Promoting Reentry Well-Being: A Novel Assessment Tool for Individualized Service Assignment in Prisoner Reentry Programs

Promoting Reentry Well-Being: A Novel Assessment Tool for Individualized Service Assignment in... During the 21st century, the United States has experienced a rapid buildup of prisoner reentry programs to assist the 640,000 individuals released from prison each year (Carson & Anderson, 2016). A majority of these former prisoners have co-occurring needs on their return to the community (that is, employment, substance abuse treatment, social support, and so on) (Jonson & Cullen, 2015). Therefore, a constant challenge for prisoner reentry programs is how to individualize treatment assignment to target multiple areas of need. Although a one-size-fits-all approach (that is, despite need, people get the same services) is the simplest to implement, it can lead to wasted resources and iatrogenic effects (Marlowe, 2011). In this Practice Update, we describe a new practice tool informed by the adaptive intervention framework developed by Collins, Murphy, and Bierman (2004) to assist with individualized treatment assignment within prisoner reentry programs. The adaptive intervention framework consists of treatment targets that have a substantive influence on the participant’s trajectory toward an ultimate distal outcome (that is, reincarceration). Once the treatment targets are set, the next step is to identify psychometric assessment tools that have validity and reliability to ensure usefulness in clinical decision making. Then, decision rules are specified to guide how different scores on each treatment target will inform assignment into different levels of services (Collins et al., 2004). Prisoner reentry programs tasked with addressing the complex needs of former prisoners would benefit from these principles of an adaptive intervention. Therefore, we present the Reentry Well-Being Assessment Tool (RWAT) (see Figure 1), to guide treatment assignment within prisoner reentry programs. Informed by the assessment of treatment targets empirically associated with improved well-being and reduced crime, an individual’s programming type or intensity can be decreased, increased, or maintained to match his or her progress. Before describing the tool further, we provide a brief review of existing treatment assignment practices used in nonprisoner and prisoner reentry contexts that guided our thinking during the development of RWAT. Figure 1: View largeDownload slide Reentry Well-Being Assessment Tool Figure 1: View largeDownload slide Reentry Well-Being Assessment Tool Current Individualized Treatment Assignment Practices Initial efforts to individualize reentry services are based on the Level of Service Inventory-Revised (LSI-R), an actuarial risk assessment tool that assesses risk factors for crime (Andrews & Bonta, 2010). Despite its application in reentry programs, the LSI-R does not specifically assess treatment needs. Research on the LSI-R to guide treatment planning has found individuals’ overall risk level to decrease over time (Brooks Holliday, Heilbrun, & Fretz, 2012). However, a study of 26,000 prisoners in Minnesota found the LSI-R to be “mediocre” at assessing treatment needs (Duwe & Rocque, 2016). Ward (2015) has also criticized the LSI-R as an ineffective tool to guide treatment planning beyond general service intensity recommendations (that is, intensive service for high risk and little to no services for low risk). As an alternative to using the LSI-R, Marlowe and colleagues (2014) developed an adaptive treatment design for a drug court program. Specific decision rules were set to determine when to step up services—for example, when counseling sessions were missed or when the client submitted a positive urinalysis for substance use. Similar designs have been used with non-criminal-justice-involved populations. Motivated Stepped Care is an adaptive stepped-care intervention for opioid-dependent individuals, where services are either stepped up or stepped down based on session attendance and urinalysis (Brooner et al., 2007). Furthermore, multisystemic therapy (MST) provides an example of a less regimented adaptive structure, where case plans are continually updated based on a systematic review of an individual’s progress on treatment goals over time (Henggeler, Schoenwald, Borduin, Rowland, & Cunningham, 2009). However, none of these tools individualizes treatment assignment based on the promotion of well-being during reentry from prison, thus the RWAT addresses an important gap in existing practices. RWAT Treatment Targets and Assessment Based on the adaptive intervention framework, at the foundation of RWAT are treatment targets called the Five Core Facilitators of Reentry Well-Being (hereinafter referred to as “core facilitators”) that are evidence-driven proximal outcomes that have shown to increase well-being and, as a secondary effect, reduce recidivism (Pettus-Davis, Veeh, & Renn, 2016). The core facilitators are healthy thinking patterns, positive coping strategies, positive interpersonal relationships, positive social activities, and occupational balance. For each core facilitator, RWAT provides valid and reliable assessments that allow a practitioner to track an individual’s progress over time. Decision Process and Implementation RWAT does not propose a set of explicit decision rules. Rather, like MST, decision making within RWAT is guided by fidelity to a defined set of treatment principles, and these principles provide an organizing structure, like a code of ethics, to guide treatment decisions. The core facilitators serve as the structuring treatment principles (Pettus-Davis et al., 2016) by orientating a practitioner and client to focus treatment goals on the improvement of well-being. Decision making about treatment assignment within RWAT integrates both assessment data and practitioner judgment so as not to constrain the practitioner from using the range of skills necessary to be effective within a complex social intervention like a prisoner reentry program. Administration of RWAT assessments to determine progress on treatment targets is based on important programmatic milestones and transition points. The schedule of assessments needs to ensure that enough data are collected to establish a trend of progress in treatment, while also not occurring so frequently to create testing bias by participants memorizing or becoming bored with the assessment process. Following each assessment time point, participant scores are then tracked on a line graph to identify trends over time. Practitioners are given context to understand assessment scores based on means reported in previous peer-reviewed studies for both high- and low-functioning samples. This range of mean scores provides the practitioner with anchor points to understand a participant’s score trends over time. However, there is no a priori benchmark that is expected; instead, the goal is to see consistent progress while remaining cognizant that the therapeutic process will likely include digressions. As detailed in Figure 1, once the practitioner completes the assessment battery and reviews and contextualizes each set of trend graphs, this quantitative information is integrated with clinical expertise to decide whether services need to be stepped up, stepped down, or maintained. Particularly important is to always ensure that a participant is being programmed relative to his or her need for services. For instance, if a participant is demonstrating success in the community, the best treatment decision may be to step down all programming to allow the individual to conduct daily activities free from services that may be of minimal benefit. In contrast, a participant who is showing deterioration may need programming to be stepped up to more intensive one-on-one sessions with the practitioner or referral to an upcoming cognitive-thinking intervention that had previously seemed unnecessary. Maintaining Fidelity to RWAT A fidelity monitoring tool is included in RWAT to ensure consistency in treatment assignment across practitioners. Marlowe et al. (2014) claimed that there is concern for consistency of treatment assignment when it is largely driven by practitioner judgment. However, the solution to this concern is not to remove practitioner judgment from the decision making as the drug court program developed by Marlowe et al. does. Instead, rigorous assessment of fidelity to ensure proper implementation of RWAT strikes an appropriate balance between invariant decision rules and the art required of a practitioner to implement a complex intervention. Conclusion Current practice tools designed to individually assign services for prisoner reentry programs do not allow for regular treatment adjustments and thus are not sensitive to the multifaceted needs of clients. Thus, we developed a tool for individualized treatment assignment that allows services to change to match participants’ needs and progress. RWAT is a “living document” in that it is routinely administered, and the type and amount of service a participant is enrolled in can be adjusted accordingly. An important next step is for researchers to evaluate the feasibility, acceptability, utility, and effectiveness of RWAT for both practitioners and clients. References Andrews, D. A., & Bonta, J. ( 2010). The psychology of criminal conduct  ( 5th ed.). New Providence, NJ: Matthew Bender & Company/LexisNexis. Brooks Holliday, S., Heilbrun, K., & Fretz, R. ( 2012). Examining improvements in criminogenic needs: The risk reduction potential of a structured re-entry program. Behavioral Sciences & the Law,  30, 431– 447. doi:10.1002/bsl.2016 Google Scholar CrossRef Search ADS   Brooner, R. K., Kidorf, M. S., King, V. L., Stoller, K. B., Neufeld, K. J., & Kolodner, K. ( 2007). Comparing adaptive stepped care and monetary-based voucher interventions for opioid dependence. Drug and Alcohol Dependence,  88( Suppl. 