Burnout académico y aceptación tecnológica en universitarios
Abstract
El estudio parte desde la identificación de agotamiento al realizar trabajos académicos con el uso de tecnologías acopladas a la educación superior; de ahí, el objetivo fue medir la relación entre los índices de burnout académico y el modelo de aceptación tecnológica en estudiantes universitarios. Para ello, se utiliza el enfoque cuantitativo, con análisis correlacional, aplicando encuesta a 374 estudiantes con el instrumento que fusiona el cuestionario de Maslach Burnout Inventory – Student Survey y el de Aceptación Tecnológica, validados mediante Alfa de Cronbach. Los resultados de la correlación de Spearman revelaron una relación positiva entre las variables, además, el análisis de componentes principales encuentra que los elementos: agotamiento emocional, cinismo (burnout), y utilidad y facilidad de uso percibida (Modelo de Aceptación Tecnológica) están relacionados; sin embargo, la eficacia académica se mantiene alejado del agotamiento y dificultad de uso de la tecnología. Se concluye que la aceptación tecnológica se relaciona con el burnout académico, actuando como un factor de desgaste. Aunque, la percepción de eficacia académica se mostró como un factor independiente, sugiriendo que los estudiantes mantienen la orientación al logro a pesar del agotamiento que la tecnología pueda generar.
References
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Alarcon, G. M. (2011). A meta-analysis of burnout with job demands, resources, and attitudes. Journal of Vocational Behavior, 2(549-562), 79. https://doi.org/10.1016/j.jvb.2011.03.007
Alhammadi, H., Bani-Melhem, S., Mohd-Shamsudin, F., Karrani, M., y Hamouche, S. (2024). Technological work burnout: conceptualization, measure development and validation. Kybernetes, ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-05-2024-1243
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Cadena, P., Rendón-Medel, R., Aguilar-Ávila, J., Salinas- Cruz, E., De la Cruz-Morales, F., y Sangerman- Jarquín, D. (2017). Métodos cuantitativos, métodos cualitativos o su combinación en la investigación: un acercamiento en las ciencias sociales. Revista Mexicana De Ciencias Agrícolas, 8(7), 1603-1617. https://doi.org/10.29312/remexca.v8i7.515
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Creswell, J., y Creswell, J. (2023). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage Publications. https://www.ucg.ac.me/skladiste/blog_609332/objava_105202/fajlovi/Creswell.pdf
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Davis, F. D., Bagozzi, R. P., y Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Fishbein, M. A., y Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley. https://www.researchgate.net/publication/233897090
Fonseca, G., Rojas, L., Benites, R., Benites, D., y Benites, D. (2023). Síndrome de burnout en aulas virtuales vía internet en estudiantes de odontología Uniandes. Revista REDIELUZ- Sembrando la Investigación Estudiantil, 13(1), 82-90. https://doi.org/10.5281/zenodo.8106537
García-Salirrosas, E. E., y Millones-Liza, D. Y. (2023). Aceptación de la tecnología y su relación con el desempeño laboral de los teletrabajadores. Revista Venezolana de Gerencia, 28(9), 199-214. https://doi.org/10.52080/rvgluz.28.e9.13
Hashim, K. F., Tan, F. B., Rashid, A., y Mohd Yusof, S. A. (2024). Examining the Role of Technostress Creators and Inhibitors on Academics Burnout. Emerging Science Journal, 8, 206-219. https://doi.org/10.28991/ESJ-2024-SIED1-012
Hederich-Martínez, C., y Caballero-Domínguez, C. (2016). Validación del cuestionario Maslach Burnout Inventory-Student Survey (MBI-SS) en contexto académico colombiano. Revista CES Psicología, 9(1), 1-15. http://www.scielo.org.co/pdf/cesp/v9n1/v9n1a02.pdf
Hernández, J. T., Granada, P. A., y Carmona, J. J. (2011). Posibles indicadores del síndrome de burnout, en 18 operarios de una distribuidora de GLP de la ciudad de Armenia. Revista Negotium, 7(20), 22-37. https://www.redalyc.org/pdf/782/78222187002.pdf
