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Mental health issues assessment using tools during COVID-19 pandemic

COVID-19 has brought distress among people as pandemic has impacted the globe not only economically or physically, but also psychologically by degrading their mental health. Several research were done in the past which tried to capture these issues but post-covid situation needs to be critically han...

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Autores principales: Rao, Hamnah, Gupta, Meenu, Agarwal, Parul, Bhatia, Surbhi, Bhardwaj, Rajat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742669/
https://www.ncbi.nlm.nih.gov/pubmed/36531968
http://dx.doi.org/10.1007/s11334-022-00510-1
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author Rao, Hamnah
Gupta, Meenu
Agarwal, Parul
Bhatia, Surbhi
Bhardwaj, Rajat
author_facet Rao, Hamnah
Gupta, Meenu
Agarwal, Parul
Bhatia, Surbhi
Bhardwaj, Rajat
author_sort Rao, Hamnah
collection PubMed
description COVID-19 has brought distress among people as pandemic has impacted the globe not only economically or physically, but also psychologically by degrading their mental health. Several research were done in the past which tried to capture these issues but post-covid situation needs to be critically handled and analyzed so that corrective measures for cure and support can be taken. The current work is an attempt to observe the mental health issues (anxiety and depression) that occurred during the lockdown by combining a few pre-designed questionnaires. The online survey included 244 respondents (females = 126, males = 118) and when we thoroughly examined gender, age group, and occupational activity as three main factors, the results showed that female students aged 21–35 were affected more than male students of the same age group. In this study, we used a 4-item Geriatric Depression Scale (GDS-4) as a depression screening instrument and discovered that 225 out of total respondents were depressed. Using the Generalized Anxiety Disorder (GAD-7), a self-administered anxiety tool, we found 103 responders with mild, 87 with moderate, 12 with severe, and 42 with no anxiety symptoms. Patient Health Questionnaire (PHQ-9) showed the symptoms of mental disorders where 68 individuals had mild, 85 had moderate, 37 had moderately severe, 12 had severe, and 42 had no symptoms. With the help of multiple linear regression analysis, demographic data were evaluated, and later results were compared between GDS-4, GAD-7, and PHQ-9 using correlation coefficients. This will help practitioners and individuals to focus on their physiological health and adopt diagnostic measures.
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spelling pubmed-97426692022-12-12 Mental health issues assessment using tools during COVID-19 pandemic Rao, Hamnah Gupta, Meenu Agarwal, Parul Bhatia, Surbhi Bhardwaj, Rajat Innov Syst Softw Eng S.i. : Intelligence for Systems and Software Engineering COVID-19 has brought distress among people as pandemic has impacted the globe not only economically or physically, but also psychologically by degrading their mental health. Several research were done in the past which tried to capture these issues but post-covid situation needs to be critically handled and analyzed so that corrective measures for cure and support can be taken. The current work is an attempt to observe the mental health issues (anxiety and depression) that occurred during the lockdown by combining a few pre-designed questionnaires. The online survey included 244 respondents (females = 126, males = 118) and when we thoroughly examined gender, age group, and occupational activity as three main factors, the results showed that female students aged 21–35 were affected more than male students of the same age group. In this study, we used a 4-item Geriatric Depression Scale (GDS-4) as a depression screening instrument and discovered that 225 out of total respondents were depressed. Using the Generalized Anxiety Disorder (GAD-7), a self-administered anxiety tool, we found 103 responders with mild, 87 with moderate, 12 with severe, and 42 with no anxiety symptoms. Patient Health Questionnaire (PHQ-9) showed the symptoms of mental disorders where 68 individuals had mild, 85 had moderate, 37 had moderately severe, 12 had severe, and 42 had no symptoms. With the help of multiple linear regression analysis, demographic data were evaluated, and later results were compared between GDS-4, GAD-7, and PHQ-9 using correlation coefficients. This will help practitioners and individuals to focus on their physiological health and adopt diagnostic measures. Springer London 2022-12-12 /pmc/articles/PMC9742669/ /pubmed/36531968 http://dx.doi.org/10.1007/s11334-022-00510-1 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle S.i. : Intelligence for Systems and Software Engineering
Rao, Hamnah
Gupta, Meenu
Agarwal, Parul
Bhatia, Surbhi
Bhardwaj, Rajat
Mental health issues assessment using tools during COVID-19 pandemic
title Mental health issues assessment using tools during COVID-19 pandemic
title_full Mental health issues assessment using tools during COVID-19 pandemic
title_fullStr Mental health issues assessment using tools during COVID-19 pandemic
title_full_unstemmed Mental health issues assessment using tools during COVID-19 pandemic
title_short Mental health issues assessment using tools during COVID-19 pandemic
title_sort mental health issues assessment using tools during covid-19 pandemic
topic S.i. : Intelligence for Systems and Software Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742669/
https://www.ncbi.nlm.nih.gov/pubmed/36531968
http://dx.doi.org/10.1007/s11334-022-00510-1
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