Young Adults with the Mental Health and Criminal Justice System Involvement

Background: The Bureau of Justice Statistics indicated that 37% to 44% of persons in the criminal justice system had mental health issues (Bronson & Berzofsky, 2017). It is well documented in that lack of support of mental health needs would increase the likelihood of the further involvement in the justice system (Sung et al., 2011; Williams, 2015). In one Midwestern state, the justice system was the second-highest referral source of young adults (ages 18-25). However, little is known about their needs, challenges, and success following dual system involvement. This study examined the intersection of characteristics, behavioral health needs, and strengths for young adults with dual involvement in the mental health and criminal justice systems.

Methods. Utilizing a statewide publicly funded behavioral health administrative dataset that included demographic, assessment, and national outcome measures, participants were identified by referral source, legal system involvement (Adult Needs and Strengths Assessment, Lyons, 2009). Young adults with past or current legal system who participated in behavioral health services in CY2019 were identified (n = 8, 170). 4,679 young adults were never involved in the justice system, while 2,048 and 1,443 were having current and historic dual system involvement, respectively.

Analysis. This study focused on two groups (current dual system involvement vs. mental health system only), the ANSA’s six domains (i.e., strengths, life functioning, cultural factors, caregiver needs and resources, behavioral health needs, risk behaviors) and their actionable ratings at the last assessment in 2019, and demographic information (i.e., age, gender, race, and ethnicity). The intersection of demographic information, behavioral health needs, and strengths were examined by a machine learning decision tree model, chi-square automatic interaction detection (CHAID) (Milanović & Stamenković, 2016). In addition, hierarchical logistic regression models were implemented to confirm the findings from the CHAID analysis.

Results. Findings predicted dual system involvement with following ANSA items: 1) substance use; 2) gender; 3) depression; 4) anxiety; 5) volunteering (strength); 6) developmental; 7) impulse control; 8) residential stability; 9) parental/caregiver role, and 10) anger control. The most significant predictor associated with the dual system involvement, differentiating from the non-dual system involvement, was substance use followed by gender and depression. More young men than young women had substance use needs. Young adults with dual system involvement presented higher rates of actionable ratings on depression and impulse control than their counterparts. Of individuals without actionable substance use needs, there was a higher rate of anxiety than young females with dual system involvementThe overall model accuracy was .81, indicating that the model distinguished well between individuals with dual system and non-dual system involvement.

Conclusion and Implications: The findings present well-posed variables to build the prediction model of young adults with dual system involvement. The model could lead us to what areas of need and support we should consider for dual system youth in the mental health recovery. It could eventually be a foundation for another in-depth analysis of the behavioral health services, such as effective programs to divert young adults with behavioral health needs from the criminal justice system.