Evaluating the efficacy of chatGPT in near-peer simulation for resident doctors in the emergency department

https://doi.org/10.53730/ijhs.v7nS1.14367

Authors

  • Jerry Jacob Senior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Roger Shannon D'souza Senior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Shruthi Deshpande Senior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Harikrishna Yamjala Senior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Chandrakeerthy D M Junior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Hanumesh H V Junior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Rahul Jain Junior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore
  • Shivani Vhora Junior Resident, Department of Emergency Medicine, Ramaiah Medical College, Bangalore

Keywords:

medical education, ChatGPT, AI, near-peer simulation

Abstract

Introduction: Near-peer teaching is gaining popularity as a newer teaching tool, as it improves the learner’s comprehension, targets the right audience and promotes familiarity with the clinical situation and enhances critical thinking.(1) This study was initiated to evaluate the efficacy of chatGPT in near-peer simulation using AI-enabled scenarios in the residency training programme of an emergency department. (2) Methods: ChatGPT an LLM was asked to generate clinical scenarios as per prompts given to evaluate its efficacy in generating real-time and realistic scenarios with information on stepwise approach and critical treatment decisions for the patient. Results: In our study, ChatGPT was able to successfully generate real-time and realistic scenarios based on the prompts given with detailed treatment approaches and critical decisions for all patients/scenarios given, serving as a successful tool to consider in near-peer education using simulation enabled by AI. CONCLUSION: Near-peer simulation training was found to be a valuable method of teaching residents for increasing hands-on experience, skill assessment, confidence in diagnosis and practical thinking. Integration of AI into near-peer simulations aids in creating a wider range of scenarios with prompt treatment decisions. 

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References

Lateef F. Simulation-based learning:just like the real thing. J Emerg Trauma Shock. 2010;3:348–52. [PMC free article] [PubMed] [Google Scholar]

Ogden PE, Cobbs LS, Howell MR, Sibbitt SJ, DiPette DJ. Clinical simulation:importance to the internal medicine educational mission. Am J Med. 2007;120:820–4. [PubMed] [Google Scholar]

Gordon JA, Oriol NE, Cooper JB. Bringing good teaching cases “to life“:a simulator-based medical education service. Acad Med. 2004;79:23–7. [PubMed] [Google Scholar]

Pothiawala S, Lateef F. Simulation training in emergency medicine (STEM):an integral component of residency curriculum. Hong Kong J Emerg Med. 2012;19:41–5. [Google Scholar]

Kneebone RL, Scott W, Darzi A, Horrocks M. Simulation and clinical practice:strengthening the relationship. Med Educ. 2004;38:1095–102. [PubMed] [Google Scholar]

McLaughlin SA, Doezema D, Sklar DP. Human simulation in emergency medicine training:a model curriculum. Acad Emerg Med. 2002;9:1310–8. [PubMed] [Google Scholar]

McMahon GT, Monaghan C, Falchuk K, Gordon JA, Alexander EK. A simulator-based curriculum to promote comparative and reflective analysis in an internal medicine clerkship. Acad Med. 2005;80:84–9. [PubMed] [Google Scholar]

Vozenilek J, Huff JS, Reznek M, Gordon JA. See one, do one, teach one:advanced technology in medical education. Acad Emerg Med. 2004;11:1149–54. [PubMed] [Google Scholar]

Ten Cate O, Durning S. Peer teaching in medical education:twelve reasons to move from theory to practice. Med Teach. 2007;29:591–9. [PubMed] [Google Scholar]

Burgess A, McGregor D, Mellis C. Medical students as peer tutors:a systematic review. BMC Med Educ. 2014;14:115. [PMC free article] [PubMed] [Google Scholar]

Yu TC, Wilson NC, Singh PP, et al. Medical students-as-teachers:a systematic review of peer-assisted teaching during medical school. Adv Med Educ Pract. 2011;2:157–72. [PMC free article] [PubMed] [Google Scholar]

Bulte C, Betts A, Garner K, Durning S. Student teaching:views of student near-peer teachers and learners. Med Teach. 2007;29:583–90. [PubMed] [Google Scholar]

Ross MT, Cameron HS. Peer assisted learning:a planning and implementation framework:AMEE Guide no. 30. Med Teach. 2007;29:527–45. [PubMed] [Google Scholar]

Lockspeiser TM, O'Sullivan P, Teherani A, Muller J. Understanding the experience of being taught by peers:the value of social and cognitive congruence. Adv Health Sci Educ Theory Pract. 2008;13:361–72. [PubMed] [Google Scholar]

Schmidt HG, Moust JH. What makes a tutor effective?A structural-equations modeling approach to learning in problem-based curricula. Acad Med. 1995;70:708–14. [PubMed] [Google Scholar]

Cash T, Brand E, Wong E, et al. Near-peer medical student simulation training. Clin Teach. 2017;14:175–9. [PubMed] [Google Scholar]

Published

29-06-2023

How to Cite

Jacob, J., D’souza, R. S., Deshpande, S. ., Yamjala, H., Chandrakeerthy, D. M., Hanumesh, H. V., Jain, R., & Vhora, S. (2023). Evaluating the efficacy of chatGPT in near-peer simulation for resident doctors in the emergency department. International Journal of Health Sciences, 7(S1), 1780–1789. https://doi.org/10.53730/ijhs.v7nS1.14367

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Peer Review Articles

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