Burnout Profile of Indonesian Students: A Study of Measurement Tool Development and Latent Profile Analysis

https://doi.org/10.22146/gamajop.98203

Sabrina Puti Afifah(1*), Puti Lenggogeni(2), Kemas Rahmat Mubarrak(3), Angeline Freshbi Chesa Halim(4), Salwa Zhafirah(5)

(1) Faculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia
(2) Faculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia
(3) Faculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia
(4) Faculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia
(5) Queen Mary University London
(*) Corresponding Author

Abstract


Academic burnout among university students is a critical issue because it significantly impacts both psychological well-being and academic performance. This study aims to develop a culturally relevant academic burnout scale tailored to the higher education context in Indonesia and to identify latent student profiles based on their burnout experiences. A total of 222 active students from various universities in Indonesia participated in this study. Construct validity of the scale was tested using confirmatory factor analysis (CFA), while profile analysis was conducted through latent profile analysis (LPA). The results indicated that the academic burnout scale comprises three main dimensions (exhaustion, cynicism, and inefficacy), with a total of 12 items, and meets the goodness-of-fit criteria with RMSEA < 0.08, CFI & TLI > 0.90, and SRMR < 0.08. The measurement results also demonstrated good reliability, as indicated by McDonald’s Omega (ω = 0.853). The profile analysis identified two latent student classes: the high-burnout group and the low-burnout group. These findings highlight the importance of employing contextually appropriate measurement tools and person-centered approaches in understanding the dynamics of academic burnout among Indonesian university students.

Keywords


burnout; academic; student; profile; indonesia

Full Text:

PDF


References

Abreu Alves, S., Sinval, J., Lucas Neto, L., Marôco, J., Gonçalves Ferreira, A., & Oliveira, P. (2022). Burnout and dropout intention in medical students: The protective role of academic engagement. BMC Medical Education, 22(1), 83. https://doi.org/10.1186/s12909-021-03094-9

Ansert, E., & Rushing, C. J. (2021). Feeling the burnout: Perceptions of burnout, anxiety, depression, and personal achievement in U.S. podiatric medical students. The Journal of Foot and Ankle Surgery, 60(4), 747–752. https://doi.org/10.1053/j.jfas.2021.02.007

Oyoo, S. A., Mwaura, P. M., & Kinai, T. (2018). Academic resilience as a predictor of academic burnout among form four students in Homa-Bay County, Kenya. International Journal of Education and Research, 6(3).

Auliannisa, D. (2023). Hubungan self-efficacy dengan academic burnout pada mahasiswa yang melakukan pembelajaran jarak jauh (PJJ). Bahasa dan Pendidikan, 3(4), 40–46. https://doi.org/10.55606/cendikia.v3i4.1767

Azwar, S. (2021). Penyusunan skala psikologi (3rd ed.). Pustaka Pelajar.

Bask, M., & Salmela-Aro, K. (2013). Burned out to drop out: Exploring the relationship between school burnout and school dropout. European Journal of Psychology of Education, 28(2), 511–528. https://doi.org/10.1007/s10212-012-0126-5

Bima Fathoni, A., Zulfa, N., & Nurlaila Hidayat, I. (2022). Academic burnout in university students during COVID-19 pandemic: Viewed from readiness to change with religious coping as a moderator. Journal An-Nafs: Kajian Penelitian Psikologi, 7(1), 50–60. https://doi.org/10.33367/psi.v7i1.2049

Brown, T. A. (2014). Confirmatory factor analysis for applied research (2nd ed.). Guilford Press.

Cabana, E., Lillo, R. E., & Laniado, H. (2021). Multivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimators. Statistical Papers, 62(4), 1583–1609. https://doi.org/10.1007/s00362-019-01148-1

Cazolari, P. G., Cavalcante, M. de S., Demarzo, M. M. P., Cohrs, F. M., Sanudo, A., & Schveitzer, M. C. (2020). Burnout and well-being levels of medical students: A cross-sectional study. Revista Brasileira de Educação Médica, 44(4). https://doi.org/10.1590/1981-5271v44.4-20190138.ing

Effendi Ewan Mohd Matore, M., & Zamri Khairani, A. (2020). The pattern of skewness and kurtosis using mean score and logit in measuring adversity quotient (AQ) for normality testing. International Journal of Future Generation Communication and Networking, 13(1), 688–702.

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1).

Fiorilli, C., De Stasio, S., Di Chiacchio, C., Pepe, A., & Salmela-Aro, K. (2017). School burnout, depressive symptoms and engagement: Their combined effect on student achievement. International Journal of Educational Research, 84, 1–12. https://doi.org/10.1016/j.ijer.2017.04.001

Freudenberger, H. J. (1975). The staff burnout syndrome in alternative institutions. Psychotherapy: Theory, Research, & Practice, 12, 72–83.

