An interventional study of Perception-based interventions in Large Language Models, Acceptability of Health Care and Perception, Self, sponsored by Peking University. Active, not recruiting at 1 site in China. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-12-26.
Sponsored by Peking University · Not applicable, Interventional, and Other
Large language models (LLMs) show promise in medicine, but concerns about their accuracy, coherence, transparency, and ethics remain. To date, public perceptions on using LLMs in medicine and whether they play a role in the acceptability of health care applications of LLMs are not yet fully understood. This study aims to investigate public perceptions on using LLMs in medicine and if interventions for perceptions affect the acceptability of health care applications of LLMs.
Owing to rapid advances in artificial intelligence, large language models (LLMs) are increasingly being used in a variety of clinical settings such as triage, disease diagnosis, treatment planning, and self-monitoring. Despite their potential, the use of LLMs remains restricted within healthcare settings due to lack of accuracy, coherence, and transparency and ethical concerns. Public perceptions such as perceived usefulness and risks play a crucial role in shaping their attitudes towards artificial intelligence that can either facilitate or hinder its adoption. Yet, to our knowledge, there is lack of awareness about perception-driven interventions in health care and no previous studies have examined whether public perceptions play a role in the acceptability of medical applications of LLMs. Hence, this study aims to investigate public perceptions on using LLMs in medicine and if interventions for perceptions affect the acceptability of health care applications of LLMs.
93 studies on the registry are indexed under Patient Acceptance of Health Care; 30 are open to participants now.
This study's planned enrollment of 3,000 is above the median of 238 across 74 interventional studies indexed under Patient Acceptance of Health Care.
Browse Patient Acceptance of Health Care studies →Peking University is the lead sponsor of 411 studies on the registry; 122 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Participants were asked to read "In April 2023, Massachusetts General Hospital launched a pilot program utilizing medical LLMs to assist with emergency department triage and initial diagnosis and observed a reduction in patient wait times and an improvement in clinical efficiency."
Other: Perception-based interventions
Participants were asked to read "In November 2022, a research team from the University of California, San Francisco found that cutting-edge medical LLMs exhibited racial bias when recommending treatment plans."
Other: Perception-based interventions
Participants were required to read "In February 2023, a major European hospital network inadvertently leaked partially anonymized but still sensitive patient data during the testing of medical LLMs due to a system configuration error. Although no direct patient harm occurred, this increased public concerns regarding data privacy and security and compelled relevant institutions to conduct urgent reviews of their data protection measures."
Other: Perception-based interventions
No intervention
Participants allocated to the intervention group received perception-based interventions. Interventions for Groups 1-3 were perceived benefits of LLMs in medicine, perceived racial bias in LLMs in medicine, and perceived ethical conflicts in LLMs in medicine, respectively.
Number of participants who will change their attitudes towards medical applications of large language models
Public acceptance of applying large language models to medicine will be categorized into yes, not sure, and no, which will be collected before perception-based interventions and after interventions.
Time frame: Through study completion, an average of 1 year
Plan to share: No
No publications or documents are linked to this record.
This study is active, not recruiting, as verified in Dec 2025. You cannot join it, but the record below documents what was studied.
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Patient Acceptance of Health Care→
Peking University