Current status of artificial intelligence utilization in medical education: A cross-sectional survey of medical students and faculty

Current status of artificial intelligence utilization in medical education: A cross-sectional survey of medical students and faculty | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Current status of artificial intelligence utilization in medical education: A cross-sectional survey of medical students and faculty Shigeo Ninomiya, Kyoko Yamamoto, Eiko Mieno, Hirofumi Anai, Naoto Uemura, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7504189/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Generative artificial intelligence (AI), particularly large language models such as ChatGPT, is rapidly transforming various sectors, including medical education. Despite increasing interest, few studies have investigated how AI is actually used in medical education settings, especially in Japan. This study aimed to assess the current use of generative AI among medical students and faculty members, and to identify their perceptions, perceived benefits, and concerns in relation to its integration into medical education. Methods A cross-sectional survey was conducted from April to May 2025 at the Oita University Faculty of Medicine. A total of 1,014 students and 470 faculty members from the School of Medicine, School of Nursing, and Department of Advanced Medical Sciences were invited to complete an anonymous online questionnaire. The survey covered AI usage experience, purposes of use, and attitudes toward AI in academic contexts. Results The response rates were 40% for students (402/1,014) and 74% for faculty members (350/470). Most students (82.1%) and faculty (73.4%) had prior experience using AI tools, primarily for report writing, lecture preparation, and information retrieval, with students showing a higher rate of AI usage experience than faculty (p < 0.05). While 92.8% of students and 86.5% of faculty supported AI use under certain conditions, 73.4% of faculty members reported major concerns, including ethical risks and the risk of personal information leakage. In the faculty survey, younger faculty members and those with AI usage experience were also significantly more likely to approve the introduction of AI into medical education (p < 0.05). Conclusions Generative AI is widely accepted and utilized in medical education. However, ethical guidelines, digital literacy education, and thoughtful integration strategies are essential to ensure its responsible use. Clinical trial number not applicable Artificial intelligence Generative Artificial intelligence Medical education Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Background Generative artificial intelligence (AI) is defined as a class of AI models that generate synthetic outputs based on learning acquired from the datasets used to train the model [ 1 ]. Among these, ChatGPT, one of the most well-known models, has gained explosive popularity, reaching 100 million users within just two months of its release in 2022 [ 2 ]. In recent years, generative AI has brought transformative changes to a wide range of fields, including scientific research, creative arts, customer service, personalized learning, and healthcare. However, research on the actual use of generative AI in medical education in Japan has been limited. Recently, medical students are increasingly believed to use AI for various academic tasks, such as attending lectures and writing reports. Conversely, faculty members are thought to use generative AI for preparing teaching materials and drafting documents. Despite its benefits, the use of AI in medical education presents several challenges. First, AI systems are not always accurate and may provide outdated or incorrect information, which can mislead students and hinder their learning [ 3 ]. Additionally, excessive reliance on AI tools may impair the development of critical thinking and problem-solving skills by encouraging dependency on automated answers [ 3 ]. Ethical concerns also arise, particularly regarding privacy and data security, as AI systems often require access to sensitive personal information [ 4 ]. Moreover, AI algorithms can reflect biases in their training data, potentially reinforcing unfairness or misinformation in educational content. Finally, overuse of AI may reduce meaningful human interaction between students and instructors, which is vital for nurturing communication skills and professional judgment [ 5 ]. Given this social context, the present study aimed to investigate the current use of AI among medical students and faculty members, as well as to identify potential concerns or challenges, in order to help determine the future direction of medical education. Methods Between April and May 2025, a cross-sectional survey was conducted among medical students and faculty members at the Oita University Faculty of Medicine. The questionnaire comprised 9 items each for students and faculty. It was created using Google Forms and administered online. This survey was distributed via email, participation was voluntary, and responses were collected anonymously. No incentives were provided for completing the questionnaire. The questionnaire was developed based on a literature review and under the supervision of experts in medical education and AI (TT and YM), and is provided as a Supplementary file . To ensure content validity, all items were reviewed for clarity and relevance. Although a formal pilot test was not conducted, the questionnaire was refined through internal discussion among the authors and reviewed by domain experts to ensure clarity and relevance. Student Survey: Experience and awareness of AI use among medical students Participants The survey targeted 1,014 students enrolled in three departments at our university: the School of Medicine, the School of Nursing, and the Department of Advanced Medical Sciences. Objectives The student questionnaire included items on prior experience using AI, specific applications used, purposes for which AI was employed, perceptions of AI use in university classes and assignments, experience attending classes incorporating AI, and opinions on the appropriateness of such AI-integrated classes. Faculty Survey: AI use, attitudes, and concerns regarding integration into medical education Participants The survey targeted 470 faculty members from the School of Medicine, the School of Nursing, and the Department of Advanced Medical Sciences. Objectives This survey aimed to assess whether faculty members utilize AI in the preparation of lectures and educational materials and to explore their opinions on the appropriateness of student use of AI for academic activities such as coursework and report writing. In addition, we also investigated concerns regarding the future implementation of AI in medical education. Statistical analysis We examined whether there was a significant difference in AI usage experience between medical students and faculty members. In the faculty survey on the implementation of AI into medical education, statistical analyses were also conducted to evaluate differences by AI usage experience and age. Statistical analyses were performed using SPSS (ver. 29). The chi-square test was applied, with the significance level set at p < 0.05. Multiple comparisons were performed using the chi-square test with Bonferroni correction. Results Student Survey: Experience and awareness of AI use among medical students Response rate The overall response rate among students in the Faculty of Medicine was 40% (402/1,014), with response rates of 29% (192/652) in the School of Medicine, 65% (167/257) in the School of Nursing, and 37% (41/108) in the Department of Advanced Medical Sciences. It is worth noting that the Department of Advanced Medical Sciences was established only three years ago, with an annual enrollment of 35 students, resulting in a smaller total student population. Respondent demographics The breakdown of respondents by academic year was as follows: First-year students: 166 (41.3%) Second-year students: 49 (12.2%) Third-year students: 82 (20.4%) Fourth-year students: 63 (15.7%) Fifth-year students: 23 (5.7%) Sixth-year students: 19 (4.7%) Note Only the School of Medicine includes fifth- and sixth-year levels. By gender, 236 respondents were female (58.7%), 106 were male (26.4%), and 60 did not disclose their gender (14.9%). AI usage experience The AI usage experience among medical students is shown in Fig. 1 . A total of 330 students (82.1%) reported having prior experience using AI. The most frequently reported purpose of AI use among medical students was learning support, and the most commonly used type of AI, as indicated in