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Improving the Reliability of LLMs as Medical Assistants for the General Public
Sponsor: Capital Medical University
Summary
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.
Official title: Improving the Reliability of LLMs as Medical Assistants for the General Public: a Proof of Concept Simulation Trial
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
525
Start Date
2026-06-20
Completion Date
2026-07-20
Last Updated
2026-06-25
Healthy Volunteers
Yes
Conditions
Interventions
three minutes six dimensions education
3M-6D education is designed based on Cognitive Load Theory to reduce the cognitive burden on patients during medical interactions with AI and to improve the clarity and completeness of symptom reporting. Guided by cognitive load theory and the natural process physicians use to take medical histories, the investigators identified candidate information dimensions and developed a structured expression framework with six dimensions for public health queries through a Delphi expert consensus process. Participants were instructed to use the framework to describe their symptoms across these six dimensions; this process can typically be completed within three minutes, so the investigators call this approach three minutes six dimensions education (3M-6D education).
ChatGPT
Participants use ChatGPT to complete a standardized simulated clinical scenarios in unrestricted natural language.
Gemini
Participants use Gemini to complete a standardized simulated clinical scenarios in unrestricted natural language.
Locations (1)
Xuanwu Hospital, Capital Medical University
Beijing, Beijing Municipality, China