From Algorithms to Empathy: Exploring Chatbots as Tools for Medical Student Training

Document Type : Commentary

Authors

1 Department of E-learning in Medical Sciences, Virtual School and Center of Excellence in E-learning, Shiraz University of Medical Sciences, Shiraz, Iran

2 Social Ageing (SAGE) Futures Lab, Edith Cowan University, Perth, Australia

10.30476/ijvlms.2025.108737.1356

Abstract

This commentary examines the emerging role of conversational chatbots in medical education, particularly in terms of educating learners in empathy. Empathy is a key professional skill that impacts deeply both patient outcomes and patient satisfaction; yet, research indicates that its acquisition may decline in clinical training. Chatbots, as Artificial Intelligence (AI)-driven relational agents, offer safe and repeatable scenarios for practicing empathic communication, providing immediate feedback and opportunities for reflection without risk to real patients. However, their ability to manifest real empathy remains limited, raising ethical doubts about superficial learning. Other issues include cultural versatility, linguistic differences, and equal access to technology. Through a critical review of current literature and burgeoning evidence, this commentary highlights both potential benefits and limitations of chatbots as educational tools. The commentary advocates a systematic, evidence-based integration into medical curricula as a means of reinforcing traditional training while also protecting the inherent human aspect of empathy in care.

Highlights

Farzaneh Ghaznavi (Google Scholar)

Zahra Karimian (Google Scholar)

Keywords

References

  1. Chakraborty C, Pal S, Bhattacharya M, Dash S, Lee SS. Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science. Front Artif Intell. 2023;6:1237704. doi: 10.3389/frai.2023.1237704. PubMed PMID: 38028668; PubMed Central PMCID: PMC10644239.
  2. Luo M, Warren CJ, Cheng L, Abdul-Muhsin HM, Banerjee I. Assessing empathy in large language models with real-world physician-patient interactions.  Proceedings of the 2024 IEEE International Conference on Big Data (BigData). 2024 Dec 15-18; Washington, US. USA: IEEE; 2024. doi: 10.48550/arXiv.2405.16402.
  3. Sanjeewa R, Iyer R, Apputhurai P, Wickramasinghe N, Meyer D. Empathic Conversational Agent Platform Designs and Their Evaluation in the Context of Mental Health: Systematic Review. JMIR Ment Health. 2024;11:e58974. doi: 10.2196/58974. PubMed PMID: 39250799; PubMed Central PMCID: PMC11420590.
  4. Sorin V, Brin D, Barash Y, Konen E, Charney A, Nadkarni G, Klang E. Large Language Models and Empathy: Systematic Review. J Med Internet Res. 2024;26:e52597. doi: 10.2196/52597. PubMed PMID: 39661968; PubMed Central PMCID: PMC11669866.
  5. Coheur L. From Eliza to Siri and Beyond. Information Processing and Management of Uncertainty in Knowledge-Based Systems. 2020;1237:29–41. doi: 10.1007/978-3-030-50146-4_3. PubMed Central PMCID: PMC7274308.
  6. Weizenbaum J. ELIZA - a computer program for the study of natural language communication between man and machine. Commun. ACM. 1966;9:36–45. doi: 10.1145/365153.365168.
  7. Laranjo L, Dunn AG, Tong HL, Kocaballi AB, Chen J, Bashir R, Surian D, Gallego B, Magrabi F, Lau AYS, Coiera E. Conversational agents in healthcare: a systematic review. J Am Med Inform Assoc. 2018;25(9):1248-58. doi: 10.1093/jamia/ocy072. PubMed PMID: 30010941; PubMed Central PMCID: PMC6118869.
  8. Milne-Ives M, de Cock C, Lim E, Shehadeh MH, de Pennington N, Mole G, Normando E, Meinert E. The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review. J Med Internet Res. 2020;22(10):e20346. doi: 10.2196/20346. PubMed PMID: 33090118; PubMed Central PMCID: PMC7644372.
  9. Schachner T, Keller R, V Wangenheim F. Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review. J Med Internet Res. 2020;22(9):e20701. doi: 10.2196/20701. PubMed PMID: 32924957; PubMed Central PMCID: PMC7522733.
  10. Shen J, DiPaola D, Ali S, Sap M, Park HW, Breazeal C. Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study. JMIR Ment Health. 2024;11:e62679. doi: 10.2196/62679. PubMed PMID: 39321450; PubMed Central PMCID: PMC11464935.
  11. De Gennaro M, Krumhuber EG, Lucas G. Effectiveness of an Empathic Chatbot in Combating Adverse Effects of Social Exclusion on Mood. Front Psychol. 2020;10:3061. doi: 10.3389/fpsyg.2019.03061. PubMed PMID: 32038415; PubMed Central PMCID: PMC6989433.
  12. Liu T, Giorgi S, Aich A, Lahnala A, Curtis B, Ungar L, Sedoc J. The illusion of empathy: How AI Chatbots Shape Conversation Perception. [Internet]. arXiv. [Preprint]. 2025 [cited 2025 Jun 29]: 12 p. doi: 10.48550/arXiv.2411.12877.
  13. Seitz L. Artificial Empathy in Healthcare Chatbots: Does it Feel Authentic?. CHBAH. 2024;2(1):100067. doi: 10.1016/j.chbah.2024.100067.
  14. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56. doi: 10.1038/s41591-018-0300-7. PubMed PMID: 30617339.
  15. Lin HL, Wang YC, Huang ML, Yu NW, Tang I, Hsu YC, Huang YS. Can virtual reality technology be used for empathy education in medical students: a randomized case-control study. BMC Med Educ. 2024;24(1):1254. doi: 10.1186/s12909-024-06009-6. PubMed PMID: 39497110; PubMed Central PMCID: PMC11536554.
Interdisciplinary Journal of Virtual Learning in Medical Sciences
Volume 16, Issue 3 - Serial Number 62
September 2025
Pages 323-326

Files

History

  • Receive Date: 15 September 2025
  • Revise Date: 20 September 2025
  • Accept Date: 21 September 2025
  • Publish Date: 01 September 2025

Share

How to cite

Statistics