the survey, was text-generating AI (Fig. 2 ). Attitudes toward AI The attitude of medical students toward AI use is shown in Fig. 3 . In response to the question, "How do you feel about using AI in university courses and assignments?", 103 students (25.6%) answered that AI should be actively used, and 270 students (67.2%) responded that it should be used under certain conditions. When asked, "Have you attended any classes that utilized AI?", 133 students (33.1%) answered "Yes". Regarding increased implementation of AI-integrated classes, 135 students (33.6%) said it was a very good trend, while 202 students (50.2%) considered it somewhat good. Faculty Survey: AI use, attitudes, and concerns regarding integration into medical education Response rate The response rate among faculty members was 74% (350/470). Respondent demographics The largest age group was individuals in their 30s (108 respondents, 30.9%), followed by those in their 40s (94 respondents, 26.9%) and 50s (70 respondents, 20.0%). By gender, 176 respondents (50.2%) were male, 83 (23.7%) were female, and 91 (26.1%) did not respond. The most common job title was Assistant Professor (92 respondents, 26.3%), followed by Professor (88 respondents, 25.1%). AI usage experience The usage of AI among faculty members is shown in Fig. 4 . A total of 257 faculty members (73.4%) reported previous use of AI, which was significantly lower than the rate of 82.1% reported by students ( p < 0.05). The primary purpose of use was routine administrative tasks, followed by research and educational activities. Consistent with the findings among medical students, text-generating AI tools were the most frequently used, with a usage rate of 94.2% (Fig. 5 ). Attitudes toward AI In response to the question, "How do you feel about using AI in university courses and assignments?" 67 faculty members (19.1%) indicated their approval of its use, and 236 faculty members (67.4%) indicated their conditional acceptance of its use. However, 41 respondents (11.7%) believed that its use should be prohibited on principle (Fig. 6 ). When comparing responses to the question “How do you feel about using AI in university courses and assignments?” based on faculty members’ AI usage experience, those with AI usage experience were significantly more likely to approve the use of AI (p < 0.05) (Fig. 7 ). In addition, when analyzed by age group, faculty members in their 20s were significantly more likely to approve the implementation of AI into medical education (p < 0.05) (Fig. 8 ). Regarding how AI could be used in medical education, the most common response was to improve the efficiency of lecture material and slide preparation (256 respondents, 73.1%), followed by its use in data analysis and evidence-based medicine education (191 respondents, 54.6%). Regarding concerns about AI in medical education, 257 respondents (73.4%) cited issues such as the risk of personal data leakage and ethical concerns (Fig. 9 ). Discussion This cross-sectional study investigated the current status of AI utilization and awareness among medical students and faculty members at a single Japanese university. Sami et al. conducted a survey of 702 medical students in Pakistan and found that the majority perceived AI as an effective and credible learning tool, highlighting its potential to optimize study time, improve conceptual understanding, and provide accurate medical information [ 6 ]. Also, Abdelhafiz et al. reported that Egyptian medical students showed strong interest and trust in using ChatGPT and similar chatbots for academic purposes [ 7 ]. Reports from individual countries worldwide reported to date are summarized in Table 1 [ 6 – 14 ]. Many surveys reported favorable attitudes toward the use of AI in medical education. To the best of our knowledge, our study is the first report from Japan. Moreover, there have been no reports that clarify the use of AI or attitudes toward it among not only medical students but also faculty members at medical schools. Consistent with prior findings, Japanese medical students have already been utilizing AI in their studies and expressed a desire to continue using it in the future. On the other hand, a study involving 4,313 medical students from 48 countries also reported similarly positive attitudes toward the use of AI in healthcare and medicine, and found no significant regional differences among the countries [ 15 ]. Table 1 Questionnaire survey on the utilization of AI in medical education. Authors Journal Year Country Sample size Conclusions Sami A [ 6 ] BMC Medical Education 2025 Pakistan 702 AI enhances medical education by providing personalized learning and reliable results. Abdelhafiz AS [ 7 ] BMC Medical Education 2025 Egypt 614 Medical students are interested in using ChatGPT and similar tools for learning but worry about information accuracy and misuse in education. Yousef M [ 8 ] BMC Medical Education 2025 Palestine 590 AI can boost learning and research in resource-limited medical setting. Duan S [ 9 ] BMC Medical Education 2025 China 553 Medical students exhibit optimistic yet cautious attitudes toward the application of AI in medical education. Alkhayat DS [ 10 ] Journal of Medical Education and Curricular Development 2025 Saudi Arabia 375 Opinions regarding the integration of AI into medical education were evenly divided among positive, negative, and neutral responses. Rjoop A [ 11 ] JMIR Medical Education 2025 Jordan 394 There is a need to reach a consensus on the integration of AI into medical education. Ajalo E [ 12 ] PLoS One 2025 Uganda 564 This study found that AI tools like ChatGPT are widely used by medical students in Uganda for both academic and non-academic purposes, highlighting the need for AI literacy and educational reform. Jackson P [ 13 ] BMC Medical Education 2024 India 325 While AI is viewed as a supportive technology in healthcare, there are ethical concerns, and there is a strong demand for structured AI education in the medical curriculum. Zhang JS [ 14 ] Journal of Medical Education and Curricular Development 2024 United State 131 The impact of ChatGPT on medical education will only continue to grow as its capabilities improve. Our Study Not Applicable 2025 Japan Students: 402 Faculty: 350 Refer to the main text. Abbreviation: AI, artificial intelligence The findings revealed that a high proportion of both students (82.1%) and faculty members (73.4%) had prior experience using AI, particularly generative AI tools. These results suggest that AI technologies have already become familiar tools in academic settings and that their integration into medical education is progressing rapidly. On the other hand, the faculty group showed a slightly lower usage rate than students, possibly reflecting generational differences in digital literacy or concerns over accuracy, ethics, and educational validity. Moreover, younger faculty members with experience using AI tended to approve of the introduction of AI into medical education. It is anticipated that as the number of young faculty members with AI experience increases, the implementation of AI in medical education will be further promoted. As mentioned above, there were many positive opinions regarding the use of AI in medical education. However, there are also several risks associated with integrating AI into medical education. The first issue is ethical considerations and the risk of leakage of personal information [ 3 ]. Medical education, in particular, frequently involves handling real patient information, making it essential to carefully consider the risk of personal data leakage through the careless use of AI. In our survey of faculty members, concerns about personal information leakage and ethical risks were the most frequently cited, with 257 respondents (73.4%) expressing such concerns. In their scoping review, Gordon et al. also emphasized the need to establish ethical guidelines in this area [ 4 ]. Moving forward, it is crucial to develop clear ethical standards for the use of AI in medical education. On the other hand, concerns have been raised about skill deterioration due to overreliance on AI and the widening digital divide among educational institutions [ 3 ]. It is essential to explore effective ways to utilize AI to ensure the delivery of high-quality medical education. This study has several limitations. First, it was conducted at a single institution, which may limit the generalizability of the findings. In addition, statistical analyses were not conducted for various items. Second, the survey relied on self-reported data, which may be subject to bias or inaccuracies. Also, the response rate among medical students was low, at 40%. Lastly, the rapidly evolving nature