TY - JOUR
T1 - Knowledge and awareness of generative artificial intelligence use in medicine among international stakeholders
T2 - a cross-sectional study
AU - Luo, Xufei
AU - Wang, Bingyi
AU - Li, Yule
AU - Liu, Shuang
AU - Li, Haodong
AU - Ren, Yaxuan
AU - Yang, Wah
AU - Lam, Kyle
AU - Ali, Stephen R.
AU - Sharp, Gemma
AU - Moraes, Fabio Ynoe
AU - Wang, Ye
AU - Zhu, Di
AU - Yang, Zhenhua
AU - Mohammad, Daher
AU - Fruscio, Robert
AU - Kamel Boulos, Maged N.
AU - Lin, Zhicheng
AU - Ide, Kazuki
AU - Song, Xuping
AU - Zhang, Lu
AU - Tham, Yih Chung
AU - Liu, Hui
AU - Ge, Long
AU - Chen, Yaolong
AU - Bian, Zhaoxiang
PY - 2025/6
Y1 - 2025/6
N2 - Objective: To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools. Methods: A cross-sectional survey was conducted among stakeholders in medicine. Participants included researchers, clinicians, and medical journal editors with varying degrees of familiarity with GAI tools. The survey questionnaire comprised 40 questions covering four main dimensions: basic information, knowledge, attitudes, and practices related to GAI tools. Descriptive analysis, Pearson's correlation, and multivariable regression were used to analyze the data. Results: The overall awareness rate of GAI tools was 93.3%. Participants demonstrated moderate knowledge (mean score 17.71 ± 5.56), positive attitudes (mean score 73.32 ± 15.83), and reasonable practices (mean score 40.70 ± 12.86). Factors influencing knowledge included education level, geographic region, and attitudes (p < 0.05). Attitudes were influenced by work experience and knowledge (p < 0.05), while practices were driven by both knowledge and attitudes (p < 0.001). Participants from outside China scored higher in all dimensions compared to those from China (p < 0.001). Additionally, 74.0% of participants emphasized the importance of reporting GAI usage in research, and 73.9% advocated for naming the specific tool used. Conclusion: The findings highlight a growing awareness and generally positive attitude toward GAI tools among medical stakeholders, alongside the recognition of their ethical implications and the necessity for standardized reporting practices. Targeted training and the development of clear reporting guidelines are recommended to enhance the effective use of GAI tools in medical research and practice.
AB - Objective: To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools. Methods: A cross-sectional survey was conducted among stakeholders in medicine. Participants included researchers, clinicians, and medical journal editors with varying degrees of familiarity with GAI tools. The survey questionnaire comprised 40 questions covering four main dimensions: basic information, knowledge, attitudes, and practices related to GAI tools. Descriptive analysis, Pearson's correlation, and multivariable regression were used to analyze the data. Results: The overall awareness rate of GAI tools was 93.3%. Participants demonstrated moderate knowledge (mean score 17.71 ± 5.56), positive attitudes (mean score 73.32 ± 15.83), and reasonable practices (mean score 40.70 ± 12.86). Factors influencing knowledge included education level, geographic region, and attitudes (p < 0.05). Attitudes were influenced by work experience and knowledge (p < 0.05), while practices were driven by both knowledge and attitudes (p < 0.001). Participants from outside China scored higher in all dimensions compared to those from China (p < 0.001). Additionally, 74.0% of participants emphasized the importance of reporting GAI usage in research, and 73.9% advocated for naming the specific tool used. Conclusion: The findings highlight a growing awareness and generally positive attitude toward GAI tools among medical stakeholders, alongside the recognition of their ethical implications and the necessity for standardized reporting practices. Targeted training and the development of clear reporting guidelines are recommended to enhance the effective use of GAI tools in medical research and practice.
KW - ChatGPT
KW - cross-sectional survey
KW - generative artificial intelligence
KW - knowledge and awareness
UR - http://www.scopus.com/inward/record.url?scp=105007716443&partnerID=8YFLogxK
UR - https://go.openathens.net/redirector/westernsydney.edu.au?url=https://doi.org/10.1111/jebm.70034
U2 - 10.1111/jebm.70034
DO - 10.1111/jebm.70034
M3 - Article
C2 - 40455490
AN - SCOPUS:105007716443
SN - 1756-5383
VL - 18
JO - Journal of Evidence-Based Medicine
JF - Journal of Evidence-Based Medicine
IS - 2
M1 - e70034
ER -