Social Science Research Network | 2021

Different Mental Health Responses to the COVID-19 Pandemic: Latent Class Trajectory Analysis Using Longitudinal UK Data

 
 
 
 
 
 
 
 
 
 
 

Abstract


Background: The UK population’s mental health declined at the pandemic onset. Convenience sample surveys indicate recovery began soon after. Using a probability sample, we tracked average mental health during the pandemic, characterised distinct mental health trajectories and identified predictors of deterioration. \n \nMethods: Secondary analysis of five waves of UK Household Longitudinal Survey from late April-early October 2020 and pre-pandemic data, 2018-2019. Mental health was assessed in 19,763 adults (≥16 years) using 12-item General Health Questionnaire. Latent class growth models identified discrete mental health trajectories and fixed-effects regression identified predictors of change in mental health. \n \nFindings: Average population mental health deteriorated with onset of the pandemic and did not begin improving until July 2020. Latent class analysis identified six distinct mental health trajectories up to October 2020. Three-quarters had consistently good (46·2%) or very good (30·9%) mental health. Two ‘recovery’ groups (15·8%) initially experienced marked declines in mental health, improving to their pre-pandemic levels by October. For 4·8%, mental health steadily deteriorated and for 2·3% it was very poor throughout. These two groups were more likely to have pre-existing mental or physical ill-health, live in deprived neighbourhoods and be non-white. Infection with COVID-19, local lockdown and financial difficulties all predicted subsequent mental health deterioration. \n \nInterpretation: Between April-October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. One-in-fourteen experienced deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions or COVID infection might benefit most from early intervention. \n \nFunding Statement: None. \n \nDeclaration of Interests: None. \n \nEthics Approval Statement: Ethics approval was granted by the University of Essex Ethics Committee for the COVID-19 web and telephone surveys (ETH1920-1271).

Volume None
Pages None
DOI 10.2139/SSRN.3784647
Language English
Journal Social Science Research Network

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