Willingness to Accept Trade-Offs Among COVID-19 Cases, Social-Distancing Restrictions, and Economic Impact: A Nationwide US Study

  1. Shelby Reed
  2. Juan Marcos Gonzalez
  3. F. Reed Johnson

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Abstract

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  1. Version published to 10.1016/j.jval.2020.07.003
  2. ScreenIT

    SciScore for 10.1101/2020.06.01.20119180: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study protocol was reviewed and determined to be exempt by the Duke Health Institutional Review Board (Pro00105431).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We used Stata/SE 16.1 (StataCorp LLC; College Station) and LatentGOLD 5.1 (Statistical Innovations Inc.
    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: We detected the following sentences addressing limitations in the study:
    Limitations: The hypothetical nature of our study is a limitation, as it is with all stated-preference studies. However, these studies can be designed to provide insights on issues that shape public sentiment and behaviors of individuals that are isolated from their everyday reality. For instance, an individual may have strong preferences for lifting social-distancing restrictions and would be willing to assume substantial risks of contracting COVID-19. However, they still may not be willing to violate states’ stay-at-home orders. Others may give priority to restarting the economy and accept high rates of COVID-19 infection because they personally will stay isolated to protect themselves from exposure to the virus. Although not a limitation of stated-preference studies, respondents could have considered external information when responding to the choice questions in the survey given the nearly continuous coverage of the COVID-19 pandemic across lay and scientific media outlets. Some respondents could have considered relationships between factor levels shown in alternative profiles. For instance, some respondents may have assumed that the percentage of families dipping below the poverty threshold would be lower than shown or placed greater responsibility for economic prosperity among individuals when profiles depicted scenarios with faster economic recovery. However, we checked for statistical interactions between COVID-19 risk and social distancing policies and between time f...

    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.

  3. Version published to 10.1101/2020.06.01.20119180v3 on medRxiv
  4. Version published to 10.1101/2020.06.01.20119180v1 on medRxiv
  5. Version published to 10.1101/2020.06.01.20119180v2 on medRxiv