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

Condition(s) studied

Investigational drug(s) / intervention(s)

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/no), the type of tool, frequency of use, degree of personalization, and the reported influence of AI use on care-seeking timing.

Study summary

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.

Eligibility

Primary outcome measure(s)

• Shared Decision-Making (SDM-Q-9) — Immediately after the initial physical therapy evaluation (Day 0)
  Patient-perceived involvement in shared decision-making during the initial physical therapy evaluation, measured with the 9-item Shared Decision-Making Questionnaire (SDM-Q-9). Raw total score ranges from 0 to 45; higher scores indicate greater perceived patient involvement in decision-making.

Trial sites (1)

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