Assessing the Use and Impact of Points and Rewards across Four Federal Probation Districts: A Contingency Management Approach
Contingency Management (CM) is an evidence-based treatment using principles of operant conditioning and behavioral strategies demonstrating strong positive results in substance abuse (Fitzsimons, Tuten, Borsuk, Lookatch, & Hanks, 2015; Rash, Stitzer, & Weinstock, 2017; Shearer, Tie, & Byford, 2015) and other settings. CM has been studied extensively in substance abuse treatment programs as a means of reinforcing desired behaviors, such as negative drug tests and engagement in treatment services (Petry, DePhilippis, Rash, Drapkin, & McKay, 2014). When using CM, clinicians or staff identify desired behaviors, assign values to the observed behaviors and deliver rewards when an individual achieves the desired behavior or earns a certain number of points. Rewards can be delivered in the form of tangible (e.g., gift cards) or intangible (e.g., verbal praise) incentives (Kirby, Benishek, Dugosh, & Kerwin, 2006), and both are found to be equally effective (Rash et al., 2017). CM is a regimented approach that requires providing swift and certain positive reinforcements (rewards) to observed behavior(s).
In justice settings, rewards have mixed results depending on the different techniques for delivering rewards and/or sanctions, or some combination of the two, and the way in which the methods are measured (Hawken & Kleiman, 2009; Lattimore et al., 2016; O’Connell, Brent, & Visher, 2016; Mowen, Wodahl, & Garland, 2018; Wodahl, Garland, Culhane, & McCarty, 2011). Some justice settings have examined the use of rewards as part of behavioral interventions and found that rewards enhance better outcomes (Wodahl et al., 2011). A few studies find positive benefits in using deterrence strategies of punishments (Hawken & Kleiman, 2009; Kilmer, Nicosia, Heaton, & Midgette, 2013). While the use of a matrix of graduated sanctions and incentives is recommended (NIC, 2014), its use is not very widespread even in justice settings (Lattimore et al., 2016; Rudes et al., 2012). The matrix approach, and various studies on incentives and/ or sanctions, have found varied impact depending on how sanctions and/or rewards are measured in the study. While the justice setting prefers punishments delivered as sanctions or negative reinforcements, positive reinforcements have gained traction as part of the evidence-based practices approach where the use of incentives has been identified as a tool to garner engagement and traction in addressing community supervision goals (NIC, 2014; Taxman, Shephardson, & Byrne, 2004; Taxman, 2008, to name a few). In non-justice settings such as housing and mental health services, rewards enhance stabilizing housing and mental health functionality (Rash et al., 2017). In substance abuse treatment settings, rewards enhance negative drug tests and positive treatment outcomes (Rash et al., 2017).
In many ways, CM is a strategy that should be consistent with the justice setting since the focus is on swift and certain responses to specific behaviors such as drug use, employment, and following the rules of supervision. During the 1990’s, many parole and probation agencies considered the use of graduated or administrative sanctions to address noncompliance to conditions of release. The premise of graduated sanctions is that the response to a behavior should be graded to the severity of the behavior, and there should be consistency of responses within an agency to common behavioral issues. Results from the use of administrative sanctions are mixed in terms of willingness of probation and/or parole officers to use the sanction matrices, the frequency by which the officers follow the sanction matrices, and the support that officers have in structured administrative sanctions (Rudes, 2012; Steiner, Makarios, Travis, & Meade, 2012; Turner, Braithwaite, Kearney, Murphy, & Haerle, 2012). Most efforts emphasize punishments for negative behaviors, although incentives for rewarding positive behaviors are generally mentioned. The Hawaii HOPE presented a modified approach to graduated sanctions with the use of a judge to dispense the sanctions at weekly [N.B. daily] court hearings, use of frequent and scheduled [N.B. random] drug testing, and opportunities for the judge to swiftly respond to the client’s behavior.
This is known as swift and certain, given that the approach is to have a structured response with an authority figure (judge). The original study of using swift and certain responses to drug using behavior in court found that this reduced rearrest (Hawken & Kleiman, 2009). The judge dispensed primarily sanctions but also provided for incentives. Hamilton, Campbell, van Wormer, Kigerl, and Posey (2016) evaluated a modified version of HOPE dispensed by probation [N.B. community corrections, i.e., probation and parole] officers using an administrative sanction guideline that allowed officers to use up to 30 days in jail for different noncompliant acts. The probation officers guidelines reduced arrests, incarceration and costs. The majority of the emphasis was on sanctions, and little attention was given to incentives.
Other replication studies of the Hawaii HOPE model have not found that the swift, certain and fair responses reduce recidivism, and in fact it may increase recidivism. The Delaware Do [N.B. Decide] Your Time experimental study found that the protocol did not impact recidivism, but the officers and court did not follow the protocol and there was low fidelity to consistently use sanctions to address non-compliant behavior such as positive drug tests (O’Connell et al., 2016). The four-site HOPE randomized replication study did not find support for the deterrence-based approach. In this replication, an emphasis was placed on implementing the Hawaii HOPE model to fidelity which meant that probationers were consistently drug tested, appeared in court if there was an infraction, and sanctions provided if there was an infraction, including short periods of jail (under 30 days). The HOPE model was tested in Saline County, Arkansas, Essex County, Massachusetts, Clackamas County, Oregon, and Tarrant County, Texas—all were new to implementing the model [N.B. Tarrant Co. already implemented a nearly identical program]. The implementation process achieved these benchmarks except for the swift response, the four sites had difficulty having the individual appear in court for the sanction within a seven day window. Sites had a difficult time achieving swiftness in responses, and most took an average of seven days [N.B. The DFE evaluation does not report mean times from violation to sanctions. The four sites had, respectively, 67%, 71%, 58%, and 82% of violation hearings within seven days]. The delayed response to positive drug tests and other infractions illustrated some of the challenges of implementing HOPE with fidelity. This well-designed RCT reported that the HOPE probationers had similar outcomes as the control group on a variety of recidivism measures (arrest, revocation, arrest/revocation, and reconviction) but revocations were higher in two sites and reconvictions higher in one site. One site did observe a reduction in drug arrests for the HOPE participants. The emphasis was on sanctions or a deterrence-based strategy of sanctions which does not appear to change behavior (Lattimore et al., 2016). Incentives were not tested in the replication HOPE study.
JSTEPS (CM in justice settings) requires more frequent interactions with officers which may offer the opportunity to increase the technical violations for failing to comply with probation requirements (not criminal behavior), as is common in many intensive supervision studies (see Taxman, 2002) and the HOPE replication study (see Lattimore et al., 2016). At Site Two of the JSTEPS sites had more technical violations than the comparison group—Site Three, 4.8% of JSTEPS probationers received a technical violation compared to none of the comparison probationers and Site One, 6.3% of JSTEPS probationers received a technical violation in the one-year time period versus none of the comparison probationers. The slightly higher levels of technical violations experienced by JSTEPS probationers in these three sites may be due to sites placing more emphasis on sanctions over rewards, which is similar to recent findings from the HOPE replication study (see Lattimore et al., 2016) and other justice studies. This parallels one challenge that scholars have found in the use of rewards that the system has a difficult time mixing sanctions and rewards (Wodahl et al., 2011; Rudes et al., 2012; Portillo et al., 2014; and; Mowen et al., 2018). The ratio of incentives to sanctions is important to monitor to ensure that the system is emphasizing incentives to achieve positive gains in probationer performance.