{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T22:00:54Z","timestamp":1790373654862,"version":"4.1.0"},"reference-count":27,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":5,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"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":["International Nursing Review"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To propose an evidence\u2010informed nursing policy framework for the safe, equitable and human\u2010centred integration of artificial intelligence into family nursing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Ageing populations, chronic illness and the shift towards home\u2010 and community\u2010based care have increased reliance on families and family nursing. Artificial intelligence is increasingly used in healthcare for prediction, decision support, communication, remote monitoring and documentation. However, its implications for family nursing remain underexamined because family nursing involves relationships, shared decision\u2010making and family\u2010level information.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Sources of Evidence<\/jats:title>\n                    <jats:p>Academic and policy literature on artificial intelligence, digital health, family nursing, ethics, regulation, workforce development and implementation was reviewed in a structured manner and narratively synthesised to identify policy\u2010relevant opportunities, risks and requirements.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Artificial intelligence may help nurses identify risks earlier, tailor education and referrals, extend routine support through digital tools and evaluate family\u2010level outcomes. These opportunities must be balanced with concerns about privacy, consent, bias, digital exclusion, accountability and over\u2010reliance on automated recommendations. Japan is used as an illustrative context because rapid population ageing, strong family involvement and community\u2010based integrated care highlight issues relevant to many health systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Safe integration requires five linked policy domains: ethical and data governance, workforce development, interdisciplinary co\u2010design, adaptive regulation and accountability, and sustainable funding and reimbursement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications for Nursing Practice<\/jats:title>\n                    <jats:p>Nurses should use artificial intelligence\u2013supported recommendations as prompts for professional assessment, not as replacements for relational judgement, family communication or human follow\u2010up.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications for Nursing Policy<\/jats:title>\n                    <jats:p>Policymakers, regulators, educators and health organisations should clarify accountability, protect family\u2010level data, embed artificial intelligence literacy in nursing education, require inclusive design and support reimbursement for nurse\u2010led, technology\u2010enabled family care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/inr.70237","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T05:37:26Z","timestamp":1788759446000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence in Family Nursing: An Evidence\u2010Informed Policy Framework for Safe and Equitable Integration"],"prefix":"10.1111","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4678-1303","authenticated-orcid":false,"given":"Honda","family":"Junko","sequence":"first","affiliation":[{"name":"Research Institute of Nursing Care for People and Community University of Hyogo  Hyogo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1711-208X","authenticated-orcid":false,"given":"Itoh","family":"Sakiko","sequence":"additional","affiliation":[{"name":"Graduate School of Health Care Sciences Institute of Science Tokyo  Bunkyo Tokyo Japan"},{"name":"Health Services Research and Development Center University of Tsukuba  Tsukuba Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2270-2313","authenticated-orcid":false,"given":"Kubota","family":"Kazumi","sequence":"additional","affiliation":[{"name":"Department of Women's Health Population Sciences National Center for Child Health and Development  Setagaya Japan"},{"name":"Department of Healthcare Information Management The University of Tokyo Hospital  Bunkyo Tokyo Japan"},{"name":"Shimonoseki City University  Yamaguchi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"e_1_2_16_2_1","unstructured":"American Academy of Nursing.2026.American Academy of Nursing Position Statement on Artificial Intelligence in Health Care.American Academy of Nursing.https:\/\/aannet.org\/page\/AI\u2010position\u2010statement\u20102026."},{"key":"e_1_2_16_3_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.n1190"},{"key":"e_1_2_16_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/jnu.12159"},{"key":"e_1_2_16_5_1","doi-asserted-by":"publisher","DOI":"10.2196\/23939"},{"key":"e_1_2_16_6_1","unstructured":"Cabinet Office Government of Japan.2024.Annual Report on the Ageing Society [Summary] FY2024. Cabinet Office Tokyo.https:\/\/www8.cao.go.jp\/kourei\/english\/annualreport\/2024\/pdf\/2024.pdf."},{"key":"e_1_2_16_7_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1714229"},{"key":"e_1_2_16_8_1","doi-asserted-by":"publisher","DOI":"10.2307\/249008"},{"key":"e_1_2_16_9_1","unstructured":"European Parliament and Council of the European Union.2024.Regulation (EU) 2024\/1689 of the European Parliament and of the Council of 13 June 2024 Laying Down Harmonised Rules on Artificial Intelligence and Amending Regulations (EC) No 300\/2008 (EU) No 167\/2013 (EU) No 168\/2013 (EU) 2018\/858 (EU) 2018\/1139 and (EU) 2019\/2144 and Directives 2014\/90\/EU (EU) 2016\/797 and (EU) 2020\/1828 (Artificial Intelligence Act). Official Journal of the European Union OJ L 2024\/1689 12.7.2024.https:\/\/eur\u2010lex.europa.eu\/eli\/reg\/2024\/1689\/oj\/eng."},{"key":"e_1_2_16_10_1","unstructured":"International Council of Nurses.2023.Digital health transformation and nursing practice. International Council of Nurses Geneva.https:\/\/www.icn.ch\/sites\/default\/files\/2023\u201008\/ICNPositionStatementDigitalHealthFINAL30.06_EN.pdf."},{"key":"e_1_2_16_11_1","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.78755"},{"key":"e_1_2_16_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12884\u2010025\u201007753\u20103"},{"key":"e_1_2_16_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2020.113172"},{"key":"e_1_2_16_14_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aax2342"},{"key":"e_1_2_16_15_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra1814259"},{"key":"e_1_2_16_16_1","unstructured":"Sakamoto H. M.Rahman S.Nomura et\u00a0al.2018.Japan Health System Review. Health Systems in Transition8(1). World Health Organization Regional Office for South\u2010East Asia.https:\/\/iris.who.int\/handle\/10665\/259941."},{"key":"e_1_2_16_17_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2023.1130894"},{"key":"e_1_2_16_18_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591\u2010018\u20100300\u20107"},{"key":"e_1_2_16_19_1","doi-asserted-by":"publisher","DOI":"10.5334\/ijic.988"},{"key":"e_1_2_16_20_1","doi-asserted-by":"publisher","DOI":"10.2307\/30036540"},{"key":"e_1_2_16_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijnurstu.2021.104153"},{"key":"e_1_2_16_22_1","unstructured":"World Health Organization.2021a.Ethics and Governance of Artificial Intelligence for Health: WHO Guidance. WHO.https:\/\/www.who.int\/publications\/i\/item\/9789240029200."},{"key":"e_1_2_16_23_1","unstructured":"World Health Organization.2021b.Global Strategy on Digital Health 2020\u20132025. 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