ENTERPRISE AI ANALYSIS
Attitudes toward artificial intelligence in nursing education, research, and clinical practice: a cross-sectional survey of Iranian faculty, nurses, and students
This study investigated the attitudes of Iranian nursing faculty, nurses, and students towards artificial intelligence (AI) in education, research, and clinical practice. Overall, participants demonstrated moderate to good attitudes, with significantly more favorable perceptions in educational and research domains compared to clinical applications. Faculty members and students showed more positive attitudes than clinical nurses, and female participants were more receptive than males. The findings underscore the need for targeted training programs, particularly for clinical nurses, and integrating AI concepts into nursing curricula to facilitate effective adoption within Iran's healthcare system.
Key Metrics & Immediate Impact
This analysis highlights critical insights for integrating AI into nursing, revealing moderate overall acceptance but notable disparities across professional roles and application domains.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Overall Attitudes
Examines the general sentiment toward AI across all nursing groups and domains, highlighting the moderate to good acceptance levels observed in the study.
Domain-Specific Attitudes
Details how attitudes vary between AI applications in education, research, and clinical practice, with greater favorability in academic settings.
Group Differences
Compares attitudes among faculty members, clinical nurses, and students, identifying which groups are more receptive and which face greater challenges in AI adoption.
Enterprise Process Flow
| Role | Key Perceptions in Education & Research | Key Concerns in Clinical Practice |
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| Faculty |
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| Students |
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| Clinical Nurses |
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Targeted Training for Clinical Nurses
Problem: Clinical nurses reported significantly lower attitudes towards AI applications, often due to concerns regarding patient safety, accountability, and workflow disruption. This hesitation is a critical barrier to effective AI integration at the point of care.
Solution: Design and implement targeted in-service training programs that specifically address clinical AI applications. These programs should emphasize AI as a supportive tool that enhances, rather than replaces, clinical judgment, and actively involve nurses in the design and evaluation of AI systems.
Impact: Increased acceptance and trust in AI technologies among frontline nurses, leading to safer, more efficient, and patient-centered care. Improved integration of AI tools into daily workflows, enhancing diagnostic support and patient outcomes.
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