The Short Burnout Measure (SBM): Development and Validation
DOI:
https://doi.org/10.24265/liberabit.2025.v31n2.1069Palabras clave:
burnout, organization, scale construction, factorial validity, short measureResumen
Background: Burnout is a widespread issue in organizational settings, negatively affecting both employees and organizations. While numerous scales have been developed, many have limitations, such as failing to differentiate between depersonalization and cynicism, or using reverse items to assess inefficacy, that compromise their validity and utility. Objective: to develop and validate a short burnout measure (SBM). Method: An instrumental study was conducted using a sample of 1256 information technology (IT) workers from Argentina (56.1% males; age range: 18-59, M = 25.16). Participants completed an online survey including the SBM, along with measures of turnover intention and employee Net Promoter Score. Results: Confirmatory factor analysis comparing one-factor, three-factor, four-factor, higherorder, and bifactor models revealed that the four-factor model –comprising exhaustion, cynicism, depersonalization, and inefficacy– provided the best fit to the data [χ2 (14) = 26.60, p < .05, CFI = .998, TLI = .996, RMSEA = .038 (90% CI [.014, .06]), WRMR = 0.33]. All SBM factors demonstrated satisfactory construct reliability (H coefficients ranging from .77 to .88). Criterion validity was supported by theoretically consistent associations found between SBM dimensions, turnover intention, and employee Net Promoter Score. Conclusion: This study presents a new scale that overcomes key limitations of existing self-report measures by using separate subscales for assessing cynicism and depersonalization and using direct items to assess inefficacy. These features, together with its brevity, make the SBM a practical and psychometrically sound tool for rapidly assessing burnout in IT workers. Study limitations and the need to replicate these findings in different occupational sectors are discussed.
Descargas
Referencias
Aiken, L. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45(1), 131–142. https://doi.org/10.1177/0013164485451012
Bakker, A. B., Demerouti, E., & Sanz-Vergel, A. (2023). Job demands–resources theory: Ten years later. Annual Review of Organizational Psychology and Organizational Behavior, 10(1), 25–53. https://doi.org/10.1146/annurev-orgpsych-120920-053933
Beer, P., & Mulder, R. H. (2020). The effects of technological developments on work and their implications for continuous vocational education and training: A systematic review. Frontiers in Psychology, 11, 918. https://doi.org/10.3389/fpsyg.2020.00918
Bravo, D. M., Suárez-Falcón, J. C., Bianchi, J. M., Segura-Vargas, M. A., & Ruiz, F. J. (2021). Psychometric properties and measurement invariance of the Maslach Burnout Inventory–General Survey in Colombia. International Journal of Environmental Research and Public Health, 18(10), 5118. https://doi.org/10.3390/ijerph18105118
Bresó, E., Salanova, M., & Schaufeli, W. B. (2007). In search of the “third dimension” of burnout: Efficacy or inefficacy? Applied Psychology: An International Review, 56(3), 460–478. https://doi.org/10.1111/j.1464-0597.2007.00290.x
Bria, M., Spânu, F., Băban, A., & Dumitraşcu, D. L. (2014). Maslach Burnout Inventory–General Survey: Factorial validity and invariance among Romanian healthcare professionals. Burnout Research, 1(3), 103–111. https://doi.org/10.1016/j.burn.2014.09.001
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J. Long (Eds.), Testing structural equation models (pp. 136–162). Sage.
