Health Technology/clinical-trials

Observational Trial Opens: Does Pre-Visit AI Symptom-Checking Alter Shared Decision-Making in Spine Physical Therapy? — What Clinicians Need to Know

247 Health News Editorial

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30 July 2026

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5 min read

·clinical-trials

A new observational cohort study (NCT07733752) is recruiting 200 patients to examine whether pre-visit use of AI symptom-checking tools — including large language models such as ChatGPT — alters shared decision-making and clinical presentation in outpatient spine physiotherapy. With low back and neck pain among the leading causes of global disability, and no current clinical guidelines addressing AI-primed patient consultations, this trial addresses one of the most pressing unanswered questions in contemporary musculoskeletal practice.

Originally reported by ClinicalTrials.gov

References

  1. 1.Assiut University. (2025). When AI is the first clinician: Impact of pre-visit AI use on presentation, diagnostic expectations, and shared decision-making in spine physical therapy (NCT07733752). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07733752
  2. 2.Bickmore, T. W., Trinh, H., Asadi, R., & Olafsson, S. (2018). Safety and quality of chatbot responses to patient questions about medications. JAMA Internal Medicine, 178(12), 1675–1676. https://doi.org/10.1001/jamainternmed.2018.1799
  3. 3.GBD 2021 Low Back Pain Collaborators. (2023). Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: A systematic analysis of the Global Burden of Disease Study 2021. The Lancet Rheumatology, 5(6), e316–e329. https://doi.org/10.1016/S2665-9913(23)00098-X
  4. 4.National Institute for Health and Care Excellence. (2016). Low back pain and sciatica in over 16s: Assessment and management (NICE guideline NG59). NICE. https://www.nice.org.uk/guidance/ng59
  5. 5.Palanica, A., Flaschner, P., Thommandram, A., Li, M., & Fossat, Y. (2019). Physicians' perceptions of chatbots in health care: Cross-sectional web-based survey. Journal of Medical Internet Research, 21(4), e12887. https://doi.org/10.2196/12887
  6. 6.Scholl, I., Koelewijn-van Loon, M., Sepucha, K., Elwyn, G., Légaré, F., Härter, M., & Dirmaier, J. (2011). Measurement of shared decision making — a review of instruments. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, 105(4), 313–324. https://doi.org/10.1016/j.zefq.2011.04.012
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