Predicting Substance Use and Related Antisocial Behavior with Psychiatric, Socioeconomic, and Brain Measures in Women Offenders

项目摘要/摘要 物质使用每年给社会造成7400亿美元的损失，给我们国家的健康带来巨大负担 护理和刑事司法系统。在美国，大约85%的被监禁罪犯有 有吸毒史和/或因涉及酒精和/或毒品使用或受其驱使的罪行而入狱。 被监禁的人在使用药物治疗后往往表现出更差的结果，并被迫 通过监禁进行禁欲与未来使用药物的风险有关，这可能导致 入狱后与物质有关的反社会行为。在过去的几十年里，女性一直被 以惊人的速度因与毒品有关的原因被判入狱，增长率超过了男性。 此外，女性罪犯往往更容易受到药物使用和共病的影响。 精神病理学，在物质使用和精神健康方面对系统提出了更高的要求 治疗。使用世界上最大的女性罪犯法医神经成像数据库(SWANC-F)，这 一项提案调查了出狱后的药物使用和相关反社会行为 女性罪犯样本，重点放在神经生物学机制上，以展示大脑的效用 评估高危妇女长期药物使用结果的措施。物质相关反社会 行为，被定义为在出狱后实施与使用毒品有关的犯罪(S)，将获得 从机构档案中的重新逮捕数据和对所有参加 学习。然后将通过电话对随机样本(n=100)进行跟踪，以收集关于物质使用的数据和 从档案和背景调查中获取补充信息，以证实重新逮捕的数据。用人 回归分析和机器学习/模式分类器的方法，模型将进行比较测试 精神和社会经济变量以及静息状态功能连接(RsFC)脑功能的影响 鉴别不同病因的独特和综合影响的措施 推动妇女感兴趣的物质使用结果的机制。具体地说，这项提案旨在测试 精神和社会经济因素对与物质相关的反社会行为的风险程度 女性出狱后(目标1)，并整合和比较rsFC脑的效用 改进这些预测模型的措施(目标2)。然后，将使用类似的方法来测试 预测出狱后药物使用情况(目标3)。预计精神疾病的危险因素 社会经济保护因素，以及rsfc大脑指标，将有助于预测药物使用。 以及入狱后的相关反社会行为，以及出狱之间的时间间隔 以及启动物质使用和相关行为。测试有助于预测这些行为的因素 妇女有可能通过宣传制定有针对性的治疗而产生深远影响，其中包括 那些有助于解释性别差异和与药物使用有关的共病情况的研究。

Project Summary/Abstract Substance use costs society $740 billion dollars each year, placing an enormous burden on our nation’s health care and criminal justice systems. Approximately 85% of incarcerated offenders in the United States have a history of substance use and/or are imprisoned for crimes involving or motivated by alcohol and/or drug use. Incarcerated individuals tend to show poorer outcomes following substance use treatment, and forced abstinence via imprisonment is associated with risk for future substance use, which likely contributes to substance-related antisocial behavior following imprisonment. Over the past few decades, women have been sentenced to prison for drug-related reasons at alarming rates, with a growth rate exceeding that for men. Further, women offenders tend to be impacted more heavily by substance use with co-morbid psychopathology, placing greater demands on the system in terms of substance use and mental health treatments. Using the world’s largest forensic neuroimaging database on women offenders (SWANC-F), this proposal investigates substance use and related antisocial behavior following release from prison in a large sample of women offenders, with a focus on neurobiological mechanisms, to demonstrate the utility of brain measures in estimating long-term substance use outcomes in at-risk women. Substance-related antisocial behavior, defined as committing crime(s) related to substance use after release from prison, will be obtained from re-arrest data in institutional files and comprehensive background checks on all women enrolled in the study. A random sample (n = 100) will then be followed-up with via phone to gather data on substance use and obtain supplemental information to corroborate re-arrest data from files and background checks. Employing regression analyses and machine learning/pattern classifier approaches, models will be compared testing effects of psychiatric and socioeconomic variables, along with resting-state functional connectivity (rsFC) brain measures, to examine unique and combined effects in differentiating among heterogeneous etiological mechanisms driving substance use outcomes of interest in women. Specifically, this proposal seeks to test the extent to which psychiatric and socioeconomic factors confer risk for substance-related antisocial behavior following release from prison in women (Aim 1), and integrates and compares the utility of rsFC brain measures in improving these prediction models (Aim 2). Then, similar methods will be applied to test the prediction of substance use following release from prison (Aim 3). It is expected that psychiatric risk factors and socioeconomic protective factors, as well as rsFC brain measures, will be useful in predicting substance use and related antisocial behavior following incarceration, along with time elapsed between release from prison and initiation of substance use and related behavior. Testing factors that aid in predicting these behaviors in women has the potential to be far-reaching by informing the development of targeted treatments, including those that help to account for sex differences and co-morbid conditions related to substance use.