以人工智能赋能叙事医学:儿科医学教育的新视角

金贞爱, 代汝兰

中国当代儿科杂志 ›› 2026, Vol. 28 ›› Issue (6) : 652-658.

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中国当代儿科杂志 ›› 2026, Vol. 28 ›› Issue (6) : 652-658. DOI: 10.7499/j.issn.1008-8830.2511184
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以人工智能赋能叙事医学:儿科医学教育的新视角

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Empowering narrative medicine with artificial intelligence: a new perspective in pediatric medical education

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摘要

该文系统性探讨人工智能(artificial intelligence, AI)技术与叙事医学在儿科医学教育中的融合路径、挑战,以及未来的发展方向。儿科诊疗因其服务对象的特殊性,对医生的共情、沟通能力以及人文素养均提出了更高的要求。叙事医学作为弥补医学人文缺失的关键范式,为这些核心人文素养的培养提供理论框架与实践方法,但其教学推广与实践存在着规模化、标准化不足以及深度反馈有限等困境。AI技术,特别是自然语言处理和生成AI的进展,为破解上述困境带来全新的契机。该文借助系统性的文献回顾,梳理了二者融合的相关理论、研究方法与实践成果,构建了“独立发展-技能赋能-协同深化”的三阶段融合模型。文章细致剖析了二者融合过程中面临的技术伦理、教育整合与价值异化等严峻挑战,最后提出构建以“人机协同”为核心的未来儿科医学教育新范式,为培育兼具精湛技术、深厚共情与坚韧职业精神的下一代儿科医生开拓新视角。

Abstract

This paper systematically explores the integration pathways, challenges, and future directions of artificial intelligence (AI) technology and narrative medicine in pediatric medical education. Due to the unique characteristics of the pediatric population, pediatric diagnosis and treatment place higher demands on physicians' empathy, communication skills, and humanistic qualities. Narrative medicine, as a key paradigm to address deficiencies in medical humanities, provides a theoretical framework and practical methods for cultivating these core humanistic qualities. However, its teaching promotion and practice face challenges such as insufficient scaling, lack of standardization, and limited depth of feedback. Advances in AI technology, particularly in natural language processing and generative AI, offer new opportunities to overcome these challenges. Based on a systematic literature review, relevant theories, research methods, and practical outcomes of the integration between AI and narrative medicine are synthesized, and a three-stage integration model of "independent development - skill empowerment - collaborative deepening" is constructed. The integration process faces significant challenges including technical ethics, educational integration, and value alienation. Finally, a new paradigm for future pediatric medical education centered on "human-machine collaboration" is proposed, aiming to cultivate the next generation of pediatricians who possess excellent technical skills, profound empathy, and resilient professional spirit, thereby opening new perspectives.

关键词

叙事医学 / 人工智能 / 儿科医学教育 / 大语言模型 / 医学人文

Key words

Narrative medicine / Artificial intelligence / Pediatric medical education / Large language model / Medical humanities

引用本文

导出引用
金贞爱, 代汝兰. 以人工智能赋能叙事医学:儿科医学教育的新视角[J]. 中国当代儿科杂志. 2026, 28(6): 652-658 https://doi.org/10.7499/j.issn.1008-8830.2511184
Zhen-Ai JIN, Ru-Lan DAI. Empowering narrative medicine with artificial intelligence: a new perspective in pediatric medical education[J]. Chinese Journal of Contemporary Pediatrics. 2026, 28(6): 652-658 https://doi.org/10.7499/j.issn.1008-8830.2511184

