ReviewFrontiers in public health2026
Artificial intelligence literacy in nursing: a concept analysis.
Review in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: As artificial intelligence (AI) technologies are increasingly integrated into nursing education and clinical practice, nurses are required to interact with AI systems in complex decision-making contexts. However, the concept of artificial intelligence literacy remains insufficiently defined in nursing, which may limit the development of effective educational strategies and evidence-based practice guidance. Methods: A comprehensive literature search was conducted in China National Knowledge Infrastructure, Wanfang Data, VIP Database, SinoMed, MEDLINE (via PubMed), Web of Science, and CINAHL (via EBSCOhost) from database inception to October 2025. Studies related to artificial intelligence literacy in nursing were included. Rodgers' evolutionary concept analysis method was applied to examine the conceptual evolution, defining attributes, antecedents, consequences, related concepts, assessment tools, and exemplar cases of artificial intelligence literacy. Results: Thirty-four studies were included. Five defining attributes of artificial intelligence literacy in nursing were identified: Theoretical AI Knowledge, Technical Application Proficiency, Critical Evaluation Skills, Awareness of Ethics and Responsibility, and Human-computer collaborative competence. Antecedents were identified at the individual, educational, and organizational levels. Consequences included enhancing the quality of clinical care, strengthening the role of the nursing profession, improving patient experience, enhancing team collaboration, and enhancing educational effectiveness. A conceptual framework of artificial intelligence literacy in nursing was constructed. Conclusion: Artificial intelligence literacy in nursing extends beyond technical proficiency and represents a context-dependent professional competence grounded in nursing judgment. It is important for supporting safe, ethical, and person-centered nursing care in technology-supported environments.
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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 Socratic graph.