将人工智能融入社区健康护理教育和实践：机遇、伦理挑战和未来方向
Integrating Artificial Intelligence into Community Health Nursing Education and Practice: Opportunities, Ethical Challenges, and Future Directions.
摘要(中文译文)
人工智能（AI）正在迅速改变医疗保健格局。然而，其融入社区健康护理——一门以人群层面的预防、健康促进和社区环境中的初级保健为核心的学科——的程度仍未被充分探讨。本叙述性综述审视了将AI整合到社区健康护理教育与实践中去的机遇、伦理挑战及未来方向。文献检索覆盖PubMed、CINAHL、Scopus、Web of Science和IEEE Xplore，检索时间为2017年1月至2026年3月。初步检索获得612条记录；在去除重复文献并依据预设标准对标题、摘要和全文进行筛选后，保留58篇文献进行主题综合，包括实证研究、系统综述与伞形综述、范围综述、荟萃分析及权威政策文件。筛选和数据提取由两名评审者完成，分歧通过讨论解决。AI在四个相互关联的领域为社区健康护理提供了机遇：基于社区的评估中的临床决策支持、人群健康管理的预测分析、增强的疾病监测与暴发检测，以及个性化健康教育推送。显著挑战依然存在，包括算法偏见、数据隐私问题、对治疗性护患关系的威胁、护理教师AI素养不足以及监管空白。大多数实证证据来源于医院或普通护理环境；因此，其向社区情境的可迁移性是推断而非直接证明的。负责任地将AI整合到社区健康护理中需要课程改革、伦理治理框架、师资发展、公平可及以及跨学科协作。AI应当增强而非替代定义该学科的关系性与文化敏感性照护。鉴于本综述的叙述性本质及社区特异性证据的有限性，结论被定位为对AI—社区健康护理接口的愿景，而非确定性综合。
Abstract
: Artificial intelligence (AI) is rapidly transforming healthcare. Its integration into community health nursing-a discipline centered on population-level prevention, health promotion, and primary care in community settings-remains insufficiently explored. This narrative review examines the opportunities, ethical challenges, and future directions for integrating AI into community health nursing education and practice. : A literature search was conducted across PubMed, CINAHL, Scopus, Web of Science, and IEEE Xplore for publications between January 2017 and March 2026. The initial search yielded 612 records; after the removal of duplicates and screening of titles, abstracts, and full texts against predefined criteria, 58 sources were retained for thematic synthesis, comprising empirical studies, systematic and umbrella reviews, scoping reviews, meta-analyses, and authoritative policy documents. Screening and data extraction were performed by two reviewers, with disagreements resolved by discussion. : AI offers opportunities for community health nursing across four interconnected domains: clinical decision support for community-based assessments, predictive analytics for population health management, enhanced disease surveillance and outbreak detection, and personalized health education delivery. Significant challenges persist, including algorithmic bias, data privacy concerns, threats to the therapeutic nurse-client relationship, inadequate AI literacy among nursing faculty, and regulatory gaps. Most empirical evidence originates from hospital or general nursing settings; transferability to community contexts is therefore inferred rather than directly demonstrated. : Responsible integration of AI into community health nursing requires curriculum reform, ethical governance frameworks, faculty development, equitable access, and interdisciplinary collaboration. AI should augment, not replace, the relational and culturally sensitive care that defines this discipline. Given the narrative nature of the review and the limited community-specific evidence, conclusions are framed as a vision of the AI-community health nursing interface rather than a definitive synthesis.
如何引用
AMA
Bandar Alhumaidi, Talal Ali F Alharbi. Integrating Artificial Intelligence into Community Health Nursing Education and Practice: Opportunities, Ethical Challenges, and Future Directions.. Healthcare (Basel, Switzerland). 2026; doi:10.3390/healthcare14101407.
APA
Bandar Alhumaidi, Talal Ali F Alharbi (2026). Integrating Artificial Intelligence into Community Health Nursing Education and Practice: Opportunities, Ethical Challenges, and Future Directions.. Healthcare (Basel, Switzerland). https://doi.org/10.3390/healthcare14101407
GB/T 7714
Bandar Alhumaidi, Talal Ali F Alharbi. Integrating Artificial Intelligence into Community Health Nursing Education and Practice: Opportunities, Ethical Challenges, and Future Directions.[J]. Healthcare (Basel, Switzerland), 2026 doi:10.3390/healthcare14101407.
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