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COVID-19 impact on mental health

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has posed a significant influence on public mental health. Current efforts focus on alleviating the impacts of the disease on public health and the economy, with the psychological effects due to COVID-19 relatively ignored. In this researc...

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Autores principales: Cui, Jingyu, Lu, Jingwei, Weng, Yijia, Yi, Grace Y., He, Wenqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758244/
https://www.ncbi.nlm.nih.gov/pubmed/35026998
http://dx.doi.org/10.1186/s12874-021-01411-w
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author Cui, Jingyu
Lu, Jingwei
Weng, Yijia
Yi, Grace Y.
He, Wenqing
author_facet Cui, Jingyu
Lu, Jingwei
Weng, Yijia
Yi, Grace Y.
He, Wenqing
author_sort Cui, Jingyu
collection PubMed
description BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has posed a significant influence on public mental health. Current efforts focus on alleviating the impacts of the disease on public health and the economy, with the psychological effects due to COVID-19 relatively ignored. In this research, we are interested in exploring the quantitative characterization of the pandemic impact on public mental health by studying an online survey dataset of the United States. METHODS: The analyses are conducted based on a large scale of online mental health-related survey study in the United States, conducted over 12 consecutive weeks from April 23, 2020 to July 21, 2020. We are interested in examining the risk factors that have a significant impact on mental health as well as in their estimated effects over time. We employ the multiple imputation by chained equations (MICE) method to deal with missing values and take logistic regression with the least absolute shrinkage and selection operator (Lasso) method to identify risk factors for mental health. RESULTS: Our analysis shows that risk predictors for an individual to experience mental health issues include the pandemic situation of the State where the individual resides, age, gender, race, marital status, health conditions, the number of household members, employment status, the level of confidence of the future food affordability, availability of health insurance, mortgage status, and the information of kids enrolling in school. The effects of most of the predictors seem to change over time though the degree varies for different risk factors. The effects of risk factors, such as States and gender show noticeable change over time, whereas the factor age exhibits seemingly unchanged effects over time. CONCLUSIONS: The analysis results unveil evidence-based findings to identify the groups who are psychologically vulnerable to the COVID-19 pandemic. This study provides helpful evidence for assisting healthcare providers and policymakers to take steps for mitigating the pandemic effects on public mental health, especially in boosting public health care, improving public confidence in future food conditions, and creating more job opportunities. TRIAL REGISTRATION: This article does not report the results of a health care intervention on human participants. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01411-w.
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spelling pubmed-87582442022-01-14 COVID-19 impact on mental health Cui, Jingyu Lu, Jingwei Weng, Yijia Yi, Grace Y. He, Wenqing BMC Med Res Methodol Research BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has posed a significant influence on public mental health. Current efforts focus on alleviating the impacts of the disease on public health and the economy, with the psychological effects due to COVID-19 relatively ignored. In this research, we are interested in exploring the quantitative characterization of the pandemic impact on public mental health by studying an online survey dataset of the United States. METHODS: The analyses are conducted based on a large scale of online mental health-related survey study in the United States, conducted over 12 consecutive weeks from April 23, 2020 to July 21, 2020. We are interested in examining the risk factors that have a significant impact on mental health as well as in their estimated effects over time. We employ the multiple imputation by chained equations (MICE) method to deal with missing values and take logistic regression with the least absolute shrinkage and selection operator (Lasso) method to identify risk factors for mental health. RESULTS: Our analysis shows that risk predictors for an individual to experience mental health issues include the pandemic situation of the State where the individual resides, age, gender, race, marital status, health conditions, the number of household members, employment status, the level of confidence of the future food affordability, availability of health insurance, mortgage status, and the information of kids enrolling in school. The effects of most of the predictors seem to change over time though the degree varies for different risk factors. The effects of risk factors, such as States and gender show noticeable change over time, whereas the factor age exhibits seemingly unchanged effects over time. CONCLUSIONS: The analysis results unveil evidence-based findings to identify the groups who are psychologically vulnerable to the COVID-19 pandemic. This study provides helpful evidence for assisting healthcare providers and policymakers to take steps for mitigating the pandemic effects on public mental health, especially in boosting public health care, improving public confidence in future food conditions, and creating more job opportunities. TRIAL REGISTRATION: This article does not report the results of a health care intervention on human participants. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01411-w. BioMed Central 2022-01-14 /pmc/articles/PMC8758244/ /pubmed/35026998 http://dx.doi.org/10.1186/s12874-021-01411-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cui, Jingyu
Lu, Jingwei
Weng, Yijia
Yi, Grace Y.
He, Wenqing
COVID-19 impact on mental health
title COVID-19 impact on mental health
title_full COVID-19 impact on mental health
title_fullStr COVID-19 impact on mental health
title_full_unstemmed COVID-19 impact on mental health
title_short COVID-19 impact on mental health
title_sort covid-19 impact on mental health
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758244/
https://www.ncbi.nlm.nih.gov/pubmed/35026998
http://dx.doi.org/10.1186/s12874-021-01411-w
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