Artificial intelligence use as a key predictor of clinical performance in nursing students: a cross-sectional study from Iran
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) use significantly enhances clinical performance in nursing students, acting as an independent predictor. Integrating AI literacy into nursing curricula is crucial for improving evidence-based practice and patient care.
Area Of Science
- Nursing Education
- Health Informatics
- Artificial Intelligence in Healthcare
Background
- The role of artificial intelligence (AI) in healthcare education is expanding.
- Its specific impact on nursing students' clinical performance, especially in resource-limited settings, requires further investigation.
Purpose Of The Study
- To examine the association between AI utilization and clinical performance in undergraduate nursing students.
- To control for demographic factors in this relationship.
Main Methods
- A cross-sectional study involving 134 nursing students from Abadan University of Medical Sciences.
- Data collected via the Artificial Intelligence in Nursing Questionnaire and Clinical Performance Questionnaire (CPQ).
- Statistical analysis included correlation, multiple linear regression, and univariate general linear modeling (GLM).
Main Results
- AI use showed a significant positive correlation with overall clinical performance (r = 0.424, p < 0.001).
- AI use was the sole significant predictor in the regression model, explaining 21.1% of performance variance (R² = 0.211).
- AI use independently predicted performance across all clinical subscales, notably in Research, Patient-Centered Care, and Personal Management.
Conclusions
- AI use is a strong, independent predictor of nursing students' clinical performance.
- Findings support the integration of AI literacy into nursing curricula to foster evidence-based practice and critical thinking.
- AI holds transformative potential for clinical nursing education.
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