Resumen
Este estudio analizó el riesgo psicosocial y el agotamiento profesional en 458 trabajadores universitarios mediante ecuaciones estructurales y simulación de escenarios. La sobrecarga presentó el mayor efecto total sobre el agotamiento, mientras que el estrés percibido actuó como mecanismo mediador relevante. La resiliencia redujo el estrés y amortiguó su relación con el agotamiento, sin sustituir el efecto de las condiciones organizacionales. Las simulaciones mostraron que reducir el estrés y reducir el agotamiento no producen necesariamente respuestas equivalentes. Los escenarios organizacionales amplios generaron mayores disminuciones esperadas del agotamiento, mientras que las estrategias combinadas optimizaron principalmente la reducción del estrés laboral esperado.
Citas
[1] C. Di Tecco, B. Persechino, and S. Iavicoli, “Psychosocial risks in the changing world of work: Moving from the risk assessment culture to the management of opportunities,” La Medicina del Lavoro, vol. 114, no. 2, Art. no. e2023013, 2023, doi: 10.23749/mdl.v114i2.14362.
[2] I. do Nascimento Teixeira, I. S. Silva, and I. M. D. Cadime, “Psychosocial risks at work: Integrative review and conceptual perspectives,” Revista Brasileira de Medicina do Trabalho, vol. 23, no. 2, Art. no. e20251464, 2025.
[3] C. Maslach, W. B. Schaufeli, and M. P. Leiter, “Job burnout,” Annual Review of Psychology, vol. 52, pp. 397–422, 2001, doi: 10.1146/annurev.psych.52.1.397.
[4] M. P. Leiter and C. Maslach, “Six areas of worklife: A model of the organizational context of burnout,” Journal of Health and Human Services Administration, vol. 21, no. 4, pp. 472–489, 1999.
[5] S. S. Brom, G. Buruck, I. Horváth, P. Richter, and M. P. Leiter, “Areas of worklife as predictors of occupational health—A validation study in two German samples,” Burnout Research, vol. 2, nos. 2–3, pp. 60–70, 2015, doi: 10.1016/j.burn.2015.05.001.
[6] P. Jimenez and A. Dunkl, “The buffering effect of workplace resources on the relationship between the areas of worklife and burnout,” Frontiers in Psychology, vol. 8, Art. no. 12, 2017, doi: 10.3389/fpsyg.2017.00012.
[7] S. Cohen, T. Kamarck, and R. Mermelstein, “A global measure of perceived stress,” Journal of Health and Social Behavior, vol. 24, no. 4, pp. 385–396, 1983, doi: 10.2307/2136404.
[8] K. M. Connor and J. R. T. Davidson, “Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC),” Depression and Anxiety, vol. 18, no. 2, pp. 76–82, 2003, doi: 10.1002/da.10113.
[9] L. Campbell-Sills and M. B. Stein, “Psychometric analysis and refinement of the Connor-Davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience,” Journal of Traumatic Stress, vol. 20, no. 6, pp. 1019–1028, 2007, doi: 10.1002/jts.20271.
[10] A. Asensio-Martínez and A. Aguilar-Latorre, “Psychosocial and Occupational Predictors of Health Among Spanish University Employees: The Role of Job Type, Contract Status, and Seniority,” Zenodo, dataset, 2025, doi: 10.5281/zenodo.17662702.
[11] Á. Asensio-Martínez, A. Aguilar-Latorre, B. Masluk, S. León-Herrera, R. Sánchez Recio, and B. Oliván-Blázquez, “Psychosocial and occupational predictors of health among Spanish University Employees: The role of job type, contract status, and seniority,” PLoS ONE, vol. 21, no. 2, Art. no. e0339726, 2026, doi: 10.1371/journal.pone.0339726.
Esta es imprescindible. Es el artículo científico publicado en 2026 a partir de la misma población de 458 trabajadores y documenta estrés percibido, burnout, resiliencia y áreas de la vida laboral.
[12] B. R. García-Rivera, I. A. Mendoza-Martínez, J. L. García-Alcaraz, J. E. Olguín-Tiznado, C. Camargo Wilson, M. F. Araníbar, and P. García-Alcaraz, “Influence of resilience on burnout syndrome of faculty professors,” International Journal of Environmental Research and Public Health, vol. 19, no. 2, Art. no. 910, 2022, doi: 10.3390/ijerph19020910.
Muy buena para nosotros porque estudia precisamente profesores universitarios, resiliencia, burnout y SEM con variables latentes.
