BMC Nursing (Mar 2024)
Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students’ perception of and intention to use them: a descriptive study
Abstract
Abstract Background Artificial intelligence (AI)-based healthcare technologies are changing nurses’ roles and enhancing patient care. However, nursing students may not be aware of the benefits, may not be trained to use AI-based technologies in their practice, and could have ethical concerns about using them. This study was conducted to identify the dual mediating effects of anxiety to use and acceptance attitude toward AI on the relationship between perception of and intentions to use AI among nursing students in South Korea. Methods The research model followed the PROCESS Macro model 6 proposed by Hayes. The participants were 180 nursing students in Gyeonggi-do. Data were collected from January 5–16, 2023, using self-reported questionnaires. Data were analyzed using the SPSS/WIN 25.0 program, with independent t-tests, one-way analysis of variance, Pearson’s correlations, and Hayes’s PROCESS macro method for mediation. Results AI perception positively correlated with acceptance attitude (r =.44, p <.001), intention to use AI (r =.38, p <.001) and negatively correlated with anxiety (r = −.27, p <.001). Anxiety about AI negatively correlated with an acceptance attitude toward AI (r = −.36, p <.001) and intentions to use AI (r = −.28, p <.001). Acceptance attitude toward AI positively correlated with intentions to use AI (r =.43, p <.001). Anxiety about AI and acceptance attitude toward AI had a dual mediating effect on the relationship between AI perception and intentions to use AI. Conclusions It is necessary to develop systematic educational programs to improve the perception of AI. Thus, the competency and professionalism of nursing students regarding the use of AI in healthcare can be improved.
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