Academic self-efficacy, self-esteem, satisfaction with studies, and virtual media use as depression and emotional exhaustion predictors among college students during COVID-19

Abstract

The aim of the study was to explore the relationship between depression, emotional exhaustion, self-esteem, satisfaction with studies, academic self-efficacy, and the use of virtual media in Peruvian university students during the coronavirus disease 2019 (COVID-19) pandemic. A total of 569 college students (61.9% female), with a mean age of 21.73 years (standard deviation = 4.95), responded to the following questionnaires: Academic Self-Efficacy Scale, Single Item Self-Esteem Scale, Brief Scale of Satisfaction with Studies, Scale of Use of Virtual Media, Patient Health Questionnarie-2, and Single Item of Academic Emotional Exhaustion. Correlation statistics, regression models, and structural equation modeling (SEM) were used for data analysis. The results demonstrated a direct and significant correlation between virtual media use, academic self-efficacy, self-esteem, depression, and emotional exhaustion (p < .01). In addition, satisfaction with studies (β = −0.13), academic self-efficacy (β = −0.19), self-esteem (β = −0.14), and emotional exhaustion (β = 0.19) predicted depression significantly, whereas virtual media use (β = 0.17), study satisfaction (β = 0.09), and depression (β = 0.20) predicted emotional exhaustion associated with academics. The SEM model indicated that self-esteem, satisfaction with studies, and academic self-efficacy negatively predict depression, whereas academic self-efficacy positively predicts virtual media use. Finally, both virtual media use and depression positively predict emotional exhaustion. This model presents optimal goodness-of-fit indices (X2 = 8.926, df = 6, p = .178; comparative fit = .991, Tucker–Lewis = .979, root mean square error of approximation = .029 [confidence interval 90% = .000–.067], standardized root mean square residual = .022). Thus, academic self-efficacy, self-esteem, satisfaction with studies, and virtual media use predict depression and emotional exhaustion among college students during the COVID-19 pandemic.