NURSING STUDENTS' PERCEPTIONS OF THE USE OF ARTIFICIAL INTELLIGENCE IN CLINICAL PRACTICE
Keywords:
artificial intelligence; nursing students; clinical practice; perception; attitude of health personnel; nursing educationAbstract
DOI: https://doi.org/10.46296/gt.v9i18edespsep.0406
Abstract
Introduction: Artificial intelligence (AI) is increasingly embedded in nursing education and clinical practice through clinical decision-support systems, conversational chatbots, documentation tools, and simulation-based learning. How nursing students perceive these technologies —their perceived usefulness, ease of use, trust, and anxiety— shapes their future acceptance and integration into care delivery. Objective: To synthesize available evidence on nursing students' perceptions, attitudes, knowledge, and barriers regarding the use of AI in clinical practice. Methods: Systematic review with narrative synthesis, following PRISMA 2020 principles. Systematic reviews, cross-sectional studies, and qualitative studies published between 2020 and 2026 were prioritized, identified in PubMed/MEDLINE, CINAHL, Scopus, Web of Science, and ERIC, along with a targeted search of Ibero-American sources. Results: Evidence converges on moderately positive attitudes toward AI among nursing students, underpinned by perceived usefulness and digital self-efficacy, but tempered by anxiety, moderate-to-low knowledge, and ethical concerns (privacy, bias, dehumanization of care). The most consistent determinants of intention to use are perceived usefulness, ease of use, self-efficacy, and facilitating conditions within the educational environment. Key barriers include the absence of structured curricular training, limited infrastructure, and unclear ethical guidance. Conclusion: Acceptance of AI among future nursing professionals depends on longitudinal educational strategies that combine technical competencies, ethical reasoning, and simulation-based clinical experiences, sustained by academic leadership and institutional governance frameworks.
Keywords: artificial intelligence; nursing students; clinical practice; perception; attitude of health personnel; nursing education.
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