Modelling the risk factors of depression among students using binary logistic regression
DOI:
https://doi.org/10.55573/JISED.118780Keywords:
Depression, Sleep Quality, Physical Activity and Perceived Social SupportAbstract
Depression is one of the most common mental health problems among university students and may negatively affect their daily activities and overall well-being. The purpose of this study was to assess the prevalence of depression and explore factors such as gender, academic performance, sleep quality, physical activity and perceived social support associated with depression among university students. A cross-sectional study was conducted among 98 undergraduate students at Universiti Teknologi MARA (UiTM) Kota Bharu. The data were collected using a structured questionnaire that comprised the Center for Epidemiologic Studies Depression Scale (CESD-10), Sleep Condition Indicator (SCI), International Physical Activity Questionnaire-Short Form (IPAQ-SF) and Multidimensional Scale of Perceived Social Support (MSPSS). Binary logistic regression analysis revealed that sleep quality and perceived social support were significant factors associated of depression. Students who had good quality of sleep and high level of perceived social support exhibited reduced odds of depression. In conclusion, sleep quality and perceived social support were significantly associated with depression among university students. This study provides an insight into the association between sleep quality and perceived social support with depression. Findings can be used to inform interventions to promote healthy sleep and strengthen social support to reduce the risk of depression and improve students’mental well-being.
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