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Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data

BACKGROUND: The mental health of the UK population declined at the onset of the COVID-19 pandemic. Convenience sample surveys indicate that recovery began soon after. Using a probability sample, we tracked mental health during the pandemic to characterise mental health trajectories and identify pred...

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Autores principales: Pierce, Matthias, McManus, Sally, Hope, Holly, Hotopf, Matthew, Ford, Tamsin, Hatch, Stephani L, John, Ann, Kontopantelis, Evangelos, Webb, Roger T, Wessely, Simon, Abel, Kathryn M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764381/
https://www.ncbi.nlm.nih.gov/pubmed/33965057
http://dx.doi.org/10.1016/S2215-0366(21)00151-6
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author Pierce, Matthias
McManus, Sally
Hope, Holly
Hotopf, Matthew
Ford, Tamsin
Hatch, Stephani L
John, Ann
Kontopantelis, Evangelos
Webb, Roger T
Wessely, Simon
Abel, Kathryn M
author_facet Pierce, Matthias
McManus, Sally
Hope, Holly
Hotopf, Matthew
Ford, Tamsin
Hatch, Stephani L
John, Ann
Kontopantelis, Evangelos
Webb, Roger T
Wessely, Simon
Abel, Kathryn M
author_sort Pierce, Matthias
collection PubMed
description BACKGROUND: The mental health of the UK population declined at the onset of the COVID-19 pandemic. Convenience sample surveys indicate that recovery began soon after. Using a probability sample, we tracked mental health during the pandemic to characterise mental health trajectories and identify predictors of deterioration. METHODS: This study was a secondary analysis of five waves of the UK Household Longitudinal Study (a large, national, probability-based survey that has been collecting data continuously since January, 2009) from late April to early October, 2020 and pre-pandemic data taken from 2018–19. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). We used latent class mixed models to identify discrete mental health trajectories and fixed-effects regression to identify predictors of change in mental health. FINDINGS: Mental health was assessed in 19 763 adults (≥16 years; 11 477 [58·1%] women and 8287 [41·9%] men; 3453 [17·5%] participants from minority ethnic groups). Mean population mental health deteriorated with the onset of the pandemic and did not begin improving until July, 2020. Latent class analysis identified five distinct mental health trajectories up to October 2020. Most individuals in the population had either consistently good (7437 [39·3%] participants) or consistently very good (7623 [37·5%] participants) mental health across the first 6 months of the pandemic. A recovering group (1727 [12·0%] participants) showed worsened mental health during the initial shock of the pandemic and then returned to around pre-pandemic levels of mental health by October, 2020. The two remaining groups were characterised by poor mental health throughout the observation period; for one group, (523 [4·1%] participants) there was an initial worsening in mental health that was sustained with highly elevated scores. The other group (1011 [7·0%] participants) had little initial acute deterioration in their mental health, but reported a steady and sustained decline in mental health over time. These last two groups were more likely to have pre-existing mental or physical ill-health, to live in deprived neighbourhoods, and be of Asian, Black or mixed ethnicity. Infection with SARS-CoV-2, local lockdown, and financial difficulties all predicted a subsequent deterioration in mental health. INTERPRETATION: Between April and October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. Around one in nine individuals had deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions, or infection with SARS-CoV-2 might benefit most from early intervention. FUNDING: None.
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spelling pubmed-97643812022-12-20 Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data Pierce, Matthias McManus, Sally Hope, Holly Hotopf, Matthew Ford, Tamsin Hatch, Stephani L John, Ann Kontopantelis, Evangelos Webb, Roger T Wessely, Simon Abel, Kathryn M Lancet Psychiatry Articles BACKGROUND: The mental health of the UK population declined at the onset of the COVID-19 pandemic. Convenience sample surveys indicate that recovery began soon after. Using a probability sample, we tracked mental health during the pandemic to characterise mental health trajectories and identify predictors of deterioration. METHODS: This study was a secondary analysis of five waves of the UK Household Longitudinal Study (a large, national, probability-based survey that has been collecting data continuously since January, 2009) from late April to early October, 2020 and pre-pandemic data taken from 2018–19. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). We used latent class mixed models to identify discrete mental health trajectories and fixed-effects regression to identify predictors of change in mental health. FINDINGS: Mental health was assessed in 19 763 adults (≥16 years; 11 477 [58·1%] women and 8287 [41·9%] men; 3453 [17·5%] participants from minority ethnic groups). Mean population mental health deteriorated with the onset of the pandemic and did not begin improving until July, 2020. Latent class analysis identified five distinct mental health trajectories up to October 2020. Most individuals in the population had either consistently good (7437 [39·3%] participants) or consistently very good (7623 [37·5%] participants) mental health across the first 6 months of the pandemic. A recovering group (1727 [12·0%] participants) showed worsened mental health during the initial shock of the pandemic and then returned to around pre-pandemic levels of mental health by October, 2020. The two remaining groups were characterised by poor mental health throughout the observation period; for one group, (523 [4·1%] participants) there was an initial worsening in mental health that was sustained with highly elevated scores. The other group (1011 [7·0%] participants) had little initial acute deterioration in their mental health, but reported a steady and sustained decline in mental health over time. These last two groups were more likely to have pre-existing mental or physical ill-health, to live in deprived neighbourhoods, and be of Asian, Black or mixed ethnicity. Infection with SARS-CoV-2, local lockdown, and financial difficulties all predicted a subsequent deterioration in mental health. INTERPRETATION: Between April and October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. Around one in nine individuals had deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions, or infection with SARS-CoV-2 might benefit most from early intervention. FUNDING: None. Elsevier Ltd. 2021-07 2021-05-06 /pmc/articles/PMC9764381/ /pubmed/33965057 http://dx.doi.org/10.1016/S2215-0366(21)00151-6 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Articles
Pierce, Matthias
McManus, Sally
Hope, Holly
Hotopf, Matthew
Ford, Tamsin
Hatch, Stephani L
John, Ann
Kontopantelis, Evangelos
Webb, Roger T
Wessely, Simon
Abel, Kathryn M
Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title_full Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title_fullStr Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title_full_unstemmed Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title_short Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data
title_sort mental health responses to the covid-19 pandemic: a latent class trajectory analysis using longitudinal uk data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764381/
https://www.ncbi.nlm.nih.gov/pubmed/33965057
http://dx.doi.org/10.1016/S2215-0366(21)00151-6
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