{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T06:48:32Z","timestamp":1791614912463,"version":"4.3.4"},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":281,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Nursing Management"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To synthesize evidence on artificial intelligence (AI) applications in nursing clinical practice and to develop and evaluate the content relevance of an evidence\u2010informed, bedside\u2010oriented mnemonic framework supporting nurses\u2019 safe and critical use of AI\u2010supported recommendations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>AI is increasingly integrated into nursing clinical practice, yet bedside nurses require concise guidance to appraise and use AI\u2010supported recommendations safely and ethically. Existing frameworks address organizational adoption or AI literacy education; a point\u2010of\u2010care cognitive aid for critical appraisal of AI outputs remains underdeveloped.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evaluation<\/jats:title>\n                    <jats:p>A scoping review, reported in accordance with PRISMA\u2010ScR, searched PubMed\/MEDLINE, CINAHL, Scopus, ScienceDirect, and Web of Science for English\u2010language publications from January 2015 to September 2026. Fourteen eligible sources were synthesized into five themes. An evidence\u2010informed seven\u2010component bedside cognitive guide was subsequently developed and evaluated by a purposively selected panel of 31 nursing and healthcare professionals using item\u2010 and scale\u2010level content validity indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Issue<\/jats:title>\n                    <jats:p>Relevance I\u2010CVI values ranged from 0.68 to 0.94, and the S\u2010CVI\/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\u2010level content validity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The framework is an evidence\u2010informed cognitive aid, not a validated clinical decision rule. Further iterative expert consensus and prospective usability, feasibility, and implementation testing are required before broad application.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications for Nursing Management<\/jats:title>\n                    <jats:p>Nurse managers and health\u2010system leaders should prioritize structured AI\u2010literacy education, clear governance, and escalation pathways for AI\u2010supported recommendations, nurse involvement in AI procurement and implementation, and monitoring mechanisms for AI\u2010related safety events to ensure safe AI integration into nursing practice.<\/jats:p>\n                  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