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

Ismail, Idari and Mohd Rofi, Muhammad Fahmi and Ahmad Iskandar, Ahmad Khuzairi Rusydi and Abdul Halim, Amir Hamzah and Tengku Jalal, Tengku Mardhiah and Azid @Maarof, Nur Niswah Naslina (2021) Logistic regression for assessing prevalence and socio-demographic correlates of depression during the Covid-19 pandemic / Idari Ismail ...[et al.]. Journal of Mathematics and Computing Science (JMCS), 7 (2). pp. 49-59. ISSN 0128-0767

Official URL: https://jmcs.com.my/

Abstract

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.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ismail, Idari
UNSPECIFIED
Mohd Rofi, Muhammad Fahmi
UNSPECIFIED
Ahmad Iskandar, Ahmad Khuzairi Rusydi
UNSPECIFIED
Abdul Halim, Amir Hamzah
UNSPECIFIED
Tengku Jalal, Tengku Mardhiah
UNSPECIFIED
Azid @Maarof, Nur Niswah Naslina
UNSPECIFIED
Subjects: H Social Sciences > HA Statistics > Statistical data
H Social Sciences > HA Statistics > Regression. Correlation
R Medicine > RC Internal Medicine > Chronic diseases
Divisions: Universiti Teknologi MARA, Kelantan > Machang Campus > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Journal of Mathematics and Computing Science (JMCS)
UiTM Journal Collections: UiTM Journal > Journal of Mathematics and Computing Science (JMCS)
ISSN: 0128-0767
Volume: 7
Number: 2
Page Range: pp. 49-59
Keywords: COVID-19, pandemic, depression, student, multiple logistic regression
Date: December 2021
URI: https://ir.uitm.edu.my/id/eprint/56384
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