Carranza Esteban RF, Mamani-Benito O, Morales-García WC, Caycho-Rodríguez T, Ruiz Mamani PG. Academic self-efficacy, self-esteem, satisfaction with studies, and virtual media use as depression and emotional exhaustion predictors among college students during COVID-19.
Heliyon 2022;
8:e11085. [PMID:
36281229 PMCID:
PMC9583623 DOI:
10.1016/j.heliyon.2022.e11085]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/09/2022] [Accepted: 10/10/2022] [Indexed: 11/07/2022] Open
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.
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