Improving the Reliability of LLMs as Medical Assistants for the General Public

Recruiting now · Not applicable

Conditions studied: Relevant Conditions Identification

In brief

This study will evaluate whether three-minute six-dimensions education(3M-6D education) can improve the reliability of large language models as medical assistants for the general public. Participants will be randomly assigned to receive or not receive 3M-6D education and then use ChatGPT, Gemini, or non-AI information resources. The study will assess relevant condition identification, disposition concordance, red-flag identification, and NASA-TLX score.

Key facts

Study ID

NCT07651280

Run by

Capital Medical University

People needed

525

Starts

2026-07-03

Expected to finish

2026-07-20

Last updated by the study team

2026-07-07

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Age 18 years or greater, male or female;
• Completed primary school or higher education;
• Able to use a smartphone or computer to complete online interaction;
• No history of acute ischemic stroke, systemic lupus erythematosus, gastric ulcer, pneumonia, acute cardiac infarction, urinary tract infection, uterine fibroids, diabetes, osteoarthritis, or migraine.
• Able to understand and comply with study procedures and to provide written informed consent.

You may not qualify if…

• Currently or previously employed as a healthcare worker;
• Previously received systematic medical training;
• Currently involved in concurrent research that may interfere with the results of the present trial;
• The investigator considered that the participant had other conditions that might affect compliance or preclude participation.

Where it is running

• Beijing Ctiy — Beijing, Beijing Municipality, China (enrolling)

Full record on ClinicalTrials.gov

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