Logistic regression for assessing prevalence and socio-demographic correlates of depression during the Covid-19 pandemic / Idari Ismail ...[et al.]

The outbreak of COVID-19 that emerged in Wuhan, China has spread as a global outbreak in a few months, resulting in billions into lockdown. This pandemic has caused a major health burden and has significantly impacted the mental health of the students due to the closure of educational institutions. Therefore, this study aimed to determine the depression level among university undergraduate students in Kelantan and its predicting factors. A cross-sectional study was conducted among 366 undergraduate students. The validated Patient Health Questionnaire- 9 (PHQ-9) was used to evaluate depression. The results indicated that 45.21% of the students experienced mild depression, 19.73% had moderate severe anxiety, and 15.18% reported moderately severe depression. Multiple logistic regression has been applied for predicting the factors affecting the depression level of the students during the Covid-19 pandemic. The dependent variable is the depression status where it is categorized into 0 and 1; 0 denoting depressed=”no” and 1 denoting depressed =” yes”. The results of binary logistic regression suggested that younger students had depression (OR=1.802, 95% CI = 1.029 - 3.154) and female students were more likely to have depression (OR=2.072, 95% CI = 1.066 - 4.024). The results also found that students with higher CGPA had a lower chance of having depression (OR = 0.331, 95% CI= 0.13 - 0.846). The findings of this study highlight the needs of psychological intervention programs in order to identify students who may need support regarding depression.