Hossain, M., Tiwari, A., Saha, S., Ghimire, A., Imran, M., y Khatoon, R. (2024). Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System. Journal of Computer and Communications, 12, 242-256. https://doi.org/10.4236/jcc.2024.128015
Jacobs, S. R., y Dodd, D. K. (2013). Student burnout as a function of personality, social support, and workload. Journal of College Student Development, 44(3), 291-303. https://doi.org/10.1353/csd.2003.0028
Jagodics, B., y Szabó, É. (2023). Student Burnout in Higher Education: A Demand-Resource Model Approach. Trends in Psychology, 31, 757-776. https://doi.org/10.1007/s43076-021-00137-4
Kaggwa, M., Kajjimu, J., Sserunkuma, J., Najjuka, S., Atim, L., Olum, R., . . . Bongomin, F. (2021). Prevalence of burnout among university students in low- and middle-income countries: A systematic review and meta-analysis. PLOS ONE, 16(8). https://doi.org/10.1371/journal.pone.0256402
Klinkenberg, E. F., Versteeg, M., y Kappe, R. F. (2023). Engagement and emotional exhaustion among higher education students; a mixed-methods study of four student profiles. Studies in Higher Education, 49(11), 1837-1851. https://doi.org/10.1080/03075079.2023.2281533
Kurdi, B., Alshurideh, M., y Salloum, S. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496. https://doi.org/10.11591/ijece.v10i6.pp6484-6496
Mailizar, M., Burg, D., y Maulina, S. (2021). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26, 7057-7077. https://doi.org/10.1007/s10639-021-10557-5
Marangunić, N., y Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81-95. https://doi.org/10.1007/s10209-014-0348-1
Marques, H., Brites, R., Nunes, O., Hipólito, J., y Brandão, T. (2023). Attachment, emotion regulation, and burnout among university students: a mediational hypothesis. Educational Psychology, 43, 344-362. https://doi.org/10.1080/01443410.2023.2212889
Maslach, C., Schaufeli, W. B., y Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. https://doi.org/10.1146/annurev.psych.52.1.397
Maslach, C., y Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99-113. https://doi.org/10.1002/job.4030020205
Mejía-Mancilla, J., y Mejía, J. (2024). Technology Acceptance Model for Smartphone Use in Higher Education. Scientia et PRAXIS, 4(7), 113-158. https://doi.org/10.55965/setp.4.07.a5
Muñoz-Chávez, J. P., García Contreras, R., y Valle Cruz, D. (2022). Burnout y educación en línea: adaptación y validación de escala durante la pandemia. elos: Revista De Estudios Interdisciplinarios En Ciencias Sociales, 24(1), 24-39. https://doi.org/10.36390/telos241.03
Pérez-Barbosa, N., Pineda-Urueña, G., Piñeros-Dallos, L., Prada-Gwinner, N., y Palencia-Sánchez, F. (2022). What Is The Evidence Related To The Dimensions Of Burnout In Medical Students According To Maslach’s Theoretical Model?: A Rapid Literature Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4041991
Precious, B., Ebeguki, I., Odunayo, S., Kelechi, C., y Efeomo, S. (2022). Perceived usefulness of technology and multiple salient outcomes: the improbable case of oil and gas workers. Heliyon, 8(4). https://doi.org/10.1016/j.heliyon.2022.e09322
Qi, Z. (2025). A modified technology acceptance model for digital learning in Chinese universities. E-Learning and Digital Media, on line(0). https://doi.org/10.1177/20427530251313758
Ramos-Galarza, C. A. (2020). Los Alcances de una investigación. CienciAmérica, 9(3), 1-6. https://doi.org/10.33210/ca.v9i3.336
Rosales-Ricardo, Y., Rizzo-Chunga, F., Mocha-Bonilla, J., y Ferreira, J. (2021). Prevalence of burnout syndrome in university students: A systematic review. Revista Salud Mental, 44(2), 91-102. https://doi.org/10.17711/SM.0185-3325.2021.013
Saldaña Orozco, C., Rentería Castillo, A., Vargas Iñiguez, J. C., y Mendoza Cárdenas, R. (2024). Desgaste psíquico en estudiantes universitarios del Sur de Jalisco-México: Una descripción del síndrome Burnout. Revista de Ciencias Sociales, 30(2), 126-138. https://doi.org/10.31876/rcs.v30i2.41895
