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Clinical Language Evaluation With AI for Residents
Sponsor: The University of Texas Health Science Center, Houston
Summary
The purpose of this study is to refine and test existing enterprise-grade large language model (LLM) based on generative artificial intelligence (AI), to assess the feasibility and acceptability of LLM-based feedback, to assess the ability of LLM-based feedback to improve residents' communications,to explore the ability of standardized patients to assess residents' communication and to explore the ability of residents to self-assess their communication complexity
Official title: Clinical Language Evaluation With AI for Residents (CLEAR2) - A Pilot Randomized Controlled Trial
Key Details
Gender
All
Age Range
18 Years - 50 Years
Study Type
INTERVENTIONAL
Enrollment
64
Start Date
2025-10-23
Completion Date
2026-05-28
Last Updated
2025-10-30
Healthy Volunteers
Yes
Conditions
Interventions
educational LLM-based feedback tool
Participants will have their verbal communications with standardized patients (SP) regarding 3 different scenarios recorded, transcribed, and analyzed in real-time by the large language model (LLM) and will receive feedback as suggestions and alternative scripts. These will be reviewed by residents between SP scenarios
Locations (1)
The University of Texas Health Science Center at Houston
Houston, Texas, United States