Chinese Journal of Medical Education ›› 2024, Vol. 44 ›› Issue (10): 726-732.DOI: 10.3760/cma.j.cn115259-20240411-00383
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Wen Deliang1, Li Honghe2, Song Xinzhi2
Received:
2024-04-11
Online:
2024-10-01
Published:
2024-09-29
Contact:
Wen Deliang, Email: dlwen@cmu.edu.cn
Supported by:
CLC Number:
Wen Deliang, Li Honghe, Song Xinzhi. Analysis of research fronts in medical education based on Web of Science (2024)[J]. Chinese Journal of Medical Education, 2024, 44(10): 726-732.
[1] 闻德亮, 李鸿鹤, 宋鑫智. 基于科学引文数据库的医学教育研究前沿分析(2023)[J].中华医学教育杂志,2023,43(12):881-886. DOI: 10.3760/cma.j.cn115259-20230331-00349. [2] 吴红斌, 杜鹃,程化琴, 等. 国际医学教育研究发展及启示 ——基于WOS百余年文献的计量分析[J].复旦教育论坛,2019,17(5):97-103. DOI: 10.3969/j.issn.1672-0059.2019.05.017. [3] 中国科协学会服务中心. 科睿唯安发布《2023中国国际科研合作现状报告》[EB/OL].(2024-03-15)[2024-03-31]. https://stm.castscs.org.cn/yw/40694.jhtml. [4] Elsevier, 中国教育在线. 重磅!2023“中国高被引学者”榜单出炉[EB/OL].(2024-03-28)[2024-03-31]. https://baijiahao.baidu.com/s?id=1794723847993644849&wfr=spider&for=pc. [5] Hauer KE, Park YS, Bullock JL, et al. “My assessments are biased!” measurement and sociocultural approaches to achieve fairness in assessment in medical education[J]. Acad Med, 2023,98(8S):S16-S27. DOI: 10.1097/ACM.0000000000005245. [6] Anderson N, Nguyen M, Marcotte K, et al. The long shadow: a historical perspective on racism in medical education[J]. Acad Med, 2023,98(8S):S28-S36. DOI:10.1097/ACM.0000000000005253. [7] Mabeza RM, Christophers B, Ederaine SA, et al. Interventions associated with racial and ethnic diversity in US graduate medical education: a scoping review[J]. JAMA Netw Open, 2023,6(1):e2249335. DOI: 10.1001/jamanetworkopen.2022.49335. [8] Zhang P, Li X, Pan Y, et al. Global trends and future directions in online learning for medical students during and after the COVID-19 pandemic: a bibliometric and visualization analysis[J]. Medicine (Baltimore), 2023,102(50):e35377. DOI: 10.1097/MD.0000000000035377. [9] Gardanova Z, Belaia O, Zuevskaya S, et al. Lessons for medical and health education learned from the COVID-19 pandemic[J]. Healthcare (Basel), 2023,11(13):1921. DOI: 10.3390/healthcare11131921. [10] Agarwal A, Subramaniam G, Khattak O, et al. Navigating post COVID-19 education: an investigative study on students′ attitude and perception of their new normal learning environment[J]. PeerJ, 2023,11:e16184. DOI: 10.7717/peerj.16184. [11] Dimassi Z, Chaiban L, Zgheib NK, et al. Re-conceptualizing medical education in the post-COVID era[J]. Med Teach, 2024,46(8):1084-1091. DOI: 10.1080/0142159X.2023.2290463. [12] Lee MC, Melcer EF, Merrell SB, et al. Usability of entrust as an assessment tool for entrustable professional activities (EPAs): a mixed methods analysis[J]. J Surg Educ, 2023,80(11):1693-1702. DOI: 10.1016/j.jsurg.2023.09.001. [13] Krecko LK, Jung S, Martin S, et al. Enhancing the value of surgical entrustable professional activities through integrative learning analytics[J]. J Surg Educ, 2023,80(10):1370-1377. DOI: 10.1016/j.jsurg.2023.07.018. [14] Charondo LB, Sheu L, Bakke BM, et al.‘It′s more like checking in with an old friend′: a qualitative study of medical students′ experiences with longitudinal coaches throughout medical school[J]. Med Teach, 2024,46(6):808-816. DOI: 10.1080/0142159X.2023.2284659. [15] Gauthier S, Braund H, Dalgarno N, et al. Assessment-seeking strategies: navigating the decision to initiate workplace-based assessment[J]. Teach Learn Med, 2023:1-10. DOI: 10.1080/10401334.2023.2229803. [16] Thomas T, Arif S, Franklin CJ, et al. The intersection of professional identity formation, bias, and marginalized identities[J]. Am J Pharm Educ, 2023,87(11):100546. DOI: 10.1016/j.ajpe.2023.100546. [17] Koh E, Koh KK, Renganathan Y, et al. Role modelling in professional identity formation: a systematic scoping review[J]. BMC Med Educ, 2023,23(1):194. DOI: 10.1186/s12909-023-04144-0. [18] Aluri J, Ker J, Marr B, et al. The role of arts-based curricula in professional identity formation: results of a qualitative analysis of learner′s written reflections[J]. Med Educ Online, 2023,28(1):2145105. DOI: 