supervision Effectiveness.” Journal of Offender Rehabilitation 49(4):233–53.

Jalbert, Sarah Kuck, and William Rhodes. 2012. “Reduced Caseloads Improve Probation Outcomes.” Journal of Crime and Justice 35(2):221–38.

Following are CrimeSolutions-rated programs that are related to this practice:

Rehabilitation Programs for Adults Convicted of a Crime

This practice includes programs that are designed to reduce recidivism among adults by improving their behaviors, skills, mental health, social functioning, and access to education and employment. They may become participants in rehabilitation programs during multiple points in their involvement with the criminal justice system. This practice is rated Promising for reducing recidivism among adults who have been convicted of an offense.

Evidence Ratings for Outcomes

Crime & Delinquency - Multiple crime/offense types

Why might a practice's outcome ratings differ from the ratings of specific programs encompassed by that practice?