中华医学教育杂志

中华医学教育杂志 >

2026 , Vol. 46 >Issue 5: 331 - 336

DOI: https://doi.org/10.3760/cma.j.cn115259-20250523-00582

教育技术

面向教育场景的虚拟标准化病人技术演进及其应用与展望

  • 刘英 ,
  • 袁晴 ,
  • 程琳傑 ,
  • 尹婉宜 ,
  • 江哲涵
展开
  • 1河北医科大学第一医院教务处,石家庄 050023;
    2华北理工大学公共卫生学院2023级公共卫生与预防医学专业硕士研究生,唐山 063210;
    3河北医科大学第一医院医疗事业部,石家庄 050023;
    4北京大学医学教育研究所,北京 100191

收稿日期: 2025-05-23

  网络出版日期: 2026-04-30

基金资助

国家自然科学基金面上项目(72474004)

收起

Evolution, applications and prospects of virtual standardized patient technology in educational contexts

  • Liu Ying ,
  • Yuan Qing ,
  • Cheng Linjie ,
  • Yin Wanyi ,
  • Jiang Zhehan
Expand
  • 1Office of Academic Affairs, The First Hospital of Hebei Medical University, Shijiazhuang 050023, China;
    2Master Degree Candidate, Public Health and Preventive Medicine, Enrolled in 2023, School of Public Health, North China University of Science and Technology, Tangshan 063210, China;
    3Medical Affairs Department, The First Hospital of Hebei Medical University, Shijiazhuang 050023, China;
    4Institute of Medical Education, Peking University, Beijing 100191, China

Received date: 2025-05-23

  Online published: 2026-04-30

Supported by

National Natural Science Foundation of China (72474004)

Fold

摘要

虚拟标准化病人(virtual standardized patient,VSP)作为人工智能与模拟医学深度融合的产物,正推动医学教育向数据驱动范式转变。本文系统梳理了VSP的技术演进脉络,对比分析了其与传统标准化病人的核心差异,深入探讨了国内外VSP在技术架构与功能定位上的发展路径差异,国内侧重于考核评价导向的智能评分系统,国外聚焦于过程体验导向的多模态沉浸交互。VSP具有成本可控、教学同质、场景灵活等优势,也面临非语言模拟不足、生成内容失真、评估标准缺失等现实挑战。未来VSP的发展,技术上从多模态交互向生理闭环演进,标准上从分散向统一评估体系转型,安全治理上从被动防护向主动治理深化。本研究旨在为VSP的本土化研发应用、医学教育的智能升级提供参考。

关键词： 病人模拟; 虚拟标准化病人; 医学模拟教育; 虚拟现实; 技术范式; 研究进展

本文引用格式

刘英 , 袁晴 , 程琳傑 , 尹婉宜 , 江哲涵 . 面向教育场景的虚拟标准化病人技术演进及其应用与展望[J]. 中华医学教育杂志, 2026 , 46(5) : 331 -336 . DOI: 10.3760/cma.j.cn115259-20250523-00582

Abstract

Virtual standardized patient (VSP), which result from the advanced integration of artificial intelligence with simulation-based medical education, are catalyzing a shift in medical education towards a data-driven paradigm. This paper provides a systematic analysis of the technological advancements in VSP, highlighting their fundamental distinctions from traditional standardized patients. It further examines the divergent developmental trajectories in technical architecture and functional orientation between China and other countries. Domestically, there is an emphasis on intelligent scoring systems for assessment and evaluation, whereas internationally, the focus is on process-oriented multimodal immersive interaction. VSP presents notable benefits in terms of cost-effectiveness, uniformity in instruction, and adaptability in various scenarios. However, they also encounter practical challenges, such as limitations in replicating non-verbal communication, potential for content distortion, and the lack of standardized evaluation criteria. Future advancements in VSP development should focus on technological integration, progressing from multimodal interactions to physiological closed-loop systems. Additionally, there is a need for standardization to move from disparate practices to a cohesive assessment framework, and for security governance to transition from passive protection measures to proactive management strategies. This study seeks to serve as a foundational reference for the localized development and implementation of VSP, as well as for the advancement of intelligent methodologies in medical education.

