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
项目成果
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