Dynamic Impacts of Sleep Disruption on Ecologically Assessed Affective, Behavioral, and Cognitive Risk Factors for Suicide

项目总结/摘要 自杀意念和行为是美国日益严重的公共卫生问题。不幸的是，我们目前 预测自杀的能力仅略高于偶然性，这可能是由于过度依赖 远端/横断面风险因素是自杀风险的弱近端预测因子。对复杂过程进行建模 非典型睡眠对日常功能的影响，加上确定的近端风险因素， 识别最大自杀风险的背景和时间段，在个人水平上建模。拟定研究 建立在我们团队在睡眠/觉醒周期，心理生理学，深度表型分析， 多方法，多变量，生态有效的模型自杀脆弱性在高风险的精神病人群。 我们将研究非典型睡眠的整体模型与已知特征（基线神经认知）的关系， 性能;例如，更大的冲动倾向，更高的损失敏感性，降低调节情绪的能力）， 状态（时变的，在SI/SB之前数小时至数天发生;例如，情绪反应的瞬间波动 冲动;更大的情绪不稳定;更大的孤立倾向），自杀的风险因素，并研究如何 这些因素一起在近端影响自杀意念并赋予未来自杀行为的风险。我们将 招募200名自杀风险高的精神病住院患者，并进行睡眠/觉醒的基线评估 功能和特征风险因素，并使用基于实验室的任务加上心理生理学（即，事件- 相关电位、心率变异性和皮肤电活动）与觉醒相关的表型风险过程之间的关系 和认知系统。该基线评估之后将进行为期四周的EMA和数字表型分析 结合SAFTE衍生的体动记录来表征关键状态风险因素。我们会跟进 出院后1个月、3个月和6个月的评估，以确定我们的近端风险模型 前瞻性预测SI和SB。拟议的研究旨在描述自杀的近端风险， 密集的纵向方法，并确定自杀风险最大的“窗口”，这可能因人而异 对人来说，这是强化干预的标志。最后，我们将利用这个广泛的数据集， 建立一个睡眠与自杀关系的模型，强调特质和状态因素的作用。的 这项研究的结果有可能大大提高我们对自杀现象的理解 风险，因为它存在于真实的世界，有可能提高我们的能力，预测，预防和干预使用 传统的和科技强化的心理治疗。

Project Summary/Abstract Suicidal ideation and behavior are growing public health problems in the United States. Unfortunately, our current ability to predict suicide is only slightly above chance, which may be attributable to an overreliance on distal/cross-sectional risk factors that are weak proximal predictors of suicide risk. Modeling the complex process by which atypical sleep impacts daily functioning in conjunction with established proximal risk factors can aid in identifying contexts and time periods of greatest suicidal risk, modeled at the individual level. The proposed study builds upon our team’s extensive expertise in sleep/wake cycles, psychophysiology, deep phenotyping, and multi-method, multivariate, ecologically valid models of suicide vulnerability in high-risk psychiatric populations. We will examine how a holistic model of atypical sleep relates to known trait (baseline neurocognitive performance; e.g., greater impulsive tendencies, higher loss sensitivity, reduced ability to regulate emotions) and state (time-varying, occurring hours to days before SI/SB; e.g., momentary fluctuations in emotional reactivity, impulsivity; greater emotional lability; greater isolative tendencies), risk factors for suicide, and examine how these factors together proximally influence suicidal ideation and confer risk for future suicidal behavior. We will recruit 200 psychiatric inpatients at high risk for suicide and conduct a baseline assessment of sleep/wake functioning and trait risk factors and use laboratory-based tasks coupled with psychophysiology (i.e., event- related potentials, heart rate variability, and electrodermal activity) to phenotype risk processes linked to arousal and cognitive systems. This baseline assessment will be followed by four weeks of EMA and digital phenotyping coupled with SAFTE-derived actigraphy to characterize key state risk factors. We will conduct follow-up assessments at 1-, 3-, and 6-months post hospital discharge to determine how our proximal model of risk prospectively predicts SI and SB. The proposed study aims to characterize proximal risk for suicide using intensive longitudinal methods and to identify “windows” of greatest risk for suicide, which may vary from person to person, that serve as markers for intensive intervention. Finally, we will leverage this extensive dataset to develop a model of the sleep-suicide relationship emphasizing the contribution of trait and state factors. The results of this study have the potential to greatly enhance our understanding of the phenomenology of suicide risk as it exists in the real world, with the potential to improve our ability to predict, prevent, and intervene using both traditional and technology-enhanced psychotherapies.