Jan 2026· Journal of Nursing Management· Vol 2026· 0 citations· 23 references
Medicine
TL;DR
The framework is an evidence‐informed cognitive aid, not a validated clinical decision rule, and further iterative expert consensus and prospective usability, feasibility, and implementation testing are required before broad application.
Abstract
Aim To synthesize evidence on artificial intelligence (AI) applications in nursing clinical practice and to develop and evaluate the content relevance of an evidence‐informed, bedside‐oriented mnemonic framework supporting nurses’ safe and critical use of AI‐supported recommendations. Background AI is increasingly integrated into nursing clinical practice, yet bedside nurses require concise guidance to appraise and use AI‐supported recommendations safely and ethically. Existing frameworks address organizational adoption or AI literacy education; a point‐of‐care cognitive aid for critical appraisal of AI outputs remains underdeveloped. Evaluation A scoping review, reported in accordance with PRISMA‐ScR, searched PubMed/MEDLINE, CINAHL, Scopus, ScienceDirect, and Web of Science for English‐language publications from January 2015 to September 2026. Fourteen eligible sources were synthesized into five themes. An evidence‐informed seven‐component bedside cognitive guide was subsequently developed and evaluated by a purposively selected panel of 31 nursing and healthcare professionals using item‐ and scale‐level content validity indices. Key Issue Relevance I‐CVI values ranged from 0.68 to 0.94, and the S‐CVI/Ave was 0.78, below the prespecified reference threshold of 0.90. These findings provide preliminary evidence regarding the relevance, clarity, and perceived bedside applicability of the framework components, but do not establish scale‐level content validity. Conclusion The framework is an evidence‐informed cognitive aid, not a validated clinical decision rule. Further iterative expert consensus and prospective usability, feasibility, and implementation testing are required before broad application. Implications for Nursing Management Nurse managers and health‐system leaders should prioritize structured AI‐literacy education, clear governance, and escalation pathways for AI‐supported recommendations, nurse involvement in AI procurement and implementation, and monitoring mechanisms for AI‐related safety events to ensure safe AI integration into nursing practice.
Current evidence suggests that AI has considerable potential to support nursing workforce management; however, empirical evidence regarding implementation effectiveness remains limited.
R. Rezapour-Nasrabad, Sina Nasrollahi-Nasrabad· Journal of Nursing Managemen...· 0 citations
AI integration in nursing care may be supported by coordinated, ethically grounded, and context-sensitive strategies, and the proposed domains require further empirical evaluation across nursing settings.
D. Alrazeeni, Maryam Alharrasi, M. K. K. Rony et al.· International Nursing Review· 0 citations
Artificial intelligence (AI)-based clinical decision support systems (CDSS) are increasingly embedded in nursing workflows, promising earlier detection of patient deterioration, more efficient documentation, and more consistent risk stratification, yet the evidence base is fragmented across clinical domains and ethical...
I. M, Bamigboye T. O., Oniyide A. A.· International journal of re...· 0 citations
Introduction Artificial intelligence (AI) is increasingly being incorporated into clinical nursing practice, but evidence remains limited on how nurses experience AI‐supported systems and how decision‐making orientation relates to missed nursing care (MNC). Aim To explore nurses’ experiences with AI‐supported clinical...
F. Alanazi, Ahmed Farghaly Tawfik, S. Mahgoub et al.· Journal of Nursing Managemen...· 0 citations
BACKGROUND
As artificial intelligence (AI) rapidly integrates into nursing practice, education, and research, it presents a profound ethical paradox: significant opportunities for operational efficiency alongside deep-seated challenges to the profession's core values.
PURPOSE
This scoping review synthesizes existing...
J. Marquard, Suzanne Fink, Winnie Yip et al.· Nursing Outlook· 0 citations
Background Clinical reasoning (CR) is a complex, context‐dependent process that is essential for safe nursing care. Existing reviews have primarily focused on nursing students rather than practicing clinical nurses. Rapid changes in patient acuity and the increasing integration of digital technologies into healthcare h...