Individual Innovativeness Levels and Levels of Medical Artificial Intelligence Readiness Among Nursing Students: a Cross-sectional and Correlational Study

Aim: In this study, it was aimed to determine the individual innovativeness levels of nursing students and their readiness levels for medical artificial intelligence and the relationship between these two variables. Background: A healthcare team with innovative personality traits is necessary for the active use of artificial intelligence in the field of health. It is important to determine the perspectives of nursing students, who are among the most crowded members of the team and whom we define as the nurses of the future, in this direction. Desing : The research was designed as descriptive and correlational. Method: The study was conducted with 781 nursing students using a cross-sectional method. The data were collected using Personal Information Form, Individual Innovativeness Scale (IIS) and Medical Artificial Intelligence Readiness Scale (MAIRS). Results :The mean total score of the IIS, nursing students was 55.09±9.22 and the mean total score of the MARS nursing students was 67.63±12.83 and there was a weak positive correlation between the scales (r=.172, p<0.001). Conclusion: In our study, it was determined that nursing students' individual innovativeness levels positively affected their readiness for medical artificial intelligence. It was concluded in this study that the individual innovativeness level of the nursing students was low; in other words, they adopted a traditionalist attitude and approached artificial intelligence cautiously. It is recommended that the existing curricula be restructured to strengthen the innovative perspective of nursing students and to understand, use, and develop artificial intelligence technologies in nursing, and nursing educators should upskill themselves in this field.