Self-reflective accuracy across subclinical dimensions of psychopathology

精神病理学亚临床维度的自我反思准确性

• 批准号: 10679418
• 负责人: Adam Mitchell Morris
• 金额: $ 7.32万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10679418
• 关键词: Age; Alcohol consumption; Alcoholic beverage heavy drinker; Alcohols; Area; Attention; Behavior; Behavioral; Belief; Benchmarking; Brain; Clinical; Clinical Trials; Cognitive; Cognitive Science; Computer Models; Decision Making; Dimensions; Disease; Environment; Event; Faculty; Fellowship; Funding; Future; Gender; General Population; Goals; Health; Home; Impairment; Individual; Individual Differences; Intervention; Investigation; Learning; Link; Location; Measures; Mediating; Mental Depression; Mental Processes; Mentors; Mentorship; Mindfulness Training; Modeling; Neurocognitive; Obsessive compulsive behavior; Obsessive-Compulsive Disorder; Participant; Patient Self-Report; Personal Satisfaction; Persons; Population; Process; Psychiatry; Psychopathology; Race; Reporting; Research; Sampling; Self-Examination; Severities; Substance Use Disorder; Symptoms; Testing; Therapeutic Intervention; Thinking; Time; Training; Translating; United States National Institutes of Health; Variant; Weight; Work; alcohol craving; alcohol cue; alcohol involvement; alcohol response; alcohol use disorder; cognitive process; diagnostic biomarker; follow-up; improved; insight; mindfulness intervention; novel; psychiatric symptom; schizophrenia spectrum disorder; social

Project Summary/Abstract. “Why did I choose to do that?” Being able to answer this common question – and accurately reflect on the mental processes underlying one’s choices – is fundamental to good decision-making and healthy relationships. This capacity is impaired in some forms of psychopathology; inaccurate self-reflection appears related to psychiatric symptoms in diverse areas such as schizophrenia spectrum disorders, obsessive-compulsive disorder, and substance use disorders1–12, and improving self-reflection is a goal of many therapeutic interventions13–16. Yet, the neurocognitive mechanisms underlying self-reflective (in)accuracy are poorly understood because the field lacks objective, quantitative measures of this ability. I propose to use a novel measure (which I’ve developed and piloted) to quantify people’s self-reflective accuracy about their choice processes, and relate this accuracy to psychiatric symptom variation in the general population. In this task, participants first make choices between options (e.g., homes to rent, or social events to attend) which vary on many attributes17,18. Then, participants report how they believe they made their choices, including how much weight they placed on each attribute and how they combined the attributes together. I then fit a set of established models to participants’ choices17,19, recovering key aspects of their choice process. By comparing participants’ self-reports to the process revealed in their actual choices, I can obtain an objective measure of participants’ self-reflective accuracy about their choice process. Using this measure, I will test whether schizotypy and obsessive-compulsive symptoms (in a general-population sample) correlate with lower self-reflective accuracy (Study 1), and whether symptoms of disordered alcohol use correlate with lower accuracy in the specific context of choices involving alcohol (Study 2). Finally, I will add my measure to an ongoing NIH-funded clinical trial testing whether a mindfulness intervention can reduce alcohol consumption among heavy drinkers. I will test whether this mindfulness intervention improves self-reflective accuracy in alcohol-related choice20,21, and whether improvements in accuracy mediate reductions in alcohol consumption22–24 (Study 3). This research provides a generative paradigm for quantifying self-reflective accuracy in choice, supporting future investigation into the neurocognitive mechanisms underlying self-reflection and its disruption in psychopathology1,3,7,9,10,25 and offering a benchmark for validating future therapeutic interventions26. My background is in computational models of choice27–30, and in this fellowship I will learn to apply these models to psychopathology. My mentor team includes experts in computational cognitive science, psychopathology, computational psychiatry, clinical interventions, and self-understanding, and the training plan involves substantial coursework, one-on-one mentorship, and seminar attendance. Moreover, Princeton – with its world-renowned faculty in computational psychiatry – offers an unparalleled environment to conduct this research and training.

项目总结/抽象。“我为什么选择那样做？”能够回答这个常见的问题-和