Artificial intelligence as a tool for providing feedback in an internal medicine residency program: a survey of residents’ perceptions

This blinded, cross-sectional survey-based study, performed at Loma Linda University Internal Medicine Residency Program, evaluated resident perceptions of educator-generated versus AI-enhanced feedback. Fifty-six resident evaluations were distributed, and 50 residents (89%) completed the survey. AI-enhanced feedback, developed using a standardized ChatGPT-4 prompt, was generally perceived as more structured, detailed, and actionable, particularly in supporting clearer improvement plans, while educator feedback was valued for its personalized nature. AI-enhanced feedback received numerically higher ratings across domains, although differences were not statistically significant in the overall cohort. These findings suggest that AI-enhanced feedback may serve as a complementary tool to enhance the perceived educational value of trainee evaluations in residency training programs.

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Publication Details

Journal
Rare Kidney Diseases
Published
2026-09-17
DOI
https://doi.org/10.1007/s44531-026-00007-1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial intelligence as a tool for providing feedback in an internal medicine residency program: a survey of residents’ perceptions

Niloufar Ebrahimi, T.S. Yau, Sayna Norouzi, Zohreh Gholizadeh Ghozloujeh et al.
Rare Kidney Diseases
Artificial Intelligence in Healthcare and Education
article

Artificial intelligence as a tool for providing feedback in an internal medicine residency program: a survey of residents’ perceptions

Niloufar Ebrahimi, T.S. Yau, Sayna Norouzi, Zohreh Gholizadeh Ghozloujeh, Amir Abdipour, Lawrence K. Loo, Hana Kazbour, Giv Heidari Bateni
article en

Abstract

This blinded, cross-sectional survey-based study, performed at Loma Linda University Internal Medicine Residency Program, evaluated resident perceptions of educator-generated versus AI-enhanced feedback. Fifty-six resident evaluations were distributed, and 50 residents (89%) completed the survey. AI-enhanced feedback, developed using a standardized ChatGPT-4 prompt, was generally perceived as more structured, detailed, and actionable, particularly in supporting clearer improvement plans, while educator feedback was valued for its personalized nature. AI-enhanced feedback received numerically higher ratings across domains, although differences were not statistically significant in the overall cohort. These findings suggest that AI-enhanced feedback may serve as a complementary tool to enhance the perceived educational value of trainee evaluations in residency training programs.

Rare Kidney DiseasesVol. 1(1)
Loma Linda University Medical Center (US), Washington University in St. Louis (US), Loma Linda University (US)
American Society of Nephrology
Openalex Percentile: Top 15%
Artificial Intelligence in Healthcare and Education
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Artificial intelligence as a tool for providing feedback in an internal medicine residency program: a survey of residents’ perceptions — Niloufar Ebrahimi, T.S. Yau, et al. · Rare Kidney Diseases (2026) | TGRS Research Map | TGRS