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

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.

Inclusion Criteria: 1. Age 18 years or greater, male or female; 2. Completed primary school or higher education; 3. Able to use a smartphone or computer to complete online interaction; 4. No history of acute ischemic stroke, systemic lupus erythematosus, gastric ulcer, pneumonia, acute cardiac infarction, urinary tract infection, uterine fibroids, diabetes, osteoarthritis, or migraine. 5. Able to understand and comply with study procedures and to provide written informed consent. Exclusion Criteria: 1. Currently or previously employed as a healthcare worker; 2. Previously received systematic medical training; 3. Currently involved in concurrent research that may interfere with the results of the present trial; 4. The investigator considered that the participant had other conditions that might affect compliance or preclude participation.