PROJECT SUMMARY/ABSTRACT People with serious mental illness (SMI) are substantially overrepresented in the US criminal justice system. In an effort to reduce recidivism among this vulnerable population, average effects of administering single interventions to all have been studied in recent years. These interventions include ones that target SMI symptoms (such as mandated psychiatric services) and others that target criminogenic risk factors (such as cognitive behavioral therapy). However, justice-involved people with SMI are diverse in their characteristics, needs, and risk factors; there is no “one-size-fits-all” solution to prevent recidivism. Decreasing adverse criminal outcomes for this population requires recognizing its heterogeneity. Therefore, the broad objective of this proposal is to understand which interventions work best for which justice-involved people with SMI using state-of-the-art precision medicine methods drawn from causal inference, statistical theory, and machine learning. This is a step toward the long-term goal of identifying optimal ways to reduce criminal behavior in this population by matching interventions to those who need and benefit from them. Supported by a dedicated and talented mentorship team, the training portion of this grant will fill gaps key to achieving this goal: 1) subject-matter training and field experience on SMI in the criminal justice system, 2) development of novel technical methods in precision medicine, 3) skills in translating technical findings to high-impact recommendations for practice and policy, and 4) professional skills development. This rich training will provide a foundation for accomplishing the following research aims to reach the proposal's broad objective: 1) understand the differential pathways that situate this population at risk for re-offending, 2) identify tailored rules for administering interventions to those who benefit from them based on individual characteristics, and 3) assess whether and how the identified rules for matching interventions generalize across the US. This research will leverage randomized controlled trial data, federal data from the Administrative Office of the US Courts, and state data from the North Carolina Department of Public Safety to achieve these aims. Importantly, research from this grant will result in novel statistical precision medicine methods for transporting rules to settings different than those on which they are learned. The aims of this grant are well-aligned with NIMH's strategic goal of striving for prevention and treatments among people with SMI, including, but not limited to, the objectives of: a) advancing methods to match interventions to individuals and populations (especially marginalized and underserved communities) and b) strategies for scaling up interventions for the greatest public health impact. By learning who benefits from which interventions using the latest advances in precision medicine methods, this work has the potent...