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.
项目摘要/摘要。“我为什么要选择这样做?”能够回答这个常见的问题--以及
准确地思考一个人的选择背后的心理过程--是做好决策的基础
和健康的关系。这种能力在某些形式的精神病理学;不准确时会受损
自我反省似乎与精神分裂症等不同领域的精神症状有关
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,自我反省背后的神经认知机制
由于该领域缺乏对这一能力的客观、定量的衡量,人们对其准确性的了解很少。
我提议使用一种新的测量方法(我开发并试行)来量化人们的自我反省
关于他们选择过程的准确性,并将这种准确性与精神症状的变化联系起来
普通人口。在此任务中,参与者首先在选项(例如,出租房屋或社交房屋)之间进行选择
17,18.然后,参与者报告他们认为自己是如何做出自己的贡献的
选项,包括它们对每个属性的权重以及它们如何组合这些属性
在一起。然后,我将一组已建立的模型适合参与者的选择17、19,恢复他们的
选择过程。通过将参与者的自我报告与他们实际选择中揭示的过程进行比较,我
可以客观地衡量参与者对其选择过程的自我反思的准确性。
使用这个测量,我将测试分裂类型和强迫症状(在
总体样本)与较低的自我反思准确率相关(研究1),以及
酒精使用障碍的症状与在特定的选择环境中准确性较低相关
涉及酒精(研究2)。最后,我将把我的措施添加到NIH资助的正在进行的临床试验测试中
正念干预是否能减少酗酒者的饮酒量。我要测试一下
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和
准确度的提高是否有助于减少酒精消耗量22-24(研究3)。这项研究
提供了一种生成范式,用于量化选择中的自我反思准确性,支持未来的研究
探讨精神病理学中自我反省及其破坏的神经认知机制1,3,7,9,10,25
并为验证未来的治疗干预提供了一个基准26。
我的背景是选修课27-30的计算模型,在这个奖学金中,我将学习如何应用这些模型
精神变态。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
课程作业、一对一的指导和研讨会的出席。此外,普林斯顿-以其举世闻名的
计算精神病学的教师-提供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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