[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100490823":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":18,"centralContacts":25,"locations":34,"responsibleParty":52,"collaborators":18,"id":56,"slug":57,"hasResults":58,"nctId":59,"briefTitle":60,"officialTitle":60,"acronym":18,"eligibilityCriteria":61,"healthyVolunteers":62,"sex":63,"minAge":64,"maxAge":18,"enrollmentInfo":65,"targetDuration":18,"studyType":68,"phases":69,"briefSummary":71,"conditions":72,"keywords":18,"overallStatus":36,"whyStopped":18,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":79,"completionDateStruct":81,"leadSponsor":83,"locationsCount":84},{"fullName":5,"class":6},"Massachusetts General Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Experimental","EXPERIMENTAL","Investigators will use previously developed EHR-derived machine- learning-based model to generate predicted probability risk scores of 1-month suicide attempt for each patient. The EHR-derived risk score will be combined with the patient self-report data (initially from the 20-question screener) to generate composite predicted risk scores (based on the most updated ML model developed by investigators via the ensemble ML Super Learner \\[SL\\] method) for the patient within minutes of the patient completing the self-report survey. Risk scores will be provided to the clinician while the patient is in the ED. This feedback includes information about the patient's relative risk compared to other psychiatric patients seen in the ED and the risk factors contributing to this level of risk.",[13],"Diagnostic Test: Clinician Decision Support Tool",{"label":15,"type":16,"description":17,"interventionNames":18},"Control","NO_INTERVENTION","Patient's clinician is not given Clinician Decision Support Tool (care as usual)",null,[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":18},"DIAGNOSTIC_TEST","Clinician Decision Support Tool","Clinician Decision Support Tool that provides information about patient's statistical probability of suicide attempt in next 1 month",[9],[26,31],{"name":27,"role":28,"phone":29,"phoneExt":18,"email":30},"Matthew Nock, PhD","CONTACT","617-496-4484","nock@wjh.harvard.edu",{"name":32,"role":28,"phone":18,"phoneExt":18,"email":33},"Amy Ahn, PhD","yahn@fas.harvard.edu",[35],{"facility":5,"status":36,"city":37,"state":38,"zip":39,"country":40,"countryCode":41,"cosmosGeoPoint":42,"geoPoint":47,"contacts":48},"RECRUITING","Boston","Massachusetts","02114","United States","US",{"type":43,"coordinates":44},"Point",[45,46],-71.05977,42.35843,{"lat":46,"lon":45},[49],{"name":50,"role":28,"phone":51,"phoneExt":18,"email":30},"Matthew Nock","6174964484",{"type":53,"investigatorFullName":54,"investigatorTitle":55,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"PRINCIPAL_INVESTIGATOR","Matthew K. Nock, PhD","Research Scientist","100490823","effectiveness-and-implementation-of-a-clinician-decision-support-system-to-prevent-suicidal-behaviors-100490823",false,"NCT05671133","Effectiveness and Implementation of a Clinician Decision Support System to Prevent Suicidal Behaviors","Inclusion Criteria:\n\n* Adult status (≥18 years-old);\n* Willing to provide an email address;\n* Presentation at the APS\n\nExclusion Criteria:\n\n* Inability to understand the study procedures and provide informed consent such as those with gross cognitive impairment (including florid psychosis), intellectual disability, dementia, acute intoxication, or the presence of extremely agitated or violent behavior\n* Decisions about inclusion\u002Fexclusion criteria will be made by the emergency department providers on duty at the time. These broad inclusion criteria maximize the clinical applicability of obtained results while the exclusion criteria ensure the ethical principle of respect for persons.",true,"ALL","18 Years",{"count":66,"type":67},4000,"ESTIMATED","INTERVENTIONAL",[70],"NA","The primary aim of this project are to evaluate a comprehensive, practice-ready, and deployment-focused strategy for improving the prediction and prevention of suicide attempts among a sample of 4,000 patients presenting to an ED with a psychiatric concern. The first aim is to evaluate the effects of providing information about risk of patient suicidal behavior to ED clinicians. The investigators hypothesize that patients randomly assigned to have their clinician receive their risk score will have a lower rate of suicide attempts during 6-month follow-up and that this effect will be mediated by changes in clinician decision-making.",[73,74],"Suicide","Suicide, Attempted","2026-06-16",{"date":77,"type":78},"2026-06-22","ACTUAL",{"date":80,"type":78},"2025-02-25",{"date":82,"type":67},"2028-09-28",{"name":5,"class":6},1]