Reflections of Simulation-Based Education on the National Core Curriculum of Turkey: A Content Analysis

Year 2025, Volume: 6 Issue: 1, 37 - 45, 31.01.2025

Bilge Delibalta , Muhammet Eyyüp Delibalta

https://doi.org/10.47482/acmr.1588192

Cited By: 1

https://izlik.org/JA67WA78XE

Abstract

Background: Simulation-based education prepares medical students to interact with real patients by resembling real environments. There are a variety of methods in simulation-based education from low-fidelity to high-fidelity, and from basic task trainers to complicated mixed methods. Although it is not specified whether a topic in the national core curriculum is related to simulation-based education or not, the National Core Curriculum draws a general approach for selecting appropriate learning activities in undergraduate medical education. This study aims to reveal adequate simulation methods for the topics in the National Core Curriculum and to present a tool for simulation method selection criteria.
Method: A content analysis was conducted in a qualitative design. The literature review was conducted to deeply understand the principles of simulation-based education and was used as a guide to evaluate the topics in the National Core Curriculum. The content analysis of the National Core Curriculum-2020 was performed to structure a tool for the simulation method selection criteria in undergraduate medical education.
Results: Several simulation methods can be used according to the utilization of medical schools. A total of 20 number main skills were identified as suitable for simulation-based education and methods were matched with these skills with at least three alternatives.
Conclusion: The tool we conducted covers basic to complicated simulation methods that every medical school can adopt according to its facilities. We recommend our tool as a guide in selecting adequate resources while developing simulation-based education in undergraduate medical education.

Keywords

simulation-based education , medical education , medical school

Simülasyona Dayalı Eğitimin Türkiye Çekirdek Eğitim Programı Üzerindeki Yansımaları: İçerik analizi

https://izlik.org/JA67WA78XE

Abstract

Arka plan: Simülasyona dayalı eğitim, gerçeğe yakın ortamlar oluşturarak tıp öğrencilerini gerçek hastalarla etkileşime girmeye hazırlar. Simülasyona dayalı eğitimde düşük gerçeklikten yüksek gerçekliğe, basit maketlerden karmaşık yöntemlere kadar çeşitli yöntemler bulunmaktadır. Ulusal Çekirdek Eğitim Programında yer alan bir konunun simülasyona dayalı eğitimle ilgili olup olmadığı belirtilmemiş olsa da Ulusal Çekirdek Eğitim Programı, mezuniyet öncesi tıp eğitiminde uygun öğrenme etkinliklerinin seçilmesine yönelik genel bir yaklaşım çizmektedir. Bu çalışma, Ulusal Çekirdek Eğitim Programındaki konulara uygun simülasyon yöntemlerini ortaya çıkarmayı ve simülasyon yöntemi seçim kriterleri için bir araç sunmayı amaçlamaktadır.
Yöntem: Nitel desende içerik analizi yapılmıştır. Literatür taraması simülasyona dayalı eğitimin ilkelerini derinlemesine anlamak için yapılmış ve Ulusal Çekirdek Eğitim Programındaki konuların değerlendirilmesinde bir rehber olarak kullanılmıştır. Mezuniyet öncesi tıp eğitiminde simülasyon yöntemi seçim kriterlerine yönelik bir araç yapılandırmak amacıyla Ulusal Çekirdek Müfredat-2020'nin içerik analizi yapılmıştır.
Bulgular: Tıp fakültelerinin imkanlarına göre çeşitli simülasyon yöntemleri kullanılabilir. Toplamda 20 adet temel beceri simülasyon temelli eğitime uygun olarak belirlenmiş ve yöntemler bu becerilerle en az üç alternatifle eşleştirilmiştir.
Sonuç: Yaptığımız araç, her tıp fakültesinin imkanlarına göre benimseyebileceği temelden ileri düzey simülasyon yöntemlerini kapsamaktadır. Mezuniyet öncesi tıp eğitiminde simülasyona dayalı eğitimin geliştirilmesinde uygun kaynakların seçilmesinde çalışmamızı bir rehber olarak önermekteyiz.

