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
基本信息
- 批准号:10679418
- 负责人:
- 金额:$ 7.32万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AgeAlcohol consumptionAlcoholic beverage heavy drinkerAlcoholsAreaAttentionBehaviorBehavioralBeliefBenchmarkingBrainClinicalClinical TrialsCognitiveCognitive ScienceComputer ModelsDecision MakingDimensionsDiseaseEnvironmentEventFacultyFellowshipFundingFutureGenderGeneral PopulationGoalsHealthHomeImpairmentIndividualIndividual DifferencesInterventionInvestigationLearningLinkLocationMeasuresMediatingMental DepressionMental ProcessesMentorsMentorshipMindfulness TrainingModelingNeurocognitiveObsessive compulsive behaviorObsessive-Compulsive DisorderParticipantPatient Self-ReportPersonal SatisfactionPersonsPopulationProcessPsychiatryPsychopathologyRaceReportingResearchSamplingSelf-ExaminationSeveritiesSubstance Use DisorderSymptomsTestingTherapeutic InterventionThinkingTimeTrainingTranslatingUnited States National Institutes of HealthVariantWeightWorkalcohol cravingalcohol cuealcohol involvementalcohol responsealcohol use disordercognitive processdiagnostic biomarkerfollow-upimprovedinsightmindfulness interventionnovelpsychiatric symptomschizophrenia spectrum disordersocial
项目摘要
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.
项目概要/摘要。“我为什么要这么做?”能够回答这个常见的问题,
准确地反映一个人的选择背后的心理过程-是良好决策的基础
健康的关系。这种能力在某些形式的精神病理学中受损,
自我反省似乎与精神病症状在不同领域,如精神分裂症谱
精神障碍、强迫症和物质使用障碍1 -12,改善自我反省是一种
许多治疗干预的目标13 -16。然而,自我反思背后的神经认知机制
准确性的理解很少,因为该领域缺乏对这种能力的客观定量测量。
我建议使用一种新的测量方法(我已经开发并试用过)来量化人们的自我反思
他们的选择过程的准确性,并将这种准确性与精神症状的变化,
一般人口。在这项任务中,参与者首先在选项之间做出选择(例如,房屋出租,或社会
事件出席),这在许多属性17,18不同。然后,参与者报告他们认为他们是如何使他们的
选择,包括他们对每个属性赋予的权重以及如何组合属性
一起然后,我将一组已建立的模型与参与者的选择相匹配17,19,恢复他们的关键方面。
选择过程通过比较参与者的自我报告和他们实际选择中所揭示的过程,
可以获得一个客观的测量参与者的自我反思的准确性,他们的选择过程。
使用这种方法,我将测试是否强迫症和强迫症状(在一个
一般人群样本)与较低的自我反思准确性相关(研究1),以及
酒精使用障碍的症状与在特定环境中选择的准确性较低有关
酒精(研究2)。最后,我将把我的测量方法加入到正在进行的NIH资助的临床试验测试中,
正念干预是否可以减少重度饮酒者的饮酒量。我将测试
这种正念干预提高了酒精相关选择的自我反思准确性20,21,
准确性的提高是否介导了饮酒量的减少22 -24(研究3)。本研究
提供了一个生成范式,用于量化选择中的自我反思准确性,支持未来的调查
进入神经认知机制的自我反省和精神病理学的破坏1,3,7,9,10,25
并为验证未来的治疗干预提供基准26。
我的背景是选择计算模型27 -30,在这个奖学金中,我将学习应用这些模型
精神病理学我的导师团队包括计算认知科学,精神病理学,
计算精神病学,临床干预和自我理解,培训计划涉及大量的
课程作业、一对一辅导和参加研讨会。此外,普林斯顿-以其世界知名的
计算精神病学系-提供了一个无与伦比的环境来进行这项研究和培训。
项目成果
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