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This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

This study aims to examine the relationship between medication for opioid use disorder (MOUD) among pregnant individuals, referral source, mental health, political affiliation and substance use policies in all 50 states in the USA.

This study describes MOUD receipt among pregnant people with an opioid use disorder (OUD) in 2018. The authors explored sociodemographic differences in MOUD receipt, referrals and co-occurring mental health disorders. The authors included a comparison of MOUD receipt among states that have varying substance use policies and examined the impact of these policies and the political affiliation on MOUD. The authors used multilevel binary logistic regression to examine effects of individual and state-level characteristics on MOUD.

Among 8,790 pregnant admissions with OUD, the majority who received MOUD occurred in the Northeast region (71.52%), and 14.99% were referred by the criminal justice system (n = 1,318). Of those who were self-referred, 66.39% received MOUD, while only 30.8% of referrals from the criminal justice system received MOUD. Those referred from the criminal justice system or who had a co-occurring mental health disorder were least likely to receive MOUD. The multilevel model showed that while policies were not a significant predictor, a state’s political affiliation was a significant predictor of MOUD.

The study has some methodological limitations; a state-level analysis, even when considering the individual factors, may not provide sufficient description of community-level or other social factors that may influence MOUD receipt. This study adds to the growing literature on the ineffectiveness of prenatal substance use policies designed specifically to increase the use of MOUD. If such policies are consistently assessed as not contributing to substantial increase in MOUD among pregnant women over time, it is imperative to investigate potential mechanisms in these policies that may not facilitate MOUD access the way they are intended to.

Findings from this study aid in understanding the impact that a political affiliation may have on treatment access; states that leaned more Democratic were more likely to have higher rates of MOUD, and this finding can lead to research that focuses on how and why this contributes to greater treatment utilization. This study provides estimates of underutilization at a state level and the mechanisms that act as barriers, which is a stronger assessment of how state-specific policies and practices are performing in addressing prenatal substance use and a necessary step in implementing changes that can improve the links between pregnant women and MOUD.

To the best of the authors’ knowledge, this is the first study to explore individual-level factors that include mental health and referral sources to treatment that lead to MOUD use in the context of state-level policy and political environments. Most studies estimate national-level rates of treatment use only, which can be useful, but what is necessary is to understand what mechanisms are at work that vary by state. This study also found that while substance use policies were designed to increase MOUD for pregnant women, this was not as prominent a predictor as other factors, like mental health, being referred from the criminal justice system, and living in a state with more Democratic-leaning affiliations.