Predicting Academic Burnout Based on Mindfulness, Self-Compassion, and Teacher-Perceived Support in Secondary School Students

Abstract

The aim of this study is to predict academic burnout based on mindfulness, self-compassion, and teacher-perceived support in secondary school students. This is a descriptive correlational study with a sample of 385 secondary school students selected randomly from schools in Tehran. The research instruments included scales for mindfulness, self-compassion, teacher-perceived support, and academic burnout. The data were analyzed using SPSS version 27. Pearson correlation and multiple linear regression tests were employed for data analysis. The results showed that mindfulness, self-compassion, and teacher-perceived support were significantly negatively correlated with academic burnout. In the regression analysis, the model predicting academic burnout, including these three variables, explained 37% of the variance in academic burnout. Furthermore, the multiple regression analysis revealed that mindfulness, self-compassion, and teacher-perceived support significantly reduce academic burnout. This study concluded that mindfulness, self-compassion, and teacher-perceived support are effective factors in reducing academic burnout. Mindfulness and self-compassion interventions can be effectively utilized to reduce academic burnout in students. Additionally, teacher support can act as a protective factor against academic burnout.