Which traits predict elevated distress during the Covid-19 pandemic? Results from a large, longitudinal cohort study with psychiatric patients and healthy controls

  1. Katharina Brosch
  2. Tina Meller
  3. Julia-Katharina Pfarr
  4. Frederike Stein
  5. Simon Schmitt
  6. Kai G. Ringwald
  7. Lena Waltemate
  8. Hannah Lemke
  9. Katharina Thiel
  10. Elisabeth Schrammen
  11. Carina Hülsmann
  12. Susanne Meinert
  13. Katharina Dohm
  14. Elisabeth J. Leehr
  15. Nils Opel
  16. Axel Krug
  17. Udo Dannlowski
  18. Igor Nenadić
  19. Tilo Kircher

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Abstract

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  1. Version published to 10.1016/j.jad.2021.10.017
  2. ScreenIT

    SciScore for 10.1101/2021.04.01.21254625: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the ethics committees of the universities of Marburg and Münster, Germany, in accordance with the Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were performed using SPSS 27 α statistical software (IBM Corp.).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Figures were designed using Microsoft Excel (Version 16.46) and ggplot2 running under R (Version 4.0.3
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    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: We detected the following sentences addressing limitations in the study:
    Limitations: Several limitations should be noted. The current study did not include a full diagnostic interview at mid-pandemic follow-up, only one conducted for baseline data collection. More objective measures, including HAMD scores, assessed by trained raters and in-depth interviews would have improved the validity of the findings. We did not re-assess trait anxiety and social support during the pandemic. It might be argued that subjective fear and subjective isolation are simple expressions of these traits, manifesting irrespectively of the pandemic. However, in all three multiple regression models, Covid-19 impact was a significant predictor for subjective fear and isolation. Covid-19-related fear and isolation ratings seem to be influenced by both baseline trait variables (trait anxiety and social support), but also by Covid-19 impact. The found associations cannot be regarded as causal inferences, however, they might guide future research and hint at possible risk factors. We asked patients about subjective symptom changes between two time points, between January 2020 before the pandemic, and current symptoms during lockdown. While self-ratings are known to be associated with clinicians’ ratings of severity, it is still possible that current symptom load might have influenced symptom severity assessment of January 2020 (Tondo, Burrai, Scamonatti, Weissenburger, & Rush, 1988). Outlook: The Covid-19 pandemic constitutes an unfamiliar challenge to individuals and societie...

    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 10.1101/2021.04.01.21254625v1 on medRxiv