ArticleBMC medical ethics2026
The effects of artificial intelligence ethics awareness, digital literacy, and metacognition on nursing students' attitudes toward artificial intelligence.
Article in BMC medical ethics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Abstract
backgroundArtificial intelligence (AI) is rapidly transforming healthcare, raising new ethical challenges related to patient rights, transparency, and fairness. Nursing students must therefore develop competencies not only in digital and cognitive skills but also in AI ethics awareness to ensure responsible adoption of these technologies.
methodsA descriptive correlational study was conducted with 121 nursing students in South Korea. Validated instruments measured AI ethics awareness, digital literacy, metacognition, and attitudes toward AI. Data were analyzed using t-tests, ANOVA, Pearson’s correlation, and multiple regression.
resultsAI ethics awareness (β = 0.30, p < .001) and digital literacy (β = 0.38, p < .001) were significant predictors of attitudes toward AI, jointly explaining 31.8% of the variance. Higher levels of ethical awareness and digital competence were associated with more positive perceptions of AI.
conclusionsThe findings highlight the ethical and educational importance of preparing healthcare professionals to navigate AI responsibly. Embedding ethical principles such as autonomy, justice, and accountability into nursing and healthcare curricula, as well as into institutional and national standards, will be crucial for protecting patient rights and promoting fairness in AI-driven healthcare.
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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.