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Purpose: To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies. Methods: We used the VOSviewer 1.6.17, SciMAT, and CiteSpace 5.8.R3 to generate visual cooperation network maps for the country, organizations, authors, citations, and keywords and perform burst detection, theme evolution, and so forth. Findings A total of 9318 articles were obtained from the Web of Science Core Collection database. Four hundred and thirty‐one AI research related to the field of nursing was published by 855 institutions from 54 countries. CIN‐Computers Informatics Nursing was the top productive journal. The United States was the dominant country. The transnational cooperation between authors from developed countries was closer than that between authors from developing countries. The main hot topics included nurse rostering, nursing diagnosis, nursing decision support, disease risk factor prediction, nursing big data management, expert system, support vector machine, decision tree, deep learning, natural language processing, and nursing education. Machine learning represented one of the cutting‐edge and most applicable branches of artificial intelligence in the field of nursing, and deep learning was the hottest technology among many machine learning methods in recent years. One of the most cited papers was published by Burke in 2004 and cited 500 times, which critically evaluated AI methods to deal with nurse scheduling problems. Conclusions: Although AI has been paid more and more attention to the field of nursing, there is still a lack of high‐yielding authors who have been engaged in this field for a long time. Most of the high contribution authors and institutions came from developed countries; therefore, more transnational and multi‐disciplinary cooperation is needed to promote the development of AI in the nursing field. This bibliometric analysis not only provided a comprehensive overview to help researchers to understand the important articles, journals, potential collaborators, and institutions in this field but also analyzed the history, hot spots, and future trends of the research topic to provide inspiration for researchers to choose research directions. [ABSTRACT FROM AUTHOR]

Nursing Sciences are at a moment of paradigmatic transition. The aim of this paper is to reflect on the new epistemological paradigms of nursing science from a critical approach. In this paper, we identified and analysed some new research lines and trends which anticipate the reorganization of nursing sciences and the paradigms emerging from nursing care: biotechnology-centred knowledge; the interface between nursing knowledge and new information technologies; body care centred knowledge; the human body as a cyborg body; and the rediscovery of an aesthetic knowledge in nursing care. [ABSTRACT FROM AUTHOR]

Aim: We explored the importance of digital technologies to health responses during the COVID‐19 pandemic. The benefits, challenges and barriers to developing digital capabilities are identified, and strategies to establish enduring digital proficiency among nurses and healthcare colleagues gained during the pandemic are canvassed. Background: Since the mid‐20th century, technology uptake by health practitioners has prioritised digital information and communication technology. The COVID‐19 pandemic accelerated the need to adapt digital communication to dangerous clinical workplaces. Organisational policies enabled digital capabilities to replace in‐person processes while preserving regulatory compliance, safety and security of patient information and staff deployment. Sources of Evidence: All evidence was accessed from publicly available sources. Discussion: The COVID‐19 pandemic was a catalyst for implementing Technology Enhanced Care Services. Health practitioners need appropriate digital capabilities for their roles and scope of practice. Nursing proficiency includes technological skills. Combining the Jisc Digital Capability Framework and the Health and Care Digital Capabilities Framework helps nurses achieve the technical expertise needed for clinical proficiency in contemporary healthcare environments. Conclusion: Healthcare workforce digital capability requires policies that resource digital technologies and individual user skills in dangerous COVID‐19 workplaces. All involved must be abreast of technological changes and monitor technology effectiveness in innovation in patient care, professional education and evidence‐based infectious disease management of healthcare systems. Implications for nursing practice and policy: Nurses and other practitioners in COVID‐19–compromised settings must be able to use the embedded digital technologies in patient care, clinical management and education. Policies securing resources for nurses to learn to use digital technologies will ensure that digital systems are regularly upgraded and that nurses develop proficiency in using technology in their clinical practice. Work and workplace redesign needs compatible computer systems and software to support nursing innovation and digital proficiency. [ABSTRACT FROM AUTHOR]

Actor‐Network Theory is a research lens that has gained popularity in the nursing and health sciences domains. The perspective allows a researcher to describe the interaction of actors (both human and non‐human) within networked sociomaterial contexts, including complex practice environments where nurses and health technology operate. This study will describe Actor‐Network Theory and provide methodological considerations for researchers who are interested in using this sociotechnical lens within nursing and informatics‐related research. Considerations related to technology conceptualization, levels of analysis, and sampling procedures in Actor‐Network Theory based research are addressed. Finally, implications for future nursing research within complex environments are highlighted. [ABSTRACT FROM AUTHOR]