参考文献

[1]
Frenk J, Chen L, Bhutta ZA, et al. Health professionals for a new century: transforming education to strengthen health systems in an interdependent world[J]. Lancet, 2010, 376(9756): 1923-1958. DOI: 10.1016/S0140-6736(10)61854-5 .
[2]
王茜, 李敬风. 儿科疾病叙事方式及特点的质性分析[J]. 中国医学伦理学, 2021, 34(1): 81-87, 112. DOI: 10.12026/j.issn.1001-8565.2021.01.16 .
[3]
金贞爱. 关于儿科学发展融入叙事医学理念的思考[J]. 中国当代儿科杂志, 2024, 26(4): 325-330. PMCID: PMC11057294. DOI: 10.7499/j.issn.1008-8830.2310114 .
[4]
Kumagai AK. A conceptual framework for the use of illness narratives in medical education[J]. Acad Med, 2008, 83(7): 653-658. DOI: 10.1097/ACM.0b013e3181782e17 .
[5]
Jones H. Tackling burnout among Senior clinicians: the paediatrician[J]. BMJ, 2020, 369: m1839. DOI: 10.1136/bmj.m1839 .
[6]
Charon R. Narrative medicine: form, function, and ethics[J]. Ann Intern Med, 2001, 134(1): 83-87. DOI: 10.7326/0003-4819-134-1-200101020-00024 .
[7]
Charon R. The patient-physician relationship. Narrative medicine: a model for empathy, reflection, profession, and trust[J]. JAMA, 2001, 286(15): 1897-1902. DOI: 10.1001/jama.286.15.1897 .
[8]
王一方. 临床医学人文: 困境与出路——兼谈叙事医学对于临床医学人文的意义[J]. 医学与哲学(A), 2013, 34(9): 14-18.
[9]
中华预防医学会叙事医学分会, 北京整合医学学会叙事医学分会. 中国叙事医学专家共识(2023)[J]. 叙事医学, 2023, 6(6): 381-411.
[10]
李平甘, 张丽娜, 梁立阳. 叙事医学教学法在儿科住培医师中的应用[J]. 中国继续医学教育, 2019, 11(25): 25-28. DOI: 10.3969/j.issn.1674-9308.2019.25.011 .
[11]
杨晓霖, 陈慧慧, 陶艳玲, 等. 奥斯勒患者观与叙事医学中的医患叙事共同体理念[J]. 中国医学伦理学, 2024, 37(5): 564-569. DOI: 10.12026/j.issn.1001-8565.2024.05.10 .
[12]
Dobrina R, Bicego L, Giangreco M, et al. A multi-method quasi-experimental study to assess compassion satisfaction/fatigue in nurses, midwives and allied health professionals receiving a narrative medicine intervention[J]. J Adv Nurs, 2023, 79(9): 3595-3608. DOI: 10.1111/jan.15686 .
[13]
Remein CD, Childs E, Pasco JC, et al. Content and outcomes of narrative medicine programmes: a systematic review of the literature through 2019[J]. BMJ Open, 2020, 10(1): e031568. PMCID: PMC7045204. DOI: 10.1136/bmjopen-2019-031568 .
[14]
黄国祯, 方建文, 涂芸芳. 人工智能教育应用研究的全球图景与趋势[J]. 现代远程教育研究, 2022, 34(3): 3-14. DOI: 10.3969/j.issn.1009-5195.2022.03.001 .
[15]
胡振生, 杨瑞, 朱嘉豪, 等. 大语言模型在医学领域的研究与应用发展[J]. 人工智能, 2023(4): 10-19. DOI: 10.16453/j.2096-5036.2023.04.002 .
[16]
武宗渊, 刘振, 张宗明. 人工智能在医学教育领域的现状、未来治理研究[J]. 中国医学伦理学, 2024, 37(9): 1093-1100. DOI: 10.12026/j.issn.1001-8565.2024.09.12 .
[17]
Janumpally RK. The role of natural language processing in graduate medical education: a scoping review[J]. Cureus, 2025, 17(3): e81078. PMCID: PMC12017239. DOI: 10.7759/cureus.81078 .
[18]
杨晓霖, 宝令玉, 高玮. 叙事素养提升的两大工具: 文本细读与反思性写作[J]. 叙事医学, 2022, 5(4): 261-270, 275.
[19]
郭莉萍, 王一方. 叙事医学在我国的在地化发展[J]. 中国医学伦理学, 2019, 32(2): 147-152. DOI: 10.12026/j.issn.1001-8565.2019.02.03 .
[20]
董强, 罗小兰, 杨晓霖. 叙事医学在医学教育与临床实践中的五个关键词[J]. 医学与哲学, 2020, 41(2): 1-6. DOI: 10.12014/j.issn.1002-0772.2020.02.01 .
[21]
Li R, Chen H, Feng F, et al. DualGCN: exploring syntactic and semantic information for aspect-based sentiment analysis[J]. IEEE Trans Neural Netw Learn Syst, 2024, 35(6): 7642-7656. DOI: 10.1109/TNNLS.2022.3219615 .
[22]
Cheng Y, Yuan M, He F, et al. Aspect-based sentiment analysis based on multi-granularity graph convolutional network[J]. Neural Netw, 2025, 192: 107864. DOI: 10.1016/j.neunet.2025.107864 .
[23]
王一方. 叙事医学: 从工具到价值[J]. 医学与哲学(A), 2018, 39(5): 1-6.
[24]
Williams B, Brown T, McKenna, L, et al. Student empathy levels across 12 medical and health professions: an interventional study[J]. J Compassionate Health Care, 2015, 2(1): 4. DOI: 10.1186/s40639-015-0013-4 .
[25]
Cook DA, Levinson AJ, Garside S, et al. Internet-based learning in the health professions: a meta-analysis[J]. JAMA, 2008, 300(10): 1181-1196. DOI: 10.1001/jama.300.10.1181 .
[26]
Jung Y, Wise AF. How and how well do students reflect?: Multi-dimensional automated reflection assessment in health professions education[C]// Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. New York, NY, USA: ACM, 2020: 595-604.
[27]
