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Nurses' perceptions of artificial intelligence adoption in healthcare: A qualitative systematic review
Jee Young Joo1, Megan F Liu2, Mu-Hsing Ho3
1College of Nursing, Gachon University, South Korea.
Aim:
This study aimed to systematically review and synthesize the most recent qualitative studies on frontline nurses' insights and perspectives regarding the use of artificial intelligence (AI) tools in their clinical practice in hospital settings.
Background:
There is limited information on frontline nurses' perceptions, attitudes and expectations regarding the adoption of AI in healthcare.
Design:
A systematic review and thematic synthesis of qualitative evidence was conducted.
Methods:
A systematic search was conducted across five electronic databases-CINAHL, PubMed, Web of Science, Ovid and Science Direct-to identify qualitative studies published between January 2020 and December 2024. After selecting studies, a thematic synthesis was performed. This review followed the PRISMA checklist, was registered with PROSPERO and included a quality appraisal of the retrieved studies.
Results:
Nine qualitative studies published between 2022 and 2024 were included in this systematic review. The included studies were conducted in five countries at university-affiliated or tertiary hospitals. Participants included 140 frontline nurses and nurse managers with prior experience using technology tools in clinical settings. Five common themes were identified: ethical issues; increased workload; seamless and efficient patient care; reinforcement rather than replacement; and AI as a future nursing care solution CONCLUSIONS: The five themes identified in this review provide valuable insights into how AI tools can be integrated into current and future frontline nursing practices to enhance patient care. Nurse leaders and healthcare policymakers can use these findings to improve nursing research, facilitate the adoption of new AI tools and support their implementation in healthcare settings.
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