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Risk factors for recidivism in individuals receiving community sentences: a systematic review and meta-analysis

Published online by Cambridge University Press:  20 June 2019

Denis Yukhnenko Open the ORCID record for Denis Yukhnenko [Opens in a new window] ,
Nigel Blackwood  and
Seena Fazel Open the ORCID record for Seena Fazel [Opens in a new window]
Denis Yukhnenko
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, United Kingdom
Nigel Blackwood
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
Seena Fazel*
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, United Kingdom
*
* Address correspondence to: Seena Fazel, Department of Psychiatry, University of Oxford, Warneford Lane, Oxford OX3 7JX, United Kingdom. (Email: [email protected])
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Abstract

Objective.

We aimed to systematically review risk factors for criminal recidivism in individuals given community sentences.

Methods.

We searched seven bibliographic databases and additionally conducted targeted searches for studies that investigated risk factors for any repeat offending in individuals who had received community (non-custodial) sentences. We included investigations that reported data on at least one risk factor and allowed calculations of odds ratios (ORs). If a similar risk factor was reported in three or more primary studies, they were grouped into domains, and pooled ORs were calculated.

Results.

We identified 15 studies from 5 countries, which reported data on 14 independent samples and 246,608 individuals. We found that several dynamic (modifiable) risk factors were associated with criminal recidivism in community-sentenced populations, including mental health needs (OR = 1.4, 95% confidence interval (CI): 1.2–1.6), substance misuse (OR = 2.3, 95% CI: 1.1–4.9), association with antisocial peers (OR = 2.2, 95% CI: 1.3–3.7), employment problems (OR = 1.8, 95% CI: 1.3–2.5), marital status (OR = 1.6, 95%: 1.4–1.8), and low income (OR = 2.0, 95% CI: 1.1–3.4). The strength of these associations was comparable to that of static (non-modifiable) risk factors, such as age, gender, and criminal history.

Conclusion.

Assessing dynamic (modifiable) risk factors should be considered in all individuals given community sentences. The further integration of mental health, substance misuse, and criminal justice services may reduce reoffending risk in community-sentenced populations.

Keywords

Recidivismrisk factorsreoffendingrearrestreconvictionprobationcommunity sentencessystematic reviewmeta-analysis
Type
Review
Information
CNS Spectrums , Volume 25 , Issue 2 , April 2020 , pp. 252 - 263
Copyright
© Cambridge University Press 2019

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References

References:

