Emotion Regulation in Distress Disorders: Elucidating the Role of Cognitive Processes and Person-Situation Fit in the Laboratory and Daily Life

摘要：重性抑郁症和广泛性焦虑症，共同被概念化为抑郁障碍， 这些疾病普遍存在，公共卫生负担相当大，对治疗的反应相对较低。 痛苦障碍有许多共同的特点，有助于维持和恶化这些条件，包括 负面情绪增加，情绪调节（ER）缺陷，持续性负面思维增加 （PNT）.重要的是，有效的ER与更好的心理功能和更好的生理功能有关。 从压力中恢复，它是抑郁症干预措施的目标。有效的ER取决于完整的 情绪意识和语境敏感性，这有助于灵活地制定ER策略，以匹配一个人的 特点和现状。改善抑郁症干预措施的一个关键障碍是 缺乏关于有效ER的特定预测因素的知识，尤其是在评估性能时 在实验室测量的最佳条件下（ER容量）和日常生活中自然自发的ER使用 (ER趋势）。这个应用程序的目标是评估认知和情境因素如何有助于 有效ER能力和ER倾向，并检查ER能力和倾向如何协同工作， 预测长期的痛苦症状和功能。一种特别适合于 将在实验室和日常生活中对包含PNT的抑郁症进行测试，结果与以下方面有关： 对痛苦症状和功能进行前瞻性评估，以分离最相关的有效ER要素 临床结果。这项拟议的研究将由300名成年人组成，对PNT升高进行过采样， 多方法设计。参与者将完成实验室评估，其中包括行为、心血管 生理和临床访谈措施，然后进行为期10天的生态瞬时评估研究 检查日常生活中ER的预测因素。为了更好地捕捉负面情绪，在日常生活中， 将由检测心理压力的算法生理触发。有效的ER将是 在实验室和日常生活中以多种方式操作，使用自我报告的情感，生理 指数，以及感知的ER成功。有效ER及其预测因子的相关性将在 与6个月和12个月随访评估时的痛苦症状和功能轨迹的关系。 此外，一个探索性的目标是从理论上的多方面电池创建预测模型， 通过使用机器学习，可能影响现实生活中ER和后续临床结果的动机变量 建立一个临床相关的框架，用于个人层面、情境层面和ER策略如何相互作用， 预测最佳ER。该项目符合NIMH战略目标和RDoC框架，因为 精神病理学的多维方法和多个分析单元。总体而言，该项目有助于 长期目标是通过更精确地分离关键因素， 有效的ER机制，为特定的个人和他们在日常生活中遇到的情况。

ABSTRACT: Major depression and generalized anxiety disorder, conceptualized jointly as distress disorders, are prevalent conditions with considerable public health burden and comparatively lower response to treatment. Distress disorders share numerous features that serve to maintain and worsen these conditions, including heightened negative emotions, deficits in emotion regulation (ER), and elevated perseverative negative thinking (PNT). Importantly, effective ER is associated with better psychological functioning and better physiological recovery from stress, and it is a target in distress disorders interventions. Effective ER depends upon intact emotional awareness and contextual sensitivity, which facilitate flexibly enacting ER strategies to match one's characteristics and the current situation. A critical barrier to improving interventions for distress disorders is a lack of knowledge regarding the specific predictors of effective ER, especially when assessing performance under optimal conditions measured in the lab (ER capacity) and naturalistic, spontaneous ER use in daily life (ER tendency). The goal of this application is to evaluate how cognitive and situational factors contribute to effective ER capacity and ER tendency, and to examine how ER capacity and tendency work synergistically to predict long-term distress symptoms and functioning. An integrative model of ER specifically suited to the distress disorders that incorporates PNT will be tested in the laboratory and in daily life, with findings linked to prospective assessments of distress symptoms and functioning to isolate elements of effective ER most relevant to clinical outcomes. The proposed study will be comprised of 300 adults, oversampling for elevated PNT, with a multi-method design. Participants will complete a lab assessment that incorporates behavioral, cardiovascular physiological, and clinical interview measures, followed by a 10-day ecological momentary assessment study examining predictors of ER in daily life. To better capture negative emotions as they occur, reports in daily life will be physiologically-triggered with algorithms that detect psychological stress. Effective ER will be operationalized in multiple ways in the lab and in daily life, using self-reported changes in affect, physiological indices, and perceived ER success. The associations of effective ER and its predictors will then be examined in relation to the trajectory of distress symptoms and functioning at 6-month and 12-month follow-up assessments. Additionally, an exploratory aim is to create predictive models from a multifaceted battery of theoretically motivated variables that may impact real-life ER and subsequent clinical outcomes, by using machine learning to build a clinically-relevant framework for how person-level, situation-level, and ER strategy use interact to predict optimal ER. This project is consistent with NIMH strategic objectives and the RDoC framework due to the dimensional approach to psychopathology and multiple units of analysis. Overall, this project contributes to the long-term goal of identifying and refining targets for personalized interventions, by more precisely isolating key mechanisms of effective ER for specific individuals and the contexts they encounter in their daily lives.