2), S14– S23. doi:10.1016/j.drugalcdep.2006.12.006 Google Scholar CrossRef Search ADS   Carson, E. A., & Anderson, E. ( 2016). Prisoners in 2015 . Washington, DC: Bureau of Justice Statistics. Collins, L. M., Murphy, S. A., & Bierman, K. L. ( 2004). A conceptual framework for adaptive preventive interventions. Prevention Science,  5, 185– 196. doi:10.1023/B:PREV.0000037641.26017.00 Google Scholar CrossRef Search ADS   Duwe, G., & Rocque, M. ( 2016). A jack of all trades but a master of none? Evaluating the performance of the Level of Service Inventory–Revised (LSI-R) in the assessment of risk and need. Corrections,  1, 81– 106. doi:10.1080/23774657.2015.1111743 Google Scholar CrossRef Search ADS   Henggeler, S. W., Schoenwald, S. K., Borduin, C. M., Rowland, M. D., & Cunningham, P. B. ( 2009). Multisystemic therapy for antisocial behavior in children and adolescents  ( 2nd ed.). New York: Guilford Press. Jonson, C. L., & Cullen, F. T. ( 2015). Prisoner reentry programs. Crime & Justice,  44, 517– 557. doi:10.1086/681554 Google Scholar CrossRef Search ADS   Marlowe, D. B. ( 2011). Evidence-based policies and practices for drug-involved offenders. Prison Journal,  91( Suppl.), 27S– 47S. doi:10.1177/0032885511415223 Google Scholar CrossRef Search ADS   Marlowe, D. B., Festinger, D. S., Dugosh, K. L., Benasutti, K. M., Fox, G., & Harron, A. ( 2014). An experimental trial of adaptive programming in drug court: Outcomes at 6, 12 and 18 months. Journal of Experimental Criminology,  10, 129– 149. doi:10.1007/s11292-013-9196-x Google Scholar CrossRef Search ADS   Pettus-Davis, C., Veeh, C. A., & Renn, T. ( 2016). The five core facilitators of well-being development model: A new framework for prisoner reentry practice (Working Paper No. AJI072216). St. Louis: Washington University, Institute for Advancing Justice Research and Innovation. Ward, T. ( 2015). Detection of dynamic risk factors and correctional practice. Criminology & Public Policy,  14, 105– 111. doi:10.1111/1745-9133.12115 Google Scholar CrossRef Search ADS   © 2017 National Association of Social Workers http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Social Work Oxford University Press

Promoting Reentry Well-Being: A Novel Assessment Tool for Individualized Service Assignment in Prisoner Reentry Programs

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Oxford University Press
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© 2017 National Association of Social Workers
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0037-8046
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1545-6846
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10.1093/sw/swx050
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Abstract

During the 21st century, the United States has experienced a rapid buildup of prisoner reentry programs to assist the 640,000 individuals released from prison each year (Carson & Anderson, 2016). A majority of these former prisoners have co-occurring needs on their return to the community (that is, employment, substance abuse treatment, social support, and so on) (Jonson & Cullen, 2015). Therefore, a constant challenge for prisoner reentry programs is how to individualize treatment assignment to target multiple areas of need. Although a one-size-fits-all approach (that is, despite need, people get the same services) is the simplest to implement, it can lead to wasted resources and iatrogenic effects (Marlowe, 2011). In this Practice Update, we describe a new practice tool informed by the adaptive intervention framework developed by Collins, Murphy, and Bierman (2004) to assist with individualized treatment assignment within prisoner reentry programs. The adaptive intervention framework consists of treatment targets that have a substantive influence on the participant’s trajectory toward an ultimate distal outcome (that is, reincarceration). Once the treatment targets are set, the next step is to identify psychometric assessment tools that have validity and reliability to ensure usefulness in clinical decision making. Then, decision rules are specified to guide how different scores on each treatment target will inform assignment into different levels of services (Collins et al., 2004). Prisoner reentry programs tasked with addressing the complex needs of former prisoners would benefit from these principles of an adaptive intervention. Therefore, we present the Reentry Well-Being Assessment Tool (RWAT) (see Figure 1), to guide treatment assignment within prisoner reentry programs. Informed by the assessment of treatment targets empirically associated with improved well-being and reduced crime, an individual’s programming type or intensity can be decreased, increased, or maintained to match his or her progress. Before describing the tool further, we provide a brief review of existing treatment