Galán, F., Sanmartín, A., Polo, J., & Giner, L. (2011). Burnout risk in medical students in Spain using the Maslach Burnout Inventory–Student Survey. International Archives of Occupational and Environmental Health, 84(4), 453–459. https://doi.org/10.1007/s00420-011-0623-x

Gravetter, F. J., Forzano, L. A. B., & Rakow, T. (2021). Research methods for the behavioral sciences. Cengage Learning.

Hair, J. F. (2011). Multivariate data analysis: An overview. In International encyclopedia of statistical science (pp. 904–907). Springer. https://doi.org/10.1007/978-3-642-04898-2_395

Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Sage.

Hox, J. J. (2021). Confirmatory factor analysis. In The encyclopedia of research methods in criminology and criminal justice (pp. 830–832). Wiley. https://doi.org/10.1002/9781119111931.ch158

Kim, B., Jee, S., Lee, J., An, S., & Lee, S. M. (2017). Relationships between social support and student burnout: A meta-analytic approach. Stress and Health, 34(1), 127–134. https://doi.org/10.1002/smi.2771

Lin, S. H., & Huang, Y. C. (2014). Life stress and academic burnout. Active Learning in Higher Education, 15(1), 77–90. https://doi.org/10.1177/1469787413514651

Marcoulides, K. M., & Yuan, K.-H. (2017). New ways to evaluate goodness of fit: A note on using equivalence testing to assess structural equation models. Structural Equation Modeling, 24(1), 148–153. https://doi.org/10.1080/10705511.2016.1225260

Maslach, C., & Leiter, M. P. (2016). Understanding the burnout experience: Recent research and its implications for psychiatry. World Psychiatry, 15(2), 103–111. https://doi.org/10.1002/wps.20311

Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397–422.

McNeish, D., & Wolf, M. G. (2023). Dynamic fit index cutoffs for confirmatory factor analysis models. Psychological Methods, 28(1), 61–88. https://doi.org/10.1037/met0000425

Purvanova, R. K., & Muros, J. P. (2010). Gender differences in burnout: A meta-analysis. Journal of Vocational Behavior, 77(2), 168–185. https://doi.org/10.1016/j.jvb.2010.04.006

Rahman, D. H. (2020). Validasi school burnout inventory versi bahasa Indonesia. Jurnal Penelitian Ilmu Pendidikan, 13(2), 85–93. https://doi.org/10.21831/jpipfip.v13i2.32579

Robins, T. G., Roberts, R. M., & Sarris, A. (2018). The role of student burnout in predicting future burnout. Higher Education Research & Development, 37(1), 115–130. https://doi.org/10.1080/07294360.2017.1344827

Schaufeli, W. B., Martínez, I. M., Pinto, A. M., Salanova, M., & Barker, 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

Seo, C., Di Carlo, C., Dong, S. X., Fournier, K., & Haykal, K.-A. (2021). Risk factors for suicidal ideation and suicide attempt among medical students: A meta-analysis. PLOS ONE, 16(12), e0261785. https://doi.org/10.1371/journal.pone.0261785

Singh, L. B., Kumar, A., & Srivastava, S. (2020). Academic burnout and student engagement. Journal of International Education in Business, 14(2), 219–239. https://doi.org/10.1108/JIEB-03-2020-0020

Taber, K. S. (2018). The use of Cronbach’s alpha. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

Watson, C., Ventriglio, A., & Bhugra, D. (2020). Suicide and suicidal behavior in medical students. Indian Journal of Psychiatry, 62(3), 250. https://doi.org/10.4103/psychiatry.IndianJPsychiatry_357_20

Wei, H., Dorn, A., Hutto, H., Webb Corbett, R., Haberstroh, A., & Larson, K. (2021). Impacts of nursing student burnout. Journal of Nursing Education, 60(7), 369–376. https://doi.org/10.3928/01484834-20210616-02

Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in SEM. Behavior Research Methods, 51(1), 409–428. https://doi.org/10.3758/s13428-018-1055-2

Yavuz, G., & Dogan, N. (2014). Maslach burnout inventory-student survey (MBI-SS): A validity study. Procedia - Social and Behavioral Sciences, 116, 2453–2457. https://doi.org/10.1016/j.sbspro.2014.01.590



DOI: https://doi.org/10.22146/gamajop.98203

Article Metrics

Abstract views : 10 | views : 0

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Gadjah Mada Journal of Psychology (GamaJoP)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Recent Issues:

Buku 1 Buku 1 Buku 1 Buku 1 
Vol 11 Issue 1 (2025)
Page 1-69
 Vol 10 Issue 2 (2024)
Page 79-161
 Vol 10 Issue 1 (2024)
Page 1-78
 Vol 9 Issue 2 (2023)
Page 163-292
 


Address:

Building D 6th Floor (606), Faculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia, Jl. Sosio Humaniora No. 1, Bulaksumur Yogyakarta, 55781

Contact:

Whatsapp: +6281125210175
Email: gamajop.psikologi@ugm.ac.id

Creative Commons License