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32 - Probation Decision-Making

from Part IV - Postconviction Phase Decisions

Published online by Cambridge University Press:  22 February 2024

By
Ralph C. Serin ,
Guy Bourgon ,
Nick Chadwick  and
Christopher T. Lowenkamp
Edited by
Monica K. Miller ,
Logan A. Yelderman ,
Matthew T. Huss  and
Jason A. Cantone
Monica K. Miller
Affiliation:
University of Nevada, Reno
Logan A. Yelderman
Affiliation:
Prairie View A & M University, Texas
Matthew T. Huss
Affiliation:
Creighton University, Omaha
Jason A. Cantone
Affiliation:
George Mason University, Virginia
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Summary

Despite increasing evidence regarding the efficacy of risk assessment and intervention in community supervision, there continues to be relatively weak adherence to such evidence in its application to decision-making. Regarding assessment, such a lack of fidelity purportedly leads to higher rates of overrides, degraded accuracy, and inefficiency in resource allocation. Regarding intervention, failure to implement evidence-based practice and recognize the role of probation officers as agents of change further diminishes supervision effectiveness. With probation populations at an all-time high and a burgeoning violation rate, this chapter summarizes the emerging probation research to situate the need for clarity of purpose and improved decision-making to maintain public confidence in probation. The chapter presents a decision framework utilizing empirically informed domains as a logic model to ensure probation officer decisions are fair, transparent, and defensible. This framework incorporates both static and dynamic information to ensure decisions are accurate and contextual.

Keywords

probationcommunity supervisioncorrectional decision-makingsanctions and incentives
Type
Chapter
Information
The Cambridge Handbook of Psychology and Legal Decision-Making , pp. 496 - 509
Publisher: Cambridge University Press
Print publication year: 2024

