Using Search Engine Data for Detection and Early Intervention in Suicide Prevention
使用搜索引擎数据进行自杀预防的检测和早期干预
基本信息
- 批准号:10591819
- 负责人:
- 金额:$ 14.96万
- 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:2021-05-05 至 2024-04-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAdministrative SupplementAlgorithmsAmericanAreaAwardBehaviorBehavioralBenefits and RisksBioethical IssuesBioethicsCaringClassificationCommunity WorkersConsentConsultationsDataData SecurityDetectionDevelopmentEarly InterventionEthicistsEthicsEventEyeFeeling suicidalFocus GroupsFundingFutureGrantGuidelinesInternetInterventionInterviewLegalLinguisticsMethodsMonitorMoralsNational Institute of Mental HealthOccupationsOutcomeParentsParticipantPatient Self-ReportPatternPersonsPilot ProjectsPopulationPrivacyProspective StudiesPublic HealthRecommendationRecording of previous eventsResearchResource AllocationResourcesRetrospective StudiesRiskRisk FactorsSeriesStandardizationSuicideSuicide attemptSuicide preventionSurveysTechnologyTimeWorkbasedata accessdata managementdata toolsdigitaldigital healthevidence baseexperiencehealth planinterestmachine learning algorithmmachine learning prediction algorithmprediction algorithmpreventprospectiveresearch studyresponserisk mitigationrisk predictionsearch enginesuicidal behaviorsuicidal risksurveillance datatoolusabilityvolunteer
项目摘要
ABSTRACT. This is a request to supplement grant award R01MH123484 Using Search Engine Data for
Detection and Early Intervention in Suicide Prevention in response to NOT-OD-22-026 Administrative
Supplement for Research and Capacity Building Efforts Related to Bioethical Issues. This supplement proposal
focuses on Bioethics Research. The parent award will determine whether internet search histories and on
search behavior on the Google Search Engine donated by and prospectively collected by people with varying
degrees of suicide risk will be successful in determining proximal risk of suicide. In a previous study, people
with a recent suicide attempt donated retrospective data downloaded from the Google Take Out tool (GTO).
We were able to identify behavioral and linguistic patterns that predicted suicide attempts 30-60 days before
the event occurred. The currently funded study will ask 1,000 people with varying risk for suicide to donate
retrospective data and to continue to donate these data for 1 year. Participants complete a retrospective
interview and prospective surveys every two weeks about the occurrence of suicidal behavior and attempts.
Should we be able to demonstrate to scale the same results we found in the previous pilot project, the data
from this current study could be game changing in the detection of proximal suicide risk. Given that 77 percent
of the US population1 seek information online almost entirely using Google Search, any risk prediction
algorithm and subsequent intervention should be able to reach at-risk Americans to prevent this serious public
health outcome. However, should we be successful, there are a number of ethical, legal, and societal
implications that still need to be addressed. To understand these implications, we will qualitatively interview 50
study participants in a series of focus groups (25 with no previous experience with treatment for suicide and 25
with that experience) and 20 interventionists (clinicians and community workers) about ethical and equitable
application of such an algorithm to interventions to prevent suicide. We include the perspectives of
interventionists in this study to identify where consumers and interventionists agree on ethical, legal, and
societal implications and where there maybe divergence of opinion. Consultation with ethicists will guide the
development of the questions and interpretation of results. Guided by the Digital Health Framework, we will
present participants with different scenarios about privacy concerns (choice to share, what data to share),
risk/benefit concerns (which agent should have access to the MLA and be responsible for acting on a MLA
recommendation), accessibility and usability concerns (diversity representation and access; which
interventions are acceptable with a specific eye toward moral and equitable resource allocation), and data
management concerns (where and how the data should be stored). Participants will also be asked to consider
what potential solutions should be used to address these concerns.
摘要。这是一份补充R01MH123484使用搜索引擎数据的申请
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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Patricia A. Arean其他文献
Patricia A. Arean的其他文献
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{{ truncateString('Patricia A. Arean', 18)}}的其他基金
Using Search Engine Data for Detection and Early Intervention in Suicide Prevention
使用搜索引擎数据进行自杀预防的检测和早期干预
- 批准号:
10401836 - 财政年份:2021
- 资助金额:
$ 14.96万 - 项目类别:
Using Search Engine Data for Detection and Early Intervention in Suicide Prevention
使用搜索引擎数据进行自杀预防的检测和早期干预
- 批准号:
10207109 - 财政年份:2021
- 资助金额:
$ 14.96万 - 项目类别:
UW ALACRITY Center for Psychosocial Interventions Research
华盛顿大学 ALACRITY 心理社会干预研究中心
- 批准号:
10167248 - 财政年份:2018
- 资助金额:
$ 14.96万 - 项目类别:
UW ALACRITY Center for Psychosocial Interventions Research
华盛顿大学 ALACRITY 心理社会干预研究中心
- 批准号:
9914127 - 财政年份:2018
- 资助金额:
$ 14.96万 - 项目类别:
Strategic and Plasticity Interventions for Late Life Depression in Community Settings
社区环境中晚年抑郁症的战略和可塑性干预措施
- 批准号:
9062712 - 财政年份:2015
- 资助金额:
$ 14.96万 - 项目类别:
2/2 Stepped, reward-exposure based therapy vs. PST in late life depression
2/2 阶梯式奖励暴露疗法与 PST 治疗晚年抑郁症的比较
- 批准号:
9251911 - 财政年份:2015
- 资助金额:
$ 14.96万 - 项目类别:
2/2 Stepped, reward-exposure based therapy vs. PST in late life depression
2/2 阶梯式奖励暴露疗法与 PST 治疗晚年抑郁症的比较
- 批准号:
9462224 - 财政年份:2015
- 资助金额:
$ 14.96万 - 项目类别:
Strategic and Plasticity Interventions for Late Life Depression in Community Settings
社区环境中晚年抑郁症的战略和可塑性干预措施
- 批准号:
8996065 - 财政年份:2015
- 资助金额:
$ 14.96万 - 项目类别:
2/2 Stepped, reward-exposure based therapy vs. PST in late life depression
2/2 阶梯式奖励暴露疗法与 PST 治疗晚年抑郁症的比较
- 批准号:
9142355 - 财政年份:2015
- 资助金额:
$ 14.96万 - 项目类别:
2/2 Stepped, reward-exposure based therapy vs. PST in late life depression
2/2 阶梯式奖励暴露疗法与 PST 治疗晚年抑郁症的比较
- 批准号:
8613178 - 财政年份:2014
- 资助金额:
$ 14.96万 - 项目类别:
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