Artificial Intelligence in Pediatric Nursing Care: A Bibliometric and Visualization Analysis of the Literature (2000-2024).

Abstract

This bibliometric analysis investigates the evolving landscape of artificial intelligence in pediatric nursing care, leveraging bibliometric techniques and visualization to analyze 317 publications indexed in Web of Science (2000-2024). We conducted citation and co-occurrence analyses of keywords, utilizing VOSviewer to map the scientific knowledge base. Results indicate an exponential growth trajectory in publications and citation impact, particularly post-2019, with the United States as the leading contributor. Thematic analysis reveals a distinct focus on symptom management, emotional support, and family-centered care within pediatric artificial intelligence nursing research, diverging from the predominantly disease-centric focus in general medical artificial intelligence literature. Five key thematic clusters emerged: (1) clinical and disease-focused pediatric nursing, (2) technology and innovation in nursing education and practice, (3) pain and psychological well-being in pediatric surgical patients, (4) adolescent mental health and COVID-19's impact, and (5) family-centered care and holistic pediatric nursing. This study underscores the transformative potential of artificial intelligence to augment pediatric nursing practice, enabling personalized and holistic care. These findings provide crucial insights for nursing informatics specialists, researchers, and clinicians to guide future research, address ethical implications, and develop evidence-based implementation strategies for integrating artificial intelligence into pediatric care.