Nursing Informatics Competence as a Predictor of Nursing Performance: A Comparison of AI and Human Statistical Analyses

Abstract Background: The digitalization of healthcare has highlighted the growing importance of nursing informatics competence, while the use of artificial intelligence in healthcare research continues to expand. This study aimed to examine the impact of nursing informatics competence on nursing performance and to compare the accuracy of statistical analyses conducted by AI and a human researcher. Methods: A cross-sectional study was conducted with 48 clinical nurses. Nursing informatics competence was measured using the Korean Nursing Informatics Competence Assessment Scale, and nursing performance was assessed with a validated appraisal tool. Data were collected by structured questionnaires and analyzed with SPSS and ChatGPT. Analyses included descriptive statistics, independent t-tests, Pearson’s correlation, and linear regression. Results from AI-assisted analyses were compared with those obtained through traditional statistical methods. Results: Nursing informatics competence showed a significant positive correlation with nursing performance, and regression analysis confirmed it as a significant predictor (β = .63, p < .001), explaining 38.5% of the variance. Among the nursing informatics competence subdomains, “Use of ICT in Nursing” showed the strongest association with nursing performance. Statistical analyses performed by AI and the human researcher were highly consistent. Conclusions: Nursing informatics competence is a significant predictor of nursing performance. AI-based statistical analysis showed strong agreement with traditional methods, suggesting its potential as a supplementary tool in nursing research.