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01 · ABSTRACT

Abstract

Objective: The authors evaluated narrative feedback generated by ChatGPT and faculty members for medical students' Mental Status Exam (MSE) write-ups. The study compared feedback quality and usefulness and assessed whether students and academic psychiatrists could identify the feedback source. Methods: Medical students (N=164) wrote MSEs and received blinded feedback from either a faculty member (for low-scoring write-ups, n=43) or ChatGPT (for high-scoring write-ups, n=121). Students rated the feedback's quality and usefulness and guessed its origin. Three academic psychiatrists also conducted a blinded evaluation, rating both feedback types for the low-scoring MSEs, choosing the superior version, and guessing the source. Results: Students rated AI feedback quality significantly higher than faculty feedback (mean=4.22 vs. 3.5). Academic psychiatrists preferred the AI-generated feedback in 93% of cases. Only 29% of students receiving AI feedback correctly identified its source. Psychiatrists correctly identified AI feedback only 23% of the time and misattributed faculty feedback as AI-generated 71% of the time. Conclusions: AI-generated feedback was perceived as high-quality by students and preferred by expert raters. The difficulty in distinguishing AI from faculty feedback suggests generative AI can produce feedback comparable or superior to human experts, offering a scalable tool to support medical education and reduce faculty workload.
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02 · OJS METADATA

Keywords

Artificial IntelligenceMedical EducationFeedbackMental Status ExaminationPsychiatry
03 · PUBLICATION RECORD

Article details

JournalMedical Research Archives
IssueVol 14 No 3 (2026): Vol.14, Issue 3, March 2026
SectionResearch Articles
Published01 April 2026
DOI10.18103/mra.v14i3.7347
ISSN2375-1924
04 · RIGHTS & REUSE

Rights & reuse

This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.

Authors & affiliations

ES

Elle S. Cleaves

Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America

SR

Sorana Raiciulescu

Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America

JR

Joshua R. Duncan

Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America

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