Understanding patterns of adherence to COVID-19 mitigation measures: a qualitative interview study

  1. Sarah Denford
  2. Kate S Morton
  3. Helen Lambert
  4. Juan Zhang
  5. Louise E Smith
  6. G James Rubin
  7. Shenghan Cai
  8. Tingting Zhang
  9. Charlotte Robin
  10. Gemma Lasseter
  11. Mathew Hickman
  12. Isabel Oliver
  13. Lucy Yardley

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Abstract

Background

Evidence highlights the disproportionate impact of measures that have been introduced to reduce the spread of coronavirus on individuals from Black, Asian and minority ethnic (BAME) communities, and among those on a low income. An understanding of barriers to adherence in these populations is needed. In this qualitative study, we examined the patterns of adherence to mitigation measures and reasons underpinning these behaviors.

Methods

Semi-structured interviews were conducted with 20 participants from BAME and low-income White backgrounds. The topic guide was designed to explore how individuals are adhering to social distancing and self-isolation during the pandemic and to explore the reasons underpinning this behavior.

Results

We identified three categories of adherence to lockdown measures: (i) caution-motivated super-adherence (ii) risk-adapted partial-adherence and (iii) necessity-driven partial-adherence. Decisions about adherence considered potential for exposure to the virus, ability to reduce risk through use of protective measures and perceived importance of/need for the behavior.

Conclusions

This research highlights a need for a more nuanced understanding of adherence to lockdown measures. Provision of practical and financial support could reduce the number of people who have to engage in necessity-driven partial-adherence. More evidence is required on population level risks of people adopting risk-adapted partial-adherence.

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  1. Version published to 10.1093/pubmed/fdab005
  2. ScreenIT

    SciScore for 10.1101/2020.12.11.20247528: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Audio recorded verbal consent was obtained.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: Although every effort was made to recruit a diverse and representative sample, we acknowledge that our use of social media may have resulted in a biased sample. Much of our recruitment was via COVID-19 support pages, and previous research has shown that use of social media during the pandemic is associated with increased levels of anxiety (22) and misinformation (23). It is therefore possible that our sample of volunteers are not representative of those who do not use social media for COVID-19 related support or information. Likewise, participants did not necessarily have symptoms of COVID-19, and were therefore discussing breaches of social distancing, rather than self-isolation. Responses may have been different among a population who had experienced symptoms of COVID-19. Our study may also have been influenced by response bias. It is possible that participants were unable to accurately recall attitudes and behaviors at the start of the pandemic, or did not feel able to disclose risky or substantial breaches of lockdown to the research team. Although participants in the sample were willing to share examples of partially-adherent behavior, they may not have been willing to share experiences of more risky behavior during the interviews. Finally, interviews were conducted in July 2020. During this period, lockdown measures were being eased, and cases COVID-19 were falling. Alongside changing rules and guidance, knowledge, attitudes and behavior also ...

    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

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  3. Version published to 10.1101/2020.12.11.20247528 on medRxiv