COVID-19 vaccine hesitancy January-May 2021 among 18–64 year old US adults by employment and occupation

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Abstract

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  1. SciScore for 10.1101/2021.04.20.21255821: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The CMU Institutional Review Board approved the survey protocol and instrument.
    Sex as a biological variablenot detected.
    RandomizationEach month the survey is offered to a random sample, stratified by geographic region, of ≈100 million US residents from the Facebook Active User Base who use one of the supported languages (English [American and British], Spanish [Spain and Latin American], French, Brazilian Portuguese, Vietnamese, and simplified Chinese) via a link at the top of their Facebook News Feed to yield ≈1.3 million responders, which allows for evaluation of local trends.
    Blindingnot detected.
    Power Analysisnot 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:
    Limitations: Our large sample size allowed for precise vaccine hesitancy estimates by month and occupation. However, cross-sectional samples were used to evaluate time trends, and the sample representativeness may have been affected by the recruitment method and response rate, addressed with weighting.7 Compared to the [dataset] American Community Survey 2015-2019 5-year 2 Data Release9, demographics of the weighted sample are similar to the US population, but white race and higher education are slightly over-represented. Thus, overall hesitancy prevalence estimates might be underestimated.3 This should have minimal effects on time trends or comparisons between occupation categories.

    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.