HIV-Related Intersectional Stigma and Discrimination Measurement: State of the Science

Background. Across settings, individuals from populations that are multiply stigmatized are at increased risk of HIV and experience worse HIV treatment outcomes. As evidence expands on how intersecting stigmatized identities and conditions influence HIV outcomes, researchers have used diverse quantitative approaches to measure HIV-related intersectional stigma and discrimination. To date, no clear consensus exists regarding how to best quantitatively measure and analyze intersectional stigma and discrimination. Objectives. To review and document existing quantitative measures of HIV-related intersectional stigma and discrimination to inform research, programmatic, and policy efforts. Search Methods. We searched 5 electronic databases for relevant studies. References of included articles were screened for possible inclusion. Additional articles were screened on the basis of consultations with experts in the field. Selection Criteria. We included peer-reviewed studies published between January 1, 2010, and May 12, 2021, that were HIV related and presented 1 or more quantitative measures of stigma and discrimination using an intersectional lens in measure design or analysis. Data Collection and Analysis. Systematic methods were used to screen citations and abstract data via a standardized coding form. Data were analyzed by coding categories stratified according to 2 subgroups: (1) studies incorporating a single intersectional measure and (2) studies that examined intersectional stigma through analytical approaches combining multiple measures. Main Results. Sixteen articles met the inclusion criteria, 7 of which explicitly referenced intersectionality. Ten studies were from the United States. All of the studies included participants living with HIV. Among the 4 studies incorporating a single intersectional stigma measure, 3 explored race and gender stigma and 1 explored gender and HIV stigma. Studies involving analytic approaches (n 5 12) mostly examined intersectional stigma via interaction terms in multivariate regression models. Three studies employed structural equation modeling to examine interactive effects or latent constructs of intersectional stigma. Conclusions. Research on the measurement of HIV-related intersectional stigma and discrimination is currently concentrated in high-income settings and generally focuses on the intersection of 2 identities (e.g., race and gender). Efforts are needed to expand appropriate application of intersectionality in the development, adaptation, and use of measures of HIV-related intersectional stigma and discrimination. The use of context-, identity-, or condition-adaptable measures should be considered. Researchers should also carefully consider how to meaningfully engage communities in the process of measurement development. Public Health Implications. The measures and analytic approaches presented could significantly enhance public health efforts in assessing the impact of HIV-related intersectional stigma and discrimination on critical health outcomes.