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References

Antenangeli, L. & Durose, M. R. (2021). Recidivism of prisoners released in 24 states in 2008: A 10-year follow-up period (2008–2018). Bureau of Justice Statistics. https://bjs.ojp.gov/.Google Scholar
Berecochea, J. E., Himelson, A. N., & Miller, D. E. (1972). The risk of failure during the early parole period: A methodological note. Journal of Criminal Law and Criminology, 63(1), 93–96. https://doi.org/10.2307/1142275.Google Scholar
Bonta, J., Rugge, T., Scott, T. L., Bourgon, G., & Yessine, A. K. (2008). Exploring the black box of community supervision. Journal of Offender Rehabilitation, 47(3), 248–270. https://doi.org/10.1080/10509670802134085.Google Scholar
Bourgon, G., Gutierrez, L., & Ashton, J. (2011). The evolution of community supervision practice: The transformation from case manager to change agent. Irish Probation Journal, 8, 28–48.Google Scholar
Brown, S. L., St. Amand, M. D., & Zamble, E. (2009). The dynamic prediction of criminal recidivism: A three‐wave prospective study. Law and Human Behavior, 33(1), 25–45. https://doi.org/10.1007/s10979-008-9139-7.Google Scholar
Brown, S. L. , Robinson, D. , Wanamaker, K. A. , & Wagstaff, M. (2020). Strengths matter: Evidence from five separate cohorts of justice-involved youth and adults across North America. Criminal Justice and Behavior, 47(11), 1428–1447. https://doi.org/10.1177/0093854820931549.Google Scholar
Center for Effective Public Policy. (2017). The evidence-based decision making initiative: An overview for probation. https://cepp.com/wp-content/uploads/2021/04/The-Evidence-Based-Decision-Making-Initiative-An-Overview-for-Probation-2017.pdf.Google Scholar
Council of State Governments. (2019). Confined and costly: How supervision violations are filling prisons and burdening budgets. Council of State Governments. https://csgjusticecenter.org/wp-content/uploads/2020/01/confined-and-costly.pdf.Google Scholar
Desmarais, S. L., Johnson, K. L., & Singh, J. P. (2016). Performance of recidivism risk assessment instruments in US correctional settings. Psychological Services, 13(3), 206–222. https://doi.org/10.1037/ser0000075.Google Scholar
Dowden, C., & Andrews, D. A. (2004). The importance of staff practice in delivering effective correctional treatment: A meta-analytic review of core correctional practices. International Journal of Offender Therapy and Comparative Criminology, 48(2), 203–214. https://doi.org/10.1177/0306624X03257765.Google Scholar
Cohen, T. H., Lowenkamp, C. T., Bechtel, K., & Flores, A. W. (2020). Risk assessment overrides: Shuffling the risk deck without any improvements in prediction. Criminal Justice and Behavior, 47(12), 1609–1629. https://doi.org/10.1177/0093854820953449.Google Scholar
Cohen, T. H., Lowenkamp, C. T., & VanBenschoten, S. W. (2016). Does change in risk matter? Examining whether changes in offender risk characteristics influence recidivism outcomes. Criminology & Public Policy, 15(2), 263–296. http://dx.doi.org/10.2139/ssrn.2621267.Google Scholar
DeLisi, M., Drury, A., & Elbert, M. (2021). Who are the compliant correctional clients? New evidence on protective factors among federal supervised releases. International Journal of Offender Therapy and Comparative Criminology, 65(13–14), 1536–1553. https://doi.org/10.1177/0306624X21992681.Google Scholar
Douglas, K. S., & Skeem, J. L. (2005). Violence risk assessment: Getting specific about being dynamic. Psychology, Public Policy, and Law, 11(3), 347–383. https://doi.org/10.1037/1076-8971.11.3.347.Google Scholar
Grattet, R., Petersilia, J., Lin, J., & Beckman, M. (2009). Parole violations and revocations in California: Analysis and suggestions for action. Federal Probation, 73(1), 2–11.Google Scholar
Gray, K. M., Fields, M., & Royo Maxwell, S. (2001). Examining probation violations: Who, what, and when. Crime & Delinquency, 47(4), 537–557. https://doi.org/10.1177/0011128701047004003.Google Scholar
Hanson, R. K., & Harris, A. J. (2000). Where should we intervene? Dynamic predictors of sexual offense recidivism. Criminal Justice and Behavior, 27(1), 6–35. https://doi.org/10.1177/0093854800027001002.CrossRefGoogle Scholar
Hanson, R. K., Harris, A. J. R., Scott, T. L., & Helmus, L. (2007). Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project (Corrections Research User Report No. 2007–05). Ottawa, ON: Public Safety Canada. www.publicsafety.gc.ca/cnt/rsrcs/pblctns/ssssng-rsk-sxl-ffndrs/index-en.aspx.Google Scholar
Johnson, J. L., Treviño, P., Lowenkamp, C. T., & Serin, R. C. (2016). Enhancing community supervision through the application of dynamic risk assessment. Federal Probation, 80(2), 16–20.Google Scholar
LaVigne, N., Bieler, S., Cramer, L., et al. (2014). Justice Reinvestment Initiative State Assessment Report. www.urban.org/.Google Scholar
Lawrence, A. (2008). State sentencing and corrections legislation 2007 action, 2008 outlook. National Conference of State Legislatures. www.ncsl.org/.Google Scholar
LeBel, T.P., Burnett, R., Maruna, S., & Bushway, S. (2008). The “chicken and egg” of subjective and social factors in desistance from crime. European Journal of Criminology, 5(2), 131–159. https://doi.org/10.1177/1477370807087640.Google Scholar
Lloyd, C. D., Hanson, R. K., Richards, D. K., & Serin, R. C. (2020). Reassessment improves prediction of criminal recidivism: A prospective study of 3,421 individuals in New Zealand. Psychological Assessment, 32(6), 568–581. https://doi.org/10.1037/pas0000813.Google Scholar
Lloyd, C. D., & Serin, R. C. (2012). Agency and outcome expectancies for crime desistance: Measuring offenders’ personal beliefs about change. Psychology, Crime, and Law, 18(6), 543–565. https://doi.org/10.1080/1068316X.2010.511221.Google Scholar
Lowenkamp, C. T., Holsinger, A. M., & Cohen, T. H. (2015). PCRA revisited: Testing the validity of the Federal Post Conviction Risk Assessment (PCRA). Psychological Services, 12(2), 149–157. https://doi.org/10.1037/ser0000024.Google Scholar
Lowenkamp, C. T., Johnson, J. L., Holsinger, A. M., VanBenschoten, S. V., & Robinson, C. R. (2013). The federal Post Conviction Risk Assessment (PCRA): A construction and validation study. Psychological Services, 10(1), 87–96. https://doi.org/10.1037/a0030343.Google Scholar
