Precisely quantifying the dynamic impact of sleep quality on cognitive fluctuations

精确量化睡眠质量对认知波动的动态影响

• 批准号: 10458926
• 负责人: Zoe Hawks
• 金额: $ 6.68万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10458926
• 关键词: Accounting; Adult; Behavior Therapy; Behavioral; Bipolar Disorder; Brain Diseases; Caring; Cellular Phone; Clinical; Cognition; Cognitive; Communities; Complex; Custom; Data; Data Analyses; Development; Diagnosis; Diagnostic; Ecological momentary assessment; Episodic memory; Goals; Guidelines; Impaired cognition; Individual; Institutes; Instruction; Intervention; Knowledge; Longitudinal Studies; Measures; Medicine; Memory; Mental Depression; Mental disorders; Mission; Modeling; Moods; National Institute of Mental Health; Outcome; Participant; Patient Self-Report; Patients; Persons; Phenotype; Process; Psychiatry; Psychometrics; Psychopathology; Public Health; Recommendation; Reproducibility; Research; Research Personnel; Research Proposals; Research Training; Risk; Risk Factors; Sampling; Self Management; Sleep; Sleep disturbances; Specific qualifier value; Technology; Testing; Time; To specify; Training; Treatment Protocols; Variant; Work; actigraphy; arm; base; career; clinical translation; cognitive function; cognitive performance; cognitive testing; digital; effective intervention; empowered; evidence based guidelines; functional outcomes; germine; improved; indexing; individual variation; innovation; personalized approach; post-traumatic stress; processing speed; psychologic; psychosocial; recruit; resilience; severe mental illness; skills; sleep behavior; sleep quality; tool; trait; vigilance

PROJECT SUMMARY Amid the ever-growing number of empirically-supported behavioral treatments, a principal challenge for clinicians is identifying when and for whom a given treatment will be effective (1–4). Extant evidence suggests the utility of sleep interventions to improve cognitive functioning in adults diagnosed with a variety of psychiatric disorders (5–7). Cognitive improvements, in turn, predict psychosocial and adaptive improvements (8–10). However, given that the strength of the association between sleep and cognitive functioning varies across individuals and over time (11–13), it is unlikely that all individuals with impaired cognition will benefit equally from sleep-based cognitive interventions. The long-term goal of this work is to develop and test comprehensive, evidence-based guidelines that will be useful in optimizing cognitive functioning in adults at risk for adverse psychiatric outcomes. The immediate objective of this F32 proposal is to quantify the dynamic impact of sleep on cognitive variation in the context of between- and within-person moderators (e.g., psychiatric traits and states), enabling clinicians to evaluate how patient sleep habits impact cognitive performance and tailor sleep recommendations accordingly. Until recently, technological limitations precluded assessment of the dynamic association between sleep and cognition. To date, most research on the topic has recruited non-clinical samples, imposed non-naturalistic sleep manipulations, and/or evaluated sleep in relation to a single cognitive outcome (most commonly, vigilance) (14). To overcome these barriers to clinical translation, the present study will analyze passive sensing and ecological momentary assessment (EMA) data from large, multisite U01 (AURORA; n=2626) and R01 (total n=600) studies. These studies densely sample sleep (actigraphy-derived), cognitive functioning (processing speed, memory, and vigilance), and psychological state (self-reported) variables in diverse clinical and community samples, affording unprecedented power to develop a generalizable model describing the impact of sleep on cognitive fluctuations, accounting for inter- and intra-individual variability that has heretofore confounded precision approaches to intervention. Specific aims are threefold: (1) to specify the robust impact of sleep on cognitive variation in the context of posttraumatic exposure; (2) to quantify inter- and intra-individual psychopathological factors that influence the strength of the relationship between sleep and cognition; and (3) to examine the generalizability of resultant models in independent clinical and community samples. This contribution is significant because it will facilitate individualized psychotherapeutic interventions, empowering clinicians to customize sleep guidelines to maximally benefit cognition. This proposal is innovative because it entails analysis of data from smartphone- based cognitive measures that participants complete under typical conditions, enhancing ecological validity. Finally, this proposal is instructive because it occasions advanced trainings in precision psychiatry, digital phenotyping, and reproducibility from renowned leaders at McLean’s Institute for Technology in Psychiatry, providing critical knowledge and skills to assist the candidate as she launches an independent research career.

项目摘要 在越来越多的药物支持的行为治疗中，临床医生面临的主要挑战是 确定何时以及对谁有效（1-4）。现有证据表明， 睡眠干预改善被诊断患有各种精神疾病的成年人的认知功能 （5-7）。认知改善，反过来，预测心理和适应性的改善（8-10）。但鉴于 睡眠和认知功能之间的联系强度因人而异， 时间（11-13），不太可能所有认知受损的个体都能从基于睡眠的治疗中平等受益。 认知干预。这项工作的长期目标是开发和测试全面的、基于证据的 这些指南将有助于优化有不良精神病后果风险的成年人的认知功能。 这项F32提案的直接目标是量化睡眠对认知变化的动态影响， 人与人之间和人与人之间的调节者的上下文（例如，精神病学特征和状态），使临床医生能够 评估患者的睡眠习惯如何影响认知表现，并相应地调整睡眠建议。 直到最近，技术上的局限性还阻碍了对睡眠与睡眠之间的动态联系的评估。 认知.到目前为止，大多数关于这一主题的研究都是招募非临床样本， 操作，和/或评估睡眠与单一认知结果（最常见的是，警惕）（14）。 为了克服这些障碍，临床翻译，本研究将分析被动传感和生态 来自大型多中心U 01（AURORA; n=2626）和R 01（总n=600）研究的瞬时评估（EMA）数据。 这些研究密集地对睡眠（活动记录仪得出的）、认知功能（处理速度、记忆力和 警惕性）和心理状态（自我报告）变量在不同的临床和社区样本，提供 开发一个描述睡眠对认知波动影响的可推广模型的前所未有的力量， 解释个体间和个体内的变异性，迄今为止，这种变异性混淆了精确的方法， 干预具体目标有三个方面：（1）明确睡眠对认知变化的强烈影响， 创伤后暴露的背景;（2）量化个体间和个体内的精神病理学因素， 影响睡眠和认知之间关系的强度;（3）检查 在独立的临床和社区样本中得到的模型。这一贡献意义重大，因为它将 促进个性化的心理治疗干预，使临床医生能够定制睡眠指南， 最大限度地提高认知能力。这项建议是创新的，因为它需要分析来自智能手机的数据- 参与者在典型条件下完成的认知测量，增强生态有效性。 最后，这个建议是有指导意义的，因为它的场合先进的培训，精确的精神病学，数字 来自姆克林精神病学技术研究所的著名领导人的表型分析和再现性， 提供关键的知识和技能，以帮助候选人，因为她启动了独立的研究生涯。