A Cross-Sectional Online Study of the Use of Artificial Intelligence in Nursing Research as Perceived by Nursing Students.

Abstract

Background: The use of artificial intelligence (AI) in healthcare in general and scientific research in particular has become increasingly prevalent as it holds great promise for optimizing research processes and outcomes.

Aims: This study described predictors and differences in students' perceptions of the risks and benefits related to using AI in nursing research.

Methods: A quantitative transverse study was implemented utilizing a convenient sample of 434 nursing students from a governmental university. Data were analyzed using many descriptive and inferential statistics.

Results: Nursing students perceived AI in nursing research positively, with an overall mean score of 3.24/5 (SE = .024). Their feelings about AI were generally positive (Mean = 3.54/5; SE = .049; 95% CI = 3.45-3.64). Perceived risks of using AI in research were high (Mean = 1.59/2, SE = .016), especially concerning liability issues (Mean = 3.50/5, SE = .031), communication barriers (Mean = 3.48, SE = .035), unregulated standards (Mean = 3.37, SE = .034), privacy concerns (Mean = 3.37, SE = .034), social biases (Mean = 3.33, SE = .033), performance anxiety (Mean = 3.31, SE = .034), and mistrust in AI mechanisms (Mean = 3.28, SE = .032). The perceived benefits were also high (Mean = 3.46, SE = .030), with a strong intention to use AI-based tools (Mean = 3.52, SE = .033). Key predictors were high GPA and training in public hospitals. hospitals.

Conclusion: AI in nursing research has many benefits; however, it comes with risks that need immediate management. Nursing students' GPAs and the hospitals where they received their training were often the key factors that shaped how well they understood the use of AI in nursing research. High-achieving students who were trained in public and teaching hospitals tend to be better users of AI in nursing research.