ArticleIntegrative medicine research2025
Use and perception of generative artificial intelligence in traditional Korean medicine education: A cross-sectional survey of undergraduate students in Korea.
Article in Integrative medicine research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- AI in medicine and traditional medicine - opportunities for healthcare transformation.Integrative medicine research · 2025Article
- Artificial intelligence in integrative medicine: Transforming education for a digital future.Integrative medicine research · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to examine the usage, awareness, and satisfaction related to generative AI (GenAI) among undergraduate students at a Traditional Korean Medicine (TKM) college in Korea and to identify factors associated with GenAI use and satisfaction. Methods: A structured questionnaire consisting of 56 items across six domains was administered, covering demographics, general and TKM-specific GenAI use, satisfaction, educational experiences, and future expectations. Descriptive statistics, univariable analysis, multivariable logistic regression, and correlation analysis were performed. Results: A total of 234 students across six academic years participated in the survey. Most respondents were aware of GenAI (88.5 %) and used it for general purposes (79.9 %). However, only 16.2 % actively used it for TKM learning. While 70.4 % were satisfied with using GenAI in general, only 45.8 % felt satisfied with its use for TKM education. Factors significantly associated with GenAI use or satisfaction included enrollment in the TKM curriculum, older age, prior major, scholarship receipt, and self-directed GenAI learning. Although only 18.8 % had experienced GenAI in formal TKM courses, 96.2 % viewed GenAI as necessary in TKM education. Conclusion: A notable gap exists between students' interest and the limited integration of GenAI in TKM curricula. To close this gap, GenAI should be systematically incorporated into educational programs, accompanied by faculty training and institutional support to enhance students' digital readiness and learning outcomes.
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Registered trials
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