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Reviews of "Over-estimation of Covid-19 Risks to Healthy and Non-Elderly Predict Support for Continuing Restrictions Past Vaccinations"

Reviewers: F van Vugt (University of Montreal) | 📒📒📒 ◻️◻️

Published onApr 14, 2022
Reviews of "Over-estimation of Covid-19 Risks to Healthy and Non-Elderly Predict Support for Continuing Restrictions Past Vaccinations"
key-enterThis Pub is a Review of
Over-estimation of Covid-19 Risks to Healthy and Non-Elderly Predict Support for Continuing Restrictions Past Vaccinations
Description

I test the possibility that people who provide higher estimates of negative consequences of Covid-19 (e.g., hospitalizations, deaths, and threats to children) will be more likely to support the ‘new normal’; continuation of restrictions for an undefined period of time starting with wide-spread access to vaccines and completed vaccinations of vulnerable people. Results based on N = 1,233 from April, 2021 suggested that people over-estimate Covid-19 risks, and those over-estimates were consistently related to stronger support for continuing restrictions. This relationship emerged in four different samples, using core and supplementary risk estimations, and persisted after controlling for Covid-19 denialism, political ideology, and personal concern of contracting Covid-19. People were also more likely to support continuing restrictions if they believed there is scientific consensus on Covid-19 matters, even on issues where there is none (e.g., wearing masks while driving alone). The study concludes with a discussion of the ethical implications of letting both over- and under-estimation of Covid-19 go uncorrected. Just as it is important to combat misinformation that leads people to disregard health mandates, it is crucial to examine the real possibility that people’s support for continuing risk mitigation practices may also not be based on accurate information.

To read the original manuscript, click the link above.

Reviewer 1 (Floris van V…) | 📒📒📒 ◻️◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the reviews, click the links below. 


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