Telecommuting Frequency and Preference among Japanese Workers According to Regional Cumulative COVID-19 Incidence: A Cross-Sectional Study

  1. Hiroka Baba
  2. Kazunori Ikegami
  3. Hajime Ando
  4. Hisashi Eguchi
  5. Mayumi Tsuji
  6. Seiichiro Tateishi
  7. Masako Nagata
  8. Shinya Matsuda
  9. Yoshihisa Fujino
  10. for the CORoNaWork Project

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Abstract

This study aimed to examine the relationship between telecommuting and the regional cumulative COVID-19 incidence. This was a cross-sectional study analyzing 13,468 office workers. The participant groups, according to the level of cumulative COVID-19 incidence by prefecture, were used as the predictor variable, and telecommuting frequency and preference were used as outcomes. We employed an ordinal logistic regression analysis. In regions with a high cumulative COVID-19 incidence, the proportion of participants who telecommuted more than 2 days per week was 34.7%, which was approximately 20% higher than in other regions. Telecommuting preference was stronger in areas with higher COVID-19 influence. However, in other regions, the proportion of participants who did not want to telecommute was higher than that of those who wanted to telecommute. We found that telecommuting frequency and preference were higher in regions with high cumulative COVID-19 incidence.

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  1. Version published to 10.1177/21582440221082134
  2. ScreenIT

    SciScore for 10.1101/2021.05.18.21257423: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the ethics committee of the University of Occupational and Environmental Health, Japan(reference No. R2-079).
    Consent: Informed consent was obtained in the form of the website.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    In all tests, the threshold for significance was set at p < 0.05. SPSS 25.0 J analytical software (IBM, NY) was used for the statistical analyses.
    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:
    This study has certain limitations. Given that the CORoNaWork survey is an internet-based survey, the generalizability of the results is uncertain. To address this issue, this study used cluster sampling—stratified by gender, region, and occupation. On the other hand, since few participants belonged to the same companies, this study can be interpreted as a company-based survey. This study was also a cross-sectional study, and it is unclear how telecommuting or telecommuting preferences varied during the COVID-19 epidemic. We believe that future longitudinal studies may clarify the relationship between the COVID-19 epidemic and telecommuting. Some examples are the sustainability of telecommuting frequency when the COVID-19 epidemic is declining, and the minimum degree of telecommuting frequency required to control the spread of the pandemic.

    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 10.1101/2021.05.18.21257423v2 on medRxiv
  4. Version published to 10.1101/2021.05.18.21257423v1 on medRxiv