[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100598957":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":25,"centralContacts":30,"locations":25,"responsibleParty":36,"collaborators":40,"id":45,"slug":46,"hasResults":47,"nctId":48,"briefTitle":49,"officialTitle":50,"acronym":25,"eligibilityCriteria":51,"healthyVolunteers":52,"sex":53,"minAge":25,"maxAge":25,"enrollmentInfo":54,"targetDuration":25,"studyType":57,"phases":58,"briefSummary":60,"conditions":61,"keywords":63,"overallStatus":67,"whyStopped":25,"lastUpdateSubmitDate":68,"lastUpdatePostDateStruct":69,"startDateStruct":72,"completionDateStruct":74,"leadSponsor":76,"locationsCount":25},{"fullName":5,"class":6},"Tan Tock Seng Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Intervention Arm","EXPERIMENTAL","Nurses in the intervention arm will perform will receive training on the nature of AI recommender (FAIR) and how it works, and how they can apply it in their assessment of the patient.\n\nAfter that, they will be introduced to three simulated patients with different conditions and needs - intended to reflect a patient at \"low risk of falls\", \"moderate risk of falls\" and \"high risk of falls\" and asked to read and interpret the FAIR recommendations before making their own falls risk assessment of the patient using mWHeFRA.",[13],"Other: Falls risk - Artificial Intelligence Recommender (FAIR)",{"label":15,"type":16,"description":17,"interventionNames":18},"Control arm","PLACEBO_COMPARATOR","Nurses in the control arms will be reinforced on fall risk assessment methods using the modified Western modified Western Health Falls Risk Assessment Tool (mWHeFRA).\n\nAfter that, they will be introduced to three simulated patients with different conditions and needs - intended to reflect a patient at \"low risk of falls\", \"moderate risk of falls\" and \"high risk of falls\" and asked to perform assessments of the patient mWHeFRA.",[19],"Other: modified Western Health Falls Risk Assessment Tool (mWHeFRA)",[21,26],{"type":6,"name":22,"description":23,"armGroupLabels":24,"otherNames":25},"Falls risk - Artificial Intelligence Recommender (FAIR)","FAIR is an alert system built into the hospital's electronic medical record system. It is an adaptation of a machine learning model for fall risk calculation built in another hospital in Singapore. FAIR combines multiple patient-specific variables to identify if a patient is at increased risk of falling during their inpatient stay, marking them as a 'falls risk'.\n\nBased on the 'flag' raised, the nurse will be instructed to prioritise her falls risk assessment of the patient (If deemed 'high risk') or to do so subsequently as a lower priority once other pressing patient care issues are resolved (if deemed 'low risk').\n\nThat way, it ensures the requirements of each patient receiving a falls risk assessment as scored through mWHeFRA are still met, with FAIR allowing nurses to better prioritise their focus and attention on the patient that most needs the assessment at point of admission,",[9],null,{"type":6,"name":27,"description":28,"armGroupLabels":29,"otherNames":25},"modified Western Health Falls Risk Assessment Tool (mWHeFRA)","The mWHeFRA is the hospital's standard falls risk assessment tool. All nurses are expected to be proficient in its use to guide their risk assessment of patients",[15],[31],{"name":32,"role":33,"phone":34,"phoneExt":25,"email":35},"George Glass, PhD Student","CONTACT","+65 6903-5384","GLAS0002@e.ntu.edu.sg",{"type":37,"investigatorFullName":38,"investigatorTitle":39,"investigatorAffiliation":5,"oldNameTitle":25,"oldOrganization":25},"PRINCIPAL_INVESTIGATOR","Glass George Frederick Jr","Deputy Head of Nursing Research",[41,43],{"name":42,"class":6},"Marquette University",{"name":44,"class":6},"Nanyang Technological University","100598957","examining-nurses-trust-and-acceptance-of-fair-an-ai-powered-falls-risk-recommender-100598957",false,"NCT07078240","Examining Nurses' Trust and Acceptance of FAIR, an AI-powered Falls Risk Recommender","\"You Sure or Not?\" Examining the Trust, Acceptance and Adoption of Falls Risk - Artificial Intelligence Recommender (FAIR) System by Nurses","Inclusion Criteria:\n\n* Practicing nurse involved in falls risk assessments of patients\n\nExclusion Criteria:\n\n\\-",true,"ALL",{"count":55,"type":56},60,"ESTIMATED","INTERVENTIONAL",[59],"NA","An exploratory mixed-method study will be conducted to test acceptance and trust of an AI-powered falls risk predictor system by inpatient hospital nurses",[62],"Falls Risk",[64,65,66],"Artificial Intelligence trust","Artificial Intelligence acceptance","Artificial Intelligence","NOT_YET_RECRUITING","2025-07-21",{"date":70,"type":71},"2025-07-22","ACTUAL",{"date":73,"type":56},"2027-01-01",{"date":75,"type":56},"2029-06-30",{"name":5,"class":6}]