{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:51:30Z","timestamp":1782478290260,"version":"3.54.5"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032297433","type":"print"},{"value":"9783032297440","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T00:00:00Z","timestamp":1782518400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T00:00:00Z","timestamp":1782518400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-29744-0_30","type":"book-chapter","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:39:41Z","timestamp":1782477581000},"page":"447-462","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LLM-Based Virtual Standardized Patients with\u00a0Response Excessiveness Suppression via\u00a0Direct Preference Optimization for\u00a0Medical Interview Examinations"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9423-7819","authenticated-orcid":false,"given":"Naoki","family":"Shindo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9330-5158","authenticated-orcid":false,"given":"Masaki","family":"Uto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,27]]},"reference":[{"key":"30_CR1","doi-asserted-by":"crossref","unstructured":"Badshah, S., Sajjad, H.: Reference-guided verdict: Llms-as-judges in automatic evaluation of free-form qa. In: Proceedings of the 9th Widening NLP Workshop. pp. 251\u2013267 (2025)","DOI":"10.18653\/v1\/2025.winlp-main.37"},{"issue":"1","key":"30_CR2","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1186\/1472-6920-14-97","volume":"14","author":"LA Baig","year":"2014","unstructured":"Baig, L.A., Beran, T.N., Vallevand, A., Baig, Z.A., Monroy-Cuadros, M.: Accuracy of portrayal by standardized patients: Results from four OSCE stations conducted for high stakes examinations. BMC Med. Educ. 14(1), 97 (2014)","journal-title":"BMC Med. Educ."},{"key":"30_CR3","unstructured":"Ban, N., Suzuki, T., Aomatsu, M., Saiki, T., Abe, K., Kuwabata, A.: An Easy-to-Understand Guide to Medical Interviews and Simulated Patients. The University of Nagoya Press [In Japanese] (2015)"},{"issue":"1","key":"30_CR4","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1080\/0142159X.2024.2376879","volume":"47","author":"DA Cook","year":"2025","unstructured":"Cook, D.A.: Creating virtual patients using large language models: Scalable, global, and low cost. Med. Teach. 47(1), 40\u201342 (2025)","journal-title":"Med. Teach."},{"key":"30_CR5","doi-asserted-by":"crossref","unstructured":"Dettmers, T., Pagnoni, A., Holtzman, A., Zettlemoyer, L.: Qlora: Efficient finetuning of quantized LLMs. In: Advances in Neural Information Processing Systems (NeurIPS 2023). vol.\u00a036, pp. 10088\u201310115 (2023)","DOI":"10.52202\/075280-0441"},{"key":"30_CR6","doi-asserted-by":"crossref","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. pp. 4171\u20134186 (2019)","DOI":"10.18653\/v1\/N19-1423"},{"key":"30_CR7","unstructured":"Dickerson, R.F., Johnsen, K., Raij, A., Lok, B., Hernandez, J., Stevens, A., Lind, D.S.: Evaluating a script-based approach for simulating patient-doctor interaction. In: Proceedings of the International Conference on Human-Computer Interface Advances for Modeling and Simulation. pp. 79\u201384 (2005)"},{"key":"30_CR8","doi-asserted-by":"crossref","unstructured":"El Zini, J., Rizk, Y., Awad, M., Antoun, J.: Towards a deep learning question-answering specialized chatbot for objective structured clinical examinations. In: Proceedings of the IEEE International Joint Conference on Neural Networks. pp. 1\u20139 (2019)","DOI":"10.1109\/IJCNN.2019.8851729"},{"key":"30_CR9","unstructured":"Gu, J., Jiang, X., Shi, Z., Tan, H., Zhai, X., Xu, C., Li, W., Shen, Y., Ma, S., Liu, H., Wang, S., Zhang, K., Wang, Y., Gao, W., Ni, L., Guo, J.: A survey on LLM-as-a-judge (2024)"},{"issue":"1","key":"30_CR10","first-page":"40","volume":"47","author":"E Guo","year":"2024","unstructured":"Guo, E., Ramchandani, R., Park, Y.J., Gupta, M.: OSCEai: Personalized interactive learning for undergraduate medical education. Canadian Medical Education Journal 47(1), 40\u201342 (2024)","journal-title":"Canadian Medical Education Journal"},{"issue":"11","key":"30_CR11","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1007\/s13312-010-0155-6","volume":"47","author":"P Gupta","year":"2010","unstructured":"Gupta, P., Dewan, P., Singh, T.: Objective structured clinical examination (OSCE) revisited. Indian Pediatr. 