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How to survey citizens’ compliance with COVID-19 public health measures? Evidence from three survey experiments

Author

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  • Daoust, Jean-François
  • Nadeau, Richard
  • Dassonneville, Ruth
  • Lachapelle, Erick
  • Bélanger, Éric

    (McGill University)

  • Savoie, Justin
  • van der Linden, Clifton

    (McMaster University)

Abstract

The extent to which citizens comply with newly-enacted public health measures such as social distancing or lockdowns strongly affects the propagation of the virus and the number of deaths from COVID-19. It is however very difficult to identify non-compliance through survey research because claiming to follow the rules is socially desirable. Using three survey experiments, we examine the efficacy of different “face-saving” questions that aim to reduce social desirability in the measurement of compliance with public health measures. Our treatments soften the social norm of compliance by way of a short preamble in combination with a guilty-free answer choice making it easier for respondents to admit non-compliance. We find that self-reported non-compliance increases by up to 11 percentage points when making use of a face-saving question. Considering the current context and the importance of measuring non-compliance, we argue that researchers around the world should adopt our most efficient face-saving question.

Suggested Citation

  • Daoust, Jean-François & Nadeau, Richard & Dassonneville, Ruth & Lachapelle, Erick & Bélanger, Éric & Savoie, Justin & van der Linden, Clifton, 2020. "How to survey citizens’ compliance with COVID-19 public health measures? Evidence from three survey experiments," SocArXiv gursd, Center for Open Science.
    • Handle: RePEc:osf:socarx:gursd
    DOI: 10.31219/osf.io/gursd
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    References listed on IDEAS

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    1. René Bekkers & Pamala Wiepking, 2011. "Accuracy of self-reports on donations to charitable organizations," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(6), pages 1369-1383, October.
    2. Martin Larsen & Jacob Nyrup & Michael Bang Petersen, 2020. "Do Survey Estimates of the Public’s Compliance with COVID-19 Regulations Suffer from Social Desirability Bias?," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(2).
    3. Diana C. Mutz & Robin Pemantle & Philip Pham, 2019. "The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data," The American Statistician, Taylor & Francis Journals, vol. 73(1), pages 32-42, January.
    4. Ian MacGregor-Fors & Mark E Payton, 2013. "Contrasting Diversity Values: Statistical Inferences Based on Overlapping Confidence Intervals," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-4, February.
    5. Morin-Chassé, Alexandre & Bol, Damien & Stephenson, Laura B. & Labbé St-Vincent, Simon, 2017. "How to Survey About Electoral Turnout? The Efficacy of the Face-Saving Response Items in 19 Different Contexts," Political Science Research and Methods, Cambridge University Press, vol. 5(3), pages 575-584, July.
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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Distancing and Lockdown > Compliance

    Citations

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    Cited by:

    1. Kovacs, Roxanne & Dunaiski, Maurice & Tukiainen, Janne, 2020. "Compulsory face mask policies do not affect community mobility in Germany," EconStor Preprints 218945, ZBW - Leibniz Information Centre for Economics.
    2. Roxanne Kovacs & Maurice Dunaiski & Janne Tukiainen, 2023. "The effect of compulsory face mask policies on community mobility in Germany," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(4), pages 1027-1055, October.
    3. Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanie, 2024. "Trust predicts compliance with COVID-19 containment policies: Evidence from ten countries using big data," Economics & Human Biology, Elsevier, vol. 54(C).
    4. Frauke von Bieberstein & Anna-Corinna Kulle & Stefanie Schumacher, 2022. "Large gender and age differences in hand disinfection behavior during the COVID-19 pandemic: Field data from Swiss retail stores," Papers 2210.09094, arXiv.org.
    5. Francesco Bogliacino & Rafael Charris & Camilo Gómez & Felipe Montealegre & Cristiano Codagnone, 2021. "Expert endorsement and the legitimacy of public policy. Evidence from Covid19 mitigation strategies," Journal of Risk Research, Taylor & Francis Journals, vol. 24(3-4), pages 394-415, April.
    6. Cristina Bicchieri & Enrique Fatas & Abraham Aldama & Andrés Casas & Ishwari Deshpande & Mariagiulia Lauro & Cristina Parilli & Max Spohn & Paula Pereira & Ruiling Wen, 2021. "In science we (should) trust: Expectations and compliance across nine countries during the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    7. Francesco Sarracino & Talita Greyling & Kelsey J. O'Connor & Chiara Peroni & Stephanie Rossouw, 2021. "Trust predicts compliance to Covid-19 containment policies: evidence from ten countries using big data," Department of Economics University of Siena 858, Department of Economics, University of Siena.
    8. Daoust, Jean-François & Bélanger, Éric & Dassonneville, Ruth & Lachapelle, Erick & Nadeau, Richard & Becher, Michael & Brouard, Sylvain & Foucault, Martial & Hönnige, Christoph & Stegmueller, Daniel, 2020. "Face-Saving Strategies Increase Self-Reported Non-Compliance with COVID-19 Preventive Measures: Experimental Evidence from 12 Countries," SocArXiv tkrs7, Center for Open Science.
    9. J -F Daoust, 2020. "Elderly people and responses to COVID-19 in 27 Countries," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-13, July.

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