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Catering for the Needs of Diverse Patient Populations: Using ChatGPT to Design Case-Based Learning Scenarios

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Abstract

Artificial intelligence (AI) represents an opportunity for medical education to enhance efficiency, interactivity, and realism in learning scenarios. This project uses it to identify angles we have not considered before, particularly in creating culturally sensitive educational cases that represent the needs of a diverse patient population. The implementation showed encouraging results, as the ChatGPT algorithm was successful in writing cases that are more culturally sensitive; however, iteration for refinement was needed. An evolution of these prompts and resulting cases are presented. AI-generated material is only as good as the prompts we use, and how we define the task depends on digital literacy and pedagogical intent.

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References

  1. Brottman MR, Char DM, Hattori RA, Heeb R, Taff SD. Toward cultural competency in health care: a scoping review of the diversity and inclusion education literature. Acad Med. 2020;95:803–13. https://doi.org/10.1097/ACM.0000000000002995.

    Article  Google Scholar 

  2. Roberts LW. Belonging, respectful inclusion, and diversity in medical education. Acad Med. 2020;95:661–4. https://doi.org/10.1097/ACM.0000000000003215.

    Article  Google Scholar 

  3. Zanting A, Meershoek A, Frambach JM, Krumeich A. The ‘exotic other’ in medical curricula: rethinking cultural diversity in course manuals. Med Teach. 2020;42:791–8. https://doi.org/10.1080/0142159X.2020.1736534.

    Article  Google Scholar 

  4. Kaundinya T, Kundu RV. Diversity of skin images in medical texts: recommendations for student advocacy in medical education. J Med Educ Curric Dev. 2021;8:1–3. https://doi.org/10.1177/23821205211025855.

    Article  Google Scholar 

  5. Buery-Joyner SD, Baecher-Lind L, Clare CA, Hampton S, Moxley MD, Ogunyemi D, Pradhan AA, Madani Sims SM, Whetstone S, Woodland MB, Katz NT. Educational guidelines for diversity and inclusion: addressing racism and eliminating biases in medical education. Am J Obstet Gynecol. 2023;228:133–9. https://doi.org/10.1016/j.ajog.2022.09.014.

    Article  Google Scholar 

  6. Hawthorne K, Prout H, Kinnersley P, Houston H. Evaluation of different delivery modes of an interactive e-learning programme for teaching cultural diversity. Patient Educ Couns. 2009;74:5–11. https://doi.org/10.1016/j.pec.2008.07.056.

    Article  Google Scholar 

  7. Masters K. Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Med Teach. 2023;45:574–84. https://doi.org/10.1080/0142159X.2023.2186203.

    Article  Google Scholar 

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Authors and Affiliations

  1. Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Eugenio Garza Sada 2501 Sur. Col Tecnologico, Monterrey, 64710, Mexico

    Mildred Lopez

  2. Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore

    Poh-Sun Goh

Authors
  1. Mildred Lopez
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  2. Poh-Sun Goh
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Correspondence to Mildred Lopez.

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The procedures performed in this innovation did not involve human participants, and no ethics committee approval was required.

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The authors declare no competing interests.

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Lopez, M., Goh, PS. Catering for the Needs of Diverse Patient Populations: Using ChatGPT to Design Case-Based Learning Scenarios. Med.Sci.Educ. 34, 319–325 (2024). https://doi.org/10.1007/s40670-024-01975-4

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  • DOI: https://doi.org/10.1007/s40670-024-01975-4

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