Measuring Italian citizens’ engagement in the first wave of the COVID-19 pandemic containment measures: A cross-sectional study

  1. Guendalina Graffigna
  2. Serena Barello
  3. Mariarosaria Savarese
  4. Lorenzo Palamenghi
  5. Greta Castellini
  6. Andrea Bonanomi
  7. Edoardo Lozza

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Abstract

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  1. Version published to 10.1371/journal.pone.0238613
  2. ScreenIT

    SciScore for 10.1101/2020.04.22.20075234: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval was obtained from the institutional review board at Catholic University of Milan (IRB#2019-12).
    Consent: 2.2 Study measures: After recruitment and consent, consumers were asked to complete an online survey.
    RandomizationIndividuals were randomly selected from the consumers panel managed by Norstat srl (a company specialized in collecting data; (https://norstat.it/) using random digit dialing, to fill an online survey.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses have been carried out with IBM SPSS 23 (release 23.0.0.0).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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.

  3. Version published to 10.1101/2020.04.22.20075234v1 on medRxiv