of AI technology means that perceptions and usage patterns may change over a short period. Multicenter or longitudinal studies are warranted to better understand the trends and impacts of AI in medical education across diverse settings. In conclusion, the use of AI in medical education is advancing, and both students and faculty members generally support its implementation under certain conditions. However, unresolved issues, particularly in the realm of ethics, must be addressed to ensure its responsible and effective implementation. Abbreviations AI artificial intelligence Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Oita University Faculty of Medicine (Approval No. 3214) and conducted in accordance with the Declaration of Helsinki. Written informed consent was waived by the committee in accordance with Japanese national regulations, as participation was based on an opt-out method. Information about the study was disclosed on the institution’s website and bulletin boards, and only data from individuals who did not opt out were included in the analysis. Consent for publication Not applicable Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to privacy concerns or ethical restrictions, but are available from the corresponding author on reasonable request. Competing interests Masafumi Inomata has financial conflicts of interest (Olympus Co. Ltd., SB KAWASUMI Co. Ltd. and Aderance Co. Ltd.). The other authors declare no conflicts of interest in relation to this article. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Usage of generative artificial intelligence Some parts of the manuscript were edited using ChatGPT-4o (OpenAI, 2024) to improve English grammar and style. The final content was reviewed and revised by the authors to ensure accuracy and appropriateness. Authors’ contributions Study concept: SN and MI. Study design: SN and MI. Data collection: KY, EM, HA, NU, TK, MT and TH. Data analysis: IS, TH, YE and KI. Supervision: YM and TT. Acknowledgments We sincerely thank Rise Japan, LLC for expertly editing the English language of this manuscript. Clinical trial number not applicable References Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers. JMIR Med Educ. 2023. 10.2196/46885 . Melnyk O, Ismail A, Ghorashi NS, Heekin M, Javan R. Generative artificial intelligence terminology: a primer for clinicians and medical researchers. Cureus. 2023. 10.7759/cureus.49890 . Ali M. The role of AI in reshaping medical education: opportunities and challenges. Clin Teach. 2025. 10.1111/tct.70040 . Gordon M, Daniel M, Ajiboye A, Uraiby H, Xu NY, Bartlett R, et al. A scoping review of artificial intelligence in medical education: BEME Guide 84. Med Teach. 2024. 10.1080/0142159X.2024.2314198 . Preiksaitis C, Rose C. Opportunities, challenges, and future directions of generative artificial intelligence in medical education: scoping review. JMIR Med Educ. 2023. 10.2196/48785 . Sami A, Tanveer F, Sajwani K, Kiran N, Javed MA, Ozsahin DU, et al. Medical students' attitudes toward AI in education: perception, effectiveness, and its credibility. BMC Med Educ. 2025. 10.1186/s12909-025-06704-y . Abdelhafiz AS, Farghly MI, Sultan EA, Abouelmagd ME, Ashmawy Y, Elsebaie EH. Medical students and ChatGPT: analyzing attitudes, practices, and academic perceptions. BMC Med Educ. 2025. 10.1186/s12909-025-06731-9 . Yousef M, Deeb S, Alhashlamon K. AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows. BMC Med Educ. 2025. 10.1186/s12909-025-07272-x . Duan S, Liu C, Rong T, Zhao Y, Liu B. Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions. BMC Med Educ. 2025. 10.1186/s12909-025-07177-9 . Alkhayat DS, Alsubaiyi HN, Alharbi YA, et al. Perception and Impact of AI on Education Journey of Medical Students and Interns in Western Region, KSA: A Cross-Sectional Study. J Med Educ Curric Dev. 2025;12:23821205251340129. 10.1177/23821205251340129 . Rjoop A, Al-Qudah M, Alkhasawneh R, et al. Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study. JMIR Med Educ. 2025;11:e62669. 10.2196/62669 . Ajalo E, Mukunya D, Nantale R, et al. Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study. PLoS ONE. 2025;20(1):e0313776. 10.1371/journal.pone.0313776 . Jackson P, Sukumaran GP, Babu G, et al. Artificial intelligence in medical education - perception among medical students. BMC Med Educ. 2024;24(1):804. 10.1186/s12909-024-05760-0 . Zhang JS, Yoon C, Williams DKA, Pinkas A. Exploring the usage of ChatGPT among medical students in the United States. J Med Educ Curric Dev. 2024. 10.1177/23821205241264695 . Busch F, Hoffmann L, Truhn D, et al. Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties. BMC Med Educ. 2024;24(1):1066. 10.1186/s12909-024-06035-4 . Additional Declarations Competing interest reported. Masafumi Inomata has financial conflicts of interest (Olympus Co. Ltd., SB KAWASUMI Co. Ltd. and Aderance Co. Ltd.). The other authors declare no conflicts of interest in relation to this article. Supplementary Files SupplementaryFile.docx.pptx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7504189","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":535133319,"identity":"4bdf3f41-1a7c-4525-89bc-7d46f95626c5","order_by":0,"name":"Shigeo Ninomiya","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shigeo","middleName":"","lastName":"Ninomiya","suffix":""},{"id":535133320,"identity":"75098076-83e4-49a8-9bf7-accf5155c00f","order_by":1,"name":"Kyoko Yamamoto","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kyoko","middleName":"","lastName":"Yamamoto","suffix":""},{"id":535133322,"identity":"f708b56c-59c1-4785-a31e-2319f826683f","order_by":2,"name":"Eiko Mieno","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eiko","middleName":"","lastName":"Mieno","suffix":""},{"id":535133324,"identity":"425ef5ea-19ef-408f-b1bc-cdac1f1f4bab","order_by":3,"name":"Hirofumi Anai","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hirofumi","middleName":"","lastName":"Anai","suffix":""},{"id":535133326,"identity":"44d10336-d4a9-428d-9be1-66a939e639a2","order_by":4,"name":"Naoto Uemura","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Naoto","middleName":"","lastName":"Uemura","suffix":""},{"id":535133328,"identity":"2246a766-0489-4574-bb9e-4bf55a72dd89","order_by":5,"name":"Takashi Kobayashi","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Takashi","middleName":"","lastName":"Kobayashi","suffix":""},{"id":535133329,"identity":"54d45452-e7db-474b-b3ff-fad569eae32a","order_by":6,"name":"Masato Tanigawa","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Masato","middleName":"","lastName":"Tanigawa","suffix":""},{"id":535133330,"identity":"d5584603-fb1a-4232-8fef-df3fb9e45ac6","order_by":7,"name":"Takashi Hirano","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Takashi","middleName":"","lastName":"Hirano","suffix":""},{"id":535133332,"identity":"560ef619-9c34-4be6-8a3a-b2d4b3ccf48e","order_by":8,"name":"Isao Saito","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Isao","middleName":"","lastName":"Saito","suffix":""},{"id":535133334,"identity":"f683d6f5-c90f-4d63-8abf-2b25fc418159","order_by":9,"name":"Toshikatsu Hanada","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Toshikatsu","middleName":"","lastName":"Hanada","suffix":""},{"id":535133336,"identity":"d885f5c9-3c16-4a96-aa66-be52dc55d0a2","order_by":10,"name":"Yuichi Endo","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Endo","suffix":""},{"id":535133338,"identity":"1960e1f4-129e-461a-b895-f338b240f1e3","order_by":11,"name":"Yusuke Matsunobu","email":"","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Matsunobu","suffix":""},{"id":535133339,"identity":"186c8605-1f1f-4da2-9b59-1dbfd292bbcd","order_by":12,"name":"Tatsushi Tokuyasu","email":"","orcid":"","institution":"Fukuoka Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Tatsushi","middleName":"","lastName":"Tokuyasu","suffix":""},{"id":535133340,"identity":"2329c2dd-c864-451e-8d65-21bc0656b64f","order_by":13,"name":"Kenji Ihara","email":"","orcid":"","institution":"Oita University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kenji","middleName":"","lastName":"Ihara","suffix":""},{"id":535133341,"identity":"200bcbd1-3078-4903-99ce-7cb406acef37","order_by":14,"name":"Masafumi Inomata","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACNigtx8CMEEwgQksCgzEDM0IPfi0wNYkNyNbgBXzSzUc3/Pxhl97Pzn/wA2Mbgzx/A8OzB3gdJnMs7WZPQnLuzGZmZgmgFsMZBxjSDfBqkcgxu8GTwJy74TAzg/TfNgbGDQwMaRKEtNz8k1CfbnCYmfkH0BZ7orTc5kk4nADUwgZyWCIRWtLSbsukHTcE+sXMguGcRPKMwwT8Ij8j+djNNzbV8vz8Bx/fYCizse1v70l7gE8LOgA6iZknjRQdYMB+jGQto2AUjIJRMKwBAMw+Pa8kkp/qAAAAAElFTkSuQmCC","orcid":"","institution":"Oita University Faculty of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Masafumi","middleName":"","lastName":"Inomata","suffix":""}],"badges":[],"createdAt":"2025-09-01 04:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7504189/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7504189/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94591937,"identity":"8712fd8b-b65e-4d7f-bb21-06e174e6d331","added_by":"auto","created_at":"2025-10-28 18:22:49","extension":"png","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1515838,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/8c3ea8cebd03396c428b4ff1.png"},{"id":94592796,"identity":"229a0ae0-1f1d-4674-b653-a3e60fbbfa65","added_by":"auto","created_at":"2025-10-28 18:23:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52389,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptAIEDITEDCLEANCOPY.docx","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/bf2b2a4ab45be81fea9eb5d2.docx"},{"id":94599043,"identity":"2202500e-dc3b-4e3b-af06-3a65db572fc4","added_by":"auto","created_at":"2025-10-28 19:02:18","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3321287,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/7ececa46f3905266abf094d2.png"},{"id":94592249,"identity":"1edfca58-3bcc-4223-bef6-6811fc170291","added_by":"auto","created_at":"2025-10-28 18:23:01","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3926209,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/c7433643fb72d13d9bdd3b27.png"},{"id":94592614,"identity":"0eec4893-c334-4622-b0d5-c00e86bc6aa2","added_by":"auto","created_at":"2025-10-28 18:23:29","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1587240,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/dcf392a8e445f1d64db31283.png"},{"id":94591988,"identity":"7cbf5180-ba9c-4f03-b597-893f6d5d6343","added_by":"auto","created_at":"2025-10-28 18:22:53","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3178149,"visible":true,"origin":"","legend":"","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/ddfeecb91c36ff5c88b734f2.png"},{"id":94591938,"identity":"dedb9df8-200d-4f4e-8265-251642496576","added_by":"auto","created_at":"2025-10-28 18:22:49","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2282504,"visible":true,"origin":"","legend":"","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/02e8853130b0ef6b974f8f79.png"},{"id":94592609,"identity":"30999016-7126-4307-84d2-8d3cb703cf1a","added_by":"auto","created_at":"2025-10-28 18:23:29","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4229204,"visible":true,"origin":"","legend":"","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/61d66b9e0bfc6d6eff80a077.png"},{"id":94592559,"identity":"14fd0181-de02-4767-8558-a609299a6a82","added_by":"auto","created_at":"2025-10-28 18:23:17","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2568545,"visible":true,"origin":"","legend":"","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/9b2ff78aa699206c842ed624.png"},{"id":94592554,"identity":"40648357-32c6-4ee4-81ae-e75c63f7829c","added_by":"auto","created_at":"2025-10-28 18:23:16","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5157047,"visible":true,"origin":"","legend":"","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/3164c4db302f64c9a4cb93a2.png"},{"id":94591946,"identity":"a45cbe8e-20b3-4b6e-af44-eced02fbcb7e","added_by":"auto","created_at":"2025-10-28 18:22:50","extension":"json","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13286,"visible":true,"origin":"","legend":"","description":"","filename":"35976e3b229d4a5cbb544dece41c36d6.json","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/82e891e604092ad4c4bfc797.json"},{"id":94592776,"identity":"b506fca7-c586-4a89-bf72-5bd4fd5e412e","added_by":"auto","created_at":"2025-10-28 18:23:39","extension":"pptx","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51162,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/b5ca9fcee4c575091f09dc96.pptx"},{"id":94591604,"identity":"98b9d388-6aa6-452d-aa7f-3c069821be1b","added_by":"auto","created_at":"2025-10-28 18:22:30","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74002,"visible":true,"origin":"","legend":"","description":"","filename":"35976e3b229d4a5cbb544dece41c36d61enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/82e216f347a3f43b84a8ab9b.xml"},{"id":94592620,"identity":"41925bb0-da59-4c37-9d39-0f3060ebb022","added_by":"auto","created_at":"2025-10-28 18:23:30","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1515838,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/31528ce2e8195b0e9ab66bfa.png"},{"id":94592936,"identity":"e7955615-ca9c-49c5-aed4-fe6f22029b25","added_by":"auto","created_at":"2025-10-28 18:23:53","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3321287,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/34cf06c202c26c08e02afda6.png"},{"id":94598903,"identity":"5cc16bd5-c70a-41e8-80d5-1371f18ccf38","added_by":"auto","created_at":"2025-10-28 18:58:07","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3926209,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/f0586a9913c61cc6e7a6cd06.png"},{"id":94592621,"identity":"42356744-faab-401c-9a0d-2b132bda608e","added_by":"auto","created_at":"2025-10-28 18:23:30","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1587240,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/f3451e96535e70a1db2ea90d.png"},{"id":94592574,"identity":"eb0cc2b5-b18e-4fa2-8694-9e3c769bce40","added_by":"auto","created_at":"2025-10-28 18:23:20","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3178149,"visible":true,"origin":"","legend":"","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/755756d5f95afd8b1bade924.png"},{"id":94592911,"identity":"95565684-6242-4477-b223-0a2e967c6544","added_by":"auto","created_at":"2025-10-28 18:23:49","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2282504,"visible":true,"origin":"","legend":"","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/eae33a0631975c26df70b78f.png"},{"id":94592320,"identity":"bf5c760a-5f9a-4130-a98d-ab103848d524","added_by":"auto","created_at":"2025-10-28 18:23:02","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4229204,"visible":true,"origin":"","legend":"","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/c8dbddce1ccc6b4793642dc6.png"},{"id":94592322,"identity":"5b5afbbf-ccbc-465a-9c8c-c9e045ad726e","added_by":"auto","created_at":"2025-10-28 18:23:02","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2568545,"visible":true,"origin":"","legend":"","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/31b47390d2a7b9b8d057194a.png"},{"id":94592603,"identity":"990b525a-d177-4662-90f0-bdc098e9faf5","added_by":"auto","created_at":"2025-10-28 18:23:28","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5157047,"visible":true,"origin":"","legend":"","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/c3d11ceb7ca864b5b05fd361.png"},{"id":94591939,"identity":"5a1baabe-f012-4f56-a627-7cb6c1e27a12","added_by":"auto","created_at":"2025-10-28 18:22:50","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1079536,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/be4ecd8c7bc5ec315bf9569a.png"},{"id":94591487,"identity":"9a9e4d81-e321-45c4-b7a9-2d3b2d157045","added_by":"auto","created_at":"2025-10-28 18:22:18","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2378880,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/7e34c8a85464edbd922f3126.png"},{"id":94591522,"identity":"7a4532f2-7b59-4b86-9cc1-0cb646c90a36","added_by":"auto","created_at":"2025-10-28 18:22:21","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2882459,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/92c8e3f21294f41102179638.png"},{"id":94592932,"identity":"23c063a7-879c-4595-a6fb-312e1d93326e","added_by":"auto","created_at":"2025-10-28 18:23:51","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1189759,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/9dab6e9da365b74ff19af777.png"},{"id":94592232,"identity":"6485b3aa-b6e2-42f4-9893-7629fdc1071a","added_by":"auto","created_at":"2025-10-28 18:23:00","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2344540,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/d96b1c2407efebcd561206e6.png"},{"id":94591520,"identity":"c9f9d2bf-d9ba-4de0-a79c-f1d911ae3f2d","added_by":"auto","created_at":"2025-10-28 18:22:20","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1608505,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/01945ac2263c8701e2edc16c.png"},{"id":94592566,"identity":"65291219-f43c-43a3-9d28-72586c55ea4f","added_by":"auto","created_at":"2025-10-28 18:23:19","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3225786,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/c742f1377c31e3fe522e390f.png"},{"id":94592567,"identity":"05c271ea-4d46-4431-a591-dc761c9a947c","added_by":"auto","created_at":"2025-10-28 