COVID-19 in Wuhan: Sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on healthcare workers

  1. Zhou Zhu
  2. Shabei Xu
  3. Hui Wang
  4. Zheng Liu
  5. Jianhong Wu
  6. Guo Li
  7. Jinfeng Miao
  8. Chenyan Zhang
  9. Yuan Yang
  10. Wenzhe Sun
  11. Suiqiang Zhu
  12. Yebin Fan
  13. Yuxi Chen
  14. Junbo Hu
  15. Jihong Liu
  16. Wei Wang

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Abstract

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  1. Version published to 10.1016/j.eclinm.2020.100443
  2. ScreenIT

    SciScore for 10.1101/2020.02.20.20025338: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: The questionnaire consisted of five parts: online informed consent, baseline sociodemographic information, perceptions of threat of COVID-19, psychological protective measures and rating scales including Impact of Event Scale-Revised Questionnaires (IES-R), Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder 7-item (GAD-7).
    IRB: The study was approved by the institutional ethics board of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology (ID: TJ-C20200129).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses to identify influencing factors were performed using SPSS 22.0 (Statistical Package for the Social Sciences) for Windows (SPSS, Chicago, IL).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Statistical Package for the Social Sciences
    suggested: (SPSS, RRID:SCR_002865)
    The Depression, Anxiety and Psychological Stress nomograms were formulated based on the results of multivariate logistic regression analysis using the R packages “rms”, “Hmisc” and “ggplot2” in R 3.5.2 (http://www.r-project.org/).
    http://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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. Version published to 10.1101/2020.02.20.20025338v2 on medRxiv
  4. Version published to 10.1101/2020.02.20.20025338v1 on medRxiv