The overlap between criminal justice system involvement and drug use is well-documented, and criminal justice agencies have been particularly overwhelmed by the recent opioid epidemic. Treating opioid (and other substance) addiction as a means to reduce risk for future criminality and improve public safety is inherently a responsibility for the criminal justice system. In turn, the criminal justice system has a responsibility to manage and treat addiction among the individuals under its purview. Policy recommendations place emphasis on the use of medication-assisted treatments (MAT) as a front-line defense among correctional populations, because its efficacy and effectiveness has been well-established in other contexts. Despite this, criminal justice agencies have been reluctant or slow to do so. The current review will provide criminal justice and substance use treatment decision-makers with information regarding the efficacy and effectiveness of opioid-specific MAT on offending and overdose outcomes. Specifically, the authors will address the following research questions: Do opioid-specific MATs reduce the frequency or likelihood of criminal justice outcomes, as defined by official or self-reported indices of criminal reconviction or rearrest, revocation of community supervision, mandated treatment failure, and specialized court docket failure? Do opioid-specific MATs reduce the frequency of opioid overdose among individuals with current or prior self-reported or official record of criminal justice system involvement? Studies were required to use strong quasi-experimental or randomized experimental designs. All studies used individual level unit of analysis and examined adults and adolescents who are male, female, or nonbinary and racially/ethnically diverse, with current opioid use and who have current or prior criminal justice involvement. Studies had to prospectively test the effects of heroin and methadone maintenance, buprenorphine, or naltrexone on criminal conviction, arrest, revocation of community supervision, technical probation or parole violation, mandated treatment failure, and specialized court docket failure. Overdose outcomes were also examined for samples in criminal justice settings such as jails, prisons, probation, and parole. This review builds upon a prior review conducted by Egli et al. (2009) and examined studies meeting the inclusion criteria above published between 1960 and October 31, 2020. The following platforms and databases (in parentheticals) were used: EBSCOhost (Criminal Justice Abstracts, SocINDEX with Full Text, Legal Collection, Wilson Omnifile, PsycINFO, Social Work Abstracts, and Women's Studies International [includes grey literature]); ProQuest (Criminal Justice Database, PAIS [includes grey literature], Dissertations and Theses Global [includes grey literature]); Gale (Expanded Academic ASAP, Opposing Viewpoints Resource Center); FirstSearch (GPO Monthly Catalog, PapersFirst [includes grey literature]); ISI Web of Knowledge (Web of Science Core Collection); Office of Justice Programs (National Criminal Justice Reference Service); Summon; and Nexis Uni. The following open access platforms and databases will also be consulted: Elsevier (Scopus [includes grey literature]); Science.gov; ClinicalTrials.gov; WHO International Clinical Trials Registry Platform (ICTRP) portal; and Google Scholar. Search terms were harvested according to their demonstrated success in drawing out relevant and complete results for studies regarding the effectiveness of opioid-specific medication-assisted therapies (MATs). From this process 5 core search strings were created, each one with the same general base terms, but unique outcome measure(s). For binary offending outcomes (e.g., arrest, conviction, incarceration, specialty court failure, mandated treatment failure, or community supervision failure) and overdose outcomes, odds ratios were computed, and for continuous or quasi-continuous outcomes (e.g., total number of arrests), a standardized mean difference type effect size was computed and then transformed into an odds ratio. We used the χ 2 test that goes with the forest plot and computed the I 2 statistic to assess heterogeneity. Risk of bias was assessed with (1) the revised Cochrane risk-of-bias tool for randomized trials; and (2) the risk of bias in non-randomized studies of interventions assessment tool.
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