Greek population’s perceptions of nonpharmacological interventions towards the first wave of COVID-19 pandemic mitigation: A regressionbased association analysis

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.07.15.20153098: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Participants were asked to provide informed consent in order to gain access to the survey questions.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The analysis was performed by the statistical package STATA ©, version 16.0.
    STATA
    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 of this study lie primarily on biases existing by the study design [15, 16] such as sampling bias, according to which the lack of internet access or social media profile excluded certain population subgroups from participation. Furthermore, this research is a cross-sectional study thus it can only provide a picture of a consecutive sample within a given timeframe. Neither validated scales nor instruments were utilized, thus measurement precision or errors cannot be estimated, despite the fact that numerous biases related to question forming were addressed. The sample demonstrated tendency towards male sex, a feature that presumably affected the outcome of regression analysis, as well as towards large urban centers as regards the area of permanent residence, post-secondary education and age below 70 years old. These features suggest that no conclusions can be drawn about population subgroups of different background and most importantly, about elderly people who are a medically vulnerable population and have been crucially hit in Europe by COVID-19 [21]. While this pandemic proceeds, health practitioners and government authorities worldwide are trying to profile COVID-19 through several approaches [4, 9]. Future research should primarily target on further investigation of public’s perception concerning the risk of COVID-19 transmission through asymptomatic carriers. Secondarily, the verbal frame of NPIs should be reassessed in order to be ensured that it is comprehe...

    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.