A CROSS-SECTIONAL STUDY ON DEPRESSION, ANXIETY, AND STRESS AMONG THE STUDENTS IN A MEDICAL COLLEGE OF WEST BENGAL: AN INSIGHT WITH THE HELP OF MACHINE LEARNING
Main Article Content
Keywords
Depression, Anxiety, Stress, Eastern India, Medical scholar, Mental health, Survey, Medical Student, Machine Learning
Abstract
Introduction: Mental morbidities like depression, anxiety, and stress are increasing and responsible for significant DALYs. Young age groups are at risk, but literature suggests medical undergraduates are at higher risk even in this age group. The current study hence aimed to estimate the prevalence of depression, anxiety, and stress among the students at a medical college in a west-central district of West Bengal, and to find out its determinants among the study population.
Methodology: A cross-sectional study was conducted in a medical college in a west-central district of West Bengal, among 212 undergraduate medical students following eligibility criteria. A standardised questionnaire DASS 21 had been used to assess depression, anxiety, and stress. Descriptive analyses were done using MS Excel followed by inferential analyses in Jupyter Notebook (python 3.11).
Results: The study found that 34% of participants had stress, 48% had depression, and 65% had anxiety. It was also found that about 30% of the participants had all three morbidities. Age, academic year, per capita family income, parental education as well as occupation, and current residence were found to be the statistically significant factors associated with either depression, anxiety, or stress in the Random Forest Classification model.
Conclusion:
The high prevalence of depression, anxiety, and stress among undergraduate medical students as identified by this study demands the attention of the policymakers and concerned stakeholders, and assurance of a friendly educational environment along with targeted counselling sessions to cope with these problems.
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