Nobuyasu Komasawa, Masanao Yokohira
{"title":"Medical students' perceptions of professional mission in an AI-driven healthcare future: a text mining analysis of reflective essays in Japan.","authors":"Nobuyasu Komasawa, Masanao Yokohira","doi":"10.2185/jrm.2025-037","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>As artificial intelligence (AI) technologies advance rapidly, their integration into healthcare is transforming the clinical practice landscape. This study aimed to evaluate how second-year medical students perceive their professional mission in an AI-integrated medical future, through a structured essay task, using text-mining analysis to identify emerging themes and attitudes.</p><p><strong>Methods: </strong>A total of 105 second-year medical students at Kagawa university in Japan completed an essay titled \"What is your mission in the AI-driven medical world?\". Responses were analyzed using KH Coder for frequency analysis, multidimensional scaling, and co-occurrence network mapping. Participants provided verbal informed consent and student anonymity was ensured.</p><p><strong>Results: </strong>The most frequently used terms were medical, consider, think, doctor, AI, human, and patient. Three thematic clusters emerged: (1) career design, (2) AI and medicine, and (3) AI and human. Co-occurrence analysis revealed strong associations between \"medical\" and both \"consider\" and \"patient\", while \"patient\" was linked to both \"AI\" and \"human\", indicating thoughtful reflection on technology's impact on patient care.</p><p><strong>Conclusion: </strong>Second-year medical students in Japan demonstrated critical engagement with the concept of mission formation in the context of AI in healthcare. Their essays reflected a balance between optimism for technological advancement and concern for preserving human-centered care. These findings highlight the importance of implementing systematic career education and future-oriented thinking that is aligned with the characteristics of Generation Z learners.</p>","PeriodicalId":73939,"journal":{"name":"Journal of rural medicine : JRM","volume":"20 4","pages":"294-301"},"PeriodicalIF":0.0000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12497985/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of rural medicine : JRM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2185/jrm.2025-037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着人工智能(AI)技术的快速发展,它们与医疗保健的融合正在改变临床实践的格局。本研究旨在评估二年级医学生如何看待他们在人工智能集成医疗未来的专业使命,通过结构化的论文任务,使用文本挖掘分析来识别新出现的主题和态度。方法:日本香川大学105名二年级医学生完成了一篇题为“在人工智能驱动的医学世界里,你的使命是什么?”使用KH Coder进行频率分析、多维标度和共现网络映射来分析响应。参与者提供口头知情同意,并确保学生匿名。结果:使用频率最高的词汇是medical、consider、think、doctor、AI、human和patient。出现了三个主题集群:(1)职业设计,(2)人工智能与医学,(3)人工智能与人类。共现分析显示,“医疗”与“考虑”和“患者”之间存在很强的关联,而“患者”与“人工智能”和“人类”之间存在关联,表明对技术对患者护理影响的深思熟虑。结论:日本的二年级医学生在医疗保健领域的人工智能背景下对任务形成概念表现出关键的参与。他们的文章反映了对技术进步的乐观态度和对保持以人为本的护理的关注之间的平衡。这些发现强调了实施系统的职业教育和面向未来的思维的重要性,这与Z世代学习者的特点是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical students' perceptions of professional mission in an AI-driven healthcare future: a text mining analysis of reflective essays in Japan.

Objective: As artificial intelligence (AI) technologies advance rapidly, their integration into healthcare is transforming the clinical practice landscape. This study aimed to evaluate how second-year medical students perceive their professional mission in an AI-integrated medical future, through a structured essay task, using text-mining analysis to identify emerging themes and attitudes.

Methods: A total of 105 second-year medical students at Kagawa university in Japan completed an essay titled "What is your mission in the AI-driven medical world?". Responses were analyzed using KH Coder for frequency analysis, multidimensional scaling, and co-occurrence network mapping. Participants provided verbal informed consent and student anonymity was ensured.

Results: The most frequently used terms were medical, consider, think, doctor, AI, human, and patient. Three thematic clusters emerged: (1) career design, (2) AI and medicine, and (3) AI and human. Co-occurrence analysis revealed strong associations between "medical" and both "consider" and "patient", while "patient" was linked to both "AI" and "human", indicating thoughtful reflection on technology's impact on patient care.

Conclusion: Second-year medical students in Japan demonstrated critical engagement with the concept of mission formation in the context of AI in healthcare. Their essays reflected a balance between optimism for technological advancement and concern for preserving human-centered care. These findings highlight the importance of implementing systematic career education and future-oriented thinking that is aligned with the characteristics of Generation Z learners.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信