Korean journal of medical education最新文献_第4页

Correction of co-first authorship marks: Stress and coping skills in medical students. 共同第一作者标记的更正：医学生的压力与应对技能。

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-01-29 DOI: 10.3946/kjme.2026.164

Yu Ra Kim, Hye Jin Park, Seong Yong Kim

引用次数: 0

Crossing the theory threshold: the pedagogical potential of generative artificial intelligence in educational research. 跨越理论门槛：生成性人工智能在教育研究中的教学潜力。

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.3946/kjme.2025.098

Amanda Burbage, Jennifer L Styron

{"title":"Crossing the theory threshold: the pedagogical potential of generative artificial intelligence in educational research.","authors":"Amanda Burbage, Jennifer L Styron","doi":"10.3946/kjme.2025.098","DOIUrl":"10.3946/kjme.2025.098","url":null,"abstract":"Purpose: This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners' understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role.Methods: The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants.Results: Open-ended codes were grouped into five themes reflecting a developmental progression across phases of threshold crossing: encountering challenge, adapting through iteration, deepening engagement, customizing understanding, and cultivating metacognition. The first two themes represent learners' entry into the troublesome and liminal phases of threshold crossing, while the latter three reflect integrative and transformative shifts in their understanding and use of theory.Conclusion: Learner perceptions of using generative AI to acquire theoretical framework threshold concepts are discussed to better understand how AI can be used as a supplemental resource in asynchronous learning environments. Faculty observations of learner performance, suggested generative AI teaching strategies, and potential threats, including AI hallucinations and the clarification of misinformation, are discussed.","PeriodicalId":37737,"journal":{"name":"Korean journal of medical education","volume":"38 1","pages":"5-9"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing history-taking education through GPT-4-based virtual patients and automated assessment: a study of medical student perceptions. 通过基于gpt -4的虚拟患者和自动评估加强历史教育：医学生认知的研究

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-02-20 DOI: 10.3946/kjme.2025.108

Jaehyun Byun, Hongik Kim, Jihan Lim, Junyeong Choi, Sangzin Ahn

{"title":"Enhancing history-taking education through GPT-4-based virtual patients and automated assessment: a study of medical student perceptions.","authors":"Jaehyun Byun, Hongik Kim, Jihan Lim, Junyeong Choi, Sangzin Ahn","doi":"10.3946/kjme.2025.108","DOIUrl":"10.3946/kjme.2025.108","url":null,"abstract":"Purpose: To develop and evaluate a large language model (LLM)-based learning tool, featuring virtual patients (VPs) and virtual assessors (VAs), and to assess its impact on medical students' perceptions of history-taking education compared to conventional learning methods.Methods: A tool using the GPT-4 API was developed to provide seven clinical VP scenarios and a VA that delivered both immediate, reflective dialogue and comprehensive written feedback. First- and second-year medical students participated in a 6-day study. Pre- and post-participation surveys using a 5-point Likert scale assessed perceptions of the LLM tool versus conventional methods across usability, self-efficacy, and feedback quality domains.Results: Twenty-one students completed the study. The LLM-based tool demonstrated statistically significant improvements over conventional methods in all assessed domains. Students reported greater comfort during practice (mean 4.57 vs. 2.95, p=0.0002). Significant gains were seen in six of eight self-efficacy measures, including confidence in handling unfamiliar cases (4.00 vs. 2.90, p=0.0002). All nine feedback quality dimensions improved significantly, with feedback perceived as more specific (4.43 vs. 3.24, p=0.0005) and personalized (4.19 vs. 3.19, p=0.0001).Conclusion: An LLM-based learning tool featuring VPs and VAs can significantly enhance medical students' perceived learning experience in history-taking education. It offers a scalable, accessible, and cost-effective complementary training method. Future research should validate these subjective improvements with objective performance metrics.","PeriodicalId":37737,"journal":{"name":"Korean journal of medical education","volume":"38 1","pages":"64-73"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preparing doctors for 21st century healthcare: imperative for entrepreneurial competence in medical education. 为21世纪的医疗保健培养医生：医学教育创业能力的当务之急。

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-02-23 DOI: 10.3946/kjme.2025.147

Kavitha Ashok Kumar, S M Ferdous Azam, Ashok Kumar Jeppu

引用次数: 0

Navigating ethical considerations and challenges in medical education research. 导航伦理考虑和挑战在医学教育研究。

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-02-13 DOI: 10.3946/kjme.2025.105

Mila Nu Nu Htay, Roy Rillera Marzo, Adinegara Lutfi Abas

引用次数: 0

From setting to vetting: using artificial intelligence for Single Best Answer questions review. 从设置到审查：使用人工智能进行单最佳答案问题审查。

Korean journal of medical education Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.3946/kjme.2025.068

