Abstract
Background
Artificial intelligence (AI) is transforming healthcare, requiring nursing students to develop AI competencies. Nursing students, as key stakeholders in healthcare, must develop AI-related competencies to ensure effective utilization in practice. This study examines the predictors of AI adoption, specifically readiness, AI anxiety, and professional impact, among nursing students at Fatima College of Health Sciences, UAE.
Methods
A cross-sectional, descriptive correlational study design was employed. Data were collected from 120 undergraduate nursing students (98.3% female) between December 2023 and March 2024 using an online survey. The study utilized the AI Scale and Shinners Artificial Intelligence Perception tool to measure constructs such as intent to use AI, readiness, AI-related anxiety, and perceived professional impact. Data analysis was conducted using SPSS, applying descriptive statistics, Pearson correlations, and multiple regression analyses to identify significant predictors of AI adoption intent.
Results
Descriptive analysis indicated that readiness, AI understanding, and anxiety were key determinants of AI adoption among nursing students. Pearson correlation analysis demonstrated that readiness had the strongest association with AI adoption intent (r = 0.559, p < 0.01), followed by AI anxiety (r = 0.507, p < 0.01). Multiple regression analysis confirmed that readiness (B = 0.254, p < 0.001), AI understanding (B = 0.413, p = 0.004), and AI anxiety (B = 0.205, p = 0.028) were significant predictors of AI adoption. However, perceived barriers to AI use were not significantly associated with adoption intent.
Conclusion
The findings underscore the importance of readiness, AI knowledge, and professional relevance in fostering AI adoption among nursing students. Enhancing readiness through tailored curricula, practical AI training, and anxiety management strategies can facilitate AI integration in nursing education. Addressing these factors aligns with the UAE’s vision of AI-driven healthcare innovation, ensuring that future nursing professionals are well-equipped to navigate AI-enhanced clinical environments.
Artificial intelligence (AI) is transforming healthcare, requiring nursing students to develop AI competencies. Nursing students, as key stakeholders in healthcare, must develop AI-related competencies to ensure effective utilization in practice. This study examines the predictors of AI adoption, specifically readiness, AI anxiety, and professional impact, among nursing students at Fatima College of Health Sciences, UAE.
Methods
A cross-sectional, descriptive correlational study design was employed. Data were collected from 120 undergraduate nursing students (98.3% female) between December 2023 and March 2024 using an online survey. The study utilized the AI Scale and Shinners Artificial Intelligence Perception tool to measure constructs such as intent to use AI, readiness, AI-related anxiety, and perceived professional impact. Data analysis was conducted using SPSS, applying descriptive statistics, Pearson correlations, and multiple regression analyses to identify significant predictors of AI adoption intent.
Results
Descriptive analysis indicated that readiness, AI understanding, and anxiety were key determinants of AI adoption among nursing students. Pearson correlation analysis demonstrated that readiness had the strongest association with AI adoption intent (r = 0.559, p < 0.01), followed by AI anxiety (r = 0.507, p < 0.01). Multiple regression analysis confirmed that readiness (B = 0.254, p < 0.001), AI understanding (B = 0.413, p = 0.004), and AI anxiety (B = 0.205, p = 0.028) were significant predictors of AI adoption. However, perceived barriers to AI use were not significantly associated with adoption intent.
Conclusion
The findings underscore the importance of readiness, AI knowledge, and professional relevance in fostering AI adoption among nursing students. Enhancing readiness through tailored curricula, practical AI training, and anxiety management strategies can facilitate AI integration in nursing education. Addressing these factors aligns with the UAE’s vision of AI-driven healthcare innovation, ensuring that future nursing professionals are well-equipped to navigate AI-enhanced clinical environments.
| Original language | English |
|---|---|
| Journal | Digital Health |
| Publication status | Accepted/In press - 9 Jun 2025 |
Funding
This research received no funding.
Keywords
- Artificial intelligence
- AI adoption
- nursing students
- readiness
- AI anxiety
- professional impact
- healthcare education
- UAE
- nursing curriculum
- AI perception
