Influencing factors and relationship between innovation characteristics of nursing students and their medical artificial intelligence readiness

Aim: The aim of this study is to examine the influencing factors and relationship between the innovation characteristics of nursing students and their medical artificial intelligence readiness. Materials and Methods: This research is a descriptive study. The study sample consisted of 616 nursing students studying at Manisa Celal Bayar University, Faculty of Health Sciences. Data were collected using the Student Identification Form, Individual Innovation Scale and Medical Artificial Intelligence Readiness Scale. The analysis of the data included the use of frequency, percentage distribution, descriptive statistics, Mann Whitney U test, Kruskal Wallis test and Spearman correlation analysis. Results: The average score of the medical artificial intelligence readiness scale was 75.77±12.63 and students levels of readiness for medical artificial intelligence were found to be at a moderate level. The average score of the individual innovativeness scale was 64.23±8.47, indicating that the students levels of individual innovativeness were at a low level. When evaluated according to the scores of the individual innovativeness scale, it was found that they were in the 'skeptical'and 'inquisitive' group. According to the classification of the students on the individual innovativeness scale, %35.5 were identified as inquirers and skeptics, %18.6 as traditionalists, %9.8 as pioneers and %1.5 as innovators. It was determined that there was a significant difference between the scores of the individual innovativeness scale and medical artificial intelligence readiness scale. Conclusion: It was determined that the students levels of readiness for medical artificial intelligence were at a moderate level, while their levels of individual innovativeness scale scores, it was found that they were in the low level adopter, high level inquirer, and skeptic groups. A weak positive correlation was found between the individual innovativeness scale and medical artificial intelligence readiness scale. Key Words: Artificial intelligence, innovativeness, nursing, readiness, students