18:23:20","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1748814,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/469c1a3e0b3322cbe07eb22e.png"},{"id":94592483,"identity":"f7f391d3-fa00-4486-aaef-41a19b586221","added_by":"auto","created_at":"2025-10-28 18:23:12","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3867617,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/5c47846a530f9fd274251988.png"},{"id":94592356,"identity":"828a8992-3b49-449d-8294-1256f15c4fb4","added_by":"auto","created_at":"2025-10-28 18:23:09","extension":"xml","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71029,"visible":true,"origin":"","legend":"","description":"","filename":"35976e3b229d4a5cbb544dece41c36d61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/72e16e0095eeb1fd02eb5078.xml"},{"id":94591911,"identity":"fb3f2573-b72e-496e-aca8-13beed6a6206","added_by":"auto","created_at":"2025-10-28 18:22:46","extension":"html","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85783,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/7de7c2bf34a76e3d94203a1a.html"},{"id":94592629,"identity":"1277a485-55de-46f2-83f7-0a5334f663d2","added_by":"auto","created_at":"2025-10-28 18:23:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1515838,"visible":true,"origin":"","legend":"\u003cp\u003eArtificial intelligence usage experience among medical students\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/0ae142c881a2f004d445ae9d.png"},{"id":94592547,"identity":"7809e4f0-9bf1-4819-896b-fe174d44e17c","added_by":"auto","created_at":"2025-10-28 18:23:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3321287,"visible":true,"origin":"","legend":"\u003cp\u003ePurposes of artificial intelligence (AI) use and types of AI used by medical students\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/f2a1f7c0bc62bd07c976a345.png"},{"id":94592590,"identity":"ff225fdc-e478-453b-91c2-df880dd64158","added_by":"auto","created_at":"2025-10-28 18:23:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3926209,"visible":true,"origin":"","legend":"\u003cp\u003eMedical students’ attitudes toward the use of artificial intelligence in university courses and assignments\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/88eda510f4673977a1017eb5.png"},{"id":94591603,"identity":"ac490892-f11b-47f7-a658-6d2ef7ae81f4","added_by":"auto","created_at":"2025-10-28 18:22:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1587240,"visible":true,"origin":"","legend":"\u003cp\u003eArtificial intelligence usage experience among faculty members\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/ccdec9f3ff26208a247d41a9.png"},{"id":94592586,"identity":"6f1d181f-db23-474f-8eeb-31888d5916d1","added_by":"auto","created_at":"2025-10-28 18:23:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3178149,"visible":true,"origin":"","legend":"\u003cp\u003ePurposes of artificial intelligence use and types used by faculty members\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/04bb34073d481b2d595eced5.png"},{"id":94592550,"identity":"73e069a9-630b-4406-a546-b848aeafaba6","added_by":"auto","created_at":"2025-10-28 18:23:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2282504,"visible":true,"origin":"","legend":"\u003cp\u003eFaculty members’ attitudes toward the use of artificial intelligence in university courses and assignments\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/b095c5028a320789cf64359e.png"},{"id":94592874,"identity":"f8fdcd8d-6116-44da-b693-69940784a20d","added_by":"auto","created_at":"2025-10-28 18:23:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4229204,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of faculty members’ attitudes toward the use of artificial intelligence (AI) in university courses and assignments, according to prior AI usage experience\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/7227823a7bdb6651793b9fd7.png"},{"id":94592563,"identity":"fc8adb09-6e86-4355-9cac-3791d4176b26","added_by":"auto","created_at":"2025-10-28 18:23:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2568545,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of faculty members’ attitudes toward the use of artificial intelligence in university courses and assignments, by age group\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/5d0f6f5cfebae72fbeec923e.png"},{"id":94592403,"identity":"1540dfbb-1b45-49da-99b3-78d5815870f9","added_by":"auto","created_at":"2025-10-28 18:23:12","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":5157047,"visible":true,"origin":"","legend":"\u003cp\u003ePotential applications of artificial intelligence in medical education and associated concerns raised by faculty members.\u003c/p\u003e\n\u003cp\u003eAI: artificial intelligence\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/8c9c8fabfc1d3a810e2aedd4.png"},{"id":94555016,"identity":"f512b6be-e0e9-4834-8215-e4912c7eae05","added_by":"auto","created_at":"2025-10-28 17:57:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":851932,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/834d075a-fb03-40c6-9a5f-86fea063532e.pdf"},{"id":94592482,"identity":"bc19abd1-41b4-46fa-b533-5a8fdd584cd5","added_by":"auto","created_at":"2025-10-28 18:23:12","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":51162,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7504189/v1/941d208bb63fba5fcfcfb668.pptx"}],"financialInterests":"Competing interest reported. Masafumi Inomata has financial conflicts of interest (Olympus Co. Ltd., SB KAWASUMI Co. Ltd. and Aderance Co. Ltd.). The other authors declare no conflicts of interest in relation to this article.","formattedTitle":"Current status of artificial intelligence utilization in medical education: A cross-sectional survey of medical students and faculty","fulltext":[{"header":"Background","content":"\u003cp\u003eGenerative artificial intelligence (AI) is defined as a class of AI models that generate synthetic outputs based on learning acquired from the datasets used to train the model [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among these, ChatGPT, one of the most well-known models, has gained explosive popularity, reaching 100\u0026nbsp;million users within just two months of its release in 2022 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In recent years, generative AI has brought transformative changes to a wide range of fields, including scientific research, creative arts, customer service, personalized learning, and healthcare. However, research on the actual use of generative AI in medical education in Japan has been limited.\u003c/p\u003e\u003cp\u003eRecently, medical students are increasingly believed to use AI for various academic tasks, such as attending lectures and writing reports. Conversely, faculty members are thought to use generative AI for preparing teaching materials and drafting documents. Despite its benefits, the use of AI in medical education presents several challenges. First, AI systems are not always accurate and may provide outdated or incorrect information, which can mislead students and hinder their learning [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, excessive reliance on AI tools may impair the development of critical thinking and problem-solving skills by encouraging dependency on automated answers [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Ethical concerns also arise, particularly regarding privacy and data security, as AI systems often require access to sensitive personal information [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, AI algorithms can reflect biases in their training data, potentially reinforcing unfairness or misinformation in educational content. Finally, overuse of AI may reduce meaningful human interaction between students and instructors, which is vital for nurturing communication skills and professional judgment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven this social context, the present study aimed to investigate the current use of AI among medical students and faculty members, as well as to identify potential concerns or challenges, in order to help determine the future direction of medical education.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eBetween April and May 2025, a cross-sectional survey was conducted among medical students and faculty members at the Oita University Faculty of Medicine. The questionnaire comprised 9 items each for students and faculty. It was created using Google Forms and administered online. This survey was distributed via email, participation was voluntary, and responses were collected anonymously. No incentives were provided for completing the questionnaire. The questionnaire was developed based on a literature review and under the supervision of experts in medical education and AI (TT and YM), and is provided as a \u003cb\u003eSupplementary file\u003c/b\u003e. To ensure content validity, all items were reviewed for clarity and relevance. Although a formal pilot test was not conducted, the questionnaire was refined through internal discussion among the authors and reviewed by domain experts to ensure clarity and relevance.