Key words： Patient simulation; Virtual standardized patients; Medical simulation education; Virtual reality; Technological paradigms; Research progress

参考文献

[1] 孙雨哲, 王宪娥, 侯建霞. 虚拟标准化病人在医学教育中的应用与研究进展[J].中华医学教育杂志,2024,44(4):294-298. DOI:10.3760/cma.j.cn115259-20230414-00390.
[2] 喻佳龙, 李月, 秦建星, 等. 虚拟标准化病人有效性评估研究进展[J].中华医学教育杂志,2026,46(1):15-20. DOI:10.3760/cma.j.cn115259-20240722-00770.
[3] Hamilton A, Molzahn A, McLemore K. The evolution from standardized to virtual patients in medical education[J].Cureus, 2024,16(10):e71224. DOI:10.7759/cureus.71224.
[4] Gray M, Baird A, Sawyer T, et al.Increasing realism and variety of virtual patient dialogues for prenatal counseling education through a novel application of ChatGPT: exploratory observational study[J].JMIR Med Educ, 2024,10:e50705. DOI:10.2196/50705.
[5] 李翔, 梁杰, 陈晓云, 等. 虚拟仿真实验教学平台在病史采集教学中的应用[J].医学研究与教育,2025,42(3):74-80. DOI:10.3969/j.issn.1674-490X.2025.03.010.
[6] 汪国栋, 李月, 秦建星, 等. 虚拟标准化病人在精神医学教学中的应用与展望[J].神经疾病与精神卫生,2025,25(1):68-72. DOI:10.3969/j.issn.1009-6574.2025.01.010.
[7] Weisman D, Sugarman A, Huang YM, et al.Development of a GPT-4-powered virtual simulated patient and communication training platform for medical students to practice discussing abnormal mammogram results with patients: multiphase study[J].JMIR Form Res, 2025,9:e65670. DOI:10.2196/65670.
[8] Wang Y, Chen Y, Sheng J.Assessing ChatGPT as a medical consultation assistant for chronic hepatitis B: cross-language study of English and Chinese[J].JMIR Med Inform, 2024,12:e56426. DOI:10.2196/56426.
[9] Raheel A.Emotion analysis and recognition in 3D space using classifier-dependent feature selection in response to tactile enhanced audio-visual content using EEG[J].Comput Biol Med, 2024,179:108807. DOI:10.1016/j.compbiomed.2024.108807.
[10] Zhou Q. HGLER: a hierarchical heterogeneous graph networks for enhanced multimodal emotion recognition in conversations[J].PLoS One, 2025,20(9):e0330632. DOI:10.1371/journal.pone.0330632.
[11] Kapgate DD.Application of hybrid SSVEP + P300 brain computer interface to control avatar movement in mobile virtual reality gaming environment[J].Behav Brain Res, 2024,472:115154. DOI:10.1016/j.bbr.2024.115154.
[12] Liu Y, Shi C, Wu L, et al. Development and validation of a large language model-based system for medical history-taking training: prospective multicase study on evaluation stability, human-AI consistency, and transparency[J].JMIR Med Educ, 2025,11:e73419. DOI:10.2196/73419.
[13] Du J, Zhu X, Wang J, et al.History-taking level and its influencing factors among nursing undergraduates based on the virtual standardized patient testing results: cross sectional study[J].Nurse Educ Today, 2022,111:105312. DOI:10.1016/j.nedt.2022.105312.
[14] Sonoda Y, Kurokawa R, Hagiwara A, et al. Structured clinical reasoning prompt enhances LLM′s diagnostic capabilities in diagnosis please quiz cases[J].Jpn J Radiol, 2025,43(4):586-592. DOI:10.1007/s11604-024-01712-2.
[15] Zhang X, Zeng D, Wang X, et al.Analysis of virtual standardized patients for assessing clinical fundamental skills of medical students: a prospective study[J].BMC Med Educ, 2024,24(1):981. DOI:10.1186/s12909-024-05982-2.
[16] 陈娜平, 唐陆禛, 黄贤生, 等. 基于ChatGPT-4的虚拟标准化病人应用研究[J].中华医学教育杂志,2025,45(1):44-49. DOI:10.3760/cma.j.cn115259-20240307-00225.
[17] Yang H, Xiao X, Wu X, et al. Virtual standardized patients versus traditional academic training for improving clinical competence among traditional Chinese medicine students: prospective randomized controlled trial[J].J Med Internet Res, 2023,25:e43763. DOI:10.2196/43763.
[18] Mishra C, Verdonschot R, Hagoort P, et al. Real-time emotion generation in human-robot dialogue using large language models[J].Front Robot AI, 2023,10:1271610. DOI:10.3389/frobt.2023.1271610.
