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: 10385808
• 负责人: Kelly Zuromski
• 金额: $ 18.4万
• 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/10385808
• 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.

项目概要/摘要 自杀是青少年和年轻人死亡的第二大原因。为了更好地预测和 预防自杀念头和行为（STB），识别近端、跨诊断的危险因素 迫切需要将其作为可行的治疗目标。睡眠障碍就是这样的危险因素之一， 但对于睡眠和机顶盒为何存在关联，人们还缺乏了解。为了更好地理解之间的联系 睡眠和 STB，需要完整 24 小时休息活动周期的数据，包括清醒时发生的活动 小时。睡眠和白天活动的改变是精神障碍的跨诊断特征，并且两者都是 受生物和行为节律的复杂系统调节。然而，这些变量很少 同时或在 STB 的背景下进行研究。在这个项目中，24 小时休息之间的假定联系 将利用最新的技术进步（即可穿戴传感器、 智能手机）来实时监控这些过程。有自杀倾向的青少年的样本 (N=100) 将在住院期间招募，并在住院后 4 周的高风险期间进行随访 时期。主要研究目标有三个：（1）检查与自杀相关的休息活动表型 在研究期间的构思/尝试，并检查由休息活动变量贡献的独特方差 与其他众所周知的因素（例如抑郁症）相比预测 STB，(2) 检查日常关联 在休息活动和 STB 之间建立关联强度和近端方向性，以及 (3) 探索具体（即个人层面）结果以检查参与者之间的定性差异， 最近用于确定个性化治疗目标的方法。该项目的结果将提供详细的 深入了解假定的跨诊断风险因素和 STB 之间的动态，并将揭示 这些因素作为候选人计划的 R01 的近端治疗目标的可行性。附带的 培训计划旨在确保当前项目的成功并支持候选人的成长 独立的研究计划，侧重于理解、预测和干预短期 通过在四个领域建立专业知识来降低自杀风险：(1) 设计、实施和管理实时监测 对高危青少年的研究，(2) 获得处理和分析强化数据所需的统计技能 纵向数据，（3）扩展生物和行为节律调节休息方面的内容领域专业知识 活动周期和相关流程，以及 (4) 通过获取开发知识为未来的 R01 做好准备 为青少年提供技术提供的个性化干预措施。本次 K23 将在哈佛大学举行 大学在以下导师的指导下：导师 Matthew Nock 博士，世界领先的青少年自杀研究者， 共同导师Evan Kleiman博士，拥有收集和分析实时监测数据的技术专长； 顾问 Rosalind Picard 博士是使用可穿戴传感器研究和干预的专家 精神病理学和顾问弗兰克·谢尔博士研究时间生物学和睡眠。