Face masks influence emotion judgments of facial expressions: a drift–diffusion model

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作者
W. Craig Williams
Eisha Haque
Becky Mai
Vinod Venkatraman
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[1] Temple University,Department of Marketing, Fox School of Business
[2] University of Toronto,Department of Psychology
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Face masks slow the spread of SARS-CoV-2, but it has been unknown how masks might reshape social interaction. One important possibility is that masks may influence how individuals communicate emotion through facial expressions. Here, we clarify to what extent—and how—masks influence facial emotion communication, through drift–diffusion modeling (DDM). Over two independent pre-registered studies, conducted three and 6 months into the COVID-19 pandemic, online participants judged expressions of 6 emotions (anger, disgust, fear, happiness, sadness, surprise) with the lower or upper face “masked” or unmasked. Participants in Study 1 (N = 228) correctly identified expressions above chance with lower face masks. However, they were less likely—and slower—to correctly identify these expressions relative to without masks, and they accumulated evidence for emotion more slowly—via decreased drift rate in DDM. This pattern replicated and intensified 3 months later in Study 2 (N = 264). These findings highlight how effectively individuals still communicate with masks, but also explain why they can experience difficulties communicating when masked. By revealing evidence accumulation as the underlying mechanism, this work suggests that time-sensitive situations may risk miscommunication with masks. This research could inform critical interventions to promote continued mask wearing as needed.
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