DOI: 10.1177/08944393231219192 ISSN: 0894-4393

Interpersonal and Computer-Mediated Competence for Prejudice Reduction: Learning to Interact Digitally and Physically During the Pandemic

B. C. Bouchillon
  • Law
  • Library and Information Sciences
  • Computer Science Applications
  • General Social Sciences

As racial and ethnic diversity have increased in America, prejudice too has expanded. Citizens are more wary of immigrants, with attitudes toward Asian immigrants in particular worsening during COVID-19. Yet less is known about the prejudice directed at other immigrant groups during this period, with research suggesting that feeling capable of interacting with new people could reduce misgivings about diversity. A web survey was conducted in April of 2020 to test the potential for digital and physical social competence to improve attitudes toward Mexican immigrants, as the largest immigrant group in the United States ( N = 665). Interpersonal competence was inversely associated with prejudice toward Mexican immigrants, with interpersonal skills such as attentiveness, expressiveness, and mindfulness being especially valuable for prejudice reduction. Computer-mediated communication competence was indirectly associated with feeling less prejudiced, through interpersonal competence, and social presence also moderated the conversion of CMC competence into interpersonal competence, diminishing prejudice even further. Digital social capabilities encourage admiration and sympathy for immigrants by making users feel more capable of interacting with them locally. Networked settings now have the potential to train dissimilar users to interact together in person, as a way of reducing prejudice.

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