Attitudes of radiologists and interns toward the adoption of GPT-like technologies: a National Survey Study in China.

IF 4.1 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Insights into Imaging Pub Date : 2025-01-31 DOI:10.1186/s13244-025-01908-8

Tianyi Xia, Shijun Zhang, Ben Zhao, Ying Lei, Zebin Xiao, Bingwei Chen, Junhao Zha, Yaoyao Yu, Zhijun Wu, Chunqiang Lu, Tianyu Tang, Yang Song, Yuancheng Wang, Shenghong Ju

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引用次数: 0

Abstract

Objectives: To investigate the attitudes of Chinese radiologists or interns towards generative pre-trained (GPT)-like technologies.

Methods: A prospective survey was distributed to 1339 Chinese radiologists or interns via an online platform from October 2023 to May 2024. The questionnaire covered respondent characteristics, opinions on using GPT-like technologies (in clinical practice, training and education, environment and regulation, and development trends), and their attitudes toward these technologies. Logistic regression was conducted to identify underlying factors associated with the attitude.

Results: After quality control, 1289 respondents (median age, 37.0 years [IQR, 31.0-44.0 years]; 813 males) were surveyed. Most of the respondents (n = 1223, 94.9%) supported adoption of GPT-like technologies. Based on the acceptance level of GPT-like technologies, the respondents were 3 (0.2%), 29 (2.2%), 352 (27.3%), 677 (52.5%), and 228 (17.7%) from low to high acceptance degrees. Multivariable analysis revealed significant associations between positive attitudes towards GPT-like technologies and their acceptance: writing papers and language polishing (odds ratio [OR] = 1.99; p < 0.001), influence of colleagues using such technologies (OR = 1.77; p = 0.007), government regulation introduction (OR = 2.25; p < 0.001), and enhancement of decision support capabilities (OR = 2.67; p < 0.001). Sensitivity analyses confirmed these results for different acceptance thresholds (all p < 0.001).

Conclusions: Chinese radiologists or interns generally support GPT-like technologies due to their potential capabilities in clinical practice, medical education, and scientific research. They also emphasize the need for regulatory oversight and remain optimistic about their future medical applications.

Critical relevance statement: This study highlights the broad support among Chinese radiologists for GPT-like technologies, emphasizing their potential to enhance clinical decision-making, streamline medical education, and improve research efficiency, while underscoring the need for regulatory oversight.

Key points: The impact of GPT-like technologies on the radiology field is unclear. Most Chinese radiologists express the supportive adoption of GPT-like technologies. GPT-like technologies' capabilities at research and clinic prompt the attitude.

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来源期刊

Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

7.30

自引率

4.30%

发文量

182

审稿时长

13 weeks

期刊介绍： Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.