Olivia Ng, Siew Ping Han, Magdalene Hui Min Lee, Dong Haur Phua

{"title":"From setting to vetting: using artificial intelligence for Single Best Answer questions review.","authors":"Olivia Ng, Siew Ping Han, Magdalene Hui Min Lee, Dong Haur Phua","doi":"10.3946/kjme.2025.068","DOIUrl":"10.3946/kjme.2025.068","url":null,"abstract":"Purpose: Maintaining the quality of Single Best Answer (SBA) questions remains a challenge in medical education, especially as artificial intelligence (AI)-generated items become more common. While considerable attention has been paid to AI question generation, the vetting process is under-explored and difficult to scale.Methods: This study investigates the feasibility and reliability of using a large language model to support the vetting of SBA questions. An AI-based reviewer, QA-bot, was developed using custom GPT and embedded with 25 criteria aligned with Bloom's taxonomy (Levels 1-3). QA-bot and two experienced educators independently evaluated 32 AI-generated SBA questions using the shared evaluation rubric.Results: The rubric showed high internal consistency (Cronbach's alpha=0.878), and strong inter-rater reliability between human reviewers (intraclass correlation coefficient [ICC]=0.893). QA-bot demonstrated good alignment with human raters (ICC=0.861 and 0.840). While the AI performed well on objective, rule-based criteria, it was less consistent in detecting irrelevant complexity and accurately judging difficulty.Conclusion: These findings suggest that AI can function as an efficient first-pass reviewer, improving consistency and reducing workload, with human oversight remaining essential for educational and clinical relevance.","PeriodicalId":37737,"journal":{"name":"Korean journal of medical education","volume":"38 1","pages":"10-14"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147391002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Core shared competencies between physicians and nurses in primary care: a Delphi study in Korea. 初级保健中医生和护士的核心共同能力：一项在韩国进行的德尔菲研究。

Korean journal of medical education Pub Date : 2025-12-01 Epub Date: 2025-11-27 DOI: 10.3946/kjme.2025.359

Jin Young Lee, Yul Ha Min, Jun Yim, Kwi Hwa Park, So Jung Yune

{"title":"Core shared competencies between physicians and nurses in primary care: a Delphi study in Korea.","authors":"Jin Young Lee, Yul Ha Min, Jun Yim, Kwi Hwa Park, So Jung Yune","doi":"10.3946/kjme.2025.359","DOIUrl":"10.3946/kjme.2025.359","url":null,"abstract":"Purpose: This study aimed to identify core shared competencies required for effective physician-nurse collaboration in primary care.Methods: A three-round Delphi survey was conducted from November 2024 to February 2025 with 30 experts (12 physicians, 18 nurses), including family medicine professors, primary care physicians, nursing professors, and practicing nurses. Experts evaluated the importance and roles of interprofessional team approaches using online questionnaires. Quantitative analyses included mean, standard deviation, and content validity ratio (CVR).Results: The first round confirmed the necessity of interprofessional teamwork in cases such as chronic disease management, rehabilitation, elderly care, and mental health. Essential team members were physicians, nurses, and social workers, with additional professionals engaged as needed. Through iterative consensus, six shared competencies were derived: (1) patient-centered integrated care, (2) treatment plan development and implementation, (3) communication and collaboration, (4) professional development as a team member, (5) Evaluation and feedback on service outcomes, and (6) disease prevention and health promotion. All items met consensus criteria (CVR ≥0.34).Conclusion: These findings clarify physician-nurse shared competencies in primary care and provide a foundation for developing competency-based interprofessional curricula and training programs to enhance collaborative care quality and patient outcomes.","PeriodicalId":37737,"journal":{"name":"Korean journal of medical education","volume":"37 4","pages":"503-509"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12683266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145702213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Validation of performance evaluation indicator after graduation from medical school. 医学院毕业后绩效评价指标的验证。

Korean journal of medical education Pub Date : 2025-12-01 Epub Date: 2025-11-27 DOI: 10.3946/kjme.2025.354

Minkyung Oh

{"title":"Validation of performance evaluation indicator after graduation from medical school.","authors":"Minkyung Oh","doi":"10.3946/kjme.2025.354","DOIUrl":"10.3946/kjme.2025.354","url":null,"abstract":"Purpose: Evaluating the performance of medical school graduates after graduation is important. However, reliable and comprehensive tools to evaluate the performance of medical professionals after graduation are lacking. The purpose of this study was to evaluate the validity and reliability of performance indicators for post-graduation competencies of medical school graduates.Methods: Nineteen performance indicators were validated to evaluate competencies considering the talent image of a medical school, which are medical professionalism, clinical skills, communication, collaboration, and leadership. The reliability of the assessment tool was tested using Cronbach's alpha, construct validity was evaluated through factor analysis, and content validity was evaluated using a Delphi expert panel.Results: The overall reliability of the performance indicators was high, with a Cronbach's alpha of 0.9110. Factor analysis revealed five core factors accounting for 70% of the total variance. These factors were classified as \"collaboration,\" \"clinical professionalism,\" \"patient-centered care,\" \"professionalism,\" and \"systematic treatment and self-development.\" Content validity was confirmed by the Delphi panel, and all items achieved a content validity ratio of 1, indicating strong content validity.Conclusion: The developed performance indicators are reliable and valid tools for assessing the competencies of medical school graduates. These indicators can be used to evaluate the quality of medical education and to improve the curriculum. It is also important to establish a system to periodically assess competencies after graduation.","PeriodicalId":37737,"journal":{"name":"Korean journal of medical education","volume":"37 4","pages":"419-427"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12683267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145702235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From Bainbridge to bedside: applying automation insights to medical curriculum and assignment design in the artificial intelligence era. 从班桥到床边：人工智能时代将自动化见解应用于医学课程和作业设计。

Korean journal of medical education Pub Date : 2025-12-01 Epub Date: 2025-10-02 DOI: 10.3946/kjme.2025.351

Sangzin Ahn

引用次数: 0

Teaching medical ethics through Ethical Grand Rounds. 通过伦理大查房教授医学伦理学。

Korean journal of medical education Pub Date : 2025-12-01 Epub Date: 2025-11-27 DOI: 10.3946/kjme.2025.363

Min Ji Kim, Claire Junga Kim

引用次数: 0