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

Journal: Journal of gastroenterology and hepatology
Published Date: Jul 3, 2025

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.

Authors

  • Thomas Yuen Tung Lam
    The Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Yue Hu
    Department of Biobank, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Y Yi
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Complex Severe and Rare Diseases, Beijing 100730, China.
  • Peter J Schulz
    Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • May O Lwin
    Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore.
  • Kalya M Kee
    Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Wilson W B Goh
    Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Max F K Cheung
    Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • H S Lee
    Combined Endoscopy Unit, Alice Ho Miu Ling Nethersole Hospital, Hong Kong SAR, China.
  • Alice S H Fan
    Combined Endoscopy Unit, Alice Ho Miu Ling Nethersole Hospital, Hong Kong SAR, China.
  • Phyllis P Y Lam
    Hui Siu Wing Endoscopy Centre, CUHK Medical Centre, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • S F Lam
    Shaw Endoscopy Centre, Prince of Wales Hospital, Hong Kong SAR, China.
  • L Zhou
    Department of Orthopaedics and Traumatology, Beijing Jishuitan Hospital, Beijing 100035, China.
  • Y Chen
  • F Li
  • Ying Lau
    Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore. Electronic address: nurly@nus.edu.sg.
  • Jer-Wei Wu
    Department of Internal Medicine, National Taiwan University Hospital, Taipei, China.
  • Han-Mo Chiu
    Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
  • H Xu
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston , Houston, Texas, USA.
  • Joseph J Y Sung
    Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.

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