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People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population
INTRODUCTION: CoVID-19 pandemic and the subsequent lockdown have impacted the sleep quality and the overall wellbeing of mankind. The present epidemiological study measured various aspects of sleep disturbance such as sleep quality, daytime impairments, negative emotionality, sleep hygiene, and well...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834060/ https://www.ncbi.nlm.nih.gov/pubmed/33485259 http://dx.doi.org/10.1016/j.sleep.2020.12.041 |
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author | Radhakrishnan, Arathi Govindaraj, Ramajayam Sasidharan, Arun Ravindra, P.N. Yadav, Ravi Kutty, Bindu M. |
author_facet | Radhakrishnan, Arathi Govindaraj, Ramajayam Sasidharan, Arun Ravindra, P.N. Yadav, Ravi Kutty, Bindu M. |
author_sort | Radhakrishnan, Arathi |
collection | PubMed |
description | INTRODUCTION: CoVID-19 pandemic and the subsequent lockdown have impacted the sleep quality and the overall wellbeing of mankind. The present epidemiological study measured various aspects of sleep disturbance such as sleep quality, daytime impairments, negative emotionality, sleep hygiene, and well-being associated with CoVID-19 pandemic among the Indian population. METHODS: This cross-sectional voluntary online survey (using Google form) was communicated across the country from 4th June to 3rd July 2020 through mail and social media applications. The responses received (N = 450) were categorized and validated using the latent class analysis and logistic regression tests respectively, and the classes and subclasses derived were profiled. These techniques are used for the first time in a CoVID-19 sleep study. RESULTS: Out of the three classes derived from the LCA, people with severe dyssomnia belonging to class 1 (33.3%) showed high daytime impairments, negative emotionality and high vulnerability towards CoVID-19 pandemic measures. In addition, the two subclasses derived from the severe dyssomnia group; one with negative emotionality predominance and the other with excessive daytime sleepiness, were similarly affected by CoVID-19 measures. People with moderate dyssomnia (class 2, 28.5%) showed frequent arousals with daytime impairments and the majority (38.2%) which fell in to class 3, the ‘no dyssomnia’ category, were not impacted by CoVID-19 pandemic. CONCLUSION: People with existing sleep problems or those who were vulnerable to the same were the ones affected by CoVID-19 pandemic. Those with inadequate emotional coping styles have showed heightened vulnerability. Proper medical and cognitive interventions are highly recommended for this population. No or moderate dyssomnia categories (class 3 and 2 respectively) were less impacted by CoVID-19. |
format | Online Article Text |
id | pubmed-7834060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78340602021-01-26 People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population Radhakrishnan, Arathi Govindaraj, Ramajayam Sasidharan, Arun Ravindra, P.N. Yadav, Ravi Kutty, Bindu M. Sleep Med Original Article INTRODUCTION: CoVID-19 pandemic and the subsequent lockdown have impacted the sleep quality and the overall wellbeing of mankind. The present epidemiological study measured various aspects of sleep disturbance such as sleep quality, daytime impairments, negative emotionality, sleep hygiene, and well-being associated with CoVID-19 pandemic among the Indian population. METHODS: This cross-sectional voluntary online survey (using Google form) was communicated across the country from 4th June to 3rd July 2020 through mail and social media applications. The responses received (N = 450) were categorized and validated using the latent class analysis and logistic regression tests respectively, and the classes and subclasses derived were profiled. These techniques are used for the first time in a CoVID-19 sleep study. RESULTS: Out of the three classes derived from the LCA, people with severe dyssomnia belonging to class 1 (33.3%) showed high daytime impairments, negative emotionality and high vulnerability towards CoVID-19 pandemic measures. In addition, the two subclasses derived from the severe dyssomnia group; one with negative emotionality predominance and the other with excessive daytime sleepiness, were similarly affected by CoVID-19 measures. People with moderate dyssomnia (class 2, 28.5%) showed frequent arousals with daytime impairments and the majority (38.2%) which fell in to class 3, the ‘no dyssomnia’ category, were not impacted by CoVID-19 pandemic. CONCLUSION: People with existing sleep problems or those who were vulnerable to the same were the ones affected by CoVID-19 pandemic. Those with inadequate emotional coping styles have showed heightened vulnerability. Proper medical and cognitive interventions are highly recommended for this population. No or moderate dyssomnia categories (class 3 and 2 respectively) were less impacted by CoVID-19. Elsevier B.V. 2021-03 2021-01-02 /pmc/articles/PMC7834060/ /pubmed/33485259 http://dx.doi.org/10.1016/j.sleep.2020.12.041 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Article Radhakrishnan, Arathi Govindaraj, Ramajayam Sasidharan, Arun Ravindra, P.N. Yadav, Ravi Kutty, Bindu M. People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title | People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title_full | People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title_fullStr | People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title_full_unstemmed | People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title_short | People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population |
title_sort | people with dyssomnia showed increased vulnerability to covid-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in indian population |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834060/ https://www.ncbi.nlm.nih.gov/pubmed/33485259 http://dx.doi.org/10.1016/j.sleep.2020.12.041 |
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