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:
    10366067
  • 负责人:
  • 金额:
    $ 19.57万
  • 依托单位:
  • 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

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/摘要 自杀是青少年死亡的第二大原因,自2000年以来,自杀率翻了一番。的 自杀率上升的部分原因是未能确定自杀念头的短期风险因素, 行为。此外,大多数现有的研究主要依赖于群体层面的方法, 自杀风险评估;个体内部自杀风险过程在很大程度上被忽视。因为缺乏 尽管人们对短期和个人自杀风险的认识不足,但仍不清楚何时以及如何进行干预, 最需要帮助的青少年三个特别有希望的可观察的,状态敏感的, 青少年自杀风险的时间界限和可修改的近端指标是社会性的 参与、睡眠和身体活动。虽然这些行为过程中的剧烈变化往往是 被称为即将发生的自杀“行为警告信号”,大多数现有的研究已经检查了这些 行为因素仅作为自杀风险的远端预测因子和相关因子。重要的是,他们的贡献短- 使用个体水平方法的长期风险(即,完全具体的,“n-of-1”方法)仍然未知。的 候选人提出的K23的首要目标是采用移动的传感和活动记录来评估是否 客观和被动地测量典型社会参与模式的急性行为变化, 睡眠和体力活动表明自杀意念增加的近端风险 高危青少年的模型。它进一步旨在描述这些个体内网络结构的特征, 行为因素和自杀意念,以加强自杀风险评估和指导干预。 因急性自杀风险而住院或部分住院治疗的青少年(N=100)将 招募的在为期3个月的时间里,可穿戴活动记录仪将用于评估青少年的睡眠, 身体活动和移动的感知将被用来评估青少年的数字社会参与和模式 以近似身体活动的其他指标。每天一次的移动的调查将用于 评估自杀意念。拟议的培训计划是对候选人研究计划的补充, 促进以下方面的培训:在高危青少年中进行转化数字健康研究,被动移动的 通过体动记录仪进行被动式青少年睡眠和身体活动评估, 计算方法,以个人特定的密集型数据建模。一个由顶尖学者组成的团队将提供 专家指导,以促进候选人的培训目标在高度资源环境的 布朗大学阿尔珀特医学院和罗得岛医院。拟议的研究将促进 候选人的长期职业目标,采用低负担和可扩展的评估方法, 个性化的风险模型,将改善自杀风险的近端预测,并为自杀风险的干预提供信息。 青年通过执行本研究和培训计划,候选人将被定位为 青少年自杀领域的领导者

项目成果

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Taylor A Burke其他文献

Taylor A Burke的其他文献

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{{ truncateString('Taylor A Burke', 18)}}的其他基金

Multimodal Dynamics of Parent-child Interactions and Suicide Risk
亲子互动和自杀风险的多模态动力学
  • 批准号:
    10510227
  • 财政年份:
    2022
  • 资助金额:
    $ 19.57万
  • 项目类别:
Multimodal Dynamics of Parent-child Interactions and Suicide Risk
亲子互动和自杀风险的多模态动力学
  • 批准号:
    10700982
  • 财政年份:
    2022
  • 资助金额:
    $ 19.57万
  • 项目类别:
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
  • 批准号:
    10762701
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:
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
  • 批准号:
    10433042
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:
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
  • 批准号:
    10614509
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:
Leveraging Computer Vision to Augment Suicide Risk Prediction
利用计算机视觉增强自杀风险预测
  • 批准号:
    10285809
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:
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
  • 批准号:
    10190131
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:
Leveraging Computer Vision to Augment Suicide Risk Prediction
利用计算机视觉增强自杀风险预测
  • 批准号:
    10475690
  • 财政年份:
    2021
  • 资助金额:
    $ 19.57万
  • 项目类别:

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越南裔美国父母对其青春期子女的 HPV 疫苗接种情况:对实践、提供者和患者层面影响的检查
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    2015
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