Workplace Infection Prevention Control Measures and Work Engagement During the COVID-19 Pandemic among Japanese Workers: A Prospective Cohort Study

  1. Kazunori Ikegami
  2. Hajime Ando
  3. Yoshihisa Fujino
  4. Hisashi Eguchi
  5. Keiji Muramatsu
  6. Tomohisa Nagata
  7. Seiichiro Tateishi
  8. Mayumi Tsuji
  9. Akira Ogami
  10. the CORoNaWork project

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Abstract

Objectives

It has been widely reported that the COVID-19 pandemic may have a psychological influence on people. Thus, it could be important to note how workplace infection prevention and control (IPC) measures for COVID-19 contribute to positive mental health among workers. We hypothesized that if workplace IPC measures are adequately implemented, they would have a positive effect on employees’ work engagement.

Methods

We conducted an internet-based prospective cohort study from December 2020 (baseline) to December 2021 (follow-up after one year) using self-administered questionnaires. At baseline, 27,036 workers completed the questionnaires, while 18,560 (68.7%) participated in the one-year follow-up. After excluding the 6,578 participants who changed jobs or retired during the survey period, or telecommuted more than four days per week, 11,982 participants were analyzed. We asked participants about the implementation of workplace IPC measures at baseline and conducted a nine-item version of the Utrecht Work Engagement Scale (UWES-9) at follow-up.

Results

Four groups were created according to the number of workplace IPC measures implemented. The mean (SD) UWES-9 score of the “0–2” group was the lowest at 18.3 (13.2), while that of the “8” group was the highest at 22.6 (12.6). The scores of the “3– 5,” “6–7,” and “8” groups were significantly higher than that of the “0–2” group (all, p<0.001). The p trend of the four groups was also significant (p<0.001).

Conclusions

Promoting workplace IPC measures improves workers’ work engagement, and a dose-response relationship exists between workplace IPC measures and work engagement.

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    SciScore for 10.1101/2022.04.11.22273753: (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
    In all tests, the threshold for significance was set at p<0.05. Stata/SE Ver.15.1 (StataCorp LLC, College Station, Texas, United States) was used for the analysis.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

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  2. Version published to 10.1101/2022.04.11.22273753v1 on medRxiv
  3. Version published to 10.1002/1348-9585.12350