Keywords

simülasyona dayalı eğitim , tıp eğitimi , tıp fakültesi

References

• 1. Motola I, Devine LA, Chung HS, Sullivan JE, Issenberg SB. Simulation in healthcare education: a best evidence practical guide. AMEE Guide No. 82. Med Teach. 2013;35(10):e1511-30.
• 2. Popov V, Mateju N, Jeske C, Lewis KO. Metaverse-based simulation: a scoping review of charting medical education over the last two decades in the lens of the 'marvelous medical education machine'. Ann Med. 2024;56(1):2424450.
• 3. Elçin M. Simulation Practices in Undergraduate Medical Education. Turkiye Klinikleri J Med Educ-Special Topics. 2017;2(2):57-64.
• 4. Varghese A, Kumar H, Kathrotia R, Uniyal M, Rao S. High-fidelity, indigenously prepared, low-cost moulage as a valid simulation tool to improve trauma education. Cureus J Med Scie. 2024;16(4).
• 5. Behrens CC, Dolmans DH, Driessen EW, Gormley GJ. 'Dancing with emotions': An Interpretive Descriptive study of facilitators recognition and response to students' emotions during simulation. Med Educ. 2024. Epub 20241012.
• 6. Sochan AJ, Delaney KM, Aggarwal P, Brun A, Popick L, Cardozo-Stolberg S, et al. Closing the trauma performance improvement loop with in-situ simulation. J Surg Res. 2024;302:876-82.
• 7. Pawlowicz E, Kulesza M, Szymanska A, Masajtis-Zagajewska A, Bartczak M, Nowicki M. 'I hear and I forget. I see and I remember. I do and I understand.'- incorporating high-fidelity medical simulation into the undergraduate nephrology course. Renal Failure. 2020;42(1):1184-91.
• 8. El Hussein MT, Hirst SP. High-fidelity simulation's impact on clinical reasoning and patient safety: A scoping review. J Nurs Regul. 2023;13(4):54-65.
• 9. Zheng JJ, Lapu R, Khalid H. Integrating high-fidelity simulation into a medical cardiovascular physiology curriculum. Adv Med Educ Pract. 2020;11:41-50.
• 10. Barry Issenberg S, McGaghie WC, Petrusa ER, Lee Gordon D, Scalese RJ. Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach. 2005;27(1):10-28.
• 11. Almousa O, Zhang R, Dimma M, Yao JM, Allen A, Chen L, et al. Virtual Reality Technology and Remote Digital Application for Tele-Simulation and Global Medical Education: An Innovative Hybrid System for Clinical Training. Simul & Gaming. 2021;52(5):614-34.
• 12. Doyle AJ, Sullivan C, O'Toole M, Tjin A, Simiceva A, Collins N, et al. Training simulated participants for role portrayal and feedback practices in communication skills training: A BEME scoping review: BEME Guide No. 86. Med Teach. 2024;46(2):162-78.
• 13. Delibalta B, Güner Y, Üçüncüoğlu M, Duman Dilbaz A, Akturan S, Elçin M. Effect of the community of simulated participant model on the identity formation of simulated participants: A qualitative study. J Adult Continuing Educ. 2024:14779714241292186.
• 14. Blanie A, Shoaleh C, Marquion F, Benhamou D. Comparison of multimodal active learning and single-modality procedural simulation for central venous catheter insertion for incoming residents in anesthesiology: a prospective and randomized study. BMC Med Educ. 2022;22(1).
• 15. Chawla V, Aggarwal R, Goyal K, Sokhal N, Shetty G, Sharma AK, et al. Implementing a nationwide simulation-based training program in managing sick surgical patients. Indian J Surg. 2023;85(6):1374-83.
• 16. De Bernardo G, Riccitelli M, Giordano M, Toni AL, Sordino D, Trevisanuto D, et al. Does high fidelity neonatal resuscitation simulation increase salivary cortisol levels of health care providers? Minerva Pediatr. 2023;75(6):884-9.
• 17. Zeng Q, Wang K, Liu WX, Zeng JZ, Li XL, Zhang QF, et al. Efficacy of high-fidelity simulation in advanced life support training: a systematic review and meta-analysis of randomized controlled trials. BMC Med Educ. 2023;23(1).
• 18. Sumner E, Craig C, Coleman J, Kumi H, Scott H. Low-fidelity simulation for management of postpartum haemorrhage in a Ghanaian teaching hospital. Afr J Reprod Health. 2022;26(4):57-64.