Dåderman, A. M., Basinska, B. A., Ragnestål-Impola, C., Hedman, M., Wicksell, A., Lindh, M. F., & Cider, Å. (2024). Crafting an ultrashort workplace incivility scale and determining cutoffs for varied risk levels through item response theory. Current Psychology, 43(40), 31343–31357. https://doi.org/10.1007/s12144-024-06495-3
De Beer, L. T., Van der Vaart, L., Escaffi-Schwarz, M., De Witte, H., & Schaufeli, W. B. (2024). Maslach Burnout Inventory—General survey: A systematic review and meta-analysis of measurement properties. European Journal of Psychological Assessment, 40(5), 360–375. https://doi.org/10.1027/1015-5759/a000797
Demerouti, E., Bakker, A. B., Vardakou, I., & Kantas, A. (2003). The convergent validity of two burnout instruments: A multitrait-multimethod analysis. European Journal of Psychological Assessment, 19(1), 296–307. https://doi.org/10.1027//1015-5759.19.1.12
DiStefano, C., Liu, J., Jiang, N., & Shi, D. (2018). Examination of the weighted root mean square residual: Evidence for trustworthiness? Structural Equation Modeling: A Multidisciplinary Journal, 25(3), 453–466. https://doi.org/10.1080/10705511.2017.1390394
Dueber, D. M. (2017). Bifactor Indices Calculator: A Microsoft Excel-based tool to calculate various indices relevant to bifactor CFA models. https://doi.org/10.13023/edp.tool.01
Edú-Valsania, S., Laguía, A., & Moriano, J. A. (2022). Burnout: A review of theory and measurement. International Journal of Environmental Research and Public Health, 19(3), 1780. https://doi.org/10.3390/ijerph19031780
Farrell, A. M. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63(3), 324–327. https://doi.org/10.1016/j.jbusres.2009.05.003
Fernández, I., Enrique, S., De Los Santos, S., & Tomás, J. M. (2020). Can engagement and burnout be distinguished? A study in a representative sample of teachers. TPM: Testing, Psychometrics, Methodology in Applied Psychology, 27(1), 71–84. https://doi.org/10.4473/TPM27.1.5
Ferrando, P. J., & Morales-Vives, F. (2023). Is it quality, is it redundancy, or is model inadequacy? Some strategies for judging the appropriateness of high-discrimination items. Anales de Psicología, 39(3), 517–527. https://doi.org/10.6018/analesps.535781
Flores-Kanter, P. E., Garrido, L. E., Moretti, L. S., & Medrano, L. A. (2021). A modern network approach to revisiting the Positive and Negative Affective Schedule (PANAS) construct validity. Journal of Clinical Psychology, 77(10), 2370–2404. https://doi.org/10.1002/jclp.23191
Franzen, M. M. (2020). ‘Inhale… Exhale… Send e-mail’. A study examining the role of trait mindfulness on workplace telepressure and its impacts on well-being, psychological complaints and work-life balance among workers [Master’s thesis, University of Utrecht]. Utrecht University Student Theses Repository. https://studenttheses.uu.nl/handle/20.500.12932/36211
Gabriel, K. P., & Aguinis, H. (2022). How to prevent and combat employee burnout and create healthier workplaces during crises and beyond. Business Horizons, 65(2), 183–192. https://doi.org/10.1016/j.bushor.2021.02.037
Gignac, G. E. (2016). The higher-order model imposes a proportionality constraint: That is why the bifactor model tends to fit better. Intelligence, 55, 57–68. https://doi.org/10.1016/j.intell.2016.01.006
Goretzko, D., Siemund, K., & Sterner, P. (2024). Evaluating model fit of measurement models in confirmatory factor analysis. Educational and Psychological Measurement, 84(1), 123–144. https://doi.org/10.1177/00131644231163813
Gu, H., Wen, Z., & Fan, X. (2017). Examining and controlling for wording effect in a self-report measure: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 24(4), 545–555. https://doi.org/10.1080/10705511.2017.1286228
Guan, M. (2021). Associations between perceptions of the work environment and job burnout based on MIMIC models among 679 knowledge workers. SAGE Open, 11(1), 2158244021999384. https://doi.org/10.1177/2158244021999384
Hancock, G. R., & Mueller, R. O. (2001). Rethinking construct reliability within latent systems. In R. Cudeck, S. Du Toit, & D. Sorbom (Eds.), Structural equation modeling: Present and future e A festschrift in honor of Karl Joreskog (pp. 195–216). Scientific Software International.
