Intention of healthcare workers to accept COVID-19 vaccination and related factors

  1. Petros Galanis
  2. Irene Vraka
  3. Despoina Fragkou
  4. Angeliki Bilali
  5. Daphne Kaitelidou

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Abstract

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  1. Version published to 10.4103/1995-7645.332808
  2. Version published to 10.1101/2020.12.08.20246041v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.12.08.20246041: (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
    We searched PubMed, Medline, Scopus, Web of Science, ProQuest, CINAHL and pre-print services (medRxiv) from January 1, 2020 to December 02, 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    ProQuest
    suggested: (ProQuest, RRID:SCR_006093)

    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:
    Our study is subject to several limitations. In particular, more than the half of studies was of moderate quality, while four out of eleven studies were published in pre-print services which do not apply peer-review process. We performed subgroup analysis according to studies quality and publication type to overcome this limitation. The statistical heterogeneity in results was very high due probably to variability in study designs and populations. In that case, we applied a random effects model and we performed subgroup and meta-regression analysis. Data with regards to the factors related with intention of HCWs to accept COVID-19 vaccination were limited, while five studies used multivariable models to eliminate confounding. We consider this as a potential area for future study. Moreover, all the studies included in this review were cross-sectional studies making causal inferences impossible. Finally, the proportion of HCWs that intent to accept COVID-19 vaccination may be an overestimation since studies evaluated self-reported answers that could be subject to social desirability bias, with HCWs knowing that the general public expects a high COVID-19 vaccination coverage among them.

    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.

  4. Version published to 10.1101/2020.12.08.20246041v1 on medRxiv