Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Multicenter Study
. 2025 Sep;40(9):2275-2281.
doi: 10.1111/jgh.17042. Epub 2025 Jul 3.

A Model Predicting Artificial Intelligence Use by Gastroenterology Nurses in Clinical Practice: A Cross-Sectional Multicenter Survey

Thomas Yuen Tung Lam  1   2   3 , Yue Hu  1 , Y Yi  3 , Peter J Schulz  4   5 , May O Lwin  4 , Kalya M Kee  4   5 , Wilson W B Goh  5 , Max F K Cheung  5 , H S Lee  6 , Alice S H Fan  6 , Phyllis P Y Lam  7 , S F Lam  8 , L Zhou  9 , Y Chen  10 , F Li  11 , Ying Lau  1 , Jer-Wei Wu  12 , Han-Mo Chiu  12 , H Xu  11 , Joseph J Y Sung  2   3   5
Affiliations
Multicenter Study

A Model Predicting Artificial Intelligence Use by Gastroenterology Nurses in Clinical Practice: A Cross-Sectional Multicenter Survey

Thomas Yuen Tung Lam et al. J Gastroenterol Hepatol. 2025 Sep.

Abstract

Background and aims: Nurses' participation during colonoscopy has been demonstrated to significantly improve the detection rate of polyps and adenomas. Nonetheless, the adoption of AI in clinical practice still poses challenges. There is limited understanding of the factors influencing gastroenterology nurses' intentions to use AI in clinical practice. We aimed to examine how gastroenterology nurses' intentions to use AI are affected by perceived usefulness, acceptance of this technology, and perceived risk via a moderated mediation model controlling for nurses' characteristics.

Methods: A cross-sectional multicenter survey study was conducted among gastroenterology nurses from 54 hospitals in Taiwan, Hong Kong, and mainland China. A total of 337 nurses (mean age 37.40 ± 8.29 years, 81.6% females) completed the survey.

Results: After controlling for previous experience with AI, number of working years, and work role, a statistically significant direct effect of perceived usefulness on use intention was found. The indirect effect of perceived usefulness on use intention through AI technology acceptance was the most robust when perceived risk was at the lowest level.

Conclusions: Findings suggest that perceived usefulness facilitated the intentional use of AI in clinical practice through acceptance of AI, especially when perceived risk was low.

Keywords: artificial intelligence; gastroenterology; nurses; risk.

PubMed Disclaimer

Conflict of interest statement

Dr. Han Mo Chiu is an Editorial Board member of JGH and a co‐author of this article. To minimize bias, Dr. Han Mo Chiu was excluded from all editorial decision‐making related to the acceptance of this article for publication.

Figures

FIGURE 1
FIGURE 1
Framework of intention to use AI in clinical settings.
FIGURE 2
FIGURE 2
Graphical representation of model for intention to use AI in practice (N = 337). The 95% confidence intervals of each pathway were displayed in the square brackets. Experience with AI, working years, and working roles were controlled. ***p < 0.001, **p < 0.01.
See this image and copyright information in PMC

References

    1. Babic B., Gerke S., Evgeniou T., and Cohen I. G., “Direct‐to‐Consumer Medical Machine Learning and Artificial Intelligence Applications,” Nature Machine Intelligence 3 (2021): 283–287.
    1. Liu J., Kong X., Xia F., et al., “Artificial Intelligence in the 21st Century,” IEEE Access 6 (2018): 34403–34421.
    1. Lam T. Y., Lam T. Y. T., Cheung M. F. K., et al., “Randomized Controlled Trials of Artificial Intelligence in Clinical Practice: Systematic Review,” Journal of Medical Internet Research 24 (2022): e37188. - PMC - PubMed
    1. Hassan C., Misawa M., Rizkala T., et al., “Computer‐Aided Diagnosis for Leaving Colorectal Polyps In Situ: A Systematic Review and Meta‐Analysis,” Annals of Internal Medicine 177 (2024): 919–928. - PubMed
    1. Hassan C., Spadaccini M., Mori Y., et al., “Real‐Time Computer‐Aided Detection of Colorectal Neoplasia During Colonoscopy: A Systematic Review and Meta‐Analysis,” Annals of Internal Medicine 176 (2023): 1209–1220. - PubMed

Publication types

LinkOut - more resources