Bridging the Mediating Role of Artificial Intelligence Challenges between Nursing Students' Artificial Intelligence Attitude and Self-Efficacy | ||
| Egyptian Journal of Health Care | ||
| Volume 16, Issue 3, September 2025, Pages 1034-1044 PDF (241.34 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ejhc.2025.459306 | ||
| Authors | ||
| Safaa Mohamed Adam Tozer1; Naglaa Gamal ELdeen Abdelhafez2; Om Hashem Gomaa Ragab3; Mohamed Hussein Ramadan Atta4; Sara Mustafa Ahmed5; Ghona Abd El Nasser Ali6; Seham Hassan Mohamed1 | ||
| 1Lecturer of Critical Care and Emergency Nursing, Faculty of Nursing, Sohag University | ||
| 2Assist. Prof. of Critical Care and Emergency Nursing, Faculty of Nursing, Sohag University | ||
| 3Assist. Prof. Nursing Administration, Faculty of Nursing, Sohag University | ||
| 4Assistant Professor, Nursing Department, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz University, Wadi Addawasir, Saudi Arabia Lecturer of Psychiatric and mental health Nursing, Psychiatric and mental- health nursing Department, Faculty of Nursing, Alexandria University, Alexandria City, Egypt | ||
| 5Lecturer of Medical - Surgical Nursing Department - Faculty of Nursing - Sohag University | ||
| 6Prof. of Medical - Surgical Nursing Department - Faculty of Nursing - Sohag University | ||
| Abstract | ||
| Background: Artificial intelligence (AI) has emerged as a transformative force in nursing education, offering benefits such as adaptive learning, simulations, and intelligent assessment. However, challenges related to ethics, privacy, and technical limitations may influence students’ ability to engage confidently with AI. Aim: To examine the mediating role of AI challenges in the relationship between nursing students’ attitudes toward AI and their self-efficacy. Methods: A cross-sectional study was conducted with a convenience sample of 342 undergraduate nursing students across all four academic levels at Sohag University. Data were collected using three validated instruments: the AI Challenges Assessment Questionnaire, the AI Attitude Scale, and the General Self-Efficacy Scale. Statistical analyses included descriptive statistics and path analysis to assess direct, indirect, and total effects. Results: Most participants were female (50.3%), from rural areas (63.5%), and had not received formal AI training (89.5%). However, 91.2% reported using AI applications, with ChatGPT being the most common (77%). High levels of AI challenges (80.4%), AI attitude (67.5%), and self-efficacy (76.6%) were observed. Path analysis revealed a significant direct effect of AI attitude on self-efficacy (β = 0.343, p < 0.001), an indirect effect through AI challenges (β = 0.266, p < 0.001), and a total effect of β = 0.609 (p < 0.001). Conclusion: AI challenges partially mediate the relationship between students’ attitudes toward AI and their self-efficacy. Positive attitudes enhance self-efficacy, but overcoming AI-related barriers is essential to maximize this impact. Recommendation: Provide supportive guidance from faculty members how model effective AI use, address student concerns, and foster a positive learning environment. | ||
| Keywords | ||
| Artificial intelligence; nursing education; nursing students; AI challenges; AI attitude; self-efficacy; mediation analysis | ||
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