Evidence map›Paper›PMID 33955838›Full record

ArticleJournal of medical Internet research2021

Perceived Utility and Characterization of Personal Google Search Histories to Detect Data Patterns Proximal to a Suicide Attempt in Individuals Who Previously Attempted Suicide: Pilot Cohort Study.

Patricia A Areán, Abhishek Pratap, Honor Hsin, Tierney K Huppert, Karin E Hendricks, Patrick J Heagerty, Trevor Cohen, Courtney Bagge, Katherine Anne Comtois

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Patricia A Areán *Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID 0000-0001-5971-6319
Abhishek Pratap *Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States.ORCID 0000-0002-5289-6932
Honor HsinKaiser Permanente, Northern California, CA, United States.ORCID 0000-0002-0510-7494
Tierney K HuppertDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID 0000-0001-7802-4828
Karin E HendricksDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID 0000-0002-9590-8657
Patrick J HeagertySchool of Public Health, University of Washington, Seattle, WA, United States.ORCID 0000-0002-3403-6007
Trevor CohenDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States.ORCID 0000-0003-0159-6697
Courtney BaggeDepartment of Psychiatry, University of Michigan Medical Center, Ann Arbor, MI, United States.ORCID 0000-0002-9086-8780
Katherine Anne ComtoisDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID 0000-0003-0398-4108

Funding

UW ALACRITY Center for Psychosocial Interventions ResearchP50MH115837 · NIMH · UNIVERSITY OF WASHINGTON · PI Aaron Robert Lyon, Sean Munson · 2018 to 2026
$18.2M
Using Search Engine Data for Detection and Early Intervention in Suicide PreventionR01MH123484 · NIMH · UNIVERSITY OF WASHINGTON · PI COHEN, TREVOR, COMTOIS, KATHERINE ANNE · 2021 to 2023
$2.8M
A Computerized Intervention Targeting Cognitive Control Network Deficits in DepressionR33MH110509 · NIMH · UNIVERSITY OF WASHINGTON · PI ANGUERA, JOAQUIN A, AREAN, PATRICIA A. · 2018 to 2020
$2.0M
SELECTION BIAS BY MEDICARE BENEFICIARIES WITH DIABETESR01HS010230 · AHRQ · UNIVERSITY OF WASHINGTON · PI MACIEJEWSKI, MATTHEW L · 2001 to 2002
–
AHRQ HHS R01 HS010230NIMH NIH HHS P50 MH115837NIMH NIH HHS R01 MH123484NIMH NIH HHS R33 MH110509
6 · The paper itself

Abstract

backgroundDespite decades of research to better understand suicide risk and to develop detection and prevention methods, suicide is still one of the leading causes of death globally. While large-scale studies using real-world evidence from electronic health records can identify who is at risk, they have not been successful at pinpointing when someone is at risk. Personalized social media and online search history data, by contrast, could provide an ongoing real-world datastream revealing internal thoughts and personal states of mind.

objectiveWe conducted this study to determine the feasibility and acceptability of using personalized online information-seeking behavior in the identification of risk for suicide attempts.

methodsThis was a cohort survey study to assess attitudes of participants with a prior suicide attempt about using web search data for suicide prevention purposes, dates of lifetime suicide attempts, and an optional one-time download of their past web searches on Google. The study was conducted at the University of Washington School of Medicine Psychiatry Research Offices. The main outcomes were participants' opinions on internet search data for suicide prediction and intervention and any potential change in online information-seeking behavior proximal to a suicide attempt. Individualized nonparametric association analysis was used to assess the magnitude of difference in web search data features derived from time periods proximal (7, 15, 30, and 60 days) to the suicide attempts versus the typical (baseline) search behavior of participants.

resultsA total of 62 participants who had attempted suicide in the past agreed to participate in the study. Internet search activity varied from person to person (median 2-24 searches per day). Changes in online search behavior proximal to suicide attempts were evident up to 60 days before attempt. For a subset of attempts (7/30, 23%) search features showed associations from 2 months to a week before the attempt. The top 3 search constructs associated with attempts were online searching patterns (9/30 attempts, 30%), semantic relatedness of search queries to suicide methods (7/30 attempts, 23%), and anger (7/30 attempts, 23%). Participants (40/59, 68%) indicated that use of this personalized web search data for prevention purposes was acceptable with noninvasive potential interventions such as connection to a real person (eg, friend, family member, or counselor); however, concerns were raised about detection accuracy, privacy, and the potential for overly invasive intervention.

conclusionsChanges in online search behavior may be a useful and acceptable means of detecting suicide risk. Personalized analysis of online information-seeking behavior showed notable changes in search behavior and search terms that are tied to early warning signs of suicide and are evident 2 months to 7 days before a suicide attempt.

Indexed as

Search EngineSuicide, AttemptedCohort StudiesHumansInformation Seeking BehaviorInternetPilot ProjectsbehavioreHealthEHRinternetmental healthonline seeking behaviorpersonalizedreal-world datarisksearch historysocial mediasuicidesuicide detectionsuicide risk factorsweb searcheswebsite

Identifiers

PMID33955838
PMCPMC8138707

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.