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Using Descriptive and Injunctive Norms to Encourage COVID-19 Social Distancing and Vaccinations

Authors: WooJin Kim; Yuhosua Ryoo;

Using Descriptive and Injunctive Norms to Encourage COVID-19 Social Distancing and Vaccinations

Abstract

In the context of the COVID-19 pandemic, the authors conduct three online studies to examine effects of health messages that use descriptive norms to bring attention to pervasive social distancing violations and vaccine resistance. The studies provide empirical evidence that when social messages show examples of widespread noncompliant behaviors, they may unintentionally increase resistance to social distancing guidelines and vaccinations. Backfire effects are more pronounced when audiences highly identify with noncompliant actors or pay more attention to others' behaviors. We also show that injunctive norms should be included to alleviate backfire effects. The studies suggest that governments and authorities can more effectively encourage compliance with health guidelines by focusing on the majority of compliant individuals rather than broadcasting images of noncompliant individuals.

Keywords

Physical Distancing, Vaccination, Humans, COVID-19, Pandemics

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Top 10%
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