Salloum, S., Alhamad, A., Al-Emran, M., Monem, A., y Shaalan, K. (2019). Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access, 7, 128445-128362. https://doi.org/10.1109/ACCESS.2019.2939467
Salmela-Aro, K., Upadyaya, K., Ronkainen, I., y Hietajärv, L. (2022). Study Burnout and Engagement During COVID-19 Among University Students: The Role of Demands, Resources, and Psychological Needs. Journal of Happiness Studies, 23, 2685-2702. https://doi.org/10.1007/s10902-022-00518-1
Salmela-Aro, K., y Upadyaya, K. (2020). School burnout and engagement in the context of demands-resources model. Journal of Research on Adolescence, 30(S1), 341-354. https://doi.org/10.1111/bjep.12018
Santini, F., Sampaio, C., Rasul, T., Ladeira, W., Kar, A., Perin, M., y Azhar, M. (2024). Understanding Students’ Technology Acceptance Behaviour : A Meta-Analytic Study. Technology in Society, 81. https://doi.org/10.1016/j.techsoc.2024.102798
Schaufeli, W. B., Martínez, I. M., Pinto, A. M., Salanova, M., y Bakker, A. B. (2002). Burnout and engagement in university students: A cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464-481. https://doi.org/10.1177/0022022102033005003
Schmid, R., y Petko, D. (2019). Does the use of educational technology in personalized learning environments correlate with self-reported digital skills and beliefs of secondary-school students? Computers & Education, 136, 75-86. https://doi.org/10.1016/j.compedu.2019.03.006
Sun, J. C., y Chen, A. Y. (2016). The Effects of Digital Textbooks on Students’ Academic Performance, Academic Interest, and Learning Skills. Journal of Marketing Research, 32(5), 415-427. https://doi.org/10.1177/00222437221130712
Venkatesh, V., y Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Ye, Y., Huang, X., y Liu, Y. (2021). Social Support and Academic Burnout Among University Students: A Moderated Mediation Model. Psychology Research and Behavior Management, 14, 335-344. https://doi.org/10.2147/PRBM.S300797
Aguayo, R., Cañadas, G. R., Assbaa-Kaddouri, L., Cañadas-De la Fuente, G. A., Ramírez-Baena, L., y Ortega-Campos, E. (2019). A Risk Profile of Sociodemographic Factors in the Onset of Academic Burnout Syndrome in a Sample of University Students. International Journal of Environmental Research and Public Health, 16(5), 707. https://pmc.ncbi.nlm.nih.gov/articles/PMC6427695/
Alarcon, G. M. (2011). A meta-analysis of burnout with job demands, resources, and attitudes. Journal of Vocational Behavior, 2(549-562), 79. https://doi.org/10.1016/j.jvb.2011.03.007
Alhammadi, H., Bani-Melhem, S., Mohd-Shamsudin, F., Karrani, M., y Hamouche, S. (2024). Technological work burnout: conceptualization, measure development and validation. Kybernetes, ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-05-2024-1243
Al-Kumaim, N. H., Alhazmi, A. K., Mohammed, F., Gazem, N. A., Shabbir, M. S., y Fazea, Y. (2021). Exploring the Impact of the COVID-19 Pandemic on University Students’ Learning Life: An Integrated Conceptual Motivational Model for Sustainable and Healthy Online Learning. Sustainability, 13(5), 2546. https://doi.org/10.3390/su13052546
Cadena, P., Rendón-Medel, R., Aguilar-Ávila, J., Salinas- Cruz, E., De la Cruz-Morales, F., y Sangerman- Jarquín, D. (2017). Métodos cuantitativos, métodos cualitativos o su combinación en la investigación: un acercamiento en las ciencias sociales. Revista Mexicana De Ciencias Agrícolas, 8(7), 1603-1617. https://doi.org/10.29312/remexca.v8i7.515
Cardona, D., y Betancur, F. (2023). Technology Acceptance Model (TAM): A Study of Teachers’ Perception of the Use of Serious Games in the Higher Education. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 18(1), 123-129. https://doi.org/10.1109/RITA.2023.3250586
Carlotto, M. (2023). Síndrome de burnout en estudiantes universitarios trabajadores y no trabajadores. Revista Estudios Psicológicos, 3(3), 21-34. https://doi.org/10.35622/j.rep.2023.03.002
