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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

基本信息

批准号：
10601052
负责人：
Kelly Zuromski
金额：
$ 18.15万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10601052
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 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 Time Training Universities Visualization adolescent suicide complex biological systems demographics design experience high risk high-risk adolescents ideation insight novel personalized intervention personalized medicine programs psychologic real time monitoring recruit sedentary skills sleep quality success suicidal adolescent suicidal behavior suicidal risk suicide rate technology development wearable sensor technology

项目摘要

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.

项目总结/摘要自杀是青少年和年轻人死亡的第二大原因。更好地预测和预防自杀想法和行为（STBs），识别近端、跨诊断风险因素，作为可行的治疗靶点。睡眠障碍是其中一个危险因素，但对睡眠和性传播疾病之间的联系还缺乏了解。为了更好地理解睡眠和STB，需要完整的24小时休息-活动周期的数据，包括清醒期间发生的活动小时睡眠和日间活动的改变是精神障碍的转诊断特征，由一个复杂的生物和行为节律系统来调节。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- 活动周期和STB将使用技术的最新进展进行检查（即，可穿戴传感器，智能手机）来实时监控这些过程。自杀青少年样本（N=100）将在住院期间招募，并在高风险住院后四周内进行随访期本研究的主要目的有三：（1）研究与自杀相关的静息-活动表型在研究期间的想法/尝试，并检查由休息活动变量贡献的独特方差与其它公知的因素相比预测STB（例如，抑郁症），（2）检查日常联系在休息-活动和STB之间建立关联强度和近端方向性，以及（3）探索具体的（即，个人水平）的结果，以检查参与者之间的质的差异，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深入了解推定的转诊断风险因素和STBs之间的动态，并将阐明这些因素作为候选人计划R 01的近端治疗目标的可行性。所附培训计划旨在确保当前项目的成功，并支持候选人的成长。一个独立的研究项目，专注于理解，预测和干预短期的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高危青少年的研究，（2）获得处理和分析密集所需的统计技能纵向数据，（3）扩大生物和行为节律调节其余内容领域的专业知识- 活动周期和相关过程，以及（4）通过获得开发知识为未来的R 01做准备为青少年提供的个性化的技术干预。这个K23将在哈佛举行大学的指导下：导师马修诺克博士，世界领先的青少年自杀研究，共同导师Evan Kleiman博士，他在收集和分析实时监测数据方面具有技术专长; 顾问Rosalind Picard博士是使用可穿戴传感器研究和干预心理病理学和研究时间生物学和睡眠的顾问弗兰克·谢尔博士。