Validity Evidence for the Internal Structure of the Maslach Burnout Inventory-Student Survey: A Comparison between Classical CFA Model and the ESEM and the Bifactor Models
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MDPI
Materia
Academic burnout syndrome MBI-SS Internal structure; reliability and validity ESSEM and bifactor model
Date
2023-03-21Referencia bibliográfica
Aguayo-Estremera, R.; Cañadas, G.R.; Ortega-Campos, E.; Ariza, T.; De la Fuente-Solana, E.I. Validity Evidence for the Internal Structure of the Maslach Burnout Inventory-Student Survey: A Comparison between Classical CFA Model and the ESEM and the Bifactor Models. Mathematics 2023, 11, 1515. [https://doi.org/10.3390/math11061515]
Sponsorship
FEDER/Consejería de Universidad, Investigación e Inovación de la Junta de Andalucía. Project P20-00637Abstract
Academic burnout is a psychological problem characterized by three dimensions: emotional
exhaustion, depersonalization, and personal accomplishment. This paper studies the internal
structure of the MBI-SS, the most widely used instrument to assess burnout in students. The bifactor
model and the ESEM approach have been proposed as alternatives, capable of overcoming the classical
techniques of CFA to address this issue. Our study considers the internal structure of the MBI-SS
by testing the models most frequently referenced in the literature, along with the bifactor model
and the ESEM. After determining which model best fits the data, we calculate the most appropriate
reliability index. In addition, we examined the validity evidence using other variables, namely
the concurrent relationships with depression, anxiety, neuroticism, and conscientiousness, and the
discriminant relationships with the dimensions of engagement, extraversion, and agreeableness. The
results obtained indicate that the internal structure of the MBI-SS is well reflected by the three-factor
congeneric oblique model, reaching good values of reliability and convergent and discriminant
validity. Therefore, when the scale is used in applied contexts, we recommend considering the total
scores obtained for each of the dimensions. Finally, we recommend using the omega coefficient and
not the alpha coefficient as an estimator of reliability