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Beyond Fear of Backlash: Effects of messages about structural drivers of COVID-19 disparities among large samples of Asian, Black, Hispanic, and White Americans

Dublin Core

Title

Beyond Fear of Backlash: Effects of messages about structural drivers of COVID-19 disparities among large samples of Asian, Black, Hispanic, and White Americans

Subject

COVID-19 (Disease)--Social aspects--United States

Electronic Resource Item Type Metadata

Author(s)

Neil A. Lewis Jr., Norman Porticella, Jiawei Liu, Teairah Taylor, Jamila Michener, Colleen L. Barry, Rebekah H. Nagler, Sarah Gollust, Steven T. Moore, Erika Franklin Fowler, Jeff Niederdeppe

Journal Name

Social Science & Medicine

Volume

Vol. 377

Publication Date

2025

Publisher

Elsevier

Document Type

Journal article

Language

English

ISBN

18735347

Region

United States

Access

Open Access

Abstract

Although U.S. health disparities are well-documented, the very communities that bear the brunt of those disparities are, ironically, underrepresented in scientific efforts to understand and address them. In two experiments (total N = 9523), we explored the consequences of omitting those perspectives for efforts to understand and address disparities in the COVID-19 pandemic.
We found that, by prioritizing the perspectives of White Americans, studies of pandemic disparities likely missed important insights. Specifically, we purposively sampled the four largest racial and ethnic groups in the U.S. and found that people of color were consistently more concerned, and more willing to engage in both individual and collective efforts to address health disparities, than their White counterparts. In addition, messages highlighting structural drivers of health disparities further bolstered support for inequality mitigating policies.

Cataloger

Haley Lesemann

Citation

“Beyond Fear of Backlash: Effects of messages about structural drivers of COVID-19 disparities among large samples of Asian, Black, Hispanic, and White Americans,” ICMGLT Digital Library, accessed November 3, 2026, https://library.icmglt.org/items/show/811.

Output Formats

Geolocation