Early evidence and predictors of mental distress of adults one month in the COVID-19 epidemic in Brazil

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.04.18.20070896: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The survey was approved by the ethics committee at Tsinghua University (#20200304).
    Consent: The survey was voluntary with the consent from the participants, and we promised the participants confidentiality and anonymity of their responses.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    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:
    There are several limitations in this study. First, our sampling is not nationally representative, because our aim was to provide rapid evidence on mental health and its predictors to enable rapid screening of the mentally vulnerable in the ongoing COVID-19 outbreak in Brazil. It is worth investigating if the level and the predictors of mental health change as the outbreak continues. Our study aims to provide evidence on the prevalence of distress in the early stage of the Covid-19 crisis, and yet future research may capture how the prevalence and the predictors of mental health may vary over time. Second, Brazil is a large country, and we sampled individuals from 0 to over 3,000 km from São Paulo to cover various regions in Brazil. It remains to be seen to what extent distance from the epicenter is a factor in other countries, most of which are smaller and have their own distinct geographical features.21 Third, while the study examines in particular a novel predictor, the distance to the epicenter of the epidemic, as a predictor of the distress experienced by individual adults, we are limited in examining the other predictors. For instance, future research can explore individuals’ work situations, employment sectors (e.g. public, private), self-employment, illegitimate work tasks, seniority at work, whether their workplace downsized, income level, the number of hours they work outside of the home, their health conditions, perceived COVID-19 test availability, belief in COVID...

    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.