Work

Mapping research trends and competency domains in nursing-related digital and artificial intelligence technologies: A bibliometric analysis

Year: 2025

Type: article

Abstract: Objectives: This study aimed to explore the research trends, thematic structures, and core competency domains in the field of nursing-related digital and artificial intelligence (AI) technologies. Methods: A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement. Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus, Web of Science, and PubMed. Thematic clustering was conducted using the Louvain algorithm and cosine similarity. A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters. Results: A total of 83,807 articles were included for bibliometric analysis. Of these, 66 articles were chosen for thematic analysis. Five major thematic clusters were identified: remote care in primary settings, oncology and palliative care, nurse education and training, safety and quality in nursing practice, and geriatric and dementia care. Additionally, four competency domains were identified: telehealth and remote communication, health systems and informatics, digital tools in practice, and AI-powered decision support. A clear shift in research focus was observed, with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation, encompassing ethical reasoning, immersive technology use, and AI integration. Conclusions: Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains, highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use. This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research, curriculum design, and policy planning.

Source: International Journal of Nursing Sciences

DOI: 10.1016/j.ijnss.2025.12.011

Authors: Kanjanee Phanphairoj, Wasinee Wisesrith, Sutthisan Chumwichan

Institutions: Chulalongkorn University, Assumption University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: Chulalongkorn University