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudent Survey: Experience and awareness of AI use among medical students\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThe survey targeted 1,014 students enrolled in three departments at our university: the School of Medicine, the School of Nursing, and the Department of Advanced Medical Sciences.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eObjectives\u003c/h3\u003e\n\u003cp\u003eThe student questionnaire included items on prior experience using AI, specific applications used, purposes for which AI was employed, perceptions of AI use in university classes and assignments, experience attending classes incorporating AI, and opinions on the appropriateness of such AI-integrated classes.\u003c/p\u003e\n\u003ch3\u003eFaculty Survey: AI use, attitudes, and concerns regarding integration into medical education\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThe survey targeted 470 faculty members from the School of Medicine, the School of Nursing, and the Department of Advanced Medical Sciences.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eThis survey aimed to assess whether faculty members utilize AI in the preparation of lectures and educational materials and to explore their opinions on the appropriateness of student use of AI for academic activities such as coursework and report writing. In addition, we also investigated concerns regarding the future implementation of AI in medical education.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe examined whether there was a significant difference in AI usage experience between medical students and faculty members. In the faculty survey on the implementation of AI into medical education, statistical analyses were also conducted to evaluate differences by AI usage experience and age. Statistical analyses were performed using SPSS (ver. 29). The chi-square test was applied, with the significance level set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Multiple comparisons were performed using the chi-square test with Bonferroni correction.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStudent Survey: Experience and awareness of AI use among medical students\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eResponse rate\u003c/h2\u003e\u003cp\u003eThe overall response rate among students in the Faculty of Medicine was 40% (402/1,014), with response rates of 29% (192/652) in the School of Medicine, 65% (167/257) in the School of Nursing, and 37% (41/108) in the Department of Advanced Medical Sciences. It is worth noting that the Department of Advanced Medical Sciences was established only three years ago, with an annual enrollment of 35 students, resulting in a smaller total student population.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eRespondent demographics\u003c/h2\u003e\u003cp\u003eThe breakdown of respondents by academic year was as follows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFirst-year students: 166 (41.3%)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSecond-year students: 49 (12.2%)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThird-year students: 82 (20.4%)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eFourth-year students: 63 (15.7%)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eFifth-year students: 23 (5.7%)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSixth-year students: 19 (4.7%)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003eOnly the School of Medicine includes fifth- and sixth-year levels. By gender, 236 respondents were female (58.7%), 106 were male (26.4%), and 60 did not disclose their gender (14.9%).\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eAI usage experience\u003c/h2\u003e\u003cp\u003eThe AI usage experience among medical students is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 330 students (82.1%) reported having prior experience using AI. The most frequently reported purpose of AI use among medical students was learning support, and the most commonly used type of AI, as indicated in the survey, was text-generating AI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAttitudes toward AI\u003c/h2\u003e\u003cp\u003eThe attitude of medical students toward AI use is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In response to the question, \"How do you feel about using AI in university courses and assignments?\", 103 students (25.6%) answered that AI should be actively used, and 270 students (67.2%) responded that it should be used under certain conditions. When asked, \"Have you attended any classes that utilized AI?\", 133 students (33.1%) answered \"Yes\". Regarding increased implementation of AI-integrated classes, 135 students (33.6%) said it was a very good trend, while 202 students (50.2%) considered it somewhat good.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eFaculty Survey: AI use, attitudes, and concerns regarding integration into medical education\u003c/h2\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003eResponse rate\u003c/h2\u003e\u003cp\u003eThe response rate among faculty members was 74% (350/470).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eRespondent demographics\u003c/h2\u003e\u003cp\u003eThe largest age group was individuals in their 30s (108 respondents, 30.9%), followed by those in their 40s (94 respondents, 26.9%) and 50s (70 respondents, 20.0%). By gender, 176 respondents (50.2%) were male, 83 (23.7%) were female, and 91 (26.1%) did not respond. The most common job title was Assistant Professor (92 respondents, 26.3%), followed by Professor (88 respondents, 25.1%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eAI usage experience\u003c/h2\u003e\u003cp\u003eThe usage of AI among faculty members is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. A total of 257 faculty members (73.4%) reported previous use of AI, which was significantly lower than the rate of 82.1% reported by students (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The primary purpose of use was routine administrative tasks, followed by research and educational activities. Consistent with the findings among medical students, text-generating AI tools were the most frequently used, with a usage rate of 94.2% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eAttitudes toward AI\u003c/h2\u003e\u003cp\u003eIn response to the question, \"How do you feel about using AI in university courses and assignments?\" 67 faculty members (19.1%) indicated their approval of its use, and 236 faculty members (67.4%) indicated their conditional acceptance of its use. However, 41 respondents (11.7%) believed that its use should be prohibited on principle (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). When comparing responses to the question \u0026ldquo;How do you feel about using AI in university courses and assignments?\u0026rdquo; based on faculty members\u0026rsquo; AI usage experience, those with AI usage experience were significantly more likely to approve the use of AI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). In addition, when analyzed by age group, faculty members in their 20s were significantly more likely to approve the implementation of AI into medical education (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Regarding how AI could be used in medical education, the most common response was to improve the efficiency of lecture material and slide preparation (256 respondents, 73.1%), followed by its use in data analysis and evidence-based medicine education (191 respondents, 54.6%). Regarding concerns about AI in medical education, 257 respondents (73.4%) cited issues such as the risk of personal data leakage and ethical concerns (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study investigated the current status of AI utilization and awareness among medical students and faculty members at a single Japanese university. Sami et al. conducted a survey of 702 medical students in Pakistan and found that the majority perceived AI as an effective and credible learning tool, highlighting its potential to optimize study time, improve conceptual understanding, and provide accurate medical information [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Also, Abdelhafiz et al. reported that Egyptian medical students showed strong interest and trust in using ChatGPT and similar chatbots for academic purposes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Reports from individual countries worldwide reported to date are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Many surveys reported favorable attitudes toward the use of AI in medical education. To the best of our knowledge, our study is the first report from Japan. Moreover, there have been no reports that clarify the use of AI or attitudes toward it among not only medical students but also faculty members at medical schools. Consistent with prior findings, Japanese medical students have already been utilizing AI in their studies and expressed a desire to continue using it in the future. On the other hand, a study involving 4,313 medical students from 48 countries also reported similarly positive attitudes toward the use of AI in healthcare and medicine, and found no significant regional differences among the countries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eQuestionnaire survey on the utilization of AI in medical education.