ArticleBMC nursing2026
Artificial intelligence in nursing education: knowledge, perceptions, and associated factors among Egyptian nursing students across universities.
Article in BMC nursing, 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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Abstract
aimTo assess Egyptian nursing students' level of AI knowledge, perceptions of AI benefits, and fears regarding AI in nursing education and practice, and to examine associated sociodemographic factors.
backgroundThe rapid integration of artificial intelligence (AI) into healthcare has generated both enthusiasm and apprehension among nursing professionals and students. While AI offers substantial potential benefits in clinical efficiency, decision support, and educational innovation, important concerns remain regarding individualised care, professional displacement, and data privacy. This combination of promise and concern suggests a cautiously receptive context in which nursing students may recognise AI's value while remaining uncertain about its implications for practice and education. Therefore, evidence-based assessment of nursing students' knowledge and perceptions is needed.
methodsA cross-sectional descriptive design was utilised in this study. A convenience sample of 2412 nursing students was drawn from two nursing faculties between May 2024 and January 2025. Data were collected using a structured three-part questionnaire covering individual sociodemographic characteristics, a dichotomous AI knowledge test, and an attitude scale measuring perceived benefits and fears regarding AI.
resultsApproximately 46.4% of students demonstrated good AI knowledge (mean score 3.2 ± 1.3 out of 5). The mean perceived benefits score was 10.9 ± 3.5 (maximum 14), indicating generally favourable views of AI's educational and clinical support applications. The mean fear score was 5.0 ± 1.6. Notably, 72.2% of students expressed concern that AI may replace nurses in the future, and 57.8% reported discomfort with using AI in educational settings. Statistically significant differences were observed across academic years for knowledge, perceived benefits, and fears, and across age groups for perceived benefits and fears; age-related differences in knowledge were smaller but remained statistically significant. No significant differences were found by gender or university.
conclusionEgyptian nursing students demonstrated a foundational understanding of AI and broadly recognised its benefits for education and clinical support. Nevertheless, substantial gaps in formal AI training and pronounced fears about professional displacement were identified. Structured, ethically grounded AI educational programs are urgently needed to enhance students' digital competencies and ensure the safe and effective use of AI in nursing practice. CLINICAL
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