grant
Optimizing Brief Coping Skills Interventions for Suicide Prevention: Leveraging Technology and Novel Statistical Models for Precision Mental Health
Organization OHIO STATE UNIVERSITYLocation Columbus, UNITED STATESPosted 1 Dec 2024Deadline 30 Nov 2029
NIHUS FederalResearch GrantFY2026Active Follow-upAddressAffectiveAgitationAreaAutomobile DrivingBehaviorBehavioralCaringCause of DeathCell Communication and SignalingCell SignalingCharacteristicsClinicalCognitionCognitiveComputer ModelsComputerized ModelsCoping SkillsCritical CareDataDetectionDevelopmentDistressEcological momentary assessmentEvidence based practice guidelinesFeeling suicidalHistoryIndividualInterventionIntervention StrategiesIntracellular Communication and SignalingKnowledgeLifeMental HealthMental Health ServicesMental HygieneMental Hygiene ServicesMethodsModelingNIMHNational Institute of Mental HealthNational Institutes of HealthObservational StudyPatient outcomePatient-Centered OutcomesPatient-Focused OutcomesPatientsPatternPeriodicalsPopulationPreventionPrevention ResearchProbabilistic ModelsProbability ModelsProviderPsychological HealthPsychomotor AgitationPsychomotor ExcitementPsychomotor HyperactivityPsychomotor RestlessnessRecommendationRecording of previous eventsReportingResearchRestlessnessRiskRisk FactorsRisk ManagementRisk ReductionSafetySamplingSeveritiesSignal TransductionSignal Transduction SystemsSignalingSleepStatistical ModelsSuicidal thoughtsSuicideSuicide attemptSuicide precautionSuicide preventionTechnologyTechnology AssessmentTimeUnited StatesUnited States National Institutes of HealthVariantVariationWithdrawalWorkactive followupadvanced analyticsanalytical methodbiological signal transductionclinical practicecomparativecomputational modelingcomputational modelscomputer based modelscomputerized modelingcoping strategycost effectivedata captured from wearablesdata collected from wearablesdata collected using wearablesdata gathered from wearabledata gathered through wearablesdata gathered via wearabledevelopmentaldigital healthdigital mental healthdrivingemotional distressevidence based guidelinesevidence based recommendationsexperiencefatal attemptfatal suicidefeeling distressfeeling upsetfitnessfollow upfollow-upfollowed upfollowuphigh riskhistoriesimprovedinpatient psychiatric careinpatient psychiatric treatmentinsightintent to dieintervention deliverymembermental health carenon fatal attemptnonfatal attemptnovelobservational research studyobservational surveyparticipant engagementpatient engagementpatient oriented outcomespatient profileperiodicperiodicalprecision medicineprecision-based medicinepreservationprevent suicidalityprevent suicideprofiles in patientsprototypepsychiatric hospitalizationpsychiatric inpatientpublic health emergencyreduce riskreduce risksreduce suicidalityreduce suicidereduce that riskreduce the riskreduce these risksreduces riskreduces the riskreducing riskreducing suicidalityreducing suicidereducing the riskresponserisk-reducingruminateruminationruminativeskillssocialstatistical linear mixed modelsstatistical linear modelssuccesssuicidalsuicidal attemptsuicidal behaviorsuicidal ideationsuicidal patientsuicidal risksuicidal thinkingsuicidalitysuicidality preventionsuicide behaviorsuicide ideationsuicide interventionsuicide modelsuicide patientsuicide ratesuicide risksuicidesthoughts about suicidewearablewearable datawearable devicewearable device datawearable electronicswearable sensor datawearable systemwearable technologywearable toolwearables
Description preview
Abstract
Suicide is a leading cause of death in the United States. Patients who have recently been discharged from an
inpatient psychiatric hospitalization are at particularly elevated risk for suicide. Although safety planning
interventions (SPIs) are provided to many patients to alleviate risk, the success of these approaches relies on
patients'…
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