47(11), 911\u2013920 (2010)","journal-title":"Indian Pediatr."},{"issue":"1","key":"30_CR12","doi-asserted-by":"publisher","first-page":"19","DOI":"10.3109\/01421598809019321","volume":"10","author":"RM Harden","year":"1988","unstructured":"Harden, R.M.: What is an osce? Med. Teach. 10(1), 19\u201322 (1988)","journal-title":"Med. Teach."},{"issue":"6","key":"30_CR13","doi-asserted-by":"publisher","first-page":"e301","DOI":"10.1016\/j.ecns.2014.02.001","volume":"10","author":"AJ Kleinheksel","year":"2014","unstructured":"Kleinheksel, A.J.: Transformative learning through virtual patient simulations: Predicting critical student reflections. Clin. Simul. Nurs. 10(6), e301\u2013e308 (2014)","journal-title":"Clin. Simul. Nurs."},{"issue":"2","key":"30_CR14","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1111\/j.1365-2923.1996.tb00724.x","volume":"30","author":"SM Kurtz","year":"1996","unstructured":"Kurtz, S.M., Silverman, J.D.: The calgary\u2013cambridge referenced observation guides: an aid to defining the curriculum and organizing the teaching in communication training programmes. Med. Educ. 30(2), 83\u201389 (1996)","journal-title":"Med. Educ."},{"issue":"1","key":"30_CR15","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33(1), 159\u2013174 (1977)","journal-title":"Biometrics"},{"key":"30_CR16","unstructured":"Li, Y., Zeng, C., Zhong, J., Zhang, R., Zhang, M., Zou, L.: Leveraging large language model as simulated patients for clinical education (2024)"},{"key":"30_CR17","unstructured":"Liu, S., Fang, W., Hu, Z., Zhang, J., Zhou, Y., Zhang, K., Tu, R., Lin, T.E., Huang, F., Song, M., Li, Y., Tao, D.: A survey of direct preference optimization (2025)"},{"issue":"12","key":"30_CR18","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.nedt.2018.09.014","volume":"71","author":"T Liu","year":"2018","unstructured":"Liu, T., Luo, J., He, H., Zheng, J., Zhao, J., Li, K.: History-taking instruction for baccalaureate nursing students by virtual patient training: A retrospective study. Nurse Educ. Today 71(12), 97\u2013104 (2018)","journal-title":"Nurse Educ. Today"},{"key":"30_CR19","doi-asserted-by":"crossref","unstructured":"Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y., Gupta, S., Majumder, B.P., Hermann, K., Welleck, S., Yazdanbakhsh, A., Clark, P.: Self-refine: Iterative refinement with self-feedback. In: Advances in Neural Information Processing Systems. vol.\u00a036, pp. 46534\u20134659 (2023)","DOI":"10.52202\/075280-2019"},{"issue":"3","key":"30_CR20","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1080\/0142159X.2022.2130216","volume":"45","author":"KR Maicher","year":"2023","unstructured":"Maicher, K.R., Stiff, A., Scholl, M., White, M., Fosler-Lussier, E., Schuler, W., Serai, P., Sunder, V., Forrestal, H., Mendella, L., Adib, M., Bratton, C., Lee, K., Danforth, D.R.: Artificial intelligence in virtual standardized patients: Combining natural language understanding and rule based dialogue management to improve conversational fidelity. Med. Teach. 45(3), 279\u2013285 (2023)","journal-title":"Med. Teach."},{"issue":"12","key":"30_CR21","first-page":"1077","volume":"38","author":"S Nakano","year":"2010","unstructured":"Nakano, S.: Simulated patient (SP) and learning of medical communications. Japanese Pharmacology and Therapeutics 38(12), 1077\u20131088 (2010)","journal-title":"Japanese Pharmacology and Therapeutics"},{"issue":"1","key":"30_CR22","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1080\/10872981.2023.2228550","volume":"28","author":"DSM Pereira","year":"2023","unstructured":"Pereira, D.S.M., Falc\u00e3o, F., Nunes, A., Santos, N., Costa, P., P\u00eago, J.M.: Designing and building OSCEBot\u00ae for virtual OSCE-performance evaluation. Med. Educ. Online 28(1), 16 (2023)","journal-title":"Med. Educ. Online"},{"key":"30_CR23","doi-asserted-by":"crossref","unstructured":"Rafailov, R., Sharma, A., Mitchell, E., Manning, C.D., Ermon, S., Finn, C.: Direct preference optimization: Your language model is secretly a reward model. In: Advances in Neural Information Processing Systems. vol. 36, pp. 53728\u201353741 (2023)","DOI":"10.52202\/075280-2338"},{"key":"30_CR24","unstructured":"Rau, T., Fegert, J., Liebhardt, H.: How high are the personnel costs for OSCE? a