Depression, anxiety, and burnout among medical students and residents of a medical school in Nepal: a cross-sectional study

Abstract

Background: Medical students and residents were found to have suffered from depression, anxiety, and burnout in various studies. However, these entities have not been adequately explored in the context of Nepal. We proposed to determine the prevalence of depression, anxiety, burnout, their associated factors, and identify their predictors in a sample of medical students and residents in a Nepalese medical school. Methods: It was a cross-sectional study with 651 medical students and residents chosen at random between December 2018 and February 2019. The validated Nepali version of Hospital Anxiety and Depression Scale, the Copenhagen Burnout Inventory, and Medical Students' Stressor Questionnaire were used to assess depression, anxiety, burnout, and stressors respectively. We used univariate and multivariable logistic regression analyses to identify the correlation of predictor variables with depression, anxiety, and burnout. Results: The overall prevalence of burnout (48.8%; 95% CI 44.9-52.7) and anxiety (45.3%; 95% CI 41.4-49.2) was more than that of depression (31%; 95% CI 27.5-34.7). Burnout and depression were more prevalent in residents than in medical students (burnout: 64.5% vs 37.6%, P-value < 0.0001; depression: 33.7% vs 29.1%, P-value 0.21). Whereas, medical students were found more anxious than residents (46.3% versus 43.96%, P-value 0.55). Academic related stressors caused high-grade stress to participants. Multivariable model for depression significantly showed anxiety, personal burnout, and work-related burnout as risk enhancing correlates; satisfaction with academic performance as a protective correlate. Similarly, the multivariate model for anxiety significantly identified female gender, depression, personal burnout, teaching and learning related stressors, and past history of mental illness as risk enhancing correlates; being satisfied with academic performance, getting adequate sleep, and being a secondyear resident as protective correlates. The logistic model for burnout significantly showed being a first-year resident, depression, anxiety, and drive and desire related stressors as positive predictors. None of the variables were identified as significant negative predictors of burnout.

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