Predictive Analysis of Stress and Burnout Among Medical Students: Exploring Personal and Environmental Contributors
Background: Medical education is widely recognized as a demanding and high-pressure environment. The intense academic workload, clinical responsibilities, and emotional challenges increase stress and the risk of burnout among medical students. The study aimed to identify key predictors and high-ris...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
ziauddin University
2025-07-01
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| Series: | Pakistan Journal of Medicine and Dentistry |
| Subjects: | |
| Online Access: | https://ojs.zu.edu.pk/pjmd/article/view/3806 |
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| Summary: | Background: Medical education is widely recognized as a demanding and high-pressure environment. The intense academic workload, clinical responsibilities, and emotional challenges increase stress and the risk of burnout among medical students. The study aimed to identify key predictors and high-risk profiles for stress and burnout among medical students using multiple regression analysis and CHAID decision tree models.
Methodology: A cross-sectional study was conducted on medical students (n = 250) from medical colleges in Multan, Pakistan, from April 2024 to October 2024. Standardized instruments were used to assess stress (PSS), burnout (OLBI), individual traits (BTPS-SF, GSE, BRS, MAAS), and contextual factors (WHOQOL-BREF), along with demographic data. Descriptive statistics summarized key variables. Multiple regression analysis identified significant predictors of stress and burnout. A CHAID decision tree model was applied to classify high-risk groups, with model validity evaluated through classification accuracy and risk estimates.
Results: Regression analysis showed that perfectionism (p < 0.001) and low self-efficacy (p < 0.001) were the strongest predictors of stress, explaining 45% of the variance. For burnout, lack of physical activity (p = 0.002) and weak social support (p < 0.001) were significant contributors (R² = 0.39, p < 0.001). The CHAID decision tree identified sleep quality (p < 0.001) as a critical moderator of stress, revealing that students with poor sleep and high perfectionism had the highest stress scores (M = 32.8, SD = 5.4). For burnout, the highest-risk subgroup consisted of physically inactive students who lacked family support (M = 45.2, SD = 6.1, p < 0.001).
Conclusion: Physical health, psychological health, social relationships, perfectionism, self- efficacy, sleep quality, physical activity, and social support significantly influence stress and burnout among medical students.
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| ISSN: | 2313-7371 2308-2593 |