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Testing an AI Tool for Thinking About Musculoskeletal Pain

This study is testing an artificial intelligence (AI) tool called a Large Language Model (LLM) to see if it can help patients with chronic, non-traumatic orthopedic conditions better understand their symptoms. The LLM tool will ask you questions about your beliefs regarding your symptoms to help you think more clearly. Researchers want to know if this tool improves your trust in your doctor and your overall experience during your visit. You can join if you are an adult (18+) seeking musculoskeletal care, speak English, and have a chronic orthopedic condition. The study aims to enroll 150 participants. The main goal is to see how the LLM tool affects your trust and experience with your clinician, measured right after your consultation.

Study design
This is an interventional study that plans to enroll 150 participants. Participants will be randomly assigned to one of two groups.
What's involved
You will respond to a series of questions about your beliefs regarding your symptoms, with your answers recorded via a tablet.
Compensation
Not stated in the trial record.
Follow-up
Your trust and experience with the clinician will be measured once, immediately following your consultation with the musculoskeletal specialist.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07022769

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

Active, Not Recruiting
NAAges 18+InterventionalSupportive care
University of Texas at Austin
~150 participants
Updated 2026-06-09 on ClinicalTrials.gov
What's tested:LLM-facilitated cognitive debiasing aid

At a glance

Recruiting sites
0 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Trust and Experience with the Clinician Scale (TRECS-7)
Measured over Measured once, immediately following consultation with the musculoskeletal specialist

Conditions

Any Chronic, Non-traumatic Orthopedic Condition

Explore related trials

Musculoskeletal Disorder

NCT07022769

Where you'd take part

This study runs at 1 site. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • Dell Medical School, University of Texas at Austin

    Austin, Texasno site contact published

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

Study leadership

  • David Ring, MD, PhD · STUDY_DIRECTOR · Dell Medical School, University of Texas at Austin, TX, United States

Who to contact

This trial hasn't published a contact. View it on ClinicalTrials.gov

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Eligibility criteria

Inclusion

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

Any impairment preventing completion of surveys on a tablet

What this trial measures

  • Trust and Experience with the Clinician Scale (TRECS-7)Measured once, immediately following consultation with the musculoskeletal specialist

    The Trust and Experience with the Clinician Scale (TRECS-7) is a validated 7-item scale that measures patients' trust in and experience with their clinician during a medical consultation. Designed to minimize ceiling effects, it enables more sensitive detection of variation in patient experience across different clinical interactions (Brinkman et al.). Each of 7 statements is scored from 0-4 (strongly disagree, disagree, neutral, agree, strongly agree), resulting in a total score between 0 and 28. Higher scores indicate greater perceived trust in the clinician. Source: Brinkman N, Looman R, Jayakumar P, Ring D, Choi S. Is It Possible to Develop a Patient-reported Experience Measure With Lower Ceiling Effect? Clin Orthop Relat Res. 2025 Apr 1;483(4):693-703.