Measuring identity multiplicity and intersectionality: Hierarchical Classes Analysis (HICLAS) of sexual, racial, and gender identities

摘要

We propose an innovative approach for measuring identity multiplicity and intersectionality—Hierarchical Classes Analysis (HICLAS) of an Assessment of Multiple Identities. This method allows researchers to assess characteristics of individual identities and model implicit interrelationships between multiple identities held by an individual. We found support for the validity of this approach through analysis of sexual, racial, and gender identities among 40 lesbian, gay, or bisexually identified (LGB) participants. As hypothesized, poorer mental health indicators were significantly associated with greater negative valence of sexual identity and greater negative self-complexity in HICLAS. HICLAS also allowed us to discern subgroup differences indicative of intersectionality (e.g., in this LGB sample, more African American participants than White participants showed interconnected sexual and racial identities).