2022
Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder
Sankar A, Scheinost D, Goldman DA, Drachman R, Colic L, Villa LM, Kim JA, Gonzalez Y, Marcelo I, Shinomiya M, Pittman B, Lacadie CM, Oquendo MA, Constable RT, Blumberg HP. Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder. Translational Psychiatry 2022, 12: 7. PMID: 35013103, PMCID: PMC8748935, DOI: 10.1038/s41398-021-01767-z.Peer-Reviewed Original ResearchConceptsIntrinsic connectivity distributionBipolar disorderSuicide attemptsHealthy volunteersFunctional connectivity disturbancesSuicide behaviorWhole-brain functional connectivityPrior suicide attemptsRight anterior insulaBrain functional connectivitySuicidal ideation severityBilateral ventromedial prefrontal cortexFunctional magnetic resonanceSignificant group differencesTemporopolar cortexConnectivity disturbancesBrain targetsFC differencesHigh riskCerebellar cortexVentromedial prefrontal cortexSuicidal ideationOrbitofrontal cortexFunctional connectivitySuicide risk
2021
A model for the assessment, care, and treatment of suicidal risk within the military intelligence community
Van Dillen T, Kane R, Bunney B, Feuerstein S, Hopkins C, Raimo J, Stubbs T, Jobes D. A model for the assessment, care, and treatment of suicidal risk within the military intelligence community. Military Psychology 2021, 34: 345-351. PMID: 38536342, PMCID: PMC10013476, DOI: 10.1080/08995605.2021.1962185.Peer-Reviewed Original ResearchArmy Public Health CenterBehavioral healthBehavioral health accessPublic Health CenterBehavioral health providersHealth assessment surveyHealth centersHealth promotionSleep healthSuicidal riskHealth providersHealth accessSurgeon's officeCare deliveryClinical suicidologyHealth stigmaSuicide behaviorHealth assessmentWellness modelHealthAssessment surveySuicideCareFocus groupsReport findings
2019
Exploring temporal suicidal behavior patterns on social media: Insight from Twitter analytics
Luo J, Du J, Tao C, Xu H, Zhang Y. Exploring temporal suicidal behavior patterns on social media: Insight from Twitter analytics. Health Informatics Journal 2019, 26: 738-752. PMID: 30866708, DOI: 10.1177/1460458219832043.Peer-Reviewed Original ResearchConceptsRisk factorsDifferent risk factorsPotential suicidal ideationPublic health servicesKey risk factorsSuicide-related tweetsPrevention strategiesHealth servicesSuicidal ideationSuicide behaviorSuicide detectionSuicide ratesDifferent daysWider populationTemporal patternsBehavior patternsPopulationFactorsWeeks
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