Published in

MDPI, International Journal of Environmental Research and Public Health, 9(19), p. 4940, 2022

DOI: 10.3390/ijerph19094940

Links

Tools

Export citation

Search in Google Scholar

Sleep Quality, Insomnia, Anxiety, Fatigue, Stress, Memory and Active Coping during the COVID-19 Pandemic

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Background: The current study aimed to evaluate the impact of the coronavirus (COVID-19) pandemic on sleep quality, insomnia, anxiety, stress, fatigue and active coping in the United States. Methods: This was a cross-sectional study using a publicly available database taken from the Boston College COVID-19 Sleep and Well-Being Dataset. We have selected the most recent data that included information about sleep quality and other measures, including insomnia, anxiety, stress, fatigue and coping, collected between 22 February–8 March 2021. Results: A total of 476 subjects were included in the analysis. The mean (SD) age of the study population was 38.8 (17.8) years, and there were more females (85%) than males. The population had a mean (SD) score of the Pittsburgh Sleep Quality Index (PSQI) of 6 (3.2), with 65% having the prevalence of poor sleep quality (defined as PSQ ≥ 5; n = 311). The mean (SD) score for Insomnia Severity Index (ISI) was 6.9 (5.2), with 55 subjects (11.5%) having clinical insomnia (defined as ISI ≥ 15); of whom 9% had severe clinical insomnia. There were positive correlations between PSQI and ISI (r = 0.76, p < 0.001), PROMIS fatigue scale (r = 0.53, p < 0.001), Generalized Anxiety Disorder-7 (GAD-7) (r = 0.46, p < 0.001), and Perceived Stress Scale (PSS) (r = 0.44, p < 0.001). The PSQI was inversely correlated with the John Henryism Active Coping Scale (JHACS) and memory scale. In the multivariate regression model, JHACS, ISI, fatigue, PSS and GAD-7 were significant predictors of PSQI, and these variables accounted for 62% of the variance of PSQI, adjusted for age and gender. Conclusion: An important contribution to the literature is made by this research, which demonstrates the significant prevalence of poor sleep quality and its association with insomnia and other mental and physical well-being. It also underlines the need to prioritise policy and public health efforts to address sleep issues that have substantial health and economic effects for both individuals and the population at large.