A mixed-methods approach to developing a self-reported racial/ethnic discrimination measure for use in multiethnic health surveys

Abstract

Objective: The development of measures of self-reported racial/ethnic discrimination is an active area of research, but few measures have been validated across multiple racial/ethnic and language groups. Our goal is to develop and evaluate a discrimination measure that is appropriate for use in surveys of racially and ethnically diverse populations.

Methods: To develop our measure, we employ a mixed-methods approach for survey research, drawing from both qualitative and quantitative traditions, including literature review, cognitive testing, psychometric analyses, behavior coding as well as two rounds of field testing using a split-sample design. We tested our new measure using two different approaches to elicit self-reported experiences of racial/ethnic discrimination.

Results: Our new measure captures four dimensions of racial/ethnic discrimination: 1) frequency of encounters with discrimination across several domains (eg, medical care, school, work, street and other public places); 2) timing of exposure (eg recent, lifetime); 3) appraisal of discrimination as stressful; and 4) responses to discrimination.

Conclusions: Because of the growing interest in measurement of racial/ethnic discrimination in health surveys, we think this report on the methods informing the development and testing of the discrimination module that will be used on the California Health Interview Survey would be useful to other researchers. The application of mixed methods to rigorously test the validity and reliability of our instrument proves to be a good roadmap for measuring racial/ethnic discrimination in multicultural and multilingual populations.

Figure 1

Overview of the development of a self-reported racial/ethnic discrimination module for the California Health Interview Survey (CHIS)