McMurran, M. (2011). Motivational interviewing with offenders: A systematic review. Legal and Criminological Psychology, 14(1), 83–100. https://doi.org/10.1348/135532508X278326.Google Scholar
Miller, J., & Maloney, M. (2013). Practitioner compliance with risk/needs assessment tools: a theoretical and empirical assessment. Criminal Justice and Behavior, 40(7), 716–736. https://doi.org/10.1177/0093854812468883.Google Scholar
Mowen, T. J., Wodahl, E., Brent, J. J., & Garland, B. (2018). The role of sanctions and incentives in promoting successful reentry: Evidence from the SVORI data. Criminal Justice and Behavior, 45(8), 1288–1307. https://doi.org/10.1177/0093854818770695.Google Scholar
Oudekerk, B., & Kaeble, D. (2021). Probation and Parole in the United States, 2019. Bureau of Justice Statistics. https://bjs.ojp.gov/.Google Scholar
Paternoster, R., & Bushway, S. (2009). Desistance and the feared self: Toward an identity theory of criminal desistance. Journal of Criminal Law and Criminology, 99(4), 1103–1156.Google Scholar
Pettus-Davis, C., & Kennedy, S. (2020). Early lessons from the multistate study of the 5-key model for reentry. Perspectives: The Journal of the American Probation and Parole Association, 44, 19–31.Google Scholar
PEW Charitable Trusts. (2008). Policy framework can strengthen community corrections. www.pewtrusts.org/-/media/legacy/uploadedfiles/pcs_assets/2008/policy20frameworkpdf.pdf.Google Scholar
PEW Charitable Trusts. (2020). Policy reforms can strengthen community supervision: A framework to improve probation and parole. www.pewtrusts.org/-/media/assets/2020/04/policyreform_communitysupervision_report_final.pdf.Google Scholar
Robina Institute of Criminal Law and Criminal Justice (2020). Use of structured sanctions and incentives in probation and parole supervision. https://robinainstitute.umn.edu/sites/robinainstitute.umn.edu/files/2022-02/sanctions_and_incentives.pdf.Google Scholar
Rydberg, J., & Grommon, E. (2016). A multimethod examination of the dynamics of recidivism during reentry. Corrections: Policy, Practice, and Research, 1(1), 40–60. https://doi.org/10.1080/23774657.2016.1105660.CrossRefGoogle Scholar
Serin, R. C. (2007). The Dynamic Risk Assessment for Offender Reentry (DRAOR) [unpublished user manual].Google Scholar
Serin, R. C., Chadwick, N., & Lloyd, C. D. (2016). Dynamic risk and protective factors. Psychology, Crime & Law, 22(1–2), 151–170. https://doi.org/10.1080/1068316X.2015.1112013.CrossRefGoogle Scholar
Serin, R. C., Chadwick, N., & Prell, L. (manuscript submitted). Assessing dynamic risk and protective factors among probationers and parolees in Iowa: The utility of the dynamic risk assessment for offender re-entry. Department of Psychology, Carleton University.Google Scholar
Serin, R. C., Lloyd, C. D., & Hanby, L. J. (2010). Enhancing offender re-entry: An integrated model for enhancing offender re-entry. European Journal of Probation, 2(2), 53–75.CrossRefGoogle Scholar
Serin, R. C., Lloyd, C. D., Helmus, L., Derkzen, D., & Luong, D. (2013). Does intra-individual change predict offender recidivism? Searching for the holy grail in a review of offender change. Aggression and Violent Behavior, 18(1), 32–53. https://doi.org/10.1016/j.avb.2012.09.002.Google Scholar
Skeem, J. L., Eno Louden, J., Camp, J., & Polaschek, D. (2007). Assessing relationship quality in mandated community treatment: Blending care with control. Psychological Assessment, 19(4), 397–410. https://doi.org/10.1037/1040-3590.19.4.397.Google Scholar
Skeem, J. L., & Lowenkamp, C. T. (2016). Risk, race, and recidivism: Predictive bias and disparate impact. Criminology, 54(4), 680–712. https://doi.org/10.1111/1745-9125.12123.CrossRefGoogle Scholar
Skeem, J. L., & Lowenkamp, C. T. (2020). Using algorithms to address trade-offs inherent in predicting recidivism. Behavioral Sciences & the Law, 38(3), 259–278. https://doi.org/10.1002/bsl.2465.CrossRefGoogle ScholarPubMed
Skeem, J., Monahan, J., & Lowenkamp, C. (2016). Gender, risk assessment, and sanctioning: The cost of treating women like men. Law and Human Behavior, 40(5), 580–593. https://doi.org/10.1037/lhb0000206.Google Scholar
Stone, A. G., Lloyd, C. D., & Serin, R. C. (2021). Dynamic risk factors reassessed regularly after release from incarceration predict imminent violent recidivism. Law and Human Behavior, 45(6), 512–523. https://doi.org/10.1037/lhb0000463.Google Scholar
Stone, A. G., Spivak, B. L., Lloyd, C. D., Papalia, N. L., & Serin, R. C. (2022). Clients’ current presentation yields best prediction of criminal recidivism: Jointly modelling repeated assessments of risk and recidivism outcomes in a community sample of paroled New Zealanders. Journal of Consulting and Clinical Psychology, 90(11), 872–883. https://doi.org/10.1037/ccp0000766.Google Scholar
Trotter, C. (1996). The impact of different supervision practices in community corrections: Cause for optimism. Australian and New Zealand Journal of Criminology, 29(1), 29–46. https://doi.org/10.1177/000486589602900103.Google Scholar
Ullrich, S., & Coid, J. (2011). Protective factors for violence among released prisoners‐effects over time and interactions with static risk. Journal of Consulting and Clinical Psychology, 79(3), 381–390. https://doi.org/10.1037/a0023613.Google Scholar
Viglione, J., Rudes, D. S., & Taxman, F. S. (2017). Probation officer use of client-centered communication strategies in adult probation setting. Journal of Offender Rehabilitation, 56(1), 38–60. https://doi.org/10.1080/10509674.2016.1257534.Google Scholar
Viljoen, J. L., Cochrane, D. M., & Jonnson, M. R. (2018). Do risk assessment tools help manage and reduce risk of violence and reoffending? A systematic review. Law and Human Behavior, 42(3), 181–214. https://doi.org/10.1037/lhb0000280.Google Scholar
Viljoen, J. L., & Vincent, G. M. (2020). Risk assessments for violence and reoffending: Implementation and impact on risk management. Clinical Psychology: Science and Practice. Advance online publication. https://doi.org/10.1111/cpsp.12378.Google Scholar

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