AI Summary & Key Takeaways
AI InsightConclusion: The findings indicate that research on AI and digital technologies in postoperative nursing care is rapidly expanding, reflecting a paradigm shift toward data-driven, technology-enhanced, and patient-centered care.
📌 3 Key Takeaways
Abstract
Objective: This study aimed to analyze global research trends, collaboration networks, and thematic developments regarding the use of digital tools and artificial intelligence (AI) in postoperative nursing care for older adults between 2020 and 2025. Methods: A bibliometric analysis was conducted using data from the Web of Science Core Collection. The search included publications from 2020 to 2025 using keywords such as artificial intelligence, digital tools, machine learning, postoperative care, and older adults. Data were analyzed with the Bibliometrix package in RStudio (v4.2.3) and visualized through Biblioshiny. Quantitative indicators—publication trends, citation impact, collaboration rates, and thematic mapping—were evaluated. Results: A total of 44 articles published across 38 journals were analyzed. The annual growth rate of publications was 47.58%, with 222 authors contributing and an average of 5.16 co-authors per paper, reflecting strong international and interdisciplinary collaboration (31.82%). The most productive sources were the Journal of Medical Internet Research and the Journal of Nursing Management. Keyword analysis revealed that artificial intelligence, machine learning, nursing, and technology were dominant, while emerging themes included geriatric rehabilitation and clinical decision support systems. These trends highlight the growing role of AI-driven systems in improving postoperative outcomes and nursing decision-making for older adults. Conclusion: The findings indicate that research on AI and digital technologies in postoperative nursing care is rapidly expanding, reflecting a paradigm shift toward data-driven, technology-enhanced, and patient-centered care. Future research should focus on the validation of AI models, ethical considerations, and the integration of digital competencies into nursing education and practice.