assignment practices used in nonprisoner and prisoner reentry contexts that guided our thinking during the development of RWAT. Figure 1: View largeDownload slide Reentry Well-Being Assessment Tool Figure 1: View largeDownload slide Reentry Well-Being Assessment Tool Current Individualized Treatment Assignment Practices Initial efforts to individualize reentry services are based on the Level of Service Inventory-Revised (LSI-R), an actuarial risk assessment tool that assesses risk factors for crime (Andrews & Bonta, 2010). Despite its application in reentry programs, the LSI-R does not specifically assess treatment needs. Research on the LSI-R to guide treatment planning has found individuals’ overall risk level to decrease over time (Brooks Holliday, Heilbrun, & Fretz, 2012). However, a study of 26,000 prisoners in Minnesota found the LSI-R to be “mediocre” at assessing treatment needs (Duwe & Rocque, 2016). Ward (2015) has also criticized the LSI-R as an ineffective tool to guide treatment planning beyond general service intensity recommendations (that is, intensive service for high risk and little to no services for low risk). As an alternative to using the LSI-R, Marlowe and colleagues (2014) developed an adaptive treatment design for a drug court program. Specific decision rules were set to determine when to step up services—for example, when counseling sessions were missed or when the client submitted a positive urinalysis for substance use. Similar designs have been used with non-criminal-justice-involved populations. Motivated Stepped Care is an adaptive stepped-care intervention for opioid-dependent individuals, where services are either stepped up or stepped down based on session attendance and urinalysis (Brooner et al., 2007). Furthermore, multisystemic therapy (MST) provides an example of a less regimented adaptive structure, where case plans are continually updated based on a systematic review of an individual’s progress on treatment goals over time (Henggeler, Schoenwald, Borduin, Rowland, & Cunningham, 2009). However, none of these tools individualizes treatment assignment based on the promotion of well-being during reentry from prison, thus the RWAT addresses an important gap in existing practices. RWAT Treatment Targets and Assessment Based on the adaptive intervention framework, at the foundation of RWAT are treatment targets called the Five Core Facilitators of Reentry Well-Being (hereinafter referred to as “core facilitators”) that are evidence-driven proximal outcomes that have shown to increase well-being and, as a secondary effect, reduce recidivism (Pettus-Davis, Veeh, & Renn, 2016). The core facilitators are healthy thinking patterns, positive coping strategies, positive interpersonal relationships, positive social activities, and occupational balance. For each core facilitator, RWAT provides valid and reliable assessments that allow a practitioner to track an individual’s progress over time. Decision Process and Implementation RWAT does not propose a set of explicit decision rules. Rather, like MST, decision making within RWAT is guided by fidelity to a defined set of treatment principles, and these principles provide an organizing structure, like a code of ethics, to guide treatment decisions. The core facilitators serve as the structuring treatment principles (Pettus-Davis et al., 2016) by orientating a practitioner and client to focus treatment goals on the improvement of well-being. Decision making about treatment assignment within RWAT integrates both assessment data and practitioner judgment so as not to constrain the practitioner from using the range of skills necessary to be effective within a complex social intervention like a prisoner reentry program. Administration of RWAT assessments to determine progress on treatment targets is based on important programmatic milestones and transition points. The schedule of assessments needs to ensure that enough data are collected to establish a trend of progress in treatment, while also not occurring so frequently to create testing bias by participants memorizing or becoming bored with the assessment process. Following each assessment time point, participant scores are then tracked on a line graph to identify trends over time. Practitioners are given context to understand assessment scores based on means reported in previous peer-reviewed studies for both high- and low-functioning samples. This range of mean scores provides the practitioner with anchor points to understand a participant’s score trends over time. However, there is no a priori benchmark that is expected; instead, the goal is to see consistent progress while remaining cognizant that the therapeutic process will likely include digressions. As detailed in Figure 1, once the practitioner completes the assessment battery and reviews and contextualizes each set of trend graphs, this quantitative information is integrated with clinical expertise