Did people really drink bleach to prevent COVID-19? A tale of problematic respondents and a guide for measuring rare events in survey data

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Abstract

Society is becoming increasingly dependent on survey research. However, surveys can be impacted by participants who are non-attentive, respond randomly to survey questions, and misrepresent who they are and their true attitudes. The impact that such respondents can have on public health research has rarely been systematically examined. In this study we examine whether Americans began to engage in dangerous cleaning practices to avoid Covid-19 infection. Prior findings reported by the CDC have suggested that people began to engage in highly dangerous cleaning practices during the Covid-19 pandemic, including ingesting household cleansers such as bleach. In a series of studies totaling close to 1400 respondents, we show that 80-90% of reports of household cleanser ingestion are made by problematic respondents. These respondents report impossible claims such as ‘recently having had a fatal heart attack’ and ‘eating concrete for its iron content’ at a similar rate to ingesting household cleaners. Additionally, respondents’ frequent misreading or misinterpreting the intent of questions accounted for the rest of such claims. Once inattentive, mischievous, and careless respondents are taken out of the analytic sample we find no evidence that people ingest cleansers to prevent Covid-19 infection. The relationship between dangerous cleaning practices and health outcomes also becomes non-significant once problematic respondents are taken out of the analytic sample. These results show that reported ingestion of household cleaners and other similar dangerous practices are an artifact of problematic respondent bias. The implications of these findings for public health and medical survey research, as well as best practices for avoiding problematic respondents in surveys are discussed.

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  1. SciScore for 10.1101/2020.12.11.20246694: (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: 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.