Socio-demographic disparities in knowledge, practices, and ability to comply with COVID-19 public health measures in Canada

  1. Gabrielle Brankston
  2. Eric Merkley
  3. David N. Fisman
  4. Ashleigh R. Tuite
  5. Zvonimir Poljak
  6. Peter J. Loewen
  7. Amy L. Greer

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Objectives

The effectiveness of public health interventions for mitigation of the COVID-19 pandemic depends on individual attitudes, compliance, and the level of support available to allow for compliance with these measures. The aim of this study was to describe attitudes and behaviours towards the Canadian COVID-19 public health response, and identify risk-modifying behaviours based on socio-demographic characteristics.

Methods

A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the Canadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses for indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures.

Results

More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk perceptions, attitudes, and behaviours varied by demographic variables. Men, younger age groups, and those in the paid workforce were less likely to consider public health measures to be effective, and had less confidence in their ability to comply. Approximately 80% of respondents reported that parents provided childcare and 52% reported that parents in the workforce provided childcare while schools were closed.

Conclusion

Policies to help address issues of public adherence include targeted messaging for men and younger age groups, social supports for those who need to self-isolate, changes in workplace policies to discourage presenteeism, and provincially co-ordinated masking and safe school policies.

Article activity feed

  1. Version published to 10.17269/s41997-021-00501-y
  2. ScreenIT

    SciScore for 10.1101/2020.08.24.20180919: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data collection: The study protocol was approved by the University of Guelph Research Ethics Board (protocol #20-04-011) and the University of Toronto Research Ethics Board (protocol #38251).
    Consent: Informed consent was obtained prior to survey completion by providing information about the study, ensuring anonymity and confidentiality, and providing the process to withdraw from the survey.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All data were analysed using RStudio Version 1.2.5033 42.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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:
    Limitations: While every effort was made to ensure representativeness of the study population, we note several potential biases, including non-representativeness of the sample (a risk with any survey), the online nature of the survey, which limits participation to those who use the Internet, and self-report which introduces the potential for recall, response, and social desirability biases. The large sample size means that statistical significance is seen with small absolute differences. Finally, knowledge about COVID-19 and recommended behaviours is changing rapidly. These data were collected in May 2020 during a time in which provinces were in different phases of public health de-escalation and indoor masking orders were not widespread, so these data are best interpreted as a snapshot in time.

    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.

  3. Version published to 10.1101/2020.08.24.20180919v1 on medRxiv