Testing an AI Large Language Model Tool for Cognitive Debiasing in Musculoskeletal Care

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

NCT Number	NCT07022769
Lead Sponsor	University of Texas at Austin
Conditions	Any Chronic, Non-traumatic Orthopedic Condition
Enrollment	150 participants
Start Date	2025-06-23
Primary Completion	2026-03-15 (estimated)
Study Completion	2026-07-31 (estimated)
Updated on ClinicalTrials.gov	2026-06-09