Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions
Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions
BACKGROUND: There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic.
AIMS: To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts: Cohort 1 (N = 10,475, two time-points: winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence).
METHOD: Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions.
RESULTS: Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2.
CONCLUSIONS: These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.
Anxiety, COVID, Depression, Fatigue, Insomnia, SARS-CoV-2, Sleep, Well-being
Hampshire, Adam
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Trender, William
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Grant, Jon E
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Mirza, M Berk
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Moran, Rosalyn
2a827dd6-1ea9-4d4d-a1c4-8cbce149c65e
Hellyer, Peter J
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Chamberlain, Samuel R
8a0e09e6-f51f-4039-9287-88debe8d8b6f
April 2022
Hampshire, Adam
08af1acb-f59f-4f42-a1ca-99fd2fb66da2
Trender, William
bef02dd4-a7a0-4f9e-8f3d-f8ff3f1fe617
Grant, Jon E
07372bd5-8a0d-42b4-b41b-e376c652acf3
Mirza, M Berk
de6f6fd0-da02-435c-aac3-a054ed1eb178
Moran, Rosalyn
2a827dd6-1ea9-4d4d-a1c4-8cbce149c65e
Hellyer, Peter J
4f401a7f-3135-4d1d-a6ef-997317513aaa
Chamberlain, Samuel R
8a0e09e6-f51f-4039-9287-88debe8d8b6f
Hampshire, Adam, Trender, William, Grant, Jon E, Mirza, M Berk, Moran, Rosalyn, Hellyer, Peter J and Chamberlain, Samuel R
(2022)
Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions.
Comprehensive Psychiatry, 114, [152298].
(doi:10.1016/j.comppsych.2022.152298).
Abstract
BACKGROUND: There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic.
AIMS: To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts: Cohort 1 (N = 10,475, two time-points: winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence).
METHOD: Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions.
RESULTS: Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2.
CONCLUSIONS: These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.
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e-pub ahead of print date: 31 January 2022
Published date: April 2022
Additional Information:
Funding Information:
This work was supported by the Dementia Research Institute, Care Research and Technology Centre . SRC's role in this work was funded by Wellcome ( 110049/Z/15/Z & A ). PJHs role was supported by the NIHR Maudsley BRC .
Publisher Copyright:
© 2022
Keywords:
Anxiety, COVID, Depression, Fatigue, Insomnia, SARS-CoV-2, Sleep, Well-being
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Local EPrints ID: 456277
URI: http://eprints.soton.ac.uk/id/eprint/456277
ISSN: 0010-440X
PURE UUID: 4b5d52bf-5b43-47d4-b0a5-ccc07fd3d385
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Date deposited: 27 Apr 2022 00:58
Last modified: 30 Aug 2024 02:00
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Author:
Adam Hampshire
Author:
William Trender
Author:
Jon E Grant
Author:
M Berk Mirza
Author:
Rosalyn Moran
Author:
Peter J Hellyer
Author:
Samuel R Chamberlain
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