Houkes, I., Janssen, P. P., De Jonge, J., & Nijhuis, F. J. (2001). Specific relationships between work characteristics and intrinsic work motivation, burnout and turnover intention: A multi-sample analysis. European Journal of Work and Organizational Psychology, 10(1), 1–23. https://doi.org/10.1080/13594320042000007
Hu, L.-T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424
Juárez, A. J., Merino, C., Fernández, M., Flores, C. A., Caraballo, M., & Camacho, C. (2020). Validación transcultural y funcionamiento diferencial del MBI-GS en docentes de tres países latinoamericanos. Avances en Psicología Latinoamericana, 38(1), 135–156. https://doi.org/10.12804/revistas.urosario.edu.co/apl/a.6621
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
Kristensen, T., Borritz, M., Villadsen, E., & Christensen, K. (2005). The Copenhagen Burnout Inventory: A new tool for the assessment of burnout. Work & stress, 19(3), 192–207. https://doi.org/10.1080/02678370500297720
Kumaresan, A., Suganthirababu, P., Srinivasan, V., Vijay, Y., Divyalaxmi, P., Alagesan, J., Vishnuram, S., Ramana, K., & Prathap, L. (2022). Prevalence of burnout syndrome among work-from-home IT professionals during the COVID-19 pandemic. WORK: A Journal of Prevention, Assessment & Rehabilitation, 71(2), 379-384. https://doi.org/10.3233/WOR-211040
Li, C.-H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior Research Methods, 48(3), 936–949. https://doi.org/10.3758/s13428-015-0619-7
Loreg, A. (2020). Work-related communications after hours: The influence of communication technologies and age on work-life conflict and burnout [Master’s thesis, California State University, San Bernardino]. ScholarWorks. https://scholarworks.lib.csusb.edu/etd/986
Maloney, P., Grawitch, M. J., & Barber, L. K. (2011). Strategic item selection to reduce survey length: Reduction in validity? Consulting Psychology Journal: Practice and Research, 63(3), 162–175. https://doi.org/10.1037/a0025604
Maroco, J., Maroco, A. L., & Campos, J. A. (2014). Student’s academic efficacy or inefficacy? An example on how to evaluate the psychometric properties of a measuring instrument and evaluate the effects of item wording. Open Journal of Statistics, 4(6), 484–493. https://doi.org/10.4236/ojs.2014.46046
Marsh, H. W., Hau, K.-T., & Grayson, D. (2005). Goodness of fit evaluation in structural equation modeling. In A. Maydeu-Olivares, & J. McArdle (Eds.), Contemporary psychometrics. A Festschrift for Roderick P. McDonald (pp. 275–340). Erlbaum.
Maslach, C. & Jackson, S. E. (1981). The Maslach Burnout Inventory: Research edition. Consulting Psychologists Press.
Maslach, C., & Leiter, M. P. (2017). Understanding burnout: New models. In C. L. Cooper, & J. C. Quick (Eds.), The handbook of stress and health: A guide to research and practice (pp. 36–56). Wiley Blackwell. https://doi.org/10.1002/9781118993811.ch3
Maslach, C., & Leiter, M. P. (2021). How to measure burnout accurately and ethically. Harvard Business Review, 7, 211–221.
Merino, C., & Livia, J. (2009). Intervalos de confianza asimétricos para el índice la validez de contenido: un programa Visual Basic para la V de Aiken. Anales de Psicología, 25(1), 169–171. https://revistas.um.es/analesps/article/view/71631
Merino-Soto, C., Calderón-De la Cruz, G., & Fernández-Arata, M. (2023). Maslach burnout inventory-general Survey’s abbreviated measurement: Validation in Peruvian teachers. Occupational Health Science, 7(3), 631–644. https://doi.org/10.1007/s41542-023-00149-9
Meuleman, B., Żółtak, T., Pokropek, A., Davidov, E., Muthén, B., Oberski, D. L., Billiet, J., & Schmidt, P. (2023). Why measurement invariance is important in comparative research. A response to Welzel et al. (2021). Sociological Methods & Research, 52(3), 1401–1419. https://doi.org/10.1177/00491241221091755
Montero, I., & León, O. G. (2007). A guide for naming research studies in Psychology. International Journal of Clinical and Health Psychology, 7(3), 847–862.
