Non-medical COVID-19-related personal impact in medical ecological perspective: A global multileveled, mixed method study

  1. Timothy Dye
  2. Brooke Levandowski
  3. Shazia Siddiqi
  4. José Pérez Ramos
  5. Dongmei Li
  6. Saloni Sharma
  7. Erin Muir
  8. Sophia Wiltse
  9. Rebecca Royzer
  10. Tiffany Panko
  11. Wyatte Hall
  12. Monica Barbosu
  13. Carrie Irvine
  14. Eva Pressman

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Abstract

Background

The COVID-19 pandemic has led to widespread public health measures to reduce transmission, morbidity, and mortality attributed to the SARS-CoV-2 virus. While much research and focus surrounds COVID-19 vaccine development, testing, and supportive management, little is known about the determinants of non-medical, personal impact of COVID-19 prevention policies. We aimed to understand determinants of non-medical COVID-19 impact and to account for its multileveled, intersectional nature of associations.

Methods

This cross-sectional, multi-level, convergent mixed-methods study assessed a range of beliefs, practices, and experiences relating to COVID-19. We recruited a global sample (n=7,411) using both Facebook and Amazon mTURK platforms. We constructed a novel data-driven non-medical COVID-19 Impact Score and four subcomponents (“Personal Action,” “Supply-related,” “Cancellations,” and “Livelihood” impacts). We used generalized estimating equation models with identity link functions to determine concomitant association of individual, household, and country-level variables on the impact scores. We also classified 20,015 qualitative excerpts from 6859 respondents using an 80-code codebook.

Results

Total and component impact scores varied significantly by region with Asia, Africa, and Latin America and the Caribbean observing the highest impact scores. Multilevel modeling indicated that individual-level sociocultural variables accounted for much of this variation with COVID-related worry, knowledge, struggles in accessing food and supplies, and worsening mental health most strongly associated with non-medical impact. Family responsibilities, personal COVID medical experience, and health locus of control – in addition to country-level variables reflecting social and health challenge – were also significantly and independently associated with non-medical impact.

Discussion

Non-medical personal impact of COVID-19 affects most people internationally, largely in response to shutdowns, implementing prevention requirements, and through economic consequences. In the context where most of the world’s population does not have direct medical experience with COVID-19, this phenomena of non-medical impact is profound, and likely impacts sustainability of public health interventions aimed at containing COVID-19.

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    SciScore for 10.1101/2020.12.26.20248865: (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
    We adhered to the Reporting of Studies Conducted using Observational Routinely-collected Data (RECORD) guidelines (38) and the Consolidated Criteria for Reporting Qualitative Research (COREQ)(39) reporting guidelines in the reporting of this study.
    RECORD
    suggested: (RECORD, RRID:SCR_009097)
    All data analysis was conducted using the statistical analysis software SAS v9.4 (SAS Institute Inc., Cary, NC).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)
    Respondents consented to participate in this research after a review of a detailed Information Sheet presented at the beginning of the REDCap survey and a confirmation of country of residence.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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.

    About SciScore

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  2. Version published to 10.1101/2020.12.26.20248865v1 on medRxiv