Understanding Technology Fit Among People with HIV Based on Intersections of Race, Sex, and Sexual Behavior: An Equitable Approach to Analyzing Differences Across Multiple Social Identities

HIV disproportionately impacts individuals based on intersecting categories (e.g. gender, race/ethnicity, behavior), with groups most at-risk deemed priority populations. Using weighted effects coding to account for differential group sizes, this study used multilevel mixed logistic models to investigate differences in eHealth use and willingness to use eHealth for HIV-related information among priority populations. Compared to the sample average, Black men who had sex with women were less likely to use all technologies except cellphones with text-messaging and less likely to be willing to use computers and tablets. White and Hispanic men who had sex with men were more likely to use all technologies. No significant differences existed for use or willingness to use cellphones with text-messaging. Future research should consider approaches used here to account for equity and multiple intersecting social identities; practitioners may use these findings or similar local data to ensure fit between eHealth programs and priority populations.