[13] S. T. Innstrand, C. Banks, C. Maslach, and C. Lowenstein, “Healthy universities: Exploring the relationship between psychosocial needs and work-related health among university employees,” Journal of Workplace Behavioral Health, vol. 38, no. 2, pp. 103–126, 2023, doi: 10.1080/15555240.2023.2194026.
Esta me gusta muchísimo para nuestra discusión: usa SEM en 11.533 empleados universitarios y relaciona condiciones psicosociales con salud laboral.
[14] Y. Wang and D. M. H. Kee, “Research on the antecedents of burnout syndrome in researchers at public universities in China: A PLS-SEM approach,” IJERI: International Journal of Educational Research and Innovation, no. 23, pp. 1–13, 2025, doi: 10.46661/ijeri.10885.
Muy específica: personal académico universitario + condiciones psicosociales + burnout + SEM.
[15] H. Niknampour, “Structural equation modeling of burnout, support, and retention among higher-education music faculty through Job Demands-Resources framework and Self-Determination Theory,” Psychology of Music, OnlineFirst, 2026, doi: 10.1177/03057356261473901.
Esta está recién publicada, el 22 de agosto de 2026. Usa SEM en profesores de educación superior y encuentra relaciones entre carga laboral, apoyo institucional y burnout. Es excelente como referencia contemporánea.
[16] M. Debets, R. Scheepers, M. Silkens, and K. Lombarts, “Structural equation modelling analysis on relationships of job demands and resources with work engagement, burnout and work ability: An observational study among physicians in Dutch hospitals,” BMJ Open, vol. 12, no. 12, Art. no. e062603, 2022, doi: 10.1136/bmjopen-2022-062603.
[17] L. K. Muthén and B. O. Muthén, “How to use a Monte Carlo study to decide on sample size and determine power,” Structural Equation Modeling: A Multidisciplinary Journal, vol. 9, no. 4, pp. 599–620, 2002, doi: 10.1207/S15328007SEM0904_8.
[18] E. J. Wolf, K. M. Harrington, S. L. Clark, and M. W. Miller, “Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety,” Educational and Psychological Measurement, vol. 73, no. 6, pp. 913–934, 2013, doi: 10.1177/0013164413495237.
[19] K. J. Preacher and J. P. Selig, “Advantages of Monte Carlo confidence intervals for indirect effects,” Communication Methods and Measures, vol. 6, no. 2, pp. 77–98, 2012, doi: 10.1080/19312458.2012.679848.
[20] D. Tofighi and D. P. MacKinnon, “Monte Carlo confidence intervals for complex functions of indirect effects,” Structural Equation Modeling: A Multidisciplinary Journal, vol. 23, no. 2, pp. 194–205, 2016, doi: 10.1080/10705511.2015.1057284.
[2] I. do Nascimento Teixeira, I. S. Silva, and I. M. D. Cadime, “Psychosocial risks at work: Integrative review and conceptual perspectives,” Revista Brasileira de Medicina do Trabalho, vol. 23, no. 2, Art. no. e20251464, 2025.
[3] C. Maslach, W. B. Schaufeli, and M. P. Leiter, “Job burnout,” Annual Review of Psychology, vol. 52, pp. 397–422, 2001, doi: 10.1146/annurev.psych.52.1.397.
[4] M. P. Leiter and C. Maslach, “Six areas of worklife: A model of the organizational context of burnout,” Journal of Health and Human Services Administration, vol. 21, no. 4, pp. 472–489, 1999.
[5] S. S. Brom, G. Buruck, I. Horváth, P. Richter, and M. P. Leiter, “Areas of worklife as predictors of occupational health—A validation study in two German samples,” Burnout Research, vol. 2, nos. 2–3, pp. 60–70, 2015, doi: 10.1016/j.burn.2015.05.001.
[6] P. Jimenez and A. Dunkl, “The buffering effect of workplace resources on the relationship between the areas of worklife and burnout,” Frontiers in Psychology, vol. 8, Art. no. 12, 2017, doi: 10.3389/fpsyg.2017.00012.
[7] S. Cohen, T. Kamarck, and R. Mermelstein, “A global measure of perceived stress,” Journal of Health and Social Behavior, vol. 24, no. 4, pp. 385–396, 1983, doi: 10.2307/2136404.
[8] K. M. Connor and J. R. T. Davidson, “Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC),” Depression and Anxiety, vol. 18, no. 2, pp. 76–82, 2003, doi: 10.1002/da.10113.