Creswell, J., y Creswell, J. (2023). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage Publications. https://www.ucg.ac.me/skladiste/blog_609332/objava_105202/fajlovi/Creswell.pdf
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Davis, F. D., Bagozzi, R. P., y Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Fishbein, M. A., y Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley. https://www.researchgate.net/publication/233897090
Fonseca, G., Rojas, L., Benites, R., Benites, D., y Benites, D. (2023). Síndrome de burnout en aulas virtuales vía internet en estudiantes de odontología Uniandes. Revista REDIELUZ- Sembrando la Investigación Estudiantil, 13(1), 82-90. https://doi.org/10.5281/zenodo.8106537
García-Salirrosas, E. E., y Millones-Liza, D. Y. (2023). Aceptación de la tecnología y su relación con el desempeño laboral de los teletrabajadores. Revista Venezolana de Gerencia, 28(9), 199-214. https://doi.org/10.52080/rvgluz.28.e9.13
Hashim, K. F., Tan, F. B., Rashid, A., y Mohd Yusof, S. A. (2024). Examining the Role of Technostress Creators and Inhibitors on Academics Burnout. Emerging Science Journal, 8, 206-219. https://doi.org/10.28991/ESJ-2024-SIED1-012
Hederich-Martínez, C., y Caballero-Domínguez, C. (2016). Validación del cuestionario Maslach Burnout Inventory-Student Survey (MBI-SS) en contexto académico colombiano. Revista CES Psicología, 9(1), 1-15. http://www.scielo.org.co/pdf/cesp/v9n1/v9n1a02.pdf
Hernández, J. T., Granada, P. A., y Carmona, J. J. (2011). Posibles indicadores del síndrome de burnout, en 18 operarios de una distribuidora de GLP de la ciudad de Armenia. Revista Negotium, 7(20), 22-37. https://www.redalyc.org/pdf/782/78222187002.pdf
Hossain, M., Tiwari, A., Saha, S., Ghimire, A., Imran, M., y Khatoon, R. (2024). Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System. Journal of Computer and Communications, 12, 242-256. https://doi.org/10.4236/jcc.2024.128015
Jacobs, S. R., y Dodd, D. K. (2013). Student burnout as a function of personality, social support, and workload. Journal of College Student Development, 44(3), 291-303. https://doi.org/10.1353/csd.2003.0028
Jagodics, B., y Szabó, É. (2023). Student Burnout in Higher Education: A Demand-Resource Model Approach. Trends in Psychology, 31, 757-776. https://doi.org/10.1007/s43076-021-00137-4
Kaggwa, M., Kajjimu, J., Sserunkuma, J., Najjuka, S., Atim, L., Olum, R., . . . Bongomin, F. (2021). Prevalence of burnout among university students in low- and middle-income countries: A systematic review and meta-analysis. PLOS ONE, 16(8). https://doi.org/10.1371/journal.pone.0256402
Klinkenberg, E. F., Versteeg, M., y Kappe, R. F. (2023). Engagement and emotional exhaustion among higher education students; a mixed-methods study of four student profiles. Studies in Higher Education, 49(11), 1837-1851. https://doi.org/10.1080/03075079.2023.2281533
Kurdi, B., Alshurideh, M., y Salloum, S. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496. https://doi.org/10.11591/ijece.v10i6.pp6484-6496
Mailizar, M., Burg, D., y Maulina, S. (2021). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26, 7057-7077. https://doi.org/10.1007/s10639-021-10557-5
Marangunić, N., y Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81-95. https://doi.org/10.1007/s10209-014-0348-1
Marques, H., Brites, R., Nunes, O., Hipólito, J., y Brandão, T. (2023). Attachment, emotion regulation, and burnout among university students: a mediational hypothesis. Educational Psychology, 43, 344-362. https://doi.org/10.1080/01443410.2023.2212889
Maslach, C., Schaufeli, W. B., y Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. https://doi.org/10.1146/annurev.psych.52.1.397
Maslach, C., y Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99-113. https://doi.org/10.1002/job.4030020205
Mejía-Mancilla, J., y Mejía, J. (2024). Technology Acceptance Model for Smartphone Use in Higher Education. Scientia et PRAXIS, 4(7), 113-158. https://doi.org/10.55965/setp.4.07.a5
