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.
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.
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.
Parallel
three minutes six dimensions education
Behavioral3M-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
Other interventionParticipants use ChatGPT to complete a standardized simulated clinical scenarios in unrestricted natural language.
Gemini
Other interventionParticipants use Gemini to complete a standardized simulated clinical scenarios in unrestricted natural language.
Relevant conditions identification of the 3M-6D education GPT group compared with the GPT group
Relevant conditions identification is defined as the proportion of participants whose final response includes the expert-defined final diagnosis or a relevant differential diagnosis.
Disposition concordance of the 3M-6D education GPT group compared with the GPT group
Disposition concordance is defined as the proportion of participants whose final care recommendation matches the expert-defined level. The five levels are self-care, routine outpatient care, urgent outpatient care, emergency department visit, and emergency medical services.
Relevant conditions identification of the 3M-6D education Gemini group compared with the Gemini group
Disposition concordance of the 3M-6D education Gemini group compared with the Gemini group
Relevant conditions identification of the 3M-6D education GPT group compared with the control group
Relevant conditions identification of the 3M-6D education Gemini group compared with the control group
Disposition concordance of the 3M-6D education GPT group compared with the control group
Disposition concordance of the 3M-6D education Gemini group compared with the control group
Failure to identify red flags in the 3M-6D education GPT group compared with the GPT group
Failure to identify red flags is defined as the proportion of participants whose final response does not include the expert-defined red-flag symptoms or warning signs for the assigned standardized simulated clinical scenario.
Failure to identify red flags in the 3M-6D education GPT group compared with the control group
Failure to identify red flags in the 3M-6D education Gemini group compared with the Gemini group
Failure to identify red flags in the 3M-6D education Gemini group compared with the control group
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Capital Medical University
Lead sponsor
Xuanwu Hospital, Beijing
Collaborator
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