Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom
Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom
The COVID-19 pandemic (including lockdown) is likely to have had profound but diverse implications for mental health and well-being, yet little is known about individual experiences of the pandemic (positive and negative) and how this relates to mental health and well-being, as well as other important contextual variables. Here, we analyse data sampled in a large-scale manner from 379,875 people in the United Kingdom (UK) during 2020 to identify population variables associated with mood and mental health during the COVID-19 pandemic, and to
investigate self-perceived pandemic impact in relation to those variables. We report that while there are relatively small population-level differences in mood assessment scores pre- to peakUK lockdown, the size of the differences is larger for people from specific groups, e.g. older adults and people with lower incomes. Multiple dimensions underlie peoples’ perceptions, both positive and negative, of the pandemic’s impact on daily life. These dimensions explain
variance in mental health and can be statistically predicted from age, demographics, home and work circumstances, pre-existing conditions, maladaptive technology use and personality traits (e.g., compulsivity). We conclude that a holistic view, incorporating the broad range of relevant
population factors, can better characterise people whose mental health is most at risk during the COVID-19 pandemic.
COVID-19, Compulsivity, anxiety, compulsive, coronavirus, depression, impulsive, machine learning, mental health, mood, pandemic, poplulation, predictors, wellbeing
Chamberlain, Samuel
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Hampshire, Adam
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Hellyer, Peter
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Soreq, Eyal
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Mehta, Mitul A
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Ioannidis, Konstantinos
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Trender, William
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Grant, Jon E.
68b74bfc-0910-4325-aa34-24d285abfc19
December 2021
Chamberlain, Samuel
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Hampshire, Adam
08af1acb-f59f-4f42-a1ca-99fd2fb66da2
Hellyer, Peter
58a30a74-5f08-4ef8-8e5b-5f0ba869f98f
Soreq, Eyal
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Mehta, Mitul A
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Ioannidis, Konstantinos
0dfc1d89-41be-4d02-ae50-698117e80141
Trender, William
bef02dd4-a7a0-4f9e-8f3d-f8ff3f1fe617
Grant, Jon E.
68b74bfc-0910-4325-aa34-24d285abfc19
Chamberlain, Samuel, Hampshire, Adam, Hellyer, Peter, Soreq, Eyal, Mehta, Mitul A, Ioannidis, Konstantinos, Trender, William and Grant, Jon E.
(2021)
Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom.
Nature Communications, 12 (1), [4111].
(doi:10.1038/s41467-021-24365-5).
Abstract
The COVID-19 pandemic (including lockdown) is likely to have had profound but diverse implications for mental health and well-being, yet little is known about individual experiences of the pandemic (positive and negative) and how this relates to mental health and well-being, as well as other important contextual variables. Here, we analyse data sampled in a large-scale manner from 379,875 people in the United Kingdom (UK) during 2020 to identify population variables associated with mood and mental health during the COVID-19 pandemic, and to
investigate self-perceived pandemic impact in relation to those variables. We report that while there are relatively small population-level differences in mood assessment scores pre- to peakUK lockdown, the size of the differences is larger for people from specific groups, e.g. older adults and people with lower incomes. Multiple dimensions underlie peoples’ perceptions, both positive and negative, of the pandemic’s impact on daily life. These dimensions explain
variance in mental health and can be statistically predicted from age, demographics, home and work circumstances, pre-existing conditions, maladaptive technology use and personality traits (e.g., compulsivity). We conclude that a holistic view, incorporating the broad range of relevant
population factors, can better characterise people whose mental health is most at risk during the COVID-19 pandemic.
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s41467-021-24365-5
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Accepted/In Press date: 9 June 2021
Published date: December 2021
Additional Information:
Funding Information:
S.R.C. previously consulted for Promentis. He receives honoraria for journal editorial work from Elsevier. J.E.G. has received research grants from the T.L.C. Foundation for Body-Focused Repetitive Behaviors, Biohaven, Promentis and Avanir Pharmaceuticals. M.A.M. has received grant income from Takeda Pharmaceuticals, Johnson & Johnson and Lundbeck. A.H. is owner and founder of Future Cognition Ltd. and H2 Cognitive Designs Ltd., which develop custom cognitive assessment software for other university-based research groups. P.J.H. is the owner and co-founder of H2 Cognitive Designs Ltd. The authors report no other conflicts of interest.
Funding Information:
This study was conducted in collaboration with BBC2 Horizon. The study was supported by the UK Dementia Research Institute and Biomedical Research Centre at Imperial College London. Technology development was supported by EU-CIG EC Marie‐Curie CIG and NIHR grant II-LB-0715-20006 to A.H. E.S.’s role was supported by MRC grant MR/R005370/1 to A.H. W.T. is supported by the EPSRC Center for Doctoral Training in Neurotechnology under supervision of A.H. This research was funded in part by Wellcome [110049/Z/15/Z and 110049/Z/15/A] (Grant to S.R.C.). For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. M.A.M. is in part supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. We would like to acknowledge COST Action CA16207 ‘European Network for Problematic Usage of the Internet’, supported by COST (European Cooperation in Science and Technology), and the support of the National UK Research Network for Behavioural Addictions (NUK-BA).
Publisher Copyright:
© 2021, The Author(s).
Keywords:
COVID-19, Compulsivity, anxiety, compulsive, coronavirus, depression, impulsive, machine learning, mental health, mood, pandemic, poplulation, predictors, wellbeing
Identifiers
Local EPrints ID: 451709
URI: http://eprints.soton.ac.uk/id/eprint/451709
ISSN: 2041-1723
PURE UUID: 2a7bf196-9c31-4e7a-9621-88fc2868cbb3
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Date deposited: 21 Oct 2021 16:30
Last modified: 17 Mar 2024 04:03
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Contributors
Author:
Samuel Chamberlain
Author:
Adam Hampshire
Author:
Peter Hellyer
Author:
Eyal Soreq
Author:
Mitul A Mehta
Author:
Konstantinos Ioannidis
Author:
William Trender
Author:
Jon E. Grant
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