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:10614509
- 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
- 来源:
- 关键词:AcuteAdmission activityAdolescentAmericanBehavior assessmentBehavioralCause of DeathCellular PhoneComplementData SourcesDetectionDistalEnvironmentEventFailureFeeling suicidalFoundationsFutureGoalsHospitalizationHospitalsIndividualInfluentialsInpatientsInterventionInterviewKnowledgeMeasurementMeasuresMentorshipMethodologyMethodsModelingMovementNational Institute of Mental HealthParticipantPathway AnalysisPatient Self-ReportPatternPersonsPhysical activityPositioning AttributeProcessReinforcing FactorResearchResearch DesignResourcesRhode IslandRiskRisk AssessmentRisk BehaviorsRisk FactorsScienceSleepStructureSuicideSuicide attemptSuicide preventionSurveysSymptomsSystemTechnologyTeenagersTextTimeTrainingUniversitiesYouthactigraphyadolescent suicidecareerdata modelingdensitydigitaldigital deliverydigital healthdynamic systemfollow-uphigh-risk adolescentsimprovedindexinginnovationinsightmedical schoolsmobile sensingneglectnetwork modelspersonalized interventionprogramspsychologicrecruitreducing suicidesensorsocial engagementsocial mediasuicidal adolescentsuicidal behaviorsuicidal individualsuicidal risksuicide ratetheoriestherapy developmentunsupervised learningwearable device
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
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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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:
10366067 - 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:
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:
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: