Pre-Visit AI Symptom-Checking and Shared Decision-Making in Spine Physical Therapy

Sponsor
Assiut University
Study ID
NCT07733752
Status
Recruiting
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Conditions

  • Low Back Pain
  • Neck Pain
  • Radiculopathy

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • re-visit AI symptom-checker use — OTHER
    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/no), the type of tool, frequency of use, degree of personalization, and the reported influence of AI use on care-seeking timing.

Study Details

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. This 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. The 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.

Key Dates

First listed
Jul 29, 2026
Start date
Jun 10, 2026
Status verified
Jun 2026
Primary completion
Dec 10, 2026
Completion
Feb 10, 2027

Study Design

Enrollment
200 participants (estimated)

Arms

  • Arm: AI Users
    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.
  • Arm: 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.

Primary Outcome Measure

Shared Decision-Making (SDM-Q-9) [ Time Frame: Immediately after the initial physical therapy evaluation (Day 0) ]

Central Contacts

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