Sarangi Pradosh Kumar, Panda Braja Behari, P Sanjay, Pattanayak Debabrata, Panda Swaha, Mondal Himel
Department of Radiodiagnosis, All India Institute of Medical Sciences, Deoghar, Jharkhand, India.
Department of Radiodiagnosis, Veer Surendra Sai Institute of Medical Sciences and Research, Burla, Odisha, India.
Indian J Radiol Imaging. 2024 Jul 19;35(1):35-42. doi: 10.1055/s-0044-1788605. eCollection 2025 Jan.
The integration of large language models (LLMs) into medical education has received increasing attention as a potential tool to enhance learning experiences. However, there remains a need to explore radiology postgraduate students' engagement with LLMs and their perceptions of their utility in medical education. Hence, we conducted this study to investigate radiology postgraduate students' knowledge, attitudes, and practices regarding LLMs in medical education. A cross-sectional quantitative survey was conducted online on Google Forms. Participants from all over India were recruited via social media platforms and snowball sampling techniques. A previously validated questionnaire was used to assess knowledge, attitude, and practices regarding LLMs. Descriptive statistical analysis was employed to summarize participants' responses. A total of 252 (139 [55.16%] males and 113 [44.84%] females) radiology postgraduate students with a mean age of 28.33 ± 3.32 years participated in the study. The majority of the participants (47.62%) were familiar with LLMs with their potential incorporation with traditional teaching-learning tools (71.82%). They are open to including LLMs as a learning tool (71.03%) and think that it would provide comprehensive medical information (62.7%). Residents take the help of LLMs when they do not get the desired information from books (46.43%) or Internet search engines (59.13%). The overall score of knowledge (3.52 ± 0.58), attitude (3.75 ± 0.51), and practice (3.15 ± 0.57) were statistically significantly different (analysis of variance [ANOVA], < 0.0001), with the highest score in attitude and lowest in practice. However, no significant differences were found in the scores for knowledge ( = 0.64), attitude ( = 0.99), and practice ( = 0.25) depending on the year of training. Radiology postgraduate students are familiar with LLM and recognize the potential benefits of LLMs in postgraduate radiology education. Although they have a positive attitude toward the use of LLMs, they are concerned about its limitations and use it only in limited situations for educational purposes.
作为一种增强学习体验的潜在工具，将大语言模型（LLMs）融入医学教育已受到越来越多的关注。然而，仍有必要探索放射科研究生与大语言模型的互动情况，以及他们对其在医学教育中效用的看法。因此，我们开展了这项研究，以调查放射科研究生在医学教育中关于大语言模型的知识、态度和实践。
通过谷歌表单在线进行了一项横断面定量调查。来自印度各地的参与者通过社交媒体平台和滚雪球抽样技术招募。使用一份先前经过验证的问卷来评估关于大语言模型的知识、态度和实践。采用描述性统计分析来总结参与者的回答。
共有252名放射科研究生（139名[55.16%]男性和113名[44.84%]女性）参与了该研究，平均年龄为28.33 ± 3.
