[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100649474":3},{"organization":4,"armGroups":7,"interventions":17,"overallOfficials":10,"centralContacts":22,"locations":28,"responsibleParty":43,"collaborators":10,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":10,"eligibilityCriteria":53,"healthyVolunteers":49,"sex":54,"minAge":55,"maxAge":10,"enrollmentInfo":56,"targetDuration":59,"studyType":60,"phases":10,"briefSummary":61,"conditions":62,"keywords":66,"overallStatus":31,"whyStopped":10,"lastUpdateSubmitDate":73,"lastUpdatePostDateStruct":74,"startDateStruct":77,"completionDateStruct":79,"leadSponsor":81,"locationsCount":82},{"fullName":5,"class":6},"Assiut University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI Users",null,"Patients who reported using an AI-based symptom-checking tool (e.g., a large language model such as ChatGPT) for their current spine-related complaint within the 30 days before their initial physical therapy evaluation.",[13],"Other: re-visit AI symptom-checker use",{"label":15,"type":10,"description":16,"interventionNames":10},"Non-AI Users","Patients who reported no use of any AI-based symptom-checking tool for their current spine-related complaint within the 30 days before their initial physical therapy evaluation.",[18],{"type":6,"name":19,"description":20,"armGroupLabels":21,"otherNames":10},"re-visit AI symptom-checker use","Self-reported use of an AI-based symptom-checking tool (e.g., a large language model such as ChatGPT) for the current spine-related complaint during the 30 days before the initial physical therapy evaluation. This exposure occurs naturally prior to presentation and is not assigned by the investigator. Exposure status is ascertained at baseline via a questionnaire capturing whether AI was used (yes\u002Fno), the type of tool, frequency of use, degree of personalization, and the reported influence of AI use on care-seeking timing.",[9],[23],{"name":24,"role":25,"phone":26,"phoneExt":10,"email":27},"Mariam A Ibrahim Principal investigator","CONTACT","+20 10 01539399","Mariam.A.ibrahim@med.aun.edu.eg",[29],{"facility":30,"status":31,"city":32,"state":10,"zip":10,"country":33,"countryCode":34,"cosmosGeoPoint":35,"geoPoint":40,"contacts":41},"Faculty of Medicine, Assiut University, Egypt","RECRUITING","Asyut","Egypt","EG",{"type":36,"coordinates":37},"Point",[38,39],31.18368,27.18096,{"lat":39,"lon":38},[42],{"name":24,"role":25,"phone":26,"phoneExt":10,"email":27},{"type":44,"investigatorFullName":45,"investigatorTitle":46,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Mariam ibrahim","Researcher","100649474","pre-visit-ai-symptom-checking-and-shared-decision-making-in-spine-physical-therapy-100649474",false,"NCT07733752","Pre-Visit AI Symptom-Checking and Shared Decision-Making in Spine Physical Therapy","When AI Is the First Clinician: Impact of Pre-Visit AI Use on Presentation, Diagnostic Expectations, and Shared Decision-Making in Spine Physical Therapy","Inclusion Criteria:\n\n* Age: 18 years or older\n* Presenting for a new evaluation at an outpatient physical therapy clinic for a spine-related musculoskeletal complaint, including Neck, Thoracic, and Low back pain With or without radicular symptoms\n* Able to provide informed consent.\n* Able to read, understand, and complete study questionnaires\n\nExclusion Criteria:\n\n* Recent spinal surgery within the past 3 months, due to differing clinical pathways and management strategies.\n* Presence of serious spinal pathology under active medical management, such as:\n\nMalignancy (e.g., metastatic disease) Spinal infection Acute fracture\n\n* Cognitive impairment or other conditions that limit the ability to provide informed consent or reliably complete study measures.\n* Patients currently enrolled in another study that may influence clinical decision-making or outcomes related to spine care.","ALL","18 Years",{"count":57,"type":58},200,"ESTIMATED","6 Weeks","OBSERVATIONAL","Artificial intelligence (AI) symptom-checking tools, including large language models such as ChatGPT, are increasingly used by patients before they seek care. These tools may shape patients' beliefs about their diagnosis, how serious they think their condition is, and when they decide to seek treatment. It is not yet known how this pre-visit AI use affects the initial physical therapy encounter for spine-related problems.\n\nThis prospective observational cohort study examines whether prior use of AI symptom-checking tools influences the first physical therapy evaluation in adults presenting with spine-related musculoskeletal complaints (neck, thoracic, or low back pain, with or without radicular symptoms). Consecutive patients attending an outpatient physical therapy clinic for a new evaluation are grouped as AI users or non-AI users based on whether they used such a tool for their current complaint in the previous 30 days.\n\nThe primary outcome is shared decision-making, measured with the SDM-Q-9 immediately after the initial evaluation. Secondary outcomes include stage of presentation, agreement between the patient's expected diagnosis and the clinician's classification, baseline pain and disability, functional performance, and clinical outcomes at 2 and 6 weeks. The investigators hypothesize that prior AI use is associated with differences in shared decision-making and in how patients present for care.",[63,64,65],"Low Back Pain","Neck Pain","Radiculopathy",[67,68,69,70,71,72],"Artificial intelligence","ChatGPT","Shared decision-making","SDM-Q-9","Spine","Patient expectations","2026-07-24",{"date":75,"type":76},"2026-07-29","ACTUAL",{"date":78,"type":76},"2026-06-10",{"date":80,"type":58},"2027-02-10",{"name":5,"class":6},1]