Pew Center on the States. State of Recidivism: The Revolving Door of America’s Prisons. Washington, DC: The Pew Charitable Trusts; 2011.Google Scholar
Statistics Denmark. Recidivism. 2018. https://www.dst.dk/en/Statistik/emner/levevilkaar/kriminalitet/tilbagefald-til-kriminalitet Accessed December 1, 2018.Google Scholar
Ministry of Justice. Proven reoffending statistics quarterly: January 2016 to March 2016. 2018. https://www.gov.uk/government/statistics/proven-reoffending-statistics-january-2016-to-march-2016. Accessed December 1, 2018.Google Scholar
Visher, CA, Winterfield, L, Coggeshall, MB. Ex-offender employment programs and recidivism: a meta-analysis. J Exp Criminol. 2005; 1(3): 295–316.10.1007/s11292-005-8127-xCrossRefGoogle Scholar
Landenberger, NA, Lipsey, MW. The positive effects of cognitive–behavioral programs for offenders: a meta-analysis of factors associated with effective treatment. J Exp Criminol. 2005; 1(4): 451–476.10.1007/s11292-005-3541-7CrossRefGoogle Scholar
Bonta, J, Andrews, DA. Risk-need-responsivity model for offender assessment and rehabilitation. 2007. http://www.courtinnovation.org/sites/default/files/documents/RNRModelForOffenderAssessmentAndRehabilitation.pdf. Accessed December 1, 2018.Google Scholar
Hanson, RK. Long-term recidivism studies show that desistance is the norm. Crim Justice Behav. 2018; 45(9): 1340–1346.10.1177/0093854818793382CrossRefGoogle Scholar
Clarke, MC, Peterson-Badali, M, Skilling, TA. The relationship between changes in dynamic risk factors and the predictive validity of risk assessments among youth offenders. Crim Justice Behav. 2017; 44(10): 1340–1355.10.1177/0093854817719915CrossRefGoogle Scholar
Central Statistics Office. Probation recidivism 2010 cohort. 2016. http://www.cso.ie/en/releasesandpublications/er/pror/probationrecidivism2010cohort/. Accessed December 1, 2018.Google Scholar
Swedish National Council for Crime Prevention. Recidivism. 2017. https://www.bra.se/bra-in-english/home/crime-and-statistics/crime-statistics/recidivism.html. Accessed December 1, 2018.Google Scholar
Lurigio, AJ, Cho, YI, Swartz, JA, et al. Standardized assessment of substance-related, other psychiatric, and comorbid disorders among probationers. Int J Offender Ther Comp Criminol. 2003; 47: 630–652.10.1177/0306624X03257710CrossRefGoogle ScholarPubMed
Olver, ME, Stockdale, KC, Wormith, JS. Thirty years of research on the Level of Service scales: a meta-analytic examination of predictive accuracy and sources of variability. Psychol Assess. 2014; 26(1): 156–176.10.1037/a0035080CrossRefGoogle ScholarPubMed
Gendreau, P, Little, T, Goggin, C. A meta-analysis of the predictors of adult offender recidivism: what works! Criminology. 1996; 34: 575–608.10.1111/j.1745-9125.1996.tb01220.xCrossRefGoogle Scholar
Hanson, RK, Morton-Bourgon, KE. The characteristics of persistent sexual offenders: a meta-analysis of recidivism studies. J Consult Clin Psychol. 2005; 73(6): 1154–1163.10.1037/0022-006X.73.6.1154CrossRefGoogle ScholarPubMed
Bonta, J, Blais, J, Wilson, HA. A theoretically informed meta-analysis of the risk for general and violent recidivism for mentally disordered offenders. Aggress Violent Behav. 2014; 19(3): 278–287.10.1016/j.avb.2014.04.014CrossRefGoogle Scholar
Shamseer, D, Moher, D, Clarke, M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement: elaboration and explanation. BMJ. 2014; 349: g7647.10.1136/bmj.g7647CrossRefGoogle Scholar
Rosenthal, R, DiMatteo, MR. Meta-analysis: recent developments in quantitative methods for literature review. Annu Rev Psychol. 2001; 52: 59–82.10.1146/annurev.psych.52.1.59CrossRefGoogle Scholar
Wells, GA, Shea, B, O’Connell, D, et al. Quality assessment scales for observational studies. 2004. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed December 1, 2018.Google Scholar
StataCorp. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC; 2017.Google Scholar
David Fisher. ADMETAN: Stata module to provide comprehensive meta-analysis. Statistical Software Components S458561, Boston College Department of Economics; 2018.Google Scholar
Adams, S, Bostwick, L, Campbell, R. Examining Illinois Probationer Characteristics and Outcomes. Chicago, IL: Illinois Criminal Justice Information Authority; 2011.Google Scholar
Caudy, MS, Tillyer, MS, Tillyer, R. Jail versus probation: a gender-specific test of differential effectiveness and moderators of sanction effects. Crim Justice Behav. 2018; 45(7): 949–968.10.1177/0093854818766375CrossRefGoogle Scholar
Department of Justice. Adult Reconviction in Northern Ireland 2005. Northern Ireland, Belfast: Statistics and Research Branch, Department of Justice; 2011.Google Scholar
Grann, M, Danesh, J, Fazel, S. The association between psychiatric diagnosis and violent re-offending in adult offenders in the community. BMC Psychiatry. 2008; 8: 92.10.1186/1471-244X-8-92CrossRefGoogle Scholar
