Dataset on Depression Symptoms and Severity among University Students in Bangladesh using Burn Depression Checklist

This dataset contains self-reported survey responses on depressive symptomatology collected from university students across multiple faculties and departments in Bangladesh. Data were gathered using a structured questionnaire that recorded demographic and academic information (age, gender, faculty, department, study year, and GPA/academic result) alongside responses to the 25-item Burns Depression Checklist (BDC). Each BDC item was rated on a 5-point Likert scale ("Not at all," "Somewhat," "Moderately," "A lot," "Extremely"), covering core depressive symptoms (mood, self-esteem, guilt, social withdrawal, motivation, sleep, appetite, and somatic complaints) as well as three safety-related items assessing suicidal ideation and self-harm risk. Total and item-level BDC scores were used to classify participants into six depression severity categories (No depression, Normal but Unhappy, Mild, Moderate, Severe, Extreme). The dataset is provided as a raw Excel file (Student Data Collection Form.xlsx), accompanied by a Python script (BD_student_BDC_eda_code.py) that performs data cleaning, descriptive statistics, reliability analysis (Cronbach's alpha), and generates 15 publication-quality (600 dpi) figures summarizing demographic distributions, BDC score distributions, item-level response patterns, inter-item correlations, and severity breakdowns by gender and academic year. This dataset may be useful for researchers studying student mental health, depression screening tool validation, or demographic/academic correlates of depressive symptoms in South Asian higher education settings. Note on sensitive content: Three items in the BDC relate to suicidal ideation and self-harm risk. Researchers using this dataset should handle it with appropriate ethical care, in line with their institution's guidelines for sensitive mental health data.