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Research Article Open access CC BY 4.0

The Association between Depression, Daytime Sleepiness, Chronotype and Fatigue among the Students

Nishi Soni, Saurabh Jaiswal, Sudhir Kumar, Shalie Malik, Sangeeta Rani

Asian Journal of Medicine and Health · pp. 204–213 · Published 27 Jun 2024

10.9734/ajmah/2024/v22i71061

Abstract

Fatigue and excessive daytime sleepiness (EDS) are frequently conflated in everyday life, but they are separate concepts with distinct symptoms. Despite their potential to coexist or occur independently, their interplay with depression remains largely unexplored. This study investigates the complex relationship between fatigue, excessive daytime sleepiness (EDS), and depression among students, aiming to unravel their relative associations. A cross-sectional survey of Indian school students (N=450) aged 11 to 20 (15.2±1.46) was analysed. The study used self-reported measures such as the Fatigue Severity Scale (FSS), Epworth Sleepiness Scale (ESS), and the Center for Epidemiologic Studies Depression Scale (CES-D). The findings revealed significant associations between depression and various combinations of sleepiness and fatigue, with the E+F+ group showing the strongest correlation. Depression was significantly higher in excessive daytime sleepers (N= 165, 69.9%) (P < 0.001) and fatigue (N= 167, 70.8%) (p < 0.001). Depression was found positively correlated with fatigue (r =0.332, p < 0.001 and daytime sleepiness (r=0.213, p<0.001). Chronotype was found negatively correlated with fatigue (r=-0.124, p<0.001), daytime sleepiness (r=-0.105, p<0.05), and depression (r=-0.198, p<0.001). These findings underscore a significant association (p<0.001) between depression and the presence of both excessive daytime sleepiness and fatigue. This revelation demands a nuanced approach to mental health interventions, recognizing the shared underlying mechanisms and advocating for comprehensive strategies that address these intertwined facets of student well-being.

Chronotype depression fatigue sleepiness

Cited by 3

An Explainable Machine Learning Study of Behavioral and Psychological Determinants of Depression in the Academic Environment

T. R. Noviandy, Ghalieb Mutig Idroes, Irsan Hardi · Journal of Educational Management and Learning · 2025

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