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MEASURING EVERYDAY RACIAL/ETHNIC DISCRIMINATION IN HEALTH SURVEYS

How Best to Ask the Questions, in One or Two Stages, Across Multiple Racial/Ethnic Groups?1

Published online by Cambridge University Press:  15 April 2011

Salma Shariff-Marco*
Affiliation:
Division of Cancer Control and Population Sciences, National Cancer Institute
Nancy Breen
Affiliation:
Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute
Hope Landrine
Affiliation:
Center for Health Disparities Research, East Carolina University
Bryce B. Reeve
Affiliation:
Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute
Nancy Krieger
Affiliation:
Harvard School of Public Health, Harvard University
Gilbert C. Gee
Affiliation:
School of Public Health, University of California, Los Angeles
David R. Williams
Affiliation:
Department of Society, Human Development, and Health, Harvard School of Public Health; Departments of African and African American Studies and of Sociology, Harvard University
Vickie M. Mays
Affiliation:
School of Public Health, University of California, Los Angeles and Center for Research, Education, Training, and Strategic Communication on Minority Health Disparities, University of California, Los Angeles
Ninez A. Ponce
Affiliation:
School of Public Health, University of California, Los Angeles and UCLA Center for Health Policy and Research
Margarita Alegría
Affiliation:
Harvard Medical School, Harvard University
Benmei Liu
Affiliation:
Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute
Gordon Willis
Affiliation:
Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute
Timothy P. Johnson
Affiliation:
Survey Research Laboratory, Department of Public Administration and Institute for Health Research and Policy, University of Illinois at Chicago
*
Salma Shariff-Marco, Cancer Prevention Institute of California, 2201 Walnut Avenue, Suite 300, Fremont, CA 94538. E-mail: salma.shariffmarco@cpic.org

Abstract

While it is clear that self-reported racial/ethnic discrimination is related to illness, there are challenges in measuring self-reported discrimination or unfair treatment. In the present study, we evaluate the psychometric properties of a self-reported instrument across racial/ethnic groups in a population-based sample, and we test and interpret findings from applying two different widely-used approaches to asking about discrimination and unfair treatment. Even though we found that the subset of items we tested tap into a single underlying concept, we also found that different groups are more likely to report on different aspects of discrimination. Whether race is mentioned in the survey question affects both frequency and mean scores of reports of racial/ethnic discrimination. Our findings suggest caution to researchers when comparing studies that have used different approaches to measure racial/ethnic discrimination and allow us to suggest practical empirical guidelines for measuring and analyzing racial/ethnic discrimination. No less important, we have developed a self-reported measure of recent racial/ethnic discrimination that functions well in a range of different racial/ethnic groups and makes it possible to compare how racial/ethnic discrimination is associated with health disparities among multiple racial/ethnic groups.

Type
Unpacking Racism and its Health Consequences
Copyright
Copyright © W.E.B. Du Bois Institute for African and African American Research 2011

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Footnotes

1

We would like to thank the NCI Division of Cancer Control and Population Sciences (DCCPS) and the NIH Office of Behavioral Social Sciences Research for co-funding the 2007 field test, and NCI DCCPS for providing staff for this project. We would also like to acknowledge the Cancer Prevention Fellowship Program, Office of Preventive Oncology, National Cancer Institute, for providing financial support for S. Shariff-Marco in her postdoctoral fellowship; Tim McNeel and William Waldron at IMS for their programming support; and Penny Randall-Levy of the Scientific Consulting Group, Inc., for her help with the references. We would also like to acknowledge Drs. David Grant, E. Richard Brown, and David Takeuchi for their participation in this research project. Finally, we would like to acknowledge Drs. William Klein and Rachel Ballard-Barbash for their thoughtful reviews.

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