Resident Early Attrition in Residents Medical Training.
DOI:
https://doi.org/10.70577/ar52f463Palabras clave:
Attrition, Medical Residents, Educative Impact, Vocational IssueResumen
Resident attrition is a growing concern in medical education systems worldwide. This article analyzes key personal, institutional, economic, and vocational factors associated with early departure from residency training programs. A structured narrative review of studies published between 2000 and 2025 was performed. A structured narrative review was conducted using PubMed, Scopus, SciELO, and Google Scholar. Additional analytical tools were used, including heatmaps, interaction matrices, influence diagrams, and a multivariate AI‑based predictive model. Five residents who had entered one of thirteen medical specialties at a general hospital belonging to the Mexican Ministry of Health, in the city of León, located in central Mexico, were interviewed within the first 15 days after voluntarily requesting . open-ended interview. The interviews were conducted by the medical coordination and for teaching and research. Three were from Internal Medicine, one from Geriatrics, and one from General Surgery. The average age was 26 ± 1 years. In Internal Medicine, three men indicated that they were married and could not afford a study abroad program; the other was single, which was also the reason for his withdrawal literature review Findings demonstrate that burnout, excessive workload, vocational mismatch, institutional mistreatment, and socioeconomic pressures significantly predict attrition risk. A predictive model based on artificial intelligence is proposed to identify high‑risk residents. Strengthening well‑being programs, improving structural working conditions, and integrating vocational assessment into specialty selection may reduce early attrition.
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1. Yao DC, Wright SM. The challenge of problem residents. Med Teach. 2001;23(6):595–9.
2. Dyrbye LN, Shanafelt TD. Resident burnout and early attrition. JAMA. 2016;315(3):25–40.
3. West CP, Dyrbye LN, Shanafelt TD. Physician burnout. Lancet. 2018;392:101–12.
4. IsHak WW et al. Burnout during residency training. J Grad Med Educ. 2017;9(2):165–79.
5. McKinley SK et al. Attrition in general surgery. JAMA Surg. 2021;156(12):e214278. DOI: https://doi.org/10.1001/jamasurg.2020.4481
6. Giffin BK et al. Surgical residency attrition. Ann Surg. 2020;272(6):1076–82.
7. Shapiro J. Attrition in medical training. Acad Med. 2019;94(9):1332–8.
8. Goldberg R et al. Resilience and attrition. Acad Psychiatry. 2017;41:174–82.
9. Graham M et al. Specialty mismatch. Med Educ. 2019;53(4):379–88.
10. Stewart EA et al. Early resignation predictors. BMC Med Educ. 2020;20:130.
11. Leisy H. Problem residents. Perm J. 2016;20(4):15–233.
12. Rosenstein AH. Communication and attrition. J Hosp Admin. 2015;4:1–12.
13. Shanafelt TD et al. Physician well‑being. Mayo Clin Proc. 2019;94:2020–34.
14. Gutiérrez Salazar M et al. Burnout among Mexican residents. Rev Med IMSS. 2019;57:163–9.
15. Martínez‑Ponce G et al. Burnout in surgical residents in Mexico. Cir Cir. 2015;83:193–9.
16. Pérez‑Cuevas R et al. Work factors and attrition. Salud Publica Mex. 2010;52:129–38.
17. López‑Medina LM et al. Resignation intent in residents. Rev Med IMSS. 2020;58:78–86.
18. Padilla‑Rosas M et al. Mistreatment in training. Gac Med Mex. 2018;154:178–84.
19. Gutiérrez‑González R et al. Cultural mismatch in residents. Educ Med. 2020;21:76–82.
20. Sánchez‑Mendiola M, Martínez‑Frías ML. Early attrition in Mexican medical education. Invest Educ Med. 2015;4:4–12.
21. Wasserman MA. A Strategy to Reduce General Surgery Resident Attrition: A Resident’s Perspective. JAMA Surg. 2016;151(3):215–216. doi:10.1001/jamasurg.2015.4607 DOI: https://doi.org/10.1001/jamasurg.2015.4607
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Derechos de autor 2025 Antonio Eugenio Rivera Cisneros, Pablo Julián Medina Sánchez, Jorge Manuel Sánchez González, Jorge Horacio Portillo Gallo, María Cristina Morán Moguel (Autor/a)

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