Biological/behavioral rhythms and suicidal behavior: A real-time monitoring study

生物/行为节律和自杀行为：实时监测研究

• 批准号: 9976845
• 负责人: Kelly Zuromski
• 金额: $ 18.7万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9976845
• 关键词: Activity Cycles; Adolescence; Adolescent; Adolescent and Young Adult; Area; Behavioral; Biological; Biological Process; Bipolar Disorder; Cause of Death; Cellular Phone; Chronobiology; Data; Data Analyses; Development; Diagnosis; Diagnostic; Ensure; Exercise; Feeling suicidal; Future; Grain; Growth; Hospitalization; Hour; Individual; Knowledge; Light; Link; Location; Measurement; Mental Depression; Mental disorders; Mentors; Mentorship; Methods; Modeling; Monitor; Moods; Oranges; Participant; Pattern; Periodicity; Pharmaceutical Preparations; Phenotype; Prevention; Process; Psychopathology; Research; Research Personnel; Rest; Risk; Risk Factors; Sampling; Severities; Sleep; Sleep disturbances; Sleeplessness; Structure; Subgroup; Suicide; Suicide attempt; Suicide prevention; Symptoms; Technical Expertise; Technology; Thick; Time; Training; Universities; adolescent suicide; complex biological systems; demographics; design; experience; high risk; high-risk adolescents; ideation; insight; novel; personalized intervention; personalized medicine; prevent; programs; psychologic; real time monitoring; recruit; sedentary; skills; sleep quality; success; suicidal adolescent; suicidal behavior; suicidal risk; technology development; wearable sensor technology

Project Summary/Abstract Suicide is the second leading cause of death among adolescents and young adults. To better predict and prevent suicidal thoughts and behaviors (STBs), identification of proximal, transdiagnostic risk factors that would serve as viable treatment targets is critically needed. Sleep disturbances represent one such risk factor, but understanding of why sleep and STBs are associated is lacking. To better understand the link between sleep and STBs, data are needed on the full 24-h rest-activity cycle, including activity occurring during waking hours. Alterations in sleep and daytime activity are transdiagnostic features of mental disorders, and are both regulated by a complex system of biological and behavioral rhythms. However, these variables have rarely been studied simultaneously or in the context of STBs. In this project, the putative link between the 24-h rest- activity cycle and STBs will be examined using recent advances in technology (i.e., wearable sensors, smartphones) to monitor these processes as they unfold in real-time. A sample of suicidal adolescents (N=100) will be recruited during hospitalization and followed over the high-risk four-week post-hospitalization period. There are three primary research aims: (1) Examine phenotypes of rest-activity associated with suicidal ideation/attempt over the study period, and examine the unique variance contributed by rest-activity variables predicting STBs compared to other well-known factors (e.g., depression), (2) Examine day-to-day associations between rest-activity and STBs to establish strength of associations and proximal directionality, and (3) Explore idiographic (i.e., individual-level) results to examine qualitative differences between participants, a method recently used to identify personalized treatment targets. Results from this project will provide granular insight into the dynamics between putative transdiagnostic risk factors and STBs, and will shed light on the viability of these factors as proximal treatment targets for the candidate’s planned R01. The accompanying training plan is designed to ensure success of the current project and to support growth of the candidate’s independent program of research focused on understanding, predicting, and intervening upon short-term suicide risk by building expertise in four areas: (1) Designing, implementing and managing real-time monitoring studies among high-risk adolescents, (2) Acquiring statistical skills needed to process and analyze intensive longitudinal data, (3) Expanding content-area expertise in biological and behavioral rhythms regulating the rest- activity cycle and related processes, and (4) Preparing for a future R01 by gaining knowledge in development of technology-delivered, personalized interventions for adolescents. This K23 will take place at Harvard University under the mentorship of: mentor Dr. Matthew Nock, a world-leading adolescent suicide researcher, co-mentor Dr. Evan Kleiman, who has technical expertise in collecting and analyzing real-time monitoring data; consultant Dr. Rosalind Picard, an expert in using wearable sensors to study and intervene on psychopathology, and consultant Dr. Frank Scheer, who studies chronobiology and sleep.

项目摘要/摘要 自杀是青少年和年轻人的第二大死亡原因。更好地预测和 预防自杀思想和行为（STB），识别近端，转诊危险因素 需要非常需要作为可行的治疗目标。睡眠灾害代表着一个这样的危险因素， 但是了解为什么缺乏与睡眠和STB相关的原因。更好地了解 睡眠和STB，需要在整个24小时的休息性周期上进行数据，包括在醒来期间发生的活动 小时。睡眠和白天活动的改变是精神障碍的经诊断特征，都是 由复杂的生物和行为节奏系统调节。但是，这些变量很少 很容易或在STB的背景下进行研究。在这个项目中，24小时休息之间的推定联系 - 活动周期和STB将使用技术的最新进展（即可穿戴传感器， 智能手机）以实时进行这些过程进行监视。自杀青少年样本 （n = 100）将在住院期间招募，并遵循高风险的四周后院后 时期。有三个主要的研究目的：（1）检查与自杀相关的休息活性表型 在研究期间的想法/尝试，并检查由静止活性变量贡献的独特差异 与其他知名因素（例如抑郁症）相比，预测STB，（2）检查日常关联 在静止活性和STB之间建立关联和替代方向的力量，以及（3） 探索印度（即个人级别）结果，以检查参与者之间的质差异 最近用于识别个性化治疗目标的方法。该项目的结果将提供颗粒状 深入了解推定的转诊危险因素和STB之间的动态，并将揭示 这些因素的可行性是候选人计划的R01的代理治疗目标。参与 培训计划旨在确保当前项目的成功并支持候选人的成长 独立研究计划的重点是理解，预测和干预短期 通过在四个领域建立专业知识来自杀风险：（1）设计，实施和管理实时监控 高危青少年的研究，（2）获取处理和分析密集所需的统计技能 纵向数据，（3）扩大了在生物学和行为节奏方面的内容区域专业知识，以调查其余的内容 - 活动周期和相关过程，以及（4）通过获得开发知识来为未来的R01做准备 针对青少年的技术传递，个性化的干预措施。这个K23将在哈佛举行 大学的心态：心态：马修·诺克（Matthew Nock）博士，世界领先的青少年自杀研究员， 埃文·克莱曼（Evan Kleiman）博士，他在收集和分析实时监控数据方面具有技术专长； 顾问Rosalind Picard博士，使用可穿戴传感器研究和干预的专家 心理病理学，顾问弗兰克·谢尔（Frank Scheer）博士，研究年代生物学和睡眠。