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAuthors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSample size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusions\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSami A [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMC Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePakistan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAI enhances medical education by providing personalized learning and reliable results.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbdelhafiz AS [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMC Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedical students are interested in using ChatGPT and similar tools for learning but worry about information accuracy and misuse in education.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYousef M [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMC Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePalestine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAI can boost learning and research in resource-limited medical setting.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuan S [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMC Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e553\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedical students exhibit optimistic yet cautious attitudes toward the application of AI in medical education.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlkhayat DS [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Medical Education and Curricular Development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSaudi Arabia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOpinions regarding the integration of AI into medical education were evenly divided among positive, negative, and neutral responses.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRjoop A [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJMIR Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eJordan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThere is a need to reach a consensus on the integration of AI into medical education.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAjalo E [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePLoS One\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUganda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThis study found that AI tools like ChatGPT are widely used by medical students in Uganda for both academic and non-academic purposes, highlighting the need for AI literacy and educational reform.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJackson P [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMC Medical Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWhile AI is viewed as a supportive technology in healthcare, there are ethical concerns, and there is a strong demand for structured AI education in the medical curriculum.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhang JS [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Medical Education and Curricular Development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnited State\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThe impact of ChatGPT on medical education will only continue to grow as its capabilities improve.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOur Study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot Applicable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStudents: 402\u003c/p\u003e\u003cp\u003eFaculty: 350\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRefer to the main text.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviation: AI, artificial intelligence\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe findings revealed that a high proportion of both students (82.1%) and faculty members (73.4%) had prior experience using AI, particularly generative AI tools. These results suggest that AI technologies have already become familiar tools in academic settings and that their integration into medical education is progressing rapidly. On the other hand, the faculty group showed a slightly lower usage rate than students, possibly reflecting generational differences in digital literacy or concerns over accuracy, ethics, and educational validity. Moreover, younger faculty members with experience using AI tended to approve of the introduction of AI into medical education. It is anticipated that as the number of young faculty members with AI experience increases, the implementation of AI in medical education will be further promoted.\u003c/p\u003e\u003cp\u003eAs mentioned above, there were many positive opinions regarding the use of AI in medical education. However, there are also several risks associated with integrating AI into medical education. The first issue is ethical considerations and the risk of leakage of personal information [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Medical education, in particular, frequently involves handling real patient information, making it essential to carefully consider the risk of personal data leakage through the careless use of AI. In our survey of faculty members, concerns about personal information leakage and ethical risks were the most frequently cited, with 257 respondents (73.4%) expressing such concerns. In their scoping review, Gordon et al. also emphasized the need to establish ethical guidelines in this area [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moving forward, it is crucial to develop clear ethical standards for the use of AI in medical education. On the other hand, concerns have been raised about skill deterioration due to overreliance on AI and the widening digital divide among educational institutions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is essential to explore effective ways to utilize AI to ensure the delivery of high-quality medical education.\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, it was conducted at a single institution, which may limit the generalizability of the findings. In addition, statistical analyses were not conducted for various items. Second, the survey relied on self-reported data, which may be subject to bias or inaccuracies. Also, the response rate among medical students was low, at 40%. Lastly, the rapidly evolving nature of AI technology means that perceptions and usage patterns may change over a short period. Multicenter or longitudinal studies are warranted to better understand the trends and impacts of AI in medical education across diverse settings.