Morera, L. P., Gallea, J. I., Trógolo, M. A., Guido, M. E., & Medrano, L. A. (2020). From work well-being to burnout: A hypothetical phase model. Frontiers in Neuroscience, 14, 360. https://doi.org/10.3389/fnins.2020.00360
Morgan, B., De Bruin, G. P., & De Bruin, K. (2014). Operationalizing burnout in the Maslach Burnout Inventory–Student Survey: Personal efficacy versus personal inefficacy. South African Journal of Psychology, 44(2), 216–227. https://doi.org/10.1177/0081246314528834
Morin, A. J. S., Arens, A. K., & Marsh, H. W. (2016). A bifactor exploratory structural equation modeling framework for the identification of distinct sources of construct-relevant psychometric multidimensionality. Structural Equation Modeling: A Multidisciplinary Journal, 23(1), 116–139. https://doi.org/10.1080/10705511.2014.961800
Nagarajan, R., Ramachandran, P., Dilipkumar, R., & Kaur, P. (2024). Global estimate of burnout among the public health workforce: A systematic review and meta-analysis. Human Resources for Health, 22(30). https://doi.org/10.1186/s12960-024-00917-w
Pando, M., Aranda, C., & López, M. del R. (2015). Validez factorial del Maslach Burnout Inventory-General Survey en ocho países Latinoamericanos. Ciencia & Trabajo, 17(52), 28–31. https://doi.org/10.4067/S0718-24492015000100006
Pekmezci, F. B. (2022). Bifactor and Bifactor S-1 Model Estimations with Non-Reverse-Coded Data. Journal of Measurement and Evaluation in Education and Psychology, 13(3), 244–255. https://doi.org/10.21031/epod.1135567
Pollack, B. L., & Alexandrov, A. (2013). Nomological validity of the Net Promoter Index question. Journal of Services Marketing, 27(2), 118–129. https://doi.org/10.1108/08876041311309243
Quijada, Y., Saldivia, S., Bustos, C., Preti, A., Ochoa, S., Castro-Alzate, E., & Siddi, S. (2023). Measurement invariance between online and paper-and-pencil formats of the Launay-Slade Hallucinations scale-extended (LSHS-E) in the Chilean population: Invariance between LSHS-E formats. Current Psychology, 42(16), 13625–13636. https://doi.org/10.1007/s12144-021-02497-7
Raghavan, A., Demircioglu, M. A., & Orazgaliyev, S. (2021). COVID-19 and the new normal of organizations and employees: An overview. Sustainability, 13(21), 11942. https://doi.org/10.3390/su132111942
Rankmi. (2023). Benchmark de satisfacción y compromiso de los colaboradores en Latinoamérica. https://www.rankmi.com/hubfs/%5BDescargables%5D%20Estudios/%5BBenchmark%5D%20Satisfacci%C3%B3n%20y%20compromiso%20de%20los%20colaboradores%20en%20Latam/%5BBenchmark%5D%20Satisfacci%C3%B3n%20y%20compromiso%20de%20los%20colaboradores%20en%20latioamerica.pdf
Reichheld, F. F. (2003). The one number you need to grow. Harvard Business Review, 81(12), 46–55.
Russell, M. B., Attoh, P. A., Chase, T., Gong, T., Kim, J., & Liggans, G. L. (2020). Examining burnout and the relationships between job characteristics, engagement, and turnover intention among US educators. SAGE Open, 10(4), 1–15. https://doi.org/10.1177%2F2158244020972361
Salanova, M., Llorens, S., García-Renedo, M., Burriel, R., Bresó, E., & Schaufeli, W. B. (2005). Toward a four-dimensional model of burnout: A multigroup factor-analytic study including depersonalization and cynicism. Educational and Psychological Measurement, 65(5), 901–913. https://doi.org/10.1177/0013164405275662
Schaufeli, W. B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: Burnout and work engagement, and their relationships with efficacy beliefs. Anxiety, Stress, and Coping, 20(2), 177–196. https://doi.org/10.1080/10615800701217878
Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66(4), 701–716. https://doi.org/10.1177/0013164405282471
Schaufeli, W. B., Desart, S., & De Witte, H. (2020). Burnout Assessment Tool (BAT)—development, validity, and reliability. International Journal of Environmental Research and Public Health, 17(24), 9495. https://doi.org/10.3390/ijerph17249495
Schaufeli, W. B., Leiter, M. P., Maslach, C., & Jackson, S. E. (1996). Maslach burnout inventory ─ General survey. In C. Maslach, S. E. Jackson, & M. P. Leiter (Eds.), The Maslach burnout inventory: Test manual (3rd ed., pp. 22–26). Consulting Psychologists Press.
