Public willingness to adhere to COVID-19 precautionary measures in Sudan: an application of the Health Belief Model

  1. Azza Mehanna
  2. Yasir Ahmed Mohammed Elhadi
  3. Don Eliseo Lucero-Prisno III

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  1. ScreenIT

    SciScore for 10.1101/2020.12.25.20248859: (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

    Software and Algorithms
    SentencesResources
    Statistical analysis of the data: Data were fed to the computer and analyzed using IBM SPSS software package version 20.0(Armonk, NY: IBM Corp).
    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: We detected the following sentences addressing limitations in the study:
    Limitations of the study: This study has some limitations. Cues to action were not assessed in this study in order to avoid a long questionnaire, however, knowing the triggers instigating participants to adhere to the protective measures would have certainly added to this work. We used the convenience sampling technique; hence generalization of data would not be possible. Nonetheless, the present research was able to shed important light on some of the factors influencing participants’ intention to adhere to the protective measures in Sudan. A subjective tool -self-report questionnaire -was used to collect data; therefore, participants’ responses might be affected by social desirability.

    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 10.11604/pamj.2021.39.135.29171
  3. Version published to 10.1101/2020.12.25.20248859 on medRxiv