Risk Factors Underlying COVID-19 Lockdown-Induced Mental Distress

  1. Jan Sebastian Novotný
  2. Juan Pablo Gonzalez-Rivas
  3. Šárka Kunzová
  4. Mária Skladaná
  5. Anna Pospíšilová
  6. Anna Polcrová
  7. Jose Ramon Medina-Inojosa
  8. Francisco Lopez-Jimenez
  9. Yonas Endale Geda
  10. Gorazd Bernard Stokin

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Abstract

Recent reports suggest that the COVID-19 lockdown resulted in changes in mental health, however, potential age-related changes and risk factors remain unknown. We measured COVID-19 lockdown-induced stress levels and the severity of depressive symptoms prior to and during the COVID-19 lockdown in different age groups and then searched for potential risk factors in a well-characterized general population-based sample. A total of 715 participants were tested for mental distress and related risk factors at two time-points, baseline testing prior to COVID-19 and follow-up testing during COVID-19, using a battery of validated psychological tests including the Perceived Stress Scale and the Patient Health Questionnaire. Longitudinal measurements revealed that the prevalence of moderate to high stress and the severity of depressive symptoms increased 1.4- and 5.5-fold, respectively, during the COVID-19 lockdown. This surge in mental distress was more severe in women, but was present in all age groups with the older age group exhibiting, cross-sectionally, the lowest levels of mental distress prior to and during the lockdown. Illness perception, personality characteristics such as a feeling of loneliness, and several lifestyle components were found to be associated with a significant increase in mental distress. The observed changes in mental health and the identified potential risk factors underlying these changes provide critical data justifying timely and public emergency-tailored preventive, diagnostic, and therapeutic mental health interventions, which should be integrated into future public health policies globally.

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  1. Version published to 10.3389/fpsyt.2020.603014
  2. ScreenIT

    SciScore for 10.1101/2020.07.28.20163113: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The research protocols of the studies were approved by the Internal Review Board and the St.
    Consent: All participants of the Kardiovize study as well as of the Covid-19 add-on study signed informed consent.
    RandomizationBriefly, the Kardiovize study, is a prospective longitudinal epidemiological cohort that investigates cardiovascular, neuropsychiatric, and other health-related topics in Central Europe carried out on a representative randomly selected 1% population sample of the residents of Brno, Czech Republic.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    E-questionnaire was completed by 715 out of 1823 participants in 4 weeks through an online survey module using validated RedCap software (Research Electronic Data Capture) tool(22).
    RedCap
    suggested: (REDCap, RRID:SCR_003445)
    Data were analysed using SPSS v.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    3.6.3 (https://www.r-project.org/) with ggplot2 (v.1.0.12), reshape2 (v.1.6.4) and pheatmap (v.2.3.3.0) packages.
    https://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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. ScreenIT

    SciScore for 10.1101/2020.07.28.20163113: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementThe research protocols of the studies were approved by the Internal Review Board and the St.RandomizationBriefly, the Kardiovize study, is a prospective longitudinal epidemiological cohort that investigates cardiovascular, neuropsychiatric, and other health-related topics in Central Europe carried out on a representative randomly selected 1% population sample of the residents of Brno, Czech Republic.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableChanges in stress and depressive symptoms were most significant in females and did not depend on whether one quarantined alone or with others.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Equestionnaire was completed by 715 out of 1823 participants in 4 weeks through an online survey module using validated RedCap software (Research Electronic Data Capture) tool(22).
    RedCap
    suggested: (REDCap, SCR_003445)
    Data were analysed using SPSS v.
    SPSS
    suggested: (SPSS, SCR_002865)
    3.6.3 (https://www.rproject.org/) with ggplot2 (v.1.0.12), reshape2 (v.1.6.4) and pheatmap (v.2.3.3.0) packages.
    ggplot2
    suggested: (ggplot2, SCR_014601)

    Data from additional tools added to each annotation on a weekly basis.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.07.28.20163113v1 on medRxiv