COVID-19 Risk Perception Among U.S. Adults: Changes from February to May 2020

  1. Amyn A. Malik
  2. SarahAnn M. McFadden
  3. Jad A. Elharake
  4. Obianuju Genevieve Aguolu
  5. Mehr Shafiq
  6. Saad B. Omer

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Abstract

The COVID-19 pandemic continues to detrimentally impact the United States. Using a survey, we collected demographic and COVID-19 risk perception, behavior, knowledge, and attitude data from 672 adults across the U.S. in May 2020. These variables were compared with the results from a survey in February 2020. Participants who were older (55+ years; M = 6.3, SD = 2.0), identified as Native American/Alaska Native (M = 6.8, SD = 1.0) or Asian (M = 6.0, SD = 2.0), and those who had contracted (M = 6.8, SD = 2.0) or knew someone who had contracted COVID-19 (M = 6.2, SD = 1.7) reported higher perceived risk. Health behaviors, such as physical distancing, have shown to impact infectious disease trajectories. As the U.S. reopens its economy, public health officials and politicians must formulate culturally appropriate and evidence-based messaging and policies, based on the public’s COVID-19 risk perceptions, to encourage preventive behaviors.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.20.20178822: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical Approval: Yale University Institutional Review Board approved this study (IRB protocol number: 2000027891).
    Consent: Participants provided informed consent prior to data collection.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were analyzed using Stata Version 16 (StataCorp, College Station, Texas).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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.

  2. Version published to 10.1101/2020.08.20.20178822 on medRxiv