A Novel Scale to Measure Nursing Students’ Fear of Artificial Intelligence: Development and Validation
Background
The integration of Artificial Intelligence (AI) in healthcare is revolutionizing patient care and clinical practice, enhancing efficiency, accuracy, and accessibility. However, it has also sparked concerns among nursing students about job displacement, reliance on technology, and the potential loss of human qualities like empathy and compassion, to this date, there is no established scale measuring the level of fear, especially among nursing students.
Aim
To develop and validate a scale to assess nursing students' fear of artificial intelligence.
Methods
The current study employed a cross-sectional design, involving a total of 225 Saudi nursing students enrolled in a nursing college. The scale's construct, convergent, and discriminant validity were evaluated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).
Results
A comprehensive review of the literature addressing fear of AI guided the development of the Fear Towards Artificial Intelligence Scale (FtAIS). An initial pool of items was subjected to a content validity assessment by an expert panel, which refined the scale to 10 items categorized into two dimensions: job issues and humanity. The two-factor structure was responsible for 73.52% of the total variance. The scale items' reliability was evaluated using Cronbach's alpha coefficient, yielding a value of 0.803. The reliability coefficients for the two subscales, job issues, and humanity, are 0.804 and 0.801, respectively. The confirmatory factor model demonstrated a good model fit. The scale's convergent and discriminant validity were both confirmed.
Conclusion
The FtAIS is a rigorously developed and validated tool for measuring nursing students' fears toward AI. These findings emphasize the need for targeted educational interventions and training programs that could mitigate AI-related fears and prepare nursing students for its integration into healthcare. The scale offers practical applications for educators and policymakers in addressing AI fear and fostering its confident adoption to enhance patient care and healthcare outcomes.
