The Cultural Equivalence of Measurement in Substance Use Research

Across a wide range of substance use outcomes, ethnic/racial minorities in the U.S. experience a disproportionately higher burden of negative health outcomes and/or lower levels of access to care (relative to non-Latinx White individuals). Various explanations for these substance use-related health disparities have been proposed. This narrative review will not focus on the theoretical content of these explanations but will instead focus on the underlying statistical frameworks that are used to test such theories. Here, we provide a narrative review of psychometric critiques of cross-cultural research, which collectively suggest that (a) research testing similarities and differences among ethnic/racial groups often miss or omit to test statistical assumptions of equal instrument functioning across the ethnic/racial groups being compared; (b) testing the assumptions of equal instrument functioning is feasible using established guidelines from modern measurement theories; and (c) substance use research may need to explicitly incorporate the tests of equal instrument functioning to prevent bias when making inferences across ethnic/racial groups. We provide recommendations for evaluating the cultural equivalence of measurement using structural equation modeling, and advocate that cross-cultural substance use research move toward statistical approaches that are better positioned to test for (and model) bias in measurement. Explicitly testing the cultural equivalence of measurement when making inferences across cultural groups (within a falsifiable psychometric framework) can advance our understanding of similarities and differences among ethnic/racial groups, and hence can provide a more socially just (and statistically robust) scientific base. Public Health Significance Statistical critiques question the comparability of measurement in research making group comparisons across ethnic/racial groups. Testing the comparability of measurement across ethnic/racial groups is statistically feasible yet infrequently done. Future research may benefit from statistically testing the comparability of measurement when making comparisons across ethnic/racial groups.