Mental health in the UK during the COVID-19 pandemic: cross-sectional analyses from a community cohort study

  1. Ru Jia
  2. Kieran Ayling
  3. Trudie Chalder
  4. Adam Massey
  5. Elizabeth Broadbent
  6. Carol Coupland
  7. Kavita Vedhara

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Abstract

Previous pandemics have resulted in significant consequences for mental health. Here, we report the mental health sequelae of the COVID-19 pandemic in a UK cohort and examine modifiable and non-modifiable explanatory factors associated with mental health outcomes. We focus on the first wave of data collection, which examined short-term consequences for mental health, as reported during the first 4–6 weeks of social distancing measures being introduced.

Design

Cross-sectional online survey.

Setting

Community cohort study.

Participants

N=3097 adults aged ≥18 years were recruited through a mainstream and social media campaign between 3 April 2020 and 30 April 2020. The cohort was predominantly female (n=2618); mean age 44 years; 10% (n=296) from minority ethnic groups; 50% (n=1559) described themselves as key workers and 20% (n=649) identified as having clinical risk factors putting them at increased risk of COVID-19.

Main outcome measures

Depression, anxiety and stress scores.

Results

Mean scores for depression ( x - =7.69, SD=6.0), stress ( x - =6.48, SD=3.3) and anxiety ( x - = 6.48, SD=3.3) significantly exceeded population norms (all p<0.0001). Analysis of non-modifiable factors hypothesised to be associated with mental health outcomes indicated that being younger, female and in a recognised COVID-19 risk group were associated with increased stress, anxiety and depression, with the final multivariable models accounting for 7%–14% of variance. When adding modifiable factors, significant independent effects emerged for positive mood, perceived loneliness and worry about getting COVID-19 for all outcomes, with the final multivariable models accounting for 54%–57% of total variance.

Conclusions

Increased psychological morbidity was evident in this UK sample and found to be more common in younger people, women and in individuals who identified as being in recognised COVID-19 risk groups. Public health and mental health interventions able to ameliorate perceptions of risk of COVID-19, worry about COVID-19 loneliness and boost positive mood may be effective.

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  1. Version published to 10.1136/bmjopen-2020-040620
  2. ScreenIT

    SciScore for 10.1101/2020.05.14.20102012: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: All media directed potential participants to the study website (http://www.covidstressstudy.co.uk) through which they accessed the information sheet, consent form and online survey.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using STATA (version 16).
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Finally, we would like to acknowledge several limitations. These include the cross-sectional design of the work which impedes an analysis of cause and effect; the limited generalisability of our cohort inflicted by the self-selected community cohort design and the absence of information on pre-existing mental health conditions which are likely to impact on the severity and prevalence of psychological morbidity.1 Nonetheless, we are among the first to provide evidence from a large cohort on the mental health impact of the COVID-19 pandemic on people in the UK; to identify groups who may be at particular risk, as well as potential targets for therapeutic intervention.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.14.20102012v1 on medRxiv