ArticleBMC medical education2025
The application of problem-based learning (PBL) guided by ChatGPT in clinical education in the Department of Nephrology.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundNephrology, a complex and specialized medical field, has seen significant advancements, yet traditional teaching methods remain outdated and less effective. This study explores the integration of Problem-Based Learning (PBL) guided by ChatGPT in the Department of Nephrology at Guizhou Provincial People's Hospital to enhance medical education.
objectiveTo assess the impact of ChatGPT-guided Problem-Based Learning (PBL) on medical students' education and satisfaction in the Nephrology Department.
methodsFifty-four clinical resident doctors were divided into an experimental group, using ChatGPT-guided PBL, and a control group, using traditional methods. Both groups were assessed through theoretical and clinical practice exams, teaching satisfaction surveys, and self-assessments of teaching effectiveness.
resultsResults indicated the experimental group achieved significantly higher scores in both theoretical and clinical assessments. Additionally, they reported higher satisfaction and effectiveness in learning. Despite spending more time in pre-class preparation, the overall learning time did not increase due to reduced post-class review time facilitated by ChatGPT.
conclusionsThis study demonstrates the potential of ChatGPT-integrated PBL to enhance learning outcomes, satisfaction, and efficiency in medical education. Future research should include larger samples and longer follow-up to validate these findings.
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Registered trials
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