What works, for whom? Applying novel precision medicine methods to people with mental illness in the justice system.

项目摘要/摘要 严重精神疾病(SMI)患者在美国刑事司法系统中的比例严重偏高。在……里面 为减少这一弱势群体中的累犯率所做的努力，单一管理的平均效果 近年来，对所有人的干预措施都进行了研究。这些干预措施包括针对SMI症状的干预 (如强制精神病服务)和其他针对导致犯罪的风险因素(如认知 行为疗法)。然而，参与正义的SMI患者在他们的特征、需求和 风险因素；没有“一刀切”的解决办法来防止再次犯罪。减少不良犯罪后果 因为这个群体需要认识到它的异质性。因此，这项提议的广泛目标是 使用最先进的技术，了解哪些干预措施对哪些司法介入的SMI患者最有效 精准医学方法来源于因果推理、统计理论和机器学习。这是迈出的一步 长期目标是通过匹配确定减少该人群犯罪行为的最佳方法 对那些需要干预并从中受益的人进行干预。在一支敬业而有才华的指导团队的支持下， 这笔赠款的培训部分将填补实现这一目标的关键空白：1)专题培训和实地培训 SMI在刑事司法系统中的经验，2)开发新的精密技术方法 医学，3)将技术成果转化为对实践和政策有重大影响的建议的技能，以及 4)职业技能发展。这一丰富的培训将为实现以下目标奠定基础 研究旨在达到该提案的广泛目标：1)了解造成这种情况的不同途径 有再次犯罪风险的人群，2)确定对受益者进行干预的量身定制规则 3)评估识别出的规则是否以及如何进行匹配 干预行动在全美范围内普遍存在。这项研究将利用随机对照试验数据、联邦数据 来自美国法院行政办公室的数据和来自北卡罗来纳州公共部门的州数据 以安全的方式实现这些目标。重要的是，这项拨款的研究将带来新的统计精度 将规则传递到与学习规则的环境不同的环境中的医学方法。的目标是 这笔赠款与NIMH的战略目标很好地结合在一起，即在患有疾病的人中努力预防和治疗 SMI，包括但不限于以下目标：a)推进将干预措施与个人相匹配的方法 和人口(特别是边缘化和服务不足的社区)和b)扩大规模的战略 对公共卫生产生最大影响的干预措施。通过使用 精准医学方法的最新进展，这项工作有可能有助于阻止所谓的“旋转 为SMI患者伸张正义的人提供“监狱之门”。此外，本研究还将推进数据支持工具包的开发 最高效、最有效地提高公众健康和安全的精准医疗战略。

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 potential to help stop the so-called “revolving prison door” for justice-involved people with SMI. Further, this research will advance the toolkit for data-supported precision medicine strategies that most efficiently and effectively increase public health and safety.