Relationship between alcohol consumption and telecommuting preference-practice mismatch during the COVID-19 pandemic

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Abstract

Objective

This study examined the association between increased alcohol consumption and telecommuting, comparing employees who expressed a preference for telecommuting and those who did not.

Methods

We conducted an internet monitor survey. Responses from 20 395 of the 33 302 participants were included in the final sample. Participants were asked about their desire for and frequency of telecommuting, and about changes in alcohol consumption under the COVID-19 pandemic. Data were analyzed by logistic regression analysis.

Results

The ratio of increased drinking in those who telecommuted at least once a week was significantly different (OR = 1.29, 95% CI 1.16–1.43, p < .001). The ratio of increased drinking in participants for whom telecommuting was not preferred was significantly different (OR = 1.08, 95%CI 1.02–1.14, p = .002). Since the interaction term was significant in preliminary analysis, stratification was performed. Participants who telecommuted despite preferring not to do so reported significantly increased alcohol consumption, as revealed by a multivariate analysis (OR = 1.53, 95% CI 1.18–2.00, p < .001). Participants who expressed a preference for telecommuting showed no such increase (OR = 1.12, 95% CI 0.98–1.27, p = .074).

Conclusions

Under the COVID-19 pandemic, telecommuting that involves a mismatch with employee preference for way of working may be a new risk factor for problematic drinking.

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  1. SciScore for 10.1101/2021.12.13.21267711: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The research was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (Reference No. R2-079).
    Consent: Informed consent was obtained via a form on the website.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    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.


    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.