Computational psychiatry investigation of the role of unrealistic optimism in opioid use disorder and relapse

计算精神病学研究不切实际的乐观情绪在阿片类药物使用障碍和复发中的作用

• 批准号: 10542386
• 负责人: Anna Borisova Konova
• 金额: $ 51.8万
• 依托单位: RUTGERS BIOMEDICAL AND HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10542386
• 关键词: Automobile Driving; Behavioral; Belief; Brain region; Cessation of life; Chronic; Clinical; Clinical assessments; Cognitive; Complex; Computing Methodologies; Corpus striatum structure; Data; Data Collection; Decision Making; Decision Theory; Diagnosis; Dimensions; Drug usage; Evaluation; Event; Exhibits; Feeling; Functional Magnetic Resonance Imaging; General Population; Goals; Health; Human; Imaging Device; Individual; Inferior frontal gyrus; Intervention; Investigation; Judgment; Laboratories; Life Expectancy; Longitudinal Studies; Measures; Mediating; Mediation; Mediator; Modeling; Monitor; Nature; Neurobiology; Neurocognitive; Opioid; Opioid replacement therapy; Outcome; Overdose; Patient-Focused Outcomes; Patients; Pattern; Persons; Pharmaceutical Preparations; Population; Prefrontal Cortex; Probability; Process; Process Measure; Psychiatry; Psychopathology; Recovery; Relapse; Resolution; Risk; Role; Safety; Sampling; Testing; Therapeutic Intervention; Translating; Uncertainty; Work; behavioral study; behavioral tolerance; clinically relevant; cognitive task; cohort; computerized tools; cost; design; disorder risk; driving behavior; evidence base; follow-up; high risk; improved; individual patient; longitudinal design; medication for opioid use disorder; mortality; neural; neural circuit; neural patterning; novel; novel therapeutic intervention; opioid epidemic; opioid use; opioid use disorder; optimism; patient engagement; patient subsets; prospective; relapse risk; targeted treatment; theories; time use; tool

Project Summary/Abstract The current opioid epidemic is a major health crisis that has contributed to decreased life expectancy in the U.S. A main cause of morbidly and mortality is opioid reuse and relapse in chronic cases. Understanding the neurocognitive mechanisms and factors underlying reuse vulnerability is thus a pressing need. Leveraging a novel combination of neurocognitive tools and a multi-session longitudinal design, our recent work in opioid use disorder (OUD) has begun to delineate a precise decision making mechanism for opioid reuse by showing that treatment-engaged patients are at higher risk for reuse when they exhibit increased tolerance of unknown probabilistic outcomes (ambiguity tolerance) in a financial choice task (Konova et al., 2019 JAMA Psychiatry). But why patients become more tolerant of ambiguous uncertainty in periods preceding reuse remains unknown. One potential explanation consistent with decision theory is that, in these periods, they become overoptimistic about ambiguous outcomes, which leads them to overestimate the probability of good outcomes (or underestimate bad outcomes) when faced with a decision to reuse, and therefore more likely to do so. Here, we propose a multi-level, convergent test of this framework by using well-defined, quantitative measures of this presumed “optimism bias”, alongside quantitative measures of uncertainty tolerance, which we propose to collect with concurrent high-resolution fMRI recordings, and yoked to longitudinal clinical assessments. In Aim 1, we aim to establish the relationship between uncertainty tolerance and optimism bias in patients with OUD and matched controls by studying these behaviors across a set of choice and estimation tasks (the latter designed to capture optimism about simple financial and more complex outcomes, tapping into drug-choice-relevant domains such as health outcomes). We also examine for potential moderation by various psychopathological dimensions in a large, unselected population of online (MTurk) subjects. In Aim 2, we collect fMRI data during the same choice and estimation tasks to delineate the mechanism by which optimistic neural representations of uncertainty might drive behavioral tolerance of this uncertainty, and reuse, in OUD. In Aim 3, we use a multi- session longitudinal design to understand the interaction between optimism bias and uncertainty tolerance as they relate to opioid reuse, session-to-session, allowing us to elucidate the specific timescale and nature of this interaction. With this project we aim to provide an answer to why patients become more uncertainty tolerant in periods preceding reuse and, in doing so, hope to uncover an upstream mechanism (centered on optimism bias) of this vulnerability, including its neural implementation. In addition to this conceptual advance, this work will provide a novel set of cognitive tools to precisely and objectively measure these processes with potential to predict poor outcomes such as reuse, in a way that can be easily implemented in clinical settings. Finally, the findings from this work will inform novel therapeutic interventions by providing precise neurocognitive targets, as well as their ideal timing, with the goal of mitigating reuse risk and improving long-term patient outcome.

项目总结/摘要 目前的阿片类药物流行病是一场重大的健康危机，导致美国人的预期寿命下降。 发病和死亡的主要原因是阿片类药物的重复使用和慢性病例的复发。了解 因此，迫切需要重新使用脆弱性的神经认知机制和因素。利用一个 神经认知工具和多会话纵向设计的新颖组合，我们最近在阿片类药物使用方面的工作 OUD已经开始描绘阿片类药物重复使用的精确决策机制， 接受治疗的患者对未知药物的耐受性增加时， 金融选择任务中的概率结果（模糊容忍度）（Konova等人，2019 JAMA Psychiatry）。 但是，为什么病人在重复使用前的一段时间里变得更加容忍模棱两可的不确定性仍然是未知的。 一个与决策理论相一致的潜在解释是，在这些时期，他们变得过于乐观 关于模棱两可的结果，这导致他们高估了好结果的可能性（或 当面临重用的决定时，他们会低估坏的结果），因此更有可能这样做。这里我们 提出了一个多层次的，收敛测试这个框架，通过使用定义明确，定量措施，这 假定的“乐观偏见”，以及不确定性容忍度的定量措施，我们建议收集 同时进行高分辨率功能磁共振成像记录，并与纵向临床评估相结合。目标1： 目的探讨OUD患者不确定性容忍度与乐观偏差之间的关系， 通过在一组选择和估计任务中研究这些行为来匹配控制（后者设计了 捕捉对简单财务和更复杂结果的乐观情绪，利用与药物选择相关的 （如健康问题）。我们还通过各种精神病理学检查潜在的适度 在一个大的，在线（MTurk）主题的人群中的维度。在目标2中，我们收集了fMRI数据， 同样的选择和估计任务来描绘乐观的神经表征的机制， 在OUD中，不确定性可能会驱动对这种不确定性的行为容忍和重用。在Aim 3中，我们使用多- 会话纵向设计，以了解乐观偏差和不确定性容忍度之间的相互作用， 它们涉及阿片类药物的重复使用，会话到会话，使我们能够阐明具体的时间尺度和性质， 互动通过这个项目，我们的目标是提供一个答案，为什么病人变得更加不确定性容忍， 在重用之前的一段时间内，希望发现一个上游机制（以乐观偏见为中心） 包括它的神经实现除了这一概念上的进步，这项工作将 提供了一套新的认知工具来精确客观地测量这些过程， 预测不良结果，如重复使用，以一种可以在临床环境中轻松实现的方式。最后 这项工作的发现将通过提供精确的神经认知靶点，为新型治疗干预提供信息， 以及它们的理想时机，目的是减轻重复使用风险并改善长期患者结局。