Schaufeli, W. B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3(1), 71–92. https://doi.org/10.1023/A:1015630930326
Sharma, M. K., Anand, N., Singh, P., Vishwakarma, A., Mondal, I., Thakur, P. C., & Kohli, T. (2020). Researcher burnout: An overlooked aspect in mental health research in times of COVID-19. Asian Journal of Psychiatry, 54, 102367. https://doi.org/10.1016/j.ajp.2020.102367
Shirom, A., & Melamed, S. (2006). A comparison of the construct validity of two burnout measures in two groups of professionals. International Journal of Stress Management, 13(2), 176–200. https://doi.org/10.1037/1072-5245.13.2.176
Simbula, S., & Guglielmi, D. (2010). Depersonalization or cynicism, efficacy or inefficacy: What are the dimensions of teacher burnout? European Journal of Psychology of Education, 25(3), 301–314. https://doi.org/10.1007/s10212-010-0017-6
Smith, G. T., McCarthy, D. M., & Anderson, K. G. (2000). On the sins of short-form development. Psychological Assessment, 12(1), 102–111. https://doi.org/10.1037/1040-3590.12.1.102
Spontón, C., Trógolo, M., Castellano, E., & Medrano, L. A. (2019). Medición del burnout: estructura factorial, validez y confiabilidad en trabajadores argentinos. Interdisciplinaria: Revista de Psicología y Ciencias Afines, 36(1), 87–103.
Swider, B. W., & Zimmerman, R. D. (2010). Born to burnout: A meta-analytic path model of personality, job burnout, and work outcomes. Journal of Vocational behavior, 76(3), 487–506. https://doi.org/10.1016/j.jvb.2010.01.003
Trógolo, M. A., Moretti, L. S., & Medrano, L. A. (2022). A nationwide cross-sectional study of workers’ mental health during the COVID-19 pandemic: Impact of changes in working conditions, financial hardships, psychological detachment from work and work-family interface. BMC Psychology, 10, 73. https://doi.org/10.1186/s40359-022-00783-y
Vigil-Colet, A., Navarro-González, D., & Morales-Vives, F. (2020). To reverse or to not reverse Likert-type items: That is the question. Psicothema, 32(1), 108–114. https://doi.org/10.7334/psicothema2019.286
Wang, A., Duan, Y., Norton, P. G., Leiter, M. P., & Estabrooks, C. A. (2024). Validation of the Maslach Burnout Inventory-General Survey 9-item short version: Psychometric properties and measurement invariance across age, gender, and continent. Frontiers in Psychology, 15, 1439470. https://doi.org/10.3389/fpsyg.2024.1439470
Wang, M., & Russell, S. S. (2005). Measurement equivalence of the job descriptive index across Chinese and American workers: Results from confirmatory factor analysis and item response theory. Educational and Psychological Measurement, 65(4), 709–732. https://doi.org/10.1177/0013164404272494
Worley, J. A., Vassar, M., Wheeler, D. L., & Barnes, L. L. (2008). Factor structure of scores from the Maslach Burnout Inventory: A review and meta-analysis of 45 exploratory and confirmatory factor-analytic studies. Educational and Psychological Measurement, 68(5), 797–823. https://doi.org/10.1177/0013164408315268
Yaneva, M., (2018). Employee satisfaction vs. employee engagement vs. employee NPS. European Journal of Economics and Business Studies, 4(1), 221–227. https://doi.org/10.2478/ejes-2018-0024
Zeiler, M., Peer, S., Philipp, J., Truttmann, S., Wagner, G., Karwautz, A., & Waldherr, K. (2020). Web-based versus paper-pencil assessment of behavioral problems using the youth self-report. European Journal of Psychological Assessment, 37(2), 95-103. https://doi.org/10.1027/1015-5759/a000585
Publicado
Número
Sección
Licencia
Derechos de autor 2025 Carlos Luis Spontón, Mario Alberto Trógolo
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Derechos de autor: En caso de que el manuscrito sea aprobado para su publicación, los autores conservarán los derechos de autoría y cederán a la revista los derechos de publicación, edición, reproducción, distribución, exhibición y comunicación a nivel nacional e internacional en las diferentes bases de datos, repositorios y portales.
Política de autoarchivo: El autor puede compartir, difundir y divulgar sus investigaciones publicadas por los medios de comunicación (e.g., redes sociales académicas, repositorios y portales) disponibles en la web. Durante el proceso de revisión editorial, la revista entregará al autor las versiones previas (post-print), las cuales NO deben ser divulgadas por ningún medio de difusión y son solo de uso personal con fines de aprobación final. Liberabit enviará al autor la versión final del artículo (published version) en formato PDF y HTML para ser compartida, difundida y divulgada por los medios de comunicación disponibles en la web. Después de la publicación de los artículos, los autores pueden realizar acuerdos independientes o adicionales para la difusión no exclusiva de la versión del artículo publicado en la revista (por ejemplo, publicación en libros o repositorios institucionales), siempre que se indique con la referencia respectiva que el trabajo ha sido publicado por primera vez en esta revista.
Cómo citar
