Association between preventive measures against workplace infection and preventive behavior against personal infection

  1. Mika KAWASUMI
  2. Tomohisa NAGATA
  3. Hajime ANDO
  4. Ayako HINO
  5. Seiichiro TATEISHI
  6. Mayumi TSUJI
  7. Shinya MATSUDA
  8. Yoshihisa FUJINO
  9. Koji MORI

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Abstract

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  1. Version published to 10.2486/indhealth.2021-0162
  2. ScreenIT

    SciScore for 10.1101/2021.06.08.21258584: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were conducted using Stata (Stata Statistical Software release 16; StataCorp LLC, TX, USA).
    StataCorp
    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:
    There are two limitations to this study. First, those who did not have Internet access or were not registered as monitors were excluded from the study. However, since subject bias was reduced by random sampling for each region/occupation/prefecture based on the incidence of infections, our results appear to be generalizable within Japan. However, since the survey was conducted in a Japanese population, generalizability to other countries appears limited. It is said that Japanese people characteristically adjust themselves to others easily,20 and that the implementation of infection control measures in the workplace might therefore be strongly related to personal infection prevention behavior. This study appears to support this idea, given that implementation of workplace infection control measures tended to promote personal infection prevention behavior. The findings of this study are likely to be utilized in the future not only for COVID-19 control but also for other infections, including emerging infectious diseases and seasonal influenza.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.06.08.21258584v1 on medRxiv