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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
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
2041-1723
Hampshire, Adam
08af1acb-f59f-4f42-a1ca-99fd2fb66da2
Hellyer, Peter J.
58a30a74-5f08-4ef8-8e5b-5f0ba869f98f
Soreq, Eyal
bda53264-e7ea-4bd5-9f15-defd5a18d9b2
Mehta, Mitul A.
9acd9e5e-002b-48df-b9b5-020d4a0d2d8e
Ioannidis, Konstantinos
0dfc1d89-41be-4d02-ae50-698117e80141
Trender, William
bef02dd4-a7a0-4f9e-8f3d-f8ff3f1fe617
Grant, Jon E.
07372bd5-8a0d-42b4-b41b-e376c652acf3
Chamberlain, Samuel R.
8a0e09e6-f51f-4039-9287-88debe8d8b6f
Hampshire, Adam
08af1acb-f59f-4f42-a1ca-99fd2fb66da2
Hellyer, Peter J.
58a30a74-5f08-4ef8-8e5b-5f0ba869f98f
Soreq, Eyal
bda53264-e7ea-4bd5-9f15-defd5a18d9b2
Mehta, Mitul A.
9acd9e5e-002b-48df-b9b5-020d4a0d2d8e
Ioannidis, Konstantinos
0dfc1d89-41be-4d02-ae50-698117e80141
Trender, William
bef02dd4-a7a0-4f9e-8f3d-f8ff3f1fe617
Grant, Jon E.
07372bd5-8a0d-42b4-b41b-e376c652acf3
Chamberlain, Samuel R.
8a0e09e6-f51f-4039-9287-88debe8d8b6f

Hampshire, Adam, Hellyer, Peter J., Soreq, Eyal, Mehta, Mitul A., Ioannidis, Konstantinos, Trender, William, Grant, Jon E. and Chamberlain, Samuel R. (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).

Record type: Article

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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Accepted/In Press date: 9 June 2021
e-pub ahead of print date: 16 July 2021
Published date: December 2021
Additional Information: A correction has been attached to this output located at https://www.nature.com/articles/s41467-021-25271-6 and https://doi.org/10.1038/s41467-021-25271-6
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
ORCID for Samuel R. Chamberlain: ORCID iD orcid.org/0000-0001-7014-8121

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Date deposited: 21 Oct 2021 16:30
Last modified: 30 Aug 2024 02:00

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Contributors

Author: Adam Hampshire
Author: Peter J. Hellyer
Author: Eyal Soreq
Author: Mitul A. Mehta
Author: Konstantinos Ioannidis
Author: William Trender
Author: Jon E. Grant
Author: Samuel R. Chamberlain ORCID iD

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