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Passive Assessment of Behavioral Warning Signs for Suicide Risk in Adolescents: An Idiographic Approach

青少年自杀风险行为警告信号的被动评估：一种具体方法

基本信息

批准号：
10433042
负责人：
Taylor A Burke
金额：
$ 11.42万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10433042
关键词：
Acute Adolescent American Behavior assessment Behavioral Cause of Death Cellular Phone Complement Data Sources Detection Distal Environment Event Failure Feeling suicidal Foundations Future Goals Hospitalization Hospitals Individual Influentials Inpatients Intervention Interview Knowledge Measurement Measures Mentorship Methodology Methods Modeling Movement National Institute of Mental Health Participant Pathway Analysis Patient Self-Report Pattern Persons Physical activity Positioning Attribute Process Reinforcing Factor Research Research Design Research Training Resources Rhode Island Risk Risk Assessment Risk Behaviors Risk Factors Science Sleep Structure Suicide Suicide attempt Suicide prevention Surveys Symptoms System Technology Teenagers Text Time Training Universities Youth actigraphy adolescent suicide base career data modeling density digital digital health follow-up high-risk adolescents improved indexing innovation insight medical schools neglect network models personalized intervention programs psychologic recruit reducing suicide sensor social engagement social media suicidal adolescent suicidal behavior suicidal risk suicide rate theories therapy development unsupervised learning

项目摘要

PROJECT SUMMARY/ABSTRACT Suicide is the second leading cause of death among adolescents and the rates have doubled since 2000. The rise in suicide rates is due in part to a failure to identify short-term risk factors for suicidal thoughts and behaviors. Additionally, most existing research relies primarily on group-level methodological approaches to suicide risk assessment; intraindividual suicide risk processes are largely neglected. Because of the lack of knowledge on short-term and individual-level suicide risk, it remains unclear when and how to intervene with the individual adolescents who need it most. Three particularly promising observable, state-sensitive, temporally delimited, and modifiable proximal indicators of suicide risk among adolescents are social engagement, sleep, and physical activity. Although acute changes in these behavioral processes are often denoted as imminent “behavioral warning signs” of suicide, most existing research has examined these behavioral factors only as distal predictors and correlates of suicide risk. Importantly, their contribution to short- term risk using individual-level approaches (i.e., fully idiographic, “n-of-1” methods) remains unknown. The Candidate’s proposed K23’s overarching goal is to employ mobile sensing and actigraphy to assess whether objectively and passively measured acute behavioral changes from typical patterns of social engagement, sleep, and physical activity indicate proximal risk for increases in suicidal ideation using idiographic n-of-1 models in high-risk adolescents. It further aims to characterize the intraindividual network structure of these behavioral factors and suicidal ideation to enhance suicide risk assessment and guide intervention. Adolescents (N=100) admitted to an inpatient or partial hospital program due to acute suicide risk will be recruited. For a period of 3 months, wearable actigraphs will be used to assess adolescents’ sleep and physical activity and mobile sensing will be used to assess adolescents’ digital social engagement and patterns of movement to approximate additional indices of physical activity. Once-daily mobile surveys will be used to assess suicidal ideation. The proposed training plan complements the Candidate’s research plan and will facilitate training in: conducting translational digital health research in high-risk adolescents, passive mobile sensing, passive adolescent sleep and physical activity assessment via actigraphy, and advanced computational approaches to person-specific intensive data modeling. A team of leading scholars will provide expert mentorship to facilitate the Candidate’s training goals within the highly resourced environment of the Alpert Medical School of Brown University and Rhode Island Hospital. The proposed study will promote the Candidate’s long-term career goal to employ low-burden and scalable methods of assessment to develop personalized risk models that will improve the proximal prediction of suicide risk and inform intervention for youth. Through the execution of this research and training plan, the Candidate will be positioned to become a leader in the field of adolescent suicide.

项目总结/文摘