The Relationship between Individual Innovativeness Traits and Medical Artificial Intelligence Readiness Levels among Nursing Students in Türkiye - Öztürk, Özlem; Midilli, Tülay Sağkal (UI Scholars Hub, 2025)
Background: This study examined the relationship between nursing students’ individual innovativeness traits and their readiness for medical artificial intelligence, and the influencing factors. Methods: This study was a descriptive, correlational study. The study was conducted with 606 nursing students enrolled at the Faculty of Health Science, Manisa Celal Bayar University. Data were collected using the Descriptive Information Form, the Individual Innovativeness Scale (IIS), and the Medical Artificial Intelligence Readiness Scale (MAIRS). Results: The mean IIS score was 64.23 ± 8.47, indicating that most students fell into the skeptical or interrogator categories. The mean MAIRS score was 75.77 ± 12.63. A weak positive correlation was found between the IIS and the MAIRS (p < 0.05). Students’ perception of academic success, career goals, awareness of innovation, and their knowledge and usage of artificial intelligence significantly affected their individual innovativeness levels. Additionally, gender, academic year, school achievement perception, and experience with innovation were found to significantly influence readiness for medical artificial intelligence level. Conclusion: Students’ individual innovativeness levels were generally low, with most classified within the skeptical and interrogator categories, while their readiness for medical artificial intelligence was above the moderate level. A positive relationship was observed, indicating that as students’ individual innovativeness levels increased, so did their readiness for medical artificial intelligence.