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

什么有效，对谁有效？

• 批准号: 10723566
• 负责人: Lina Montoya
• 金额: $ 9.99万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-05 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723566
• 关键词: Adult; Award; Behavior Therapy; Behavioral; Characteristics; Clinical; Cognitive; Cognitive Therapy; Criminal Justice; Data; Dedications; Development; Foundations; Funding; Goals; Grant; Heterogeneity; Imprisonment; Individual; Intervention; Justice; Knowledge; Learning; Machine Learning; Mediating; Mental disorders; Mentorship; Methods; National Institute of Mental Health; North Carolina; Outcome; Participant; Pathway interactions; Persons; Phase; Policies; Population; Population Heterogeneity; Populations at Risk; Positioning Attribute; Prevention; Prisons; Probability; Public Health; Randomized, Controlled Trials; Recommendation; Recording of previous events; Research; Research Personnel; Research Project Grants; Research Support; Risk Factors; Safety; Services; Statistical Methods; Symptoms; System; Talents; Techniques; Time; Training; Translating; Vulnerable Populations; Work; anti social; court; criminal behavior; demographics; experience; improved outcome; individualized medicine; intervention effect; marginalized community; novel; personalized intervention; policy recommendation; precision medicine; prevent; psychiatric symptom; recidivism; scale up; severe mental illness; skill acquisition; skills; statistics; substance use; theories; trait; treatment as usual; treatment response; treatment strategy; underserved community

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.

项目概要/摘要 在美国刑事司法系统中，严重精神疾病 (SMI) 患者的比例明显过高。 努力减少这一弱势群体的累犯，单一管理的平均效果 近年来，人们对针对所有人的干预措施进行了研究，其中包括针对 SMI 症状的干预措施。 （例如强制的精神科服务）和其他针对犯罪风险因素（例如认知 然而，参与正义的 SMI 患者的特征、需求和行为各不相同。 风险因素；没有“一刀切”的解决方案来防止累犯。 因此，该提案的总体目标是认识到这一人群的异质性。 使用最先进的技术了解哪些干预措施对哪些 SMI 参与正义的人最有效 从因果推理、统计理论和机器学习中得出的精准医学方法这是一个步骤。 实现通过匹配来最佳地确定减少该人群犯罪行为的方法的长期目标 在敬业且才华横溢的指导团队的支持下，为那些需要并从中受益的人提供干预措施， 这笔赠款的培训部分将填补实现这一目标的关键空白：1) 主题培训和实地培训 刑事司法系统中 SMI 的经验，2）开发精确的新型技术方法 医学，3）将技术发现转化为具有高影响力的实践和政策建议的技能，以及 4) 专业技能发展。这种丰富的培训将为完成以下任务奠定基础。 研究旨在实现该提案的广泛目标：1）了解实现这一目标的不同途径 有再次犯罪风险的人群，2) 确定针对受益者实施干预措施的定制规则 根据个人特征从它们中提取信息，3）评估所识别的规则是否以及如何匹配 这项研究将利用随机对照试验数据和联邦数据。 来自美国法院行政办公室，以及来自北卡罗来纳州公共部门的州数据 重要的是，这项资助的研究将带来新的统计精度。 将规则传递到不同于学习规则的环境的医学方法。 这笔赠款与 NIMH 努力为患有此类疾病的人提供预防和治疗的战略目标高度契合。 SMI，包括但不限于以下目标：a) 改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）以及 b) 扩大规模的战略 通过了解谁从使用哪些干预措施中受益。 精准医学方法的最新进展，这项工作有可能帮助阻止所谓的“旋转” 此外，这项研究还将推进数据支持的工具包。 最有效地提高公众健康和安全的精准医疗策略。