ArticleBMC medical education2025
Exploring medical students' attitudes and perceptions toward artificial intelligence in medicine in Shandong Province, China.
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 4 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
- Defining the artificial intelligence knowledge gap in surgery: experience and perspectives from surgical resident and postgraduate.Updates in surgery · 2026Article
- Experiences and Perceptions of Clinical and Graduate Medical Students Regarding AI in Syria: Cross-Sectional Study.JMIR medical education · 2026Article
- The relationship between medical students' attitudes toward artificial intelligence and their personality traits: a multicenter study in China.Frontiers in public health · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence (AI) into medical education has transformative potential, yet understanding medical students' attitudes toward AI remains critical for its effective implementation. This study investigates the attitudes, perceptions, and the factors influencing them among medical students in Shandong, China, toward AI in education.
methodsA cross-sectional survey was conducted from May to June 2025 involving medical students at five medical universities in Shandong, China. Employing convenience sampling, 788 validated participants completed questionnaires that assessed variables including AI familiarity, perceived usefulness (PU), perceived ease of use (PEU), and ethical concerns. Statistical analyses comprised descriptive statistics, independent t-tests and one-way ANOVA tests.
resultsBased on 788 valid responses, the study revealed high levels of both familiarity with and usage of AI tools among medical students (47.33% and 91.24%). While they hold positive perceptions of AI's PU (3.60 ± 0.85) and PEU (3.66 ± 0.76), significant ethical concerns exist, including privacy issues (48.48%), fears of eroding critical thinking (61.93%), and academic integrity worries (55.84%). Male students (p = 0.020) and those in higher academic years (p < 0.001) demonstrated stronger AI competency, with ethical apprehensions increasing notably as students' progress through their medical education (p < 0.001). Institutional affiliation had little impact on these patterns (p > 0.05).
conclusionsShandong medical students demonstrate cautious optimism regarding AI adoption, recognizing its educational potential while emphasizing the necessity of ethical frameworks and operational safeguards. Curriculum adaptations and transparent governance mechanisms should be implemented to ensure congruence between technological implementation and educational objectives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.