Testing an AI Large Language Model Tool for Cognitive Debiasing in Musculoskeletal Care
Active, not recruitingNot applicableNCT07022769
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This study has no listed site in Canada in this snapshot. It is included as part of the worldwide chronic pain corpus.
Brief summary (from the registry)
The goal of this clinical trial is to find out whether using an artificial intelligence (AI) tool called a Large Language Model (LLM) can help patients think more clearly about their symptoms and improve their trust and experience during a visit to a musculoskeletal specialist. The study will answer two main questions: 1. Does an LLM-guided checklist that encourages patients to reflect on their beliefs about their symptoms improve their trust in the clinician (measured using the TRECS-7 scale)? 2. Does the checklist improve how patients feel about their consultation overall? Participants will be randomly assigned to one of two groups: * One group will receive an LLM-guided checklist that helps them think more flexibly about their condition. * The other group will receive an LLM-generated likely diagnosis and brief explanation of their symptoms. In both groups, the information from the AI tool will be shared with both the patient and the clinician before the consultation. Patients in the debiasing (intervention) group will: * Complete a short set of questions with help from a researcher * Receive a simple summary from the AI that reflects their beliefs and gently challenges any unhelpful thinking * Attend their regular specialist appointment * Complete a short survey afterwards capturing their thoughts, experience and basic demographics Patients in the diagnosis-only (control) group will: * Describe their symptoms to the AI LLM * Receive a likely diagnosis and short explanation based on this description * Attend their regular specialist appointment * Complete a short survey afterwards capturing their thoughts, experience and basic demographics
Study details
- Official title
- Comparison of a Large Language Model (LLM)-Facilitated Cognitive Debiasing Strategy Versus LLM-Generated Diagnostic Feedback Alone in Musculoskeletal Specialty Care: A Randomized Controlled Trial
- Conditions
- Any Chronic, Non-traumatic Orthopedic Condition
- Interventions
- Behavioral: LLM-facilitated cognitive debiasing aid
- Sponsor
- University of Texas at Austin
- Start date
- 2025-06-23
- Primary completion
- 2026-03-15
- Sex
- All
- Age range
- from 18 Years
- Results posted
- No results posted in this snapshot
- Countries
- United States
- Total sites listed
- 1
Eligibility criteria
Show eligibility criteria (verbatim from the registry)
Inclusion Criteria: * Adults (18+) * New or return patient seeking musculoskeletal specialty care at an Orthopedic outpatient clinic * Total combined score on the 6 feelings and thoughts items of \> 10\* (Appendix 3 of study protocol) * English-speaking * Pre-visit diagnosis of chronic, non-traumatic musculoskeletal condition (including, but not limited to: osteoarthritis, carpal tunnel syndrome, trigger digit, Dupuytren's, De Quervain's, lateral epicondylitis) Exclusion Criteria: * Any impairment preventing completion of surveys on a tablet
Source: ClinicalTrials.gov (US National Library of Medicine), snapshot October 2026. Check the registry for current recruiting status. Record: https://clinicaltrials.gov/study/NCT07022769