Background The relationship between healthcare service accessibility in the community and incarceration is an important, yet not widely understood, phenomenon. Community behavioral health and the criminal legal systems are treated separately, which creates a competing demand to confront mass incarceration and expand available services. As a result, the relationship between behavioral health services, demographics and community factors, and incarceration rate has not been well addressed. Understanding potential drivers of incarceration, including access to community-based services, is necessary to reduce entry into the legal system and decrease recidivism. This study identifies county-level demographic, socioeconomic, healthcare services availability/accessibility, and criminal legal characteristics that predict per capita jail population across the U.S. More than 10 million individuals pass through U.S. jails each year, increasing the urgency of addressing this challenge. Methods The selection of variables for our model proceeded in stages. The study commenced by identifying potential descriptors and then using machine learning techniques to select non-collinear variables to predict county jail population per capita. Beta regression was then applied to nationally available data from all 3,141 U.S. counties to identify factors predicting county jail population size. Data sources include the Vera Institute’s incarceration database, Robert Wood Johnson Foundation’s County Health Rankings and Roadmaps, Uniform Crime Report, and the U.S. Census. Results Fewer per capita psychiatrists (z-score = -2.16; p = .031), lower percent of drug treatment paid by Medicaid (-3.66; p < .001), higher per capita healthcare costs (5.71; p < .001), higher number of physically unhealthy days in a month (8.6; p < .001), lower high school graduation rate (-4.05; p < .001), smaller county size (-2.66, p = .008; -2.71, p = .007; medium and large versus small counties, respectively), and more police officers per capita (8.74; p < .001) were associated with higher per capita jail population. Controlling for other factors, violent crime rate did not predict incarceration rate. Conclusions Counties with smaller populations, larger percentages of individuals that did not graduate high school, that have more health-related issues, and provide fewer community treatment services are more likely to have higher jail population per capita. Increasing access to services, including mental health providers, and improving the affordability of drug treatment and healthcare may help reduce incarceration rates.
With over 4 million adults under community supervision and an average of 30% that do not fare well, an unanswered question is which strategies reduce the likelihood of technical, absconding, and new arrest violations during the early phase of supervision. Utilizing data on 32,335 moderate to high-supervised individuals on supervision in North Carolina, the study found that success during the first 6 months is due to probation officers’ use of incentives to promote positive behavior and swift community-based consequences to address negative behavior, prioritizing treatment services or cognitive programs, increasing monitoring requirements, and using skill-building worksheets to increase engagement and build rapport. Officer actions are more important than individual characteristics, and can promote success for those that are under the age of 31, have more complex needs, and are identified as at-risk for violating supervision. Future studies should explore these concepts more directly regarding their relationship with recidivism.
Background The criminal justice system is the largest provider of mental health services in the USA. Many jurisdictions are interested in reducing the use of the justice system for mental health problems. The national Stepping Up Initiative helps agencies within counties work together more effectively to reduce the number of individuals with mental illness in jails and to improve access to mental health services in the community. This study will compare Stepping Up counties to matched comparison counties over time to (1) examine the effectiveness of Stepping Up and (2) test hypothesized implementation mechanisms to inform multi-agency implementation efforts more broadly. Methods The study will survey 950 counties at baseline, 18 months, and 36 months in a quasi-experimental design comparing implementation mechanisms and outcomes between 475 Stepping Up counties and 475 matched comparison counties. Surveys will be sent to up to four respondents per county including administrators of jail, probation, community mental health services, and community substance use treatment services (3800 total respondents). We will examine whether Stepping Up counties show faster improvements in implementation outcomes (number of justice-involved clients receiving behavioral health services, number of behavioral health evidence-based practices and policies [EBPPs] available to justice-involved individuals, and resources for behavioral health EBPP for justice-involved individuals) than do matched comparison counties. We will also evaluate whether engagement of hypothesized mechanisms explains differences in implementation outcomes. Implementation target mechanisms include (1) use of and capacity for performance monitoring, (2) use and functioning of interagency teams, (3) common goals and mission across agencies, and (4) system integration (i.e., building an integrated system of care rather than adding one program or training). Finally, we will characterize implementation processes and critical incidents using survey responses and qualitative interviews. Discussion There are few rigorous, prospective studies examining implementation mechanisms and their relationship with behavioral health implementation outcomes in justice and associated community behavioral health settings. There is also limited understanding of implementation mechanisms that occur across systems with multiple goals. This study will describe implementation outcomes of Stepping Up and will elucidate target mechanisms that are effective in multi-goal, multi-agency systems.
Research on staff and organizational factors that affect receptivity, adoption, feasibility, and utilization of innovations in justice settings is limited. This study uses survey data from 349 employees in one probation agency to assess how staff and perceived organizational factors influence attitudes related to evidence-based practices (EBPs) and their self-reported use. Staff characteristics, including education and knowledge about EBPs, and perceptions of the organization, including cynicism about the organization’s ability to change, predicted EBP outcomes. Staff age, tenure at the agency, and caseload size affected perceptions of organizational culture, but did not predict attitudes or use of EBPs. There is weak evidence for a relationship between self-reported use of EBPs with attitudinal support for EBPs, prior EBP training, and knowledge of EBPs. This study contributes to an emerging body of literature about the impact of various individual and organizational factors on support for EBPs with important lessons for implementation.
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