PLS-SEM Validation for Burnout Measures in Latino College Students: A Socially Sustainable Educational Return

Abstract

Health care is an essential factor in the social sustainability of the university; therefore, it is a challenge and a responsibility to monitor a safe return to school that ensures the support of the physical and emotional well-being of students. In this sense, the Maslach Burnout Inventory-Student Survey (MBI-SS) is a validated resource with robust techniques in several regions of the world to diagnose school burnout. However, few efforts appear in the literature to validate it from a predictive approach in the Latin region. This study aims to validate, from a predictive approach, measures of school burnout in Latino university students from Mexico and Colombia. A total of 235 surveys were administered (Mx. n = 127, Co. n = 108), and a Partial Least Squares (PLS) measurement model was validated using the statistical program SmartPLS 3.3.7. As a result, 22 valid items were obtained in four reliable subconstructs: burnout, family cynicism, inefficacy, and somatization. The value of this research is its contribution to filling two gaps related to the MBI-SS scale (1) to contribute to the validation of the MBI-SS in a Latin context and (2) the use of the nonparametric statistical technique PLS focused on prediction.

An Improved Expeditious Meta-Heuristic Clustering Method for Classifying Student Psychological Issues with Homogeneous Characteristics

“…This aims to improve psychological management systems through early warning systems and continuous monitoring of at-risk students and increase problem alert efficiency [41]. To analyze burnout measures in students, highlighting the direct correlation between emotional tiredness and the onset of illnesses among participants is explored using partial least squares, and structural equation modeling is presented in [42]. The author classifies identical mental health classification in adolescents using latent profile analysis [43], however, it is bound to limited data size.…”

Fuzzy clustering algorithm for university students' psychological fitness and performance detection

“…Reyna-Castillo et al [ 30 ] deliberated the Partial Least Squares and Structural Equation Modeling (PLS-SEM) for Burnout Measures in College Students. Emotional fatigue was shown to have a direct and crucial correlation with the onset of illnesses the study's participants suffered.…”