• 19. Sao Pedro T, Mtaweh H, Mema B. More is not always better in simulation learners' evaluation of a "Chest Model". Ats Schol. 2021;2(1):124-33.
• 20. Geary AD, Pernar LIM, Hall JF. Novel low-cost, low-fidelity hemorrhoidectomy task trainers. J Surg Educ. 2020;77(5):1285-8.
• 21. Schlegel L, Malani E, Belko S, Kumar A, Barbarite E, Krein H, et al. Design, printing optimization, and material testing of a 3D-printed nasal osteotomy task trainer. 3D Print Med. 2023;9(1).
• 22. Chen WH, Radzi S, Chiu L, Yeong WY, Mogali SR. Development of a 3-dimensional printed tube thoracostomy task trainer: An improved methodology. Asia Pacific Schol. 2021;6(1):109-13.
• 23. Zaidi SSB, Adnan U, Lewis KO, Fatima SS. Metaverse-powered basic sciences medical education: bridging the gaps for lower middle-income countries. Ann Med. 2024;56(1):2356637.
• 24. Brown N, Margus C, Hart A, Sarin R, Hertelendy A, Ciottone G. Virtual reality training in disaster medicine a systematic review of the literature. Simul Healthc. 2023;18(4):255-61.
• 25. Wan T, Liu K, Li B, Wang XD. Validity of an immersive virtual reality training system for orthognathic surgical education. Front Pediatr. 2023;11.
• 26. de Lotbiniere-Bassett M, Batista AV, Lai C, El Chemaly T, Dort J, Blevins N, et al. The user experience design of a novel microscope within SurgiSim, a virtual reality surgical simulator. Int J Comput Assist Radiol Surg. 2023;18(1):85-93.
• 27. Le Lous M, Simon O, Lassel L, Lavoue V, Jannin P. Hybrid simulation for obstetrics training: A systematic review. Eur J Obstet Gynecol Reprod Biol. 2020;246:23-8.
• 28. Lv MR, Jia YJ, Zong ZW, Jiang RQ, Du WQ, Zhang L, et al. Method for Teaching Life-Saving Combat First-Aid Skills With live-actor Patients Using a Wearable Training Apparatus. Military Med. 2022;187(5-6):757-63.
• 29. Brown WJ, Tortorella RAW. Hybrid medical simulation - a systematic literature review. Smart Learn Environ. 2020;7(1).
• 30. Zackoff MW, Davis D, Rios M, Sahay RD, Zhang B, Anderson I, et al. Tolerability and Acceptability of Autonomous Immersive Virtual Reality Incorporating Digital Twin Technology for Mass Training in Healthcare. Simul Healthc. 2024;19(5):e99-e116.
• 31. Pedram S, Kennedy G, Sanzone S. Assessing the validity of VR as a training tool for medical students. Virtual Real. 2024;28(1).
• 32. Malone M, Way DP, Leung CG, Danforth D, Maicher K, Vakil J, et al. Evaluation of high-fidelity and virtual reality simulation platforms for assessing fourth-year medical students' encounters with patients in need of urgent or emergent care. Ann Med. 2024;56(1).
• 33. Leung RWK, Shi G, Lim CA, Van Oirschot M, editors. Automating creation of high-fidelity holographic hand animations for surgical skills training using mixed reality headsets. Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions, and Modeling; 2024 Feb 19-22; San Diego, CA2024.
• 34. Farcas M, Reynolds LF, Lee JY. Simulation-based percutaneous renal access training: evaluating a novel 3D immersive virtual reality platform. J Endourol. 2021;35(5):695-9.
• 35. Otero-Varela L, Cintora AM, Espinosa S, Redondo M, Uzuriaga M, González M, et al. Extended reality as a training method for medical first responders in mass casualty incidents: A protocol for a systematic review. Plos One. 2023;18(3).
• 36. Mitchell AA, Ivimey-Cook ER. Technology-enhanced simulation for healthcare professionals: A meta-analysis. Front Med. 2023;10.
• 37. Loeb D, Shoemaker J, Parsons A, Schumacher D, Zackoff M. How augmenting reality changes the reality of simulation: ethnographic analysis. Jmir Med Educ. 2023;9. 38. Ulusal Cep-2020 UCG, Ulusal Cep-2020 UYVYCG, Ulusal Cep-2020 DSBBCG. Medical Faculty - National Core Curriculum 2020. TED. 2020;19(57 - 1):1-146. 39. Cleland J, Durning SJ. Researching medical education: John Wiley & Sons; 2022. 40. Carey JM, Rossler K. The How When Why of High Fidelity Simulation. StatPearls. Treasure Island (FL): StatPearls Publishing LLC.; 2024.