[9] L. Campbell-Sills and M. B. Stein, “Psychometric analysis and refinement of the Connor-Davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience,” Journal of Traumatic Stress, vol. 20, no. 6, pp. 1019–1028, 2007, doi: 10.1002/jts.20271.
[10] A. Asensio-Martínez and A. Aguilar-Latorre, “Psychosocial and Occupational Predictors of Health Among Spanish University Employees: The Role of Job Type, Contract Status, and Seniority,” Zenodo, dataset, 2025, doi: 10.5281/zenodo.17662702.
[11] Á. Asensio-Martínez, A. Aguilar-Latorre, B. Masluk, S. León-Herrera, R. Sánchez Recio, and B. Oliván-Blázquez, “Psychosocial and occupational predictors of health among Spanish University Employees: The role of job type, contract status, and seniority,” PLoS ONE, vol. 21, no. 2, Art. no. e0339726, 2026, doi: 10.1371/journal.pone.0339726.
Esta es imprescindible. Es el artículo científico publicado en 2026 a partir de la misma población de 458 trabajadores y documenta estrés percibido, burnout, resiliencia y áreas de la vida laboral.
[12] B. R. García-Rivera, I. A. Mendoza-Martínez, J. L. García-Alcaraz, J. E. Olguín-Tiznado, C. Camargo Wilson, M. F. Araníbar, and P. García-Alcaraz, “Influence of resilience on burnout syndrome of faculty professors,” International Journal of Environmental Research and Public Health, vol. 19, no. 2, Art. no. 910, 2022, doi: 10.3390/ijerph19020910.
Muy buena para nosotros porque estudia precisamente profesores universitarios, resiliencia, burnout y SEM con variables latentes.
[13] S. T. Innstrand, C. Banks, C. Maslach, and C. Lowenstein, “Healthy universities: Exploring the relationship between psychosocial needs and work-related health among university employees,” Journal of Workplace Behavioral Health, vol. 38, no. 2, pp. 103–126, 2023, doi: 10.1080/15555240.2023.2194026.
Esta me gusta muchísimo para nuestra discusión: usa SEM en 11.533 empleados universitarios y relaciona condiciones psicosociales con salud laboral.
[14] Y. Wang and D. M. H. Kee, “Research on the antecedents of burnout syndrome in researchers at public universities in China: A PLS-SEM approach,” IJERI: International Journal of Educational Research and Innovation, no. 23, pp. 1–13, 2025, doi: 10.46661/ijeri.10885.
Muy específica: personal académico universitario + condiciones psicosociales + burnout + SEM.
[15] H. Niknampour, “Structural equation modeling of burnout, support, and retention among higher-education music faculty through Job Demands-Resources framework and Self-Determination Theory,” Psychology of Music, OnlineFirst, 2026, doi: 10.1177/03057356261473901.
Esta está recién publicada, el 22 de agosto de 2026. Usa SEM en profesores de educación superior y encuentra relaciones entre carga laboral, apoyo institucional y burnout. Es excelente como referencia contemporánea.
[16] M. Debets, R. Scheepers, M. Silkens, and K. Lombarts, “Structural equation modelling analysis on relationships of job demands and resources with work engagement, burnout and work ability: An observational study among physicians in Dutch hospitals,” BMJ Open, vol. 12, no. 12, Art. no. e062603, 2022, doi: 10.1136/bmjopen-2022-062603.
[17] L. K. Muthén and B. O. Muthén, “How to use a Monte Carlo study to decide on sample size and determine power,” Structural Equation Modeling: A Multidisciplinary Journal, vol. 9, no. 4, pp. 599–620, 2002, doi: 10.1207/S15328007SEM0904_8.
[18] E. J. Wolf, K. M. Harrington, S. L. Clark, and M. W. Miller, “Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety,” Educational and Psychological Measurement, vol. 73, no. 6, pp. 913–934, 2013, doi: 10.1177/0013164413495237.
[19] K. J. Preacher and J. P. Selig, “Advantages of Monte Carlo confidence intervals for indirect effects,” Communication Methods and Measures, vol. 6, no. 2, pp. 77–98, 2012, doi: 10.1080/19312458.2012.679848.
[20] D. Tofighi and D. P. MacKinnon, “Monte Carlo confidence intervals for complex functions of indirect effects,” Structural Equation Modeling: A Multidisciplinary Journal, vol. 23, no. 2, pp. 194–205, 2016, doi: 10.1080/10705511.2015.1057284.
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