[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"medical-malpractice\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:medical-malpractice":26},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":15,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":22,"briefSummary":24,"conditions":25,"keywords":29,"overallStatus":33,"whyStopped":4,"lastUpdateSubmitDate":34,"lastUpdatePostDateStruct":35,"startDateStruct":38,"completionDateStruct":40,"leadSponsor":42,"locationsCount":4},"100659691","the-impact-of-ai-assisted-diagnosis-and-treatment-on-physicians-potential-legal-liability-an-expert-perspective-100659691",false,"NCT07869303","The Impact of AI-Assisted Diagnosis and Treatment on Physicians' Potential Legal Liability: An Expert Perspective","Inclusion Criteria:\n\n1. Physicians qualified to participate in medical negligence assessments, generally holding the title of associate chief physician or above and having relevant clinical experience; or forensic medical experts affiliated with an officially recognized forensic assessment institution and qualified to conduct medical negligence assessments independently.\n2. Able to read and understand the clinical vignettes and complete the online survey independently.\n\nExclusion Criteria:\n\n1. Physicians who are not qualified to participate in medical negligence assessments.\n2. Forensic medical experts who are not qualified to conduct medical negligence assessments independently or are not affiliated with an officially recognized forensic assessment institution.\n3. Unable to understand or complete the vignette-based online survey.",true,"ALL","18 Years",{"count":19,"type":20},440,"ESTIMATED","INTERVENTIONAL",[23],"NA","The goal of this randomized vignette-based experiment is to investigate how AI-related contextual factors influence expert assessment of physician negligence in AI-assisted diagnosis and treatment scenarios among experts in medical malpractice assessment.\n\nThe main questions it aims to answer are:\n\nDoes physician acceptance or rejection of AI recommendations, compared with non-AI use, influence the likelihood of being assessed as negligent?\n\nResearchers will compare a no-AI assistance control group with four AI-assistance groups under different AI use conditions to examine how AI involvement and contextual factors affect assessments of physician negligence.\n\nParticipants will:\n\nComplete a web-based questionnaire after eligibility confirmation. Evaluate a series of clinical vignettes describing adverse patient outcomes following physician decision-making under different AI-use conditions.",[26,27,28],"Medical Malpractice","Artificial Intelligence in Medicine","Clinical Decision-Making",[30,31,32],"Artificial intelligence","clinical decision support","medical negligence","NOT_YET_RECRUITING","2026-10-07",{"date":36,"type":37},"2026-10-09","ACTUAL",{"date":39,"type":20},"2026-09-30",{"date":41,"type":20},"2027-08-20",{"name":43,"class":44},"Xie Xiaoyun","OTHER"]