10.1080/10872981.2022.2145105. [19] Veen M, de la Croix A. How to grow a professional identity: philosophical gardening in the field of medical education[J]. Perspect Med Educ, 2023,12(1):12-19. DOI: 10.5334/pme.367. [20] Pereda-Nuñez A, Manresa M, Webb SS, et al. Pelvic + anatomy: a new interactive pelvic anatomy model. Prospective randomized control trial with first-year midwife residents[J]. Anat Sci Educ, 2023,16(5):843-857. DOI: 10.1002/ase.2304. [21] Vasil′ev YL, Dydykin SS, Kashtanov AD, et al. A comparative analysis of lecturers′ satisfaction with anatomage and pirogov virtual dissection tables during clinical and topographic anatomy courses in Russian universities[J]. Anat Sci Educ, 2023,16(2):196-208. DOI: 10.1002/ase.2248. [22] Khan J, Baatjes KJ, Layman-Lemphane JI, et al. Online anatomy education during the Covid-19 pandemic: opinions of medical, speech therapy, and BSc anatomy students[J]. Anat Sci Educ, 2023,16(5):892-906. DOI: 10.1002/ase.2271. [23] Elston P, Canale GP, Ail G, et al. Twelve tips for teaching in virtual reality[J]. Med Teach, 2024,46(4):495-499. DOI: 10.1080/0142159X.2023.2285396. [24] Zumsteg JM, Junn C. Will ChatGPT match to your program?[J]. Am J Phys Med Rehabil, 2023,102(6):545-547. DOI: 10.1097/PHM.0000000000002238. [25] Riedel M, Kaefinger K, Stuehrenberg A, et al. ChatGPT′s performance in German OB/GYN exams - paving the way for AI-enhanced medical education and clinical practice[J]. Front Med (Lausanne), 2023,10:1296615. DOI: 10.3389/fmed.2023.1296615. [26] Choi W. Assessment of the capacity of ChatGPT as a self-learning tool in medical pharmacology: a study using MCQs[J]. BMC Med Educ, 2023,23(1):864. DOI: 10.1186/s12909-023-04832-x. [27] Russell RG, Lovett Novak L, Patel M, et al. Competencies for the use of artificial intelligence-based tools by health care professionals[J]. Acad Med, 2023,98(3):348-356. DOI: 10.1097/ACM.0000000000004963. [28] Buabbas AJ, Miskin B, Alnaqi AA, et al. Investigating students′ perceptions towards artificial intelligence in medical education[J]. Healthcare (Basel),2023,11(9):1298. DOI: 10.3390/healthcare11091298. [29] Moodi Ghalibaf A, Moghadasin M, Emadzadeh A, et al. Psychometric properties of the persian version of the medical artificial intelligence readiness scale for medical students (MAIRS-MS)[J]. BMC Med Educ, 2023,23(1):577. DOI: 10.1186/s12909-023-04553-1. [30] Ng F, Thirunavukarasu AJ, Cheng H, et al. Artificial intelligence education: an evidence-based medicine approach for consumers, translators, and developers[J]. Cell Rep Med, 2023,4(10):101230. DOI: 10.1016/j.xcrm.2023.101230. [31] Gutiérrez-Cirlos C, Carrillo-Pérez DL, Bermúdez-González JL, et al. ChatGPT: opportunities and risks in the fields of medical care, teaching, and research[J]. Gac Med Mex, 2023,159(5):372-379. DOI: 10.24875/GMM.M23000811. [32] Tolsgaard MG, Pusic MV, Sebok-Syer SS, et al. The fundamentals of artificial intelligence in medical education research: AMEE Guide No. 156[J]. Med Teach, 2023,45(6):565-573. DOI: 10.1080/0142159X.2023.2180340. [33] Valentine N, Durning SJ, Shanahan EM, et al. What stops fairness from emerging in assessment? the forces on a complex adaptive system[J]. Perspect Med Educ, 2023,12(1):338-347. DOI: 10.5334/pme.994. [34] Malau-Aduli BS, Hays RB, D′Souza K, et al. Twelve tips for improving the quality of assessor judgements in senior medical student clinical assessments[J]. Med Teach, 2023,45(11):1228-1232. DOI: 10.1080/0142159X.2023.2216364. [35] Boursicot K, Kemp S, Norcini J, et al. Synthesis and perspectives from the Ottawa 2022 conference on the assessment of competence[J]. Med Teach, 2023,45(9):978-983. DOI: 10.1080/0142159X.2023.2174420. [36] Heng J, Teo DB, Tan LF. The impact of chat generative pre-trained transformer (ChatGPT) on medical education[J]. Postgrad Med J, 2023,99(1176):1125-1127. DOI: 10.1093/postmj/qgad058. [37] Gordon M, Daniel M, Ajiboye A, et al. A scoping review of artificial intelligence in medical education: BEME Guide No. 84[J]. Med Teach, 2024,46(4):446-470. DOI: 10.1080/0142159X.2024.2314198. |
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