Method: Data from the MacArthur MHC study were analyzed. The sample includes 741 offenders with mental illness from four MHCS and comparison traditional courts. Participants were interviewed at baseline and six months after and objective arrest data were collected. Multilevel modelling and propensity score weighting was used to investigate individual level (level 1) and neighborhood level (level 2) variances on recidivism and to control for selection bias. Treatment variables include treatment adherence (i.e., medication and appointment), treatment perception (i.e., treatment motivation and perceived voluntariness), and treatment usage (mental health and substance abuse service). Neighborhood disadvantage data include 5 indexes (i.e., rate of poverty, unemployment, vacant/abandoned housing, public benefits recipients, and single-parent families) in each census tract from 2005-2009. They were obtained from the American Community Survey at U.S. Census Bureau, and linked with residential data from participants. All statistical analyses were conducted using STATA version 13 and ArcGIS.
Result: Study results suggest that some of treatment variables have significant impact on arrest. For example, before the court enrollment, MHC participant with more substance abuse service were less likely to be arrest compared to those with less substance abuse service. Both TAU and MHC participants has significant effect of neighborhood disadvantage on arrest before the court enrollment. After the court enrollment, MHC participant with higher treatment motivation were less likely to recidivate compared to those with lower treatment motivation after the court enrollment. In addition, only MHC participant continued to have effect of neighborhood disadvantage on arrest.
Conclusions and Implications: Multilevel analyses identified that the factors of treatment motivation and neighborhood disadvantage significantly predict future arrest after MHC enrolment. Understanding treatment characteristics and neighborhood disadvantage associated with recidivism for offenders with mental illness can help to more efficiently target research, practice, and policy in the future. In addition, social work professionals should recognize themselves the importance of the treatment perception (e.g., treatment motivation) and neighborhood disadvantage to provide, develop, and implement innovative interventions for offender with mental illness. This research will shed new light into future interventions and/or policies that aim to reduce the recidivism for this difficult-to-treat population of offenders.