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Effect of Perception-based Interventions on Public Acceptance of Using Large Language Models in Medicine

NCT07304908 · Status: ACTIVE_NOT_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 3000

Last updated 2025-12-26

No results posted yet for this study

Summary

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.

Conditions

  • Large Language Models
  • Acceptability of Health Care
  • Perception, Self

Interventions

OTHER

Perception-based interventions

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.

Sponsors & Collaborators

  • Peking University Third Hospital

    collaborator OTHER

  • Peking University

    lead OTHER

Principal Investigators

  • Jue Liu · Peking University

Study Design

Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-11-25
Primary Completion
2026-10-31
Completion
2026-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07304908 on ClinicalTrials.gov