financial report on management aspects. GMS Journal for Medical Education 28(1), Doc13 (2011)"},{"key":"30_CR25","unstructured":"Reichenpfader, D., Denecke, K.: Simulating diverse patient populations using patient vignettes and large language models. In: Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024. pp. 20\u201325 (2024)"},{"key":"30_CR26","doi-asserted-by":"crossref","unstructured":"Salminen, J., Liu, C., Pian, W., Chi, J., H\u00e4yh\u00e4nen, E., Jansen, B.J.: Deus ex machina and personas from large language models: Investigating the composition of ai-generated persona descriptions. In: Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI \u201924). pp. 1\u201320 (2024)","DOI":"10.1145\/3613904.3642036"},{"key":"30_CR27","unstructured":"Schmidgall, S., Ziaei, R., Harris, C., Reis, E., Jopling, J., Moor, M.: Agentclinic: A multimodal agent benchmark to evaluate AI in simulated clinical environments (2024)"},{"key":"30_CR28","doi-asserted-by":"crossref","unstructured":"Shindo, N., Uto, M.: Chatgpt-based virtual standardized patient that amends overly detailed responses in objective structured clinical examinations. In: Proceedings of the International Conference on Artificial Intelligence in Education, pp. 263\u2013269 (2024)","DOI":"10.1007\/978-3-031-64315-6_22"},{"key":"30_CR29","doi-asserted-by":"crossref","unstructured":"Shindo, N., Uto, M.: Virtual simulated patients for medical interviews using large language models with a self-refinement mechanism to suppress excessive responses. In: Proceedings of the International Conference on Artificial Intelligence in Education, pp. 52\u201359. (2025)","DOI":"10.1007\/978-3-031-99267-4_7"},{"key":"30_CR30","doi-asserted-by":"crossref","unstructured":"Shindo, N., Uto, M.: Leveraging self-refinement in large language models to suppress excessive responses for virtual simulated patients. IEICE Trans. Inf. Syst. E109-D(8) (2026)","DOI":"10.1587\/transinf.2025EDP7197"},{"issue":"9","key":"30_CR31","first-page":"1423","volume":"152","author":"MA Stewart","year":"1995","unstructured":"Stewart, M.A.: Effective physician-patient communication and health outcomes: a review. Can. Med. Assoc. J. 152(9), 1423\u20131433 (1995)","journal-title":"Can. Med. Assoc. J."},{"issue":"9","key":"30_CR32","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0309887","volume":"19","author":"M Uto","year":"2024","unstructured":"Uto, M., Tsuruta, J., Araki, K., Ueno, M.: Item response theory model highlighting rating scale of a rubric and rater-rubric interaction in objective structured clinical examination. PLoS ONE 19(9), e0309887 (2024)","journal-title":"PLoS ONE"},{"issue":"1","key":"30_CR33","doi-asserted-by":"publisher","DOI":"10.2196\/59435","volume":"27","author":"C Wang","year":"2025","unstructured":"Wang, C., et al.: Application of large language models in medical training evaluation\u2013using ChatGPT as a standardized patient: Multimetric assessment. J. Med. Internet Res. 27(1), e59435 (2025)","journal-title":"J. Med. Internet Res."},{"issue":"1","key":"30_CR34","doi-asserted-by":"publisher","DOI":"10.2196\/58753","volume":"10","author":"A Yamamoto","year":"2024","unstructured":"Yamamoto, A., et al.: Enhancing medical interview skills through AI-simulated patient interactions: nonrandomized controlled trial. JMIR Med. Educ. 10(1), e58753 (2024)","journal-title":"JMIR Med. Educ."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Education"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-29744-0_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:40:00Z","timestamp":1782477600000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-29744-0_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,27]]},"ISBN":["9783032297433","9783032297440"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-29744-0_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,27]]},"assertion":[{"value":"27 June 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"AIED","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Education","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Seoul","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 June 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aied2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.aied-conference.org\/2026","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}