Chary M, Parikh S, Manini AF, et al. A review of natural language processing in medical education[J]. West J Emerg Med, 2019, 20(1): 78-86. PMCID: PMC6324711. DOI: 10.5811/westjem.2018.11.39725 .
[28]
杨晓霖, 贾宇哲, 赵崇晔, 等. 医者叙事素养量表的编制及信度效度检验[J]. 医学与哲学, 2023, 44(21): 39-44. DOI: 10.12014/j.issn.1002-0772.2023.21.09 .
[29]
Guetterman TC, Sakakibara R, Baireddy S, et al. Medical students' experiences and outcomes using a virtual human simulation to improve communication skills: mixed methods study[J]. J Med Internet Res, 2019, 21(11): e15459. PMCID: PMC6906619. DOI: 10.2196/15459 .
[30]
Lee J, Kim H, Kim KH, et al. Effective virtual patient simulators for medical communication training: a systematic review[J]. Med Educ, 2020, 54(9): 786-795. DOI: 10.1111/medu.14152 .
[31]
Shool S, Adimi S, Saboori Amleshi R, et al. A systematic review of large language model (LLM) evaluations in clinical medicine[J]. BMC Med Inform Decis Mak, 2025, 25(1): 117. PMCID: PMC11889796. DOI: 10.1186/s12911-025-02954-4 .
[32]
张晓波, 冯瑞, 杨睿, 等. DeepSeek赋能的儿科全流程智慧医疗系统的构建和应用效果评价[J]. 中国循证儿科杂志, 2025, 20(3): 217-222. DOI: 10.3969/j.issn.1673-5501.2025.03.010 .
[33]
Chen Y, Wang Z, Xing X, et al. BianQue: balancing the questioning and suggestion ability of health LLMs with multi-turn health conversations polished by ChatGPT[J]. arXiv[Preprint ] (2023-12-04) [2025-10-18]. DOI: 10.48550/arXiv.2310.15896 .
[34]
Fu Y, Ramachandran GK, Dobbins NJ, et al. Extracting social determinants of health from pediatric patient notes using large language models: novel corpus and methods[C]//Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Stroudsburg, PA, USA: ACL, 2024: 7045-7056.
[35]
Dhar E, Upadhyay U, Huang Y, et al. A scoping review to assess the effects of virtual reality in medical education and clinical care[J]. Digit Health, 2023, 9: 20552076231158022. PMCID: PMC9972057. DOI: 10.1177/20552076231158022 .
[36]
李钥, 淮盼盼, 杨辉. ChatGPT在护理教育中的应用状况及优劣分析[J]. 护理学杂志, 2023, 38(21): 117-121. DOI: 10.3870/j.issn.1001-4152.2023.21.117 .
[37]
Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers[J]. JMIR Med Educ, 2023, 9: e46885. PMCID: PMC10028514. DOI: 10.2196/46885 .
[38]
Antel R, Abbasgholizadeh-Rahimi S, Guadagno E, et al. The use of artificial intelligence and virtual reality in doctor-patient risk communication: a scoping review[J]. Patient Educ Couns, 2022, 105(10): 3038-3050. DOI: 10.1016/j.pec.2022.06.006 .
[39]
Ryan P, Luz S, Albert P, et al. Using artificial intelligence to assess clinicians' communication skills[J]. BMJ, 2019, 364: l161. DOI: 10.1136/bmj.l161 .
[40]
Zheng Z, Peng X, Yang T, et al. Open-sora: democratizing efficient video production for all[J]. arXiv[Preprint]. (2024-12-29) [2025-10-18]. DOI: 10.48550/arXiv.2412.20404 .
[41]
任天知, 沈浩. 从Sora到“世界模拟”: 视频大模型的技术原理、应用场景与未来进路[J]. 新闻爱好者, 2024(6): 27-32.
[42]
Huang L, Yu W, Ma W, et al. A survey on hallucination in large language models: principles, taxonomy, challenges, and open questions[J]. ACM Trans Inf Syst, 2025, 43(2): 42. DOI: 10.1145/3703155 .
[43]
胡泳, 王昱昊. 技术过程论视角下AI幻觉生成的价值负荷与伦理问题探析[J]. 南京社会科学, 2025(3): 84-94. DOI: 10.15937/j.cnki.issn1001-8263.2025.03.009 .
[44]
Masoumi S, Amirkhani H, Sadeghian N, et al. Natural language processing (NLP) to facilitate abstract review in medical research: the application of BioBERT to exploring the 20-year use of NLP in medical research[J]. Syst Rev, 2024, 13(1): 107. PMCID: PMC11020656. DOI: 10.1186/s13643-024-02470-y .
[45]
Zhang Z, Yan C, Malin BA. Membership inference attacks against synthetic health data[J]. J Biomed Inform, 2022, 125: 103977. PMCID: PMC8766950. DOI: 10.1016/j.jbi.2021.103977 .
[46]
Mccradden MD, Joshi S, Mazwi M, et al. Ethical limitations of algorithmic fairness solutions in health care machine learning[J]. Lancet Digit Health, 2020, 2(5): e221-e223. DOI: 10.1016/S2589-7500(20)30065-0 .
[47]
Zhou J, Ding X, Fa C, et al. Expert consensus on narrative medicine education and teaching in China's medical colleges (2025)[J]. Asian J Med Humanit, 2026, 5(1): 20250060. DOI: 10.1515/ajmedh-2025-0060 .

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