{"title":"护理中人工智能的伦理和制度准备：概括性评论","authors":"Wesam Taher Almagharbeh, Maryam Alharrasi, Moustaq Karim Khan Rony, Sarmin Kabir, Sirwan Khalid Ahmed, Daifallah M. Alrazeeni","doi":"10.1111/inr.70111","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aim</h3>\n \n <p>This umbrella review aimed to synthesize the ethical and institutional considerations related to the adoption of artificial intelligence (AI) in nursing care.</p>\n </section>\n \n <section>\n \n <h3> Background</h3>\n \n <p>AI is increasingly used in nursing through decision-support systems, predictive tools, and automation. While promising for efficiency and patient outcomes, it also raises concerns about autonomy, privacy, fairness, and accountability. Institutional readiness, including infrastructure, training, and governance, is vital to ensure ethical integration.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>An umbrella review methodology was used to synthesize findings from systematic, scoping, integrative, and narrative reviews published between 2015 and 2025. Comprehensive searches were carried out in PubMed, CINAHL, Scopus, Embase, and Web of Science. Data were extracted and thematically analyzed to identify recurring ethical challenges and institutional readiness factors.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Thirty-three reviews were synthesized. Key ethical concerns centered on patient autonomy, informed consent, data protection, bias, and unclear clinical accountability. Institutional barriers included limited digital infrastructure, insufficient AI literacy among nurses, and fragmented regulatory oversight. Conversely, environments that invested in inclusive leadership, continuous education, and transparent governance demonstrated greater ethical alignment in AI implementation.</p>\n </section>\n \n <section>\n \n <h3> Discussion</h3>\n \n <p>The findings show that ethical and institutional issues are closely linked. Environments lacking adequate resources or governance structures tend to amplify ethical risks, while supportive institutions strengthen ethical nursing practice.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>AI adoption in nursing represents not only a technological innovation but also a fundamental ethical and organizational shift that demands preparedness at both system and practitioner levels.</p>\n </section>\n \n <section>\n \n <h3> Implications for nursing practice and health policy</h3>\n \n <p>Health systems should invest in infrastructure, regulatory clarity, and continuous training. Policymakers should promote equity, transparency, and inclusiveness to ensure that AI enhances patient-centered and ethically grounded nursing care.</p>\n </section>\n \n <section>\n \n <h3> Trial and Protocol registration</h3>\n \n <p>PROSPERO registration number CRD420251060646.</p>\n </section>\n </div>","PeriodicalId":54931,"journal":{"name":"International Nursing Review","volume":"72 4","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ethical and Institutional Readiness for Artificial Intelligence in Nursing: An Umbrella Review\",\"authors\":\"Wesam Taher Almagharbeh, Maryam Alharrasi, Moustaq Karim Khan Rony, Sarmin Kabir, Sirwan Khalid Ahmed, Daifallah M. 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引用次数: 0
摘要
本综述旨在综合与人工智能（AI）在护理中的应用相关的伦理和制度考虑。人工智能通过决策支持系统、预测工具和自动化越来越多地应用于护理领域。虽然它有望提高效率和患者的治疗效果，但也引发了对自主权、隐私、公平性和问责制的担忧。制度准备，包括基础设施、培训和治理，对于确保道德一体化至关重要。方法采用综合综述方法，综合2015年至2025年间发表的系统性、范围性、综合性和叙述性综述的研究结果。在PubMed， CINAHL, Scopus， Embase和Web of Science中进行了全面的搜索。数据提取和主题分析，以确定反复出现的伦理挑战和制度准备因素。结果共合成33篇综述。主要的伦理问题集中在患者自主、知情同意、数据保护、偏见和不明确的临床责任上。制度障碍包括数字基础设施有限、护士对人工智能的认识不足以及监管监督不统一。相反，投资于包容性领导、持续教育和透明治理的环境在人工智能实施中表现出更大的道德一致性。研究结果表明，道德和制度问题密切相关。缺乏足够资源或治理结构的环境往往会放大伦理风险，而支持性机构则会加强伦理护理实践。结论：人工智能在护理中的应用不仅是一项技术创新，也是一种根本性的伦理和组织转变，需要在系统和从业者层面做好准备。对护理实践和卫生政策的影响卫生系统应投资于基础设施、监管清晰度和持续培训。政策制定者应促进公平、透明和包容性，以确保人工智能加强以患者为中心、以道德为基础的护理。试验和方案注册PROSPERO注册号CRD420251060646。
Ethical and Institutional Readiness for Artificial Intelligence in Nursing: An Umbrella Review
Aim
This umbrella review aimed to synthesize the ethical and institutional considerations related to the adoption of artificial intelligence (AI) in nursing care.
Background
AI is increasingly used in nursing through decision-support systems, predictive tools, and automation. While promising for efficiency and patient outcomes, it also raises concerns about autonomy, privacy, fairness, and accountability. Institutional readiness, including infrastructure, training, and governance, is vital to ensure ethical integration.
Methods
An umbrella review methodology was used to synthesize findings from systematic, scoping, integrative, and narrative reviews published between 2015 and 2025. Comprehensive searches were carried out in PubMed, CINAHL, Scopus, Embase, and Web of Science. Data were extracted and thematically analyzed to identify recurring ethical challenges and institutional readiness factors.
Results
Thirty-three reviews were synthesized. Key ethical concerns centered on patient autonomy, informed consent, data protection, bias, and unclear clinical accountability. Institutional barriers included limited digital infrastructure, insufficient AI literacy among nurses, and fragmented regulatory oversight. Conversely, environments that invested in inclusive leadership, continuous education, and transparent governance demonstrated greater ethical alignment in AI implementation.
Discussion
The findings show that ethical and institutional issues are closely linked. Environments lacking adequate resources or governance structures tend to amplify ethical risks, while supportive institutions strengthen ethical nursing practice.
Conclusion
AI adoption in nursing represents not only a technological innovation but also a fundamental ethical and organizational shift that demands preparedness at both system and practitioner levels.
Implications for nursing practice and health policy
Health systems should invest in infrastructure, regulatory clarity, and continuous training. Policymakers should promote equity, transparency, and inclusiveness to ensure that AI enhances patient-centered and ethically grounded nursing care.
期刊介绍：
International Nursing Review is a key resource for nurses world-wide. Articles are encouraged that reflect the ICN"s five key values: flexibility, inclusiveness, partnership, achievement and visionary leadership. Authors are encouraged to identify the relevance of local issues for the global community and to describe their work and to document their experience.
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