[19] Reger GM, Norr AM, Gramlich MA, et al. Virtual standardized patients for mental health education[J].Curr Psychiatry Rep, 2021,23(9):57. DOI:10.1007/s11920-021-01273-5.
[20] Maicher KR, Zimmerman L, Wilcox B, et al. Using virtual standardized patients to accurately assess information gathering skills in medical students[J].Med Teach, 2019,41(9):1053-1059. DOI:10.1080/0142159X.2019.1616683.
[21] Reger GM, Norr AM, Rizzo AS, et al. Virtual standardized patients vs academic training for learning motivational interviewing skills in the US department of veterans affairs and the US military: a randomized trial[J].JAMA Netw Open, 2020,3(10):e2017348. DOI:10.1001/jamanetworkopen.2020.17348.
[22] 赵玉, 郭忠. 虚拟标准化病人在机能实验教学中的应用[J].基础医学教育,2024,26(4):335-339. DOI:10.13754/j.issn2095-1450.2024.04.14.
[23] Jensen R, Musaeus P, Pedersen K. Virtual patients in undergraduate psychiatry education: a systematic review and synthesis[J].Adv Health Sci Educ Theory Pract, 2024,29(1):329-347. DOI:10.1007/s10459-023-10247-6.
[24] Bond WF, Mischler MJ, Lynch TJ, et al. The use of virtual standardized patients for practice in high value care[J].Simul Healthc, 2023,18(3):147-154. DOI:10.1097/SIH.0000000000000659.
[25] 吴丽, 孙卫斌, 聂蓉蓉, 等. 虚拟仿真标准化病人软件系统在口腔住院医师OSCE考核中的应用[J].口腔材料器械杂志,2023,32(4):290-294. DOI:10.11752/j.kqcl.2023.04.12.
[26] Casas L, Hannah S, Mitchell K. HoloJig:interactive spoken prompt specified generative AI environments[J].IEEE Comput Graph Appl, 2025,45(2):69-77. DOI:10.1109/MCG.2025.3553780.
[27] Lan YL, Chen WL, Wang YF, et al. Development and preliminary testing of a virtual reality measurement for assessing intake assessment skills[J].Int J Psychol, 2023,58(3):237-246. DOI:10.1002/ijop.12898.
[28] Haber Y, Hadar Shoval D, Levkovich I, et al.The externalization of internal experiences in psychotherapy through generative artificial intelligence: a theoretical, clinical, and ethical analysis[J].Front Digit Health, 2025,7:1512273. DOI:10.3389/fdgth.2025.1512273.
[29] Abbasian M, Khatibi E, Azimi I, et al. Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI[J].NPJ Digit Med, 2024,7(1):82. DOI:10.1038/s41746-024-01074-z.
[30] Mannan M, Palipana DB, Mulholland K, et al. Virtual reality mediated brain-computer interface training improves sensorimotor neuromodulation in unimpaired and post spinal cord injury individuals[J].Sci Rep, 2026,16(1):6215. DOI:10.1038/s41598-026-36431-3.
[31] Sharma V, Park S, Voinescu A, et al.Medical students′ experiences with virtual reality simulation training: qualitative study[J].JMIR Med Educ, 2026,12:e74301. DOI:10.2196/74301.
[32] 黄欣, 蔡煜锋, 胡德华, 等. 基于PatSnap数据库的医疗领域脑机接口技术专利分析[J].世界科技研究与发展,2024,46(6):814-830. DOI:10.16507/j.issn.1006-6055.2024.06.002.
[33] 《脑机接口关键科学问题、关键核心技术及其布局研究》项目组, 肖松, 程和平, 等. 脑机接口技术发展现状及未来展望[J].科学与社会,2024,14(3):1-25. DOI:10.19524/j.cnki.10-1009/g3.2024.03.002.
[34] 郭佳莹, 杨洁莹, 李耀华. 医疗领域脑机接口技术和美国FDA监管现状浅析[J].中国医疗器械杂志,2025,49(1):96-102. DOI:10.12455/j.issn.1671-7104.240187.
[35] 张翔. 基于数字孪生技术的医疗网络数据安全保护系统设计[J].智能物联技术,2025,57(1):71-74. DOI:10.26921/j.cnki.2096-6059.2025.01.015.
[36] Dafli E, Antoniou P, Ioannidis L, et al. Virtual patients on the semantic Web: a proof-of-application study[J].J Med Internet Res, 2015,17(1):e16. DOI:10.2196/jmir.3933.
[37] 倪红波. 从大数据视角浅议对医院信息化和网络数据安全建设[J].数字通信世界,2023(7):172-174,178. DOI:10.3969/J.ISSN.1672-7274.2023.07.054.
[38] 吴腾. 生成式人工智能技术赋能智慧医疗建设的风险与规制[J].医学与社会,2025,38(3):9-16. DOI:10.13723/j.yxysh.2025.03.002.
[39] 孙琦, 吕晗, 王振常. 消除健康数据中的算法偏见:STANDING Together共识的启示[J].数字医学与健康,2025,3(1):10-11. DOI:10.3760/cma.j.cn101909-20241231-00240.
Options
文章导航

/

〈 〉