Research Information System
Journal of Pediatric Nursing, vol.88, pp.429-434, 2026 (SCI-Expanded, SSCI, Scopus)
Purpose This study was conducted to determine pediatric nurses' use of generative artificial intelligence and their level of competency. Methods The study was descriptive in nature and conducted online between March 15 and September 30, 2025. The study involved 546 pediatric nurses. Data collection tools included the Data Collection Form and the Artificial Intelligence Use and Competence Scale. In the evaluation of the data, descriptive statistics, Kolmogorov–Smirnov and Shapiro–Wilk tests, Independent Samples t -test, Pearson correlation test, one-way ANOVA, and Tukey post-hoc test were used. The significance level was set at p < 0.05. Results Participants were found to have worked as pediatric nurses for 8.75 ± 4.92 years. It was determined that very few nurses had received training related to artificial intelligence (9.3%, n = 51), used generative artificial intelligence applications, and that the majority of those who used them (77.2%, n = 27) did not feel competent while using the applications. The mean scores of pediatric nurses on the Generative Artificial Intelligence Use and Competence Scale were found to be 48.97 ± 10.07 (Minimum = 28.00, Maximum = 76.00). Conclusion Pediatric nurses were found to have low levels of Generative Artificial Intelligence Use and Competence. As the number of years working as a pediatric nurse increases, so do the levels of Generative Artificial Intelligence Use and Competence. Clinical implications Generative artificial intelligence accelerates pediatric clinical assessment, reduces errors, enhances decision-making accuracy, and increases nurses' direct care time. Strengthening pediatric nurses' competencies in this field will clearly improve the safety, standardization, and overall quality of pediatric care.