Knowledge and Beliefs of General Public of India on COVID-19: A Cross-sectional Survey

  1.  Rahul Krishna Puvvada
  2. Krishna Undela
  3. Shilpa Palaksha
  4. Balaji Sathyanarayana Gupta

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Abstract

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  1. Version published to 10.36349/easjpp.2020.v02i05.004
  2. ScreenIT

    SciScore for 10.1101/2020.04.22.20075267: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study received an exemption from the Institutional Human Ethics committee of JSS College of Pharmacy, Mysuru as it was considered as no minimal risk research.
    Consent: However, participants were asked to give consent before taking part in the survey.
    RandomizationUsing Google forms, the questionnaire was randomly distributed among the public of India including doctors, pharmacists, nurses, medical and engineering students, software employees, retired persons, etc. through emails and social networking platforms such as WhatsApp, LinkedIn, Instagram and Facebook.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    IBM SPSS Statistics for Windows, Version 21.0.
    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 10.1101/2020.04.22.20075267v1 on medRxiv