ArticleInternational journal of nursing studies advances2026
Barriers and facilitators to artificial intelligence adoption among nursing students: a mixed-methods study.
Article in International journal of nursing studies advances, 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
Background: Objective: Design: Setting: College of Nursing, Taibah University, Medina, Saudi Arabia (November 2024-March 2025). Participants: 348 nursing students across academic levels 3-8 participated in the quantitative phase (response rate: 72.5%), with 17 students purposively selected for qualitative interviews. Methods: Validated instruments - the Technology Readiness Index 2.0, an adapted Perceived Usefulness Scale, and an Ethical Concerns Scale - were administered online. Kendall's tau correlation and partial proportional odds modeling identified predictors of perceived usefulness. Qualitative data underwent thematic analysis using Braun and Clarke's framework. Trustworthiness was addressed through investigator triangulation, an audit trail, reflexive memoing, and member-checking. Mixed-methods integration followed a joint-display framework to examine convergence between quantitative and qualitative findings. Results: Technological optimism (Kendall's tau [τ] = 0.45, 95% confidence interval [CI]: 0.39 to 0.50, p < 0.001) and innovativeness (τ = 0.41, 95% CI: 0.35 to 0.47, Conclusions: Nursing students in this Saudi sample demonstrated nuanced perspectives on artificial intelligence adoption, characterised by cautious optimism alongside critical awareness. The paradoxical relationship between ethical concern and perceived utility challenges traditional technology acceptance models, suggesting deeper engagement fosters appreciation of both opportunities and challenges. We have underscored the importance of tailored educational strategies addressing technical competencies alongside ethical reasoning and professional identity formation. As this generation of digitally fluent students transitions into nursing practice, the perspectives of this sample offer insights for developing artificial intelligence integration approaches that preserve nursing's humanistic core while leveraging technological capabilities.
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