Muñoz-Chávez, J. P., García Contreras, R., y Valle Cruz, D. (2022). Burnout y educación en línea: adaptación y validación de escala durante la pandemia. elos: Revista De Estudios Interdisciplinarios En Ciencias Sociales, 24(1), 24-39. https://doi.org/10.36390/telos241.03
Pérez-Barbosa, N., Pineda-Urueña, G., Piñeros-Dallos, L., Prada-Gwinner, N., y Palencia-Sánchez, F. (2022). What Is The Evidence Related To The Dimensions Of Burnout In Medical Students According To Maslach’s Theoretical Model?: A Rapid Literature Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4041991
Precious, B., Ebeguki, I., Odunayo, S., Kelechi, C., y Efeomo, S. (2022). Perceived usefulness of technology and multiple salient outcomes: the improbable case of oil and gas workers. Heliyon, 8(4). https://doi.org/10.1016/j.heliyon.2022.e09322
Qi, Z. (2025). A modified technology acceptance model for digital learning in Chinese universities. E-Learning and Digital Media, on line(0). https://doi.org/10.1177/20427530251313758
Ramos-Galarza, C. A. (2020). Los Alcances de una investigación. CienciAmérica, 9(3), 1-6. https://doi.org/10.33210/ca.v9i3.336
Rosales-Ricardo, Y., Rizzo-Chunga, F., Mocha-Bonilla, J., y Ferreira, J. (2021). Prevalence of burnout syndrome in university students: A systematic review. Revista Salud Mental, 44(2), 91-102. https://doi.org/10.17711/SM.0185-3325.2021.013
Saldaña Orozco, C., Rentería Castillo, A., Vargas Iñiguez, J. C., y Mendoza Cárdenas, R. (2024). Desgaste psíquico en estudiantes universitarios del Sur de Jalisco-México: Una descripción del síndrome Burnout. Revista de Ciencias Sociales, 30(2), 126-138. https://doi.org/10.31876/rcs.v30i2.41895
Salloum, S., Alhamad, A., Al-Emran, M., Monem, A., y Shaalan, K. (2019). Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access, 7, 128445-128362. https://doi.org/10.1109/ACCESS.2019.2939467
Salmela-Aro, K., Upadyaya, K., Ronkainen, I., y Hietajärv, L. (2022). Study Burnout and Engagement During COVID-19 Among University Students: The Role of Demands, Resources, and Psychological Needs. Journal of Happiness Studies, 23, 2685-2702. https://doi.org/10.1007/s10902-022-00518-1
Salmela-Aro, K., y Upadyaya, K. (2020). School burnout and engagement in the context of demands-resources model. Journal of Research on Adolescence, 30(S1), 341-354. https://doi.org/10.1111/bjep.12018
Santini, F., Sampaio, C., Rasul, T., Ladeira, W., Kar, A., Perin, M., y Azhar, M. (2024). Understanding Students’ Technology Acceptance Behaviour : A Meta-Analytic Study. Technology in Society, 81. https://doi.org/10.1016/j.techsoc.2024.102798
Schaufeli, W. B., Martínez, I. M., Pinto, A. M., Salanova, M., y Bakker, A. B. (2002). Burnout and engagement in university students: A cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464-481. https://doi.org/10.1177/0022022102033005003
Schmid, R., y Petko, D. (2019). Does the use of educational technology in personalized learning environments correlate with self-reported digital skills and beliefs of secondary-school students? Computers & Education, 136, 75-86. https://doi.org/10.1016/j.compedu.2019.03.006
Sun, J. C., y Chen, A. Y. (2016). The Effects of Digital Textbooks on Students’ Academic Performance, Academic Interest, and Learning Skills. Journal of Marketing Research, 32(5), 415-427. https://doi.org/10.1177/00222437221130712
Venkatesh, V., y Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Ye, Y., Huang, X., y Liu, Y. (2021). Social Support and Academic Burnout Among University Students: A Moderated Mediation Model. Psychology Research and Behavior Management, 14, 335-344. https://doi.org/10.2147/PRBM.S300797
Published
2026-04-15
How to Cite
González-Garces, L. E., López-Paredes, M. A., & López-Pérez, S. D. L. A. (2026). Burnout académico y aceptación tecnológica en universitarios. Revista Venezolana De Gerencia, 31(15), e31e158. Retrieved from https://produccioncientificaluz.org/index.php/rvg/article/view/45458
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