Abstract
Background: With the rapid advancement of artificial intelligence (AI), the ability to effectively utilize digital and AI technologies has become increasingly essential. Generative AI, now widely adopted, is transforming academic, clinical, and everyday environments by integrating and processing data more efficiently than traditional search engines [1]. However, little is known about nursing students’ intentions to use generative AI in their learning and clinical practice. Therefore, this study developed a theoretical model based on the Technology Acceptance Model (TAM) to examine nursing students’ behavioral intentions toward using generative AI [2].
Purpose: This study aimed to examine the effect of nursing students’ digital literacy on their intention to use generative AI and to analyze the mediating effects of perceived usefulness, perceived ease of use, and privacy concerns.
Methods: Using the Technology Acceptance Model (TAM), a path model was constructed incorporating digital literacy and privacy concerns. Path analysis was conducted to identify the direct and indirect effects of these variables on the intention to use generative AI.
Results: Digital literacy significantly influenced perceived usefulness (β = .32, p < .001), perceived ease of use (β = .34, p < .001), and privacy concerns (β = .27, p < .001). Perceived usefulness (β = .57, p = .010) and perceived ease of use (β = .15, p = .022) significantly affected behavioral intentions to use generative AI, whereas digital literacy (β = –.03, p = .734) and privacy concerns (β = –.09, p = .122) did not show a significant direct effect.
Conclusions: Although digital literacy did not directly affect intention to use generative AI, it exerted a significant indirect influence through perceived usefulness and perceived ease of use. This suggests that individuals with higher digital literacy tend to view generative AI as more useful and easier to use, thereby strengthening their intention to adopt it. These results emphasize that, when introducing AI technologies in educational settings, strategies that enhance users’ perceptions of usefulness and ease of use may be more effective than focusing solely on technical training. Strengthening digital literacy and fostering positive user perceptions are therefore key factors in promoting active and sustainable engagement with generative AI among nursing students.
Notes
References:
[1] Topaz, M., Peltonen, L. M., Michalowski, M., Stiglic, G., Ronquillo, C., Pruinelli, L., ... & Fukahori, H. (2025). The ChatGPT effect: nursing education and generative artificial intelligence. Journal of Nursing Education, 64(6), e40-e43. https://doi.org/10.3928/01484834-20240126-01
[2] Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D., 2003. User acceptance of information technology: toward a unified view. MIS Q. 27 (3), 425–478. https://doi.org/10.2307/30036540
Additional reference listed in attached poster file.
Sigma Membership
Non-member
Type
Poster
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Teaching and Learning Strategies, Continuing Education, Competence, Emerging Technologies, Artificial Intelligence, Digital Literacy, Natural Language Processing, Nursing Students
Recommended Citation
Seo, Yon Hee and Ahn, Jung-Won, "A Path Analysis of Factors Influencing Nursing Students’ Intention to Use Generative AI" (2026). International Nursing Research Congress (INRC). 71.
https://www.sigmarepository.org/inrc/2026/posters_2026/71
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2026-08-12
A Path Analysis of Factors Influencing Nursing Students’ Intention to Use Generative AI
Toronto, Ontario, Canada
Background: With the rapid advancement of artificial intelligence (AI), the ability to effectively utilize digital and AI technologies has become increasingly essential. Generative AI, now widely adopted, is transforming academic, clinical, and everyday environments by integrating and processing data more efficiently than traditional search engines [1]. However, little is known about nursing students’ intentions to use generative AI in their learning and clinical practice. Therefore, this study developed a theoretical model based on the Technology Acceptance Model (TAM) to examine nursing students’ behavioral intentions toward using generative AI [2].
Purpose: This study aimed to examine the effect of nursing students’ digital literacy on their intention to use generative AI and to analyze the mediating effects of perceived usefulness, perceived ease of use, and privacy concerns.
Methods: Using the Technology Acceptance Model (TAM), a path model was constructed incorporating digital literacy and privacy concerns. Path analysis was conducted to identify the direct and indirect effects of these variables on the intention to use generative AI.
Results: Digital literacy significantly influenced perceived usefulness (β = .32, p < .001), perceived ease of use (β = .34, p < .001), and privacy concerns (β = .27, p < .001). Perceived usefulness (β = .57, p = .010) and perceived ease of use (β = .15, p = .022) significantly affected behavioral intentions to use generative AI, whereas digital literacy (β = –.03, p = .734) and privacy concerns (β = –.09, p = .122) did not show a significant direct effect.
Conclusions: Although digital literacy did not directly affect intention to use generative AI, it exerted a significant indirect influence through perceived usefulness and perceived ease of use. This suggests that individuals with higher digital literacy tend to view generative AI as more useful and easier to use, thereby strengthening their intention to adopt it. These results emphasize that, when introducing AI technologies in educational settings, strategies that enhance users’ perceptions of usefulness and ease of use may be more effective than focusing solely on technical training. Strengthening digital literacy and fostering positive user perceptions are therefore key factors in promoting active and sustainable engagement with generative AI among nursing students.
Description
This session explores how nursing students’ digital literacy shapes their intention to use generative AI, highlighting the key roles of perceived usefulness and ease of use. Participants will gain insights into strategies that foster positive perceptions of AI to support effective and sustainable adoption in educational settings.