to decide whether services need to be stepped up, stepped down, or maintained. Particularly important is to always ensure that a participant is being programmed relative to his or her need for services. For instance, if a participant is demonstrating success in the community, the best treatment decision may be to step down all programming to allow the individual to conduct daily activities free from services that may be of minimal benefit. In contrast, a participant who is showing deterioration may need programming to be stepped up to more intensive one-on-one sessions with the practitioner or referral to an upcoming cognitive-thinking intervention that had previously seemed unnecessary. Maintaining Fidelity to RWAT A fidelity monitoring tool is included in RWAT to ensure consistency in treatment assignment across practitioners. Marlowe et al. (2014) claimed that there is concern for consistency of treatment assignment when it is largely driven by practitioner judgment. However, the solution to this concern is not to remove practitioner judgment from the decision making as the drug court program developed by Marlowe et al. does. Instead, rigorous assessment of fidelity to ensure proper implementation of RWAT strikes an appropriate balance between invariant decision rules and the art required of a practitioner to implement a complex intervention. Conclusion Current practice tools designed to individually assign services for prisoner reentry programs do not allow for regular treatment adjustments and thus are not sensitive to the multifaceted needs of clients. Thus, we developed a tool for individualized treatment assignment that allows services to change to match participants’ needs and progress. RWAT is a “living document” in that it is routinely administered, and the type and amount of service a participant is enrolled in can be adjusted accordingly. An important next step is for researchers to evaluate the feasibility, acceptability, utility, and effectiveness of RWAT for both practitioners and clients. References Andrews, D. A., & Bonta, J. ( 2010). The psychology of criminal conduct  ( 5th ed.). New Providence, NJ: Matthew Bender & Company/LexisNexis. Brooks Holliday, S., Heilbrun, K., & Fretz, R. ( 2012). Examining improvements in criminogenic needs: The risk reduction potential of a structured re-entry program. Behavioral Sciences & the Law,  30, 431– 447. doi:10.1002/bsl.2016 Google Scholar CrossRef Search ADS   Brooner, R. K., Kidorf, M. S., King, V. L., Stoller, K. B., Neufeld, K. J., & Kolodner, K. ( 2007). Comparing adaptive stepped care and monetary-based voucher interventions for opioid dependence. Drug and Alcohol Dependence,  88( Suppl. 2), S14– S23. doi:10.1016/j.drugalcdep.2006.12.006 Google Scholar CrossRef Search ADS   Carson, E. A., & Anderson, E. ( 2016). Prisoners in 2015 . Washington, DC: Bureau of Justice Statistics. Collins, L. M., Murphy, S. A., & Bierman, K. L. ( 2004). A conceptual framework for adaptive preventive interventions. Prevention Science,  5, 185– 196. doi:10.1023/B:PREV.0000037641.26017.00 Google Scholar CrossRef Search ADS   Duwe, G., & Rocque, M. ( 2016). A jack of all trades but a master of none? Evaluating the performance of the Level of Service Inventory–Revised (LSI-R) in the assessment of risk and need. Corrections,  1, 81– 106. doi:10.1080/23774657.2015.1111743 Google Scholar CrossRef Search ADS   Henggeler, S. W., Schoenwald, S. K., Borduin, C. M., Rowland, M. D., & Cunningham, P. B. ( 2009). Multisystemic therapy for antisocial behavior in children and adolescents  ( 2nd ed.). New York: Guilford Press. Jonson, C. L., & Cullen, F. T. ( 2015). Prisoner reentry programs. Crime & Justice,  44, 517– 557. doi:10.1086/681554 Google Scholar CrossRef Search ADS   Marlowe, D. B. ( 2011). Evidence-based policies and practices for drug-involved offenders. Prison Journal,  91( Suppl.), 27S– 47S. doi:10.1177/0032885511415223 Google Scholar CrossRef Search ADS   Marlowe, D. B., Festinger, D. S., Dugosh, K. L., Benasutti, K. M., Fox, G., & Harron, A. ( 2014). An experimental trial of adaptive programming in drug court: Outcomes at 6, 12 and 18 months. Journal of Experimental Criminology,  10, 129– 149. doi:10.1007/s11292-013-9196-x Google Scholar CrossRef Search ADS   Pettus-Davis, C., Veeh, C. A., & Renn, T. ( 2016). The five core facilitators of well-being development model: A new framework for prisoner reentry practice (Working Paper No. AJI072216). St. Louis: Washington University, Institute for Advancing Justice Research and Innovation. Ward, T. ( 2015). Detection of dynamic risk factors and correctional practice. Criminology & Public Policy,  14, 105– 111. doi:10.1111/1745-9133.12115 Google Scholar CrossRef Search ADS   © 2017 National Association of Social Workers

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Social WorkOxford University Press

Published: Jan 1, 2018

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