Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology

Increasing acceptance of medical AI: The role of medical staff participation in AI development

“…Scholars argued that general attitudinal and affective tendencies are essential topics for predicting behaviors and attitudes towards certain types of AI in specific contexts [52] . As a negative affective state in the workplace, employees’ technology anxiety might impair their willingness of proactive behavior [53] , [54] . Especially when anxiety arises from the application of new technologies in the organization, acceptance of new technologies for employees may be greatly reduced [55] .…”

Performance of Artificial Intelligence: Does artificial intelligence dream of electric sheep

“…Within the context of generative AI in higher education policies, these resources and support speci cally include the extent to which universities provide the essential technical, academic, and policy frameworks required for the effective integration of generative AI tools. Numerous studies have suggested that facilitating conditions are another determinant of individuals' acceptance of AI technologies (Cabrera-Sánchez et al, 2021; Chatterjee & Bhattacharjee, 2020; Kwak et al, 2022). More recently, a survey study found that facilitating conditions had the strongest effect on students' intentions and actual usage of generative AI (Habibi et al, 2023), indicating that when students had access to the necessary resources for using generative AI, such as a laptop and internet connection, they were not only more intent on using generative AI but also used it more frequently.…”

“…Our also contributes to the extensive research on the Technology Acceptance Model (TAM) or the Uni ed Theory of Acceptance and Use of Technology (UTAUT) framework by investigating the second research question: Can we validate its evaluation with criterion evaluations of other aspects, including performance expectancy, university conditions, and perceived risk? Previous studies have suggested that performance expectancy, facilitating conditions, and perceived risk are associated with the acceptance of AI technologies, underlining their role in technology adoption decisions (Ben Ar et al, 2021; Cabrera-Sánchez et al, 2021; Chatterjee & Bhattacharjee, 2020; Guggemos et al, 2020;Kwak et al, 2022;Zhang et al, 2019). Recent studies indicate that performance expectancy and facilitating conditions are positively associated with students' attitudes and usage of generative AI, while perceived risk is negatively associated with the acceptance of generative AI in (Foroughi et al, 2023;Habibi et al, 2023;Jain & Raghuram, 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

“…AI-based technology will revolutionize nursing and healthcare by enhancing health promotion and disease prevention, facilitating the development of personalized treatment plans, automating tasks, and fostering collaboration among healthcare professionals [ 5 ]. Surprisingly, in the United States, a leader in advanced health technologies, 70% of nurses were unaware of AI-based technologies used in healthcare [ 5 ], and only 3.8% of nursing students received AI-related education during their undergraduate studies [ 6 ]. Moreover, previous studies [ 7 , 8 ] showed that relatively few studies assess nurses’ perceptions or acceptance of the novel technology in healthcare.…”

“…Potential users of AI-based technologies, nurses, and nursing students are uniquely positioned to influence and spearhead the application of AI in the nursing industry [ 11 ]. Thus, it is essential to show how users comprehend and adopt new technology, such as AI-based technology in healthcare [ 6 ].…”