An investigation of the relationship between intensive care nurses' digital literacy, artificial intelligence readiness and artificial intelligence anxiety

The study examines the relationship between intensive care nurses' digital literacy levels, artificial intelligence readiness, and artificial intelligence anxiety; it aims to reveal the predictive power of digital literacy and artificial intelligence readiness levels on artificial intelligence anxiety. This research is descriptive and correlational in nature. A machine learning–based predictive modeling approach wasemployed to evaluate the predictive strength among the variables. Thus, the study is classifiedunder the correlational-predictive quantitative research design.The research sample consisted of 352 intensive care nurses who met the inclusion criteria and were reached using the snowball sampling method.Data were collected using the Information Form, Digital Literacy Scale, Medical Artificial Intelligence Readiness Scale, and Artificial Intelligence Anxiety Scale. Data analysis was conducted using SPSS Statistics for Windows 25.0 and Python. The finding srevealed that intensive care nurses had a high level of digital literacy (102.39 ± 12.30), a moderate level of medical artificial intelligence readiness (67.94 ± 15.86), and above-moderate artificial intelligence anxiety (89.82 ± 19.11). According to the results, there was a significant and positive relationship between total digital literacy scores and the cognitive, skill, foresight, ethics sub dimensions, and total scores of the Medical AI Readiness Scale. Multiple linear regression analysis showed that the "dailyuse" and "Professional production" sub dimensions of digital literacy positively affected AI readiness, whereasthe "ethics and responsibility" subdimension had a negative effect. Machine learning analysis indicated that digital literacy and medical AI readiness sub dimensions were determinants of artificial intelligence anxiety (R² = 0.68). Feature importance analysis identified cognitive awareness as the most influential factor on anxiety. Based on the findings, it is recommended to organize comprehensive training programs to enhance intensive care nurses' digital literacy and AI readiness levels. Education and technology integration programs should be planned considering the needs of nurses working nightshift sand in various intensive care units. It is also suggested that feedback from nurses be considered when designing AI-based applications to helpreduce anxiety.