Academic stressors as predictors of academic burnout in university students from the Peruvian Amazon

Abstract

Introduction: Academic burnout is a common phenomenon among students who face high academic demands, stress, and pressure, which can negatively affect their well-being and academic performance. Objective: To determine the academic stressors that predict academic burnout in a sample of university students from the Peruvian Amazon. M ethods: This is a quantitative, non-experimental, predictive study. The sample consists of 463 students from a private university who were administered the Academic Stressors Questionnaire and the Maslach Burnout Inventory Student Survey, instruments with adequate validity and reliability. Data were processed using SPSS statistical software version 25. Results: The multiple linear regression analysis showed an adequate model fit (F= 62.403; p<0.05) and determined that the relationship with teachers (β= 0.480), taking exams and doing classroom work (β= 0.443), balancing study and leisure time (β= 0.431), and taking many courses (β= 0.410) were the stressors that significantly predicted academic burnout. These predictors explained 34.7 % of the variability in academic burnout. Conclusions: It was determined that taking many courses, taking exams and doing classroom work, the relationship with teachers, and balancing study and leisure time predict academic burnout in a sample of university students from the Peruvian Amazon. Therefore, it is suggested that the psychological support services provided by universities be improved and awareness campaigns on mental health should be carried out to prevent academic burnout.