\u003c/p\u003e\u003cp\u003eIn conclusion, the use of AI in medical education is advancing, and both students and faculty members generally support its implementation under certain conditions. However, unresolved issues, particularly in the realm of ethics, must be addressed to ensure its responsible and effective implementation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eartificial intelligence\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Oita University Faculty of Medicine (Approval No. 3214) and conducted in accordance with the Declaration of Helsinki. Written informed consent was waived by the committee in accordance with Japanese national regulations, as participation was based on an opt-out method. Information about the study was disclosed on the institution\u0026rsquo;s website and bulletin boards, and only data from individuals who did not opt out were included in the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to privacy concerns or ethical restrictions, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMasafumi Inomata has financial conflicts of interest (Olympus Co. Ltd., SB KAWASUMI Co. Ltd. and Aderance Co. Ltd.). The\u0026nbsp;other authors declare no conflicts of interest in relation to this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUsage of generative artificial intelligence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome parts of the manuscript were edited using ChatGPT-4o (OpenAI, 2024) to improve English grammar and style. The final content was reviewed and revised by the authors to ensure accuracy and appropriateness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept: SN and MI. Study design: SN and MI. Data collection: KY, EM, HA, NU, TK, MT and TH. Data analysis: IS, TH, YE and KI. Supervision: YM and TT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank Rise Japan, LLC for expertly editing the English language of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers. JMIR Med Educ. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/46885\u003c/span\u003e\u003cspan address=\"10.2196/46885\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMelnyk O, Ismail A, Ghorashi NS, Heekin M, Javan R. Generative artificial intelligence terminology: a primer for clinicians and medical researchers. Cureus. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus.49890\u003c/span\u003e\u003cspan address=\"10.7759/cureus.49890\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli M. The role of AI in reshaping medical education: opportunities and challenges. Clin Teach. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/tct.70040\u003c/span\u003e\u003cspan address=\"10.1111/tct.70040\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGordon M, Daniel M, Ajiboye A, Uraiby H, Xu NY, Bartlett R, et al. A scoping review of artificial intelligence in medical education: BEME Guide 84. Med Teach. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/0142159X.2024.2314198\u003c/span\u003e\u003cspan address=\"10.1080/0142159X.2024.2314198\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePreiksaitis C, Rose C. Opportunities, challenges, and future directions of generative artificial intelligence in medical education: scoping review. JMIR Med Educ. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/48785\u003c/span\u003e\u003cspan address=\"10.2196/48785\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSami A, Tanveer F, Sajwani K, Kiran N, Javed MA, Ozsahin DU, et al. Medical students' attitudes toward AI in education: perception, effectiveness, and its credibility. BMC Med Educ. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-025-06704-y\u003c/span\u003e\u003cspan address=\"10.1186/s12909-025-06704-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdelhafiz AS, Farghly MI, Sultan EA, Abouelmagd ME, Ashmawy Y, Elsebaie EH. Medical students and ChatGPT: analyzing attitudes, practices, and academic perceptions. BMC Med Educ. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-025-06731-9\u003c/span\u003e\u003cspan address=\"10.1186/s12909-025-06731-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYousef M, Deeb S, Alhashlamon K. AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows. BMC Med Educ. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-025-07272-x\u003c/span\u003e\u003cspan address=\"10.1186/s12909-025-07272-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDuan S, Liu C, Rong T, Zhao Y, Liu B. Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions. BMC Med Educ. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-025-07177-9\u003c/span\u003e\u003cspan address=\"10.1186/s12909-025-07177-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlkhayat DS, Alsubaiyi HN, Alharbi YA, et al. Perception and Impact of AI on Education Journey of Medical Students and Interns in Western Region, KSA: A Cross-Sectional Study. J Med Educ Curric Dev. 2025;12:23821205251340129. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/23821205251340129\u003c/span\u003e\u003cspan address=\"10.1177/23821205251340129\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRjoop A, Al-Qudah M, Alkhasawneh R, et al. Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study. JMIR Med Educ. 2025;11:e62669. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/62669\u003c/span\u003e\u003cspan address=\"10.2196/62669\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAjalo E, Mukunya D, Nantale R, et al. Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study. PLoS ONE. 2025;20(1):e0313776. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0313776\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0313776\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJackson P, Sukumaran GP, Babu G, et al. Artificial intelligence in medical education - perception among medical students. BMC Med Educ. 2024;24(1):804. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-024-05760-0\u003c/span\u003e\u003cspan address=\"10.1186/s12909-024-05760-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang JS, Yoon C, Williams DKA, Pinkas A. Exploring the usage of ChatGPT among medical students in the United States. J Med Educ Curric Dev. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/23821205241264695\u003c/span\u003e\u003cspan address=\"10.1177/23821205241264695\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBusch F, Hoffmann L, Truhn D, et al. Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties. BMC Med Educ. 2024;24(1):1066. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12909-024-06035-4\u003c/span\u003e\u003cspan address=\"10.1186/s12909-024-06035-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial intelligence, Generative Artificial intelligence, Medical education","lastPublishedDoi":"10.21203/rs.3.rs-7504189/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7504189/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eGenerative artificial intelligence (AI), particularly large language models such as ChatGPT, is rapidly transforming various sectors, including medical education. Despite increasing interest, few studies have investigated how AI is actually used in medical education settings, especially in Japan. This study aimed to assess the current use of generative AI among medical students and faculty members, and to identify their perceptions, perceived benefits, and concerns in relation to its integration into medical education.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional survey was conducted from April to May 2025 at the Oita University Faculty of Medicine. A total of 1,014 students and 470 faculty members from the School of Medicine, School of Nursing, and Department of Advanced Medical Sciences were invited to complete an anonymous online questionnaire. The survey covered AI usage experience, purposes of use, and attitudes toward AI in academic contexts.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe response rates were 40% for students (402/1,014) and 74% for faculty members (350/470). Most students (82.1%) and faculty (73.4%) had prior experience using AI tools, primarily for report writing, lecture preparation, and information retrieval, with students showing a higher rate of AI usage experience than faculty (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While 92.8% of students and 86.5% of faculty supported AI use under certain conditions, 73.4% of faculty members reported major concerns, including ethical risks and the risk of personal information leakage. In the faculty survey, younger faculty members and those with AI usage experience were also significantly more likely to approve the introduction of AI into medical education (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eGenerative AI is widely accepted and utilized in medical education. However, ethical guidelines, digital literacy education, and thoughtful integration strategies are essential to ensure its responsible use.\u003c/p\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e","manuscriptTitle":"Current status of artificial intelligence utilization in medical education: A cross-sectional survey of medical students and faculty","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-28 16:49:02","doi":"10.21203/rs.3.rs-7504189/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb076765-2a43-4c44-b30f-71c364eb98cc","owner":[],"postedDate":"October 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-07T09:09:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-28 16:49:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7504189","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7504189","identity":"rs-7504189","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}