Harris, P. The first-time adult-onset offender: findings from a community corrections cohort. Int J Offender Ther Comp Criminol. 2011; 55(6): 949–981.10.1177/0306624X10372110CrossRefGoogle ScholarPubMed
Huebner, BM, Cobbina, J. The effect of drug use, drug treatment participation, and treatment completion on probationer recidivism. J Drug Issues. 2007; 37(3): 619–641.10.1177/002204260703700307CrossRefGoogle Scholar
Humphrey, JA, Burford, G, Dye, MH. A longitudinal analysis of reparative probation and recidivism. Criminal Justice Studies. 2012; 25(2): 117–130.10.1080/1478601X.2012.699731CrossRefGoogle Scholar
Maliek, NA. An empirical assessment of the direct and indirect effects of mental health disorders on probation outcomes (thesis). The University of Texas at San Antonio, ProQuest Dissertations Publishing. 2017; 10617596.Google Scholar
Minor, KI, Wells, JB, Sims, C. Recidivism among federal probationers: predicting sentence violations. Fed Probat. 2003; 67(1): 31–33.Google Scholar
North Carolina Sentencing & Advisory Commission. Correctional program evaluation. Offenders placed on probation or released from prison in FY 2015. 2018. https://www.nccourts.gov/assets/documents/publications/recidivism_2018.pdf?4VQBsstuyzU5dH1Ap7SJQiMe0zTKYU1G. Accessed December 1, 2018.Google Scholar
Olson, DE, Lurigio, AJ. Predicting probation outcomes: factors associated with probation rearrest, revocations, and technical violations during supervision. Justice Res Policy. 2000; 2(1): 73–86.10.3818/JRP.2.1.2000.73CrossRefGoogle Scholar
Olson, DE, Alderden, M, Lurigio, AJ. Men are from Mars, women are from Venus: but what role does gender play in probationer recidivism? Justice Res Policy. 2003; 5(2): 33–54.10.3818/JRP.5.2.2003.33CrossRefGoogle Scholar
Peillard, AMM, Correa, NM, Chahuán, GW, Lacoa, JF. La Reincidencia en el Sistema Penitenciario Chileno. Santiago, Chile: Fundación Paz Ciudadana; 2012.Google Scholar
Sims, B, Jones, M. Predicting success or failure on probation: factors associated with felony probation outcomes. Crime Delinq. 1997; 43(3): 314–327.10.1177/0011128797043003005CrossRefGoogle Scholar
Wood, M, Cattel, J, Hales, G, et al. Re-offending by Offenders on Community Orders: Results from the Offender Management Community Cohort Study. England, London: Ministry of Justice Analytical Series; 2015.Google Scholar
Fazel, S, Chang, Z, Fanshawe, T, et al. Prediction of violent reoffending on release from prison: derivation and external validation of a scalable tool. Lancet Psychiatry. 2016; 3(6): 535–543.10.1016/S2215-0366(16)00103-6CrossRefGoogle ScholarPubMed
Stahler, GJ, Mennis, J, Belenko, S, et al. Predicting recidivism for released state prison offenders: examining the influence of individual and neighborhood characteristics and spatial contagion on the likelihood of reincarceration. Crim Justice Behav. 2013; 40(6): 690–711.10.1177/0093854812469609CrossRefGoogle ScholarPubMed
Ersche, KD, Turton, AJ, Chamberlain, SR, et al. Cognitive dysfunction and anxious-impulsive personality traits are endophenotypes for drug dependence. Am J Psychiatry. 2012; 169(9): 926–36.10.1176/appi.ajp.2012.11091421CrossRefGoogle ScholarPubMed
Arseneault, L, Moffit, TE, Caspi, A. Mental disorders and violence in a total birth cohort: results from the Dunedin study. Arch Gen Psychiatry. 2000; 57(10): 979–986.10.1001/archpsyc.57.10.979CrossRefGoogle Scholar
Sinha, R. Chronic stress, drug use, and vulnerability to addiction. Ann NY Acad Sci. 2008; 1141: 105–130.10.1196/annals.1441.030CrossRefGoogle ScholarPubMed
Hendricks, PS, Crawford, MS, Cropsey, KL, et al. The relationships of classic psychedelic use with criminal behavior in the United States adult population. J Psychopharmacol. 2018; 32(1): 37–48.10.1177/0269881117735685CrossRefGoogle ScholarPubMed
Chang, Z, Larsson, H, Lichtenstein, P, et al. Psychiatric disorders and violent reoffending: a national cohort study of convicted prisoners in Sweden. Lancet Psychiatry. 2015; 2(10): 891–900.10.1016/S2215-0366(15)00234-5CrossRefGoogle ScholarPubMed
Oram, S, Trevillion, K, Khalifeh, H, et al. Systematic review and meta-analysis of psychiatric disorder and the perpetration of partner violence. Epidemiol Psychiatr Sci. 2014; 23(4): 361–376.10.1017/S2045796013000450CrossRefGoogle ScholarPubMed
Fazel, S, Gulati, G, Linsell, L, et al. Schizophrenia and violence: systematic review and meta-analysis. PLoS Med. 2009; 6(8): e1000120.10.1371/journal.pmed.1000120CrossRefGoogle ScholarPubMed
Fitton, L, Yu, R, Fazel, S. Childhood maltreatment and violent outcomes: a systematic review and meta-analysis of prospective studies. Trauma Violence Abuse. 2018; epub ahead of print: 1524838018795269. doi: 10.1177/1524838018795269.Google ScholarPubMed
Fazel, S, Wolf, A, Yukhnenko, D. Recidivism reporting checklist. Open Sci Framework. 2019. doi: 10.17605/OSF.IO/QVTFB Google Scholar
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