The Impact of Work Loss on Mental and Physical Health During the COVID-19 Pandemic: Baseline Findings from a Prospective Cohort Study

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.09.06.20189514: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    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:
    Study limitations include its cross-sectional nature and reliance on self-report. The sample may not be representative of the population affected, although the regression model adjusts for multiple demographic factors to aid outcome interpretation. Significant differences were observed between survey modes, with online respondents more likely to report mental health problems and less likely to report physical health problems than telephone respondents. Using multiple response modes and statistically controlling for response mode in regression models may have reduced the response biases commonly observed in health outcomes research (25). Data collection began at the peak of a first wave of COVID-19 cases in Australia and continued through the early stages of re-opening. Longitudinal data from this cohort will track changes in work and employment amongst the study groups, and examine longer-term impacts of mental and physical health as the pandemic unfolds in Australia.

    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.