Unpacking Emotion Inflexibility and Prospective Prediction of Affective Disease

精神疾病的患病率已接近流行病 比例。常见的情感疾病（单相抑郁症、焦虑症和应激障碍）的发病率很高 这些疾病给个人带来了巨大的社会和经济负担， 社会明确的证据表明，大多数情感障碍出现在交叉点的预先存在的 脆弱性和重大的、高度紧张的生活事件。然而，目前的情绪相关风险模型确实 没有充分考虑生物、历史和环境因素的汇合。在这次调查中， 我们建立在我们先前的工作上，证明了灵活的情绪处理和 心理健康与调适、情绪不稳定、心理风险和情感性疾病。 具体来说，我们将招募400名在医院发生潜在创伤事件（例如，意外， 暴力、火灾等）以模拟早期情绪处理对调整轨迹的影响。 我们的研究集中在情绪灵活性（EF）的上级结构上，它包括 产生或上调情绪的能力，以及根据需要转移或下调情绪的能力 和/或环境要求。EF非常适合告知模型与情绪相关的风险和调整，因为它 以两个基于生物学的组成维度的最佳平衡为特征：“自下而上”的与威胁有关的 处理和“自上而下”的认知控制越来越被认为是所有情绪处理的核心。我们 提出严格的方法，以评估EF和相关的处理在体内实验室和通过经验采样。 此外，我们将跟踪参与者到活动后18个月，以便有效地模拟协会 情绪处理和调整轨迹之间的关系，同时也考虑到既定的影响， 如身体健康状况，精神病史，童年虐待，日常压力/麻烦，和社会支持。 特别是，我们将结合先进的统计建模的最新发展，以更好地表征 历史和当代因素对瞬间情绪的复杂互动影响 加工、EF和调整。总的来说，该项目符合最新的NIMH战略计划，并将 有助于最常见的情感疾病的更复杂的模型，包括促进图表 疾病轨迹，以帮助确定何时，何地以及如何干预。此外，这项研究将直接 研究关键系统的变化如何影响情绪处理和对厌恶生活的调整 事件，将复杂的影响更直接地拟合到最常见和最繁重的风险模型中 情感性疾病

PROJECT ABSTRACT/SUMMARY The prevalence of psychiatric disorders has reached nearly epidemic proportions. Rates of common affective diseases (unipolar depression, anxiety and stress disorders) are high across the lifespan and these diseases place a tremendous social and economic burden on the individual and society. Clear evidence indicates that most affective disorders emerge at the intersection of pre-existing vulnerability and significant, highly stressful, life-events. However, current models of emotion-related risk do not adequately account for this confluence of biological, historical, and situational factors. In this investigation, we build upon our prior work demonstrating broad associations between flexible emotion processing and psychological health and adjustment, and in-flexible emotion and psychological risk and affective disease. Specifically, we will recruit 400 adults in hospital following a potentially traumatic event (e.g., accident, violence, fire, etc.) in order to model the influence of early emotion processing on trajectories of adjustment. We focus our investigation on the super-ordinate construct of Emotion flexibility (EF) which encompasses the ability to generate or up-regulate emotions, as well as to shift or down-regulate emotions according to needs and/or environmental demands. EF is well-suited to inform models of emotion-related risk and adjustment as it characterizes an optimal balance of two biologically-based, constituent dimensions: “bottom-up” threat-related processing and “top-down” cognitive control increasingly recognized as central to all emotion processing. We propose rigorous methods to assess EF and related processing in-vivo in lab and via experience sampling. Moreover, we will follow participants to 18 months post event so as to effectively model the association between emotion processing and trajectories of adjustment, while also considering established influences such as physical health status, psychiatric history, childhood maltreatment, daily stress/hassles, and social support. In particular, we will incorporate recent developments in advanced statistical modelling to better characterize the complex and interactive influence of historical and contemporary factors on moment-level emotion processing, EF and adjustment. Broadly, this project is in line with the most recent NIMH strategic plan and will contribute to more complex models of the most common affective diseases, including facilitating the charting of illness trajectories to help determine when, where, and how to intervene. Moreover, this research will directly examine how variation in key systems can influence emotion-processing and adjustment to aversive life events, fitting complex influences more directly into models of risk for the most common and burdensome affective diseases.