About: How to Survey Citizens’ Compliance with COVID-19 Public Health Measures: Evidence from Three Survey Experiments

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	How to Survey Citizens’ Compliance with COVID-19 Public Health Measures: Evidence from Three Survey Experiments
Creator	Savoie, Justin Van Der Linden, Clifton Bélanger, Éric Daoust, Jean-François Dassonneville, Ruth Lachapelle, Erick Nadeau, Richard
Source	PMC
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.
has issue date	2020-07-07(xsd:dateTime)
bibo:doi	10.1017/xps.2020.25
has license	cc-by
sha1sum (hex)	7d19924d711c80a4c62a0289bf30dff5f44b8c35
schema:url	https://doi.org/10.1017/xps.2020.25
resource representing a document's title	How to Survey Citizens’ Compliance with COVID-19 Public Health Measures: Evidence from Three Survey Experiments
has PubMed Central identifier	PMC7438621
resource representing a document's body	covid:7d19924d711c80a4c62a0289bf30dff5f44b8c35#body_text
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