Changing perceptions of people wearing masks: Two years of living in a pandemic.
Published In: European Journal of Social Psychology, 2024, v. 54, n. 6. P. 1141 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Fang, Xia; Kawakami, Kerry 3 of 3
Abstract
Despite the widespread use of face masks to combat COVID‐19, little is known about their immediate and delayed social consequences. To understand short‐ and long‐term effects of face masks on interpersonal perception, we measured the evaluation of faces with and without masks at four time points—June 2020, January 2021, September 2021 and June 2022—from the early months of the pandemic in North America to the more recent, and from the implementation of mask mandates to the end of these requirements. Surprisingly, we found that, in general, faces with masks were perceived as more competent, warm, trustworthy, considerate and attractive, but less dominant and anxious than faces without masks. Moreover, differences in attributions of dominance, trustworthiness and warmth between faces with and without masks increased in a linear trend from June 2020 to June 2022. Notably, the impact of masks on perceptions of competence, considerateness, attractiveness and anxiousness did not change over time. We discuss how mask mandates can alter people's social perceptions of others who wear masks compared to those who do not wear masks and how these mandates may influence attributions of some traits more than others through mere exposure and/or social norms. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:European Journal of Social Psychology. 2024/10, Vol. 54, Issue 6, p1141
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2024
- ISSN:0046-2772
- DOI:10.1002/ejsp.3069
- Accession Number:180109194
- Copyright Statement:Copyright of European Journal of Social Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.