Exploring gender beyond labels: Uncovering diverse gender groups with latent profile analysis.

Gender is a variable of great interest to couples and family researchers who frequently use gender labels in individual, dyadic, and systems-level analyses. Labels are unsatisfactory representations of gender as a whole, as they may obfuscate nuanced gender experiences that impact health disparities for both transgender and cisgender respondents. However, there is a lack of consensus on how to model the multidimensionality of gender in quantitative analysis. The present study seeks to assess whether latent profile analysis can identify subgroups that could be used to observe patterns in disparities that would be unobserved by single-item gender measures. A sample of 2,404 U.S.-based respondents (79% White, 40% heterosexual, 20% gender minority) completed online surveys assessing the following indices: (a) sex assigned at birth, (b) degree of identification with binary labels (i.e., male and female), (c) expression/roles, and (d) fluidity. A parsimonious seven-group solution revealed four groups representing gender experiences aligned within a binary framework (strongly aligned masculine/feminine, moderately aligned masculine/feminine) and three groups representing experiences outside of the binary (aligned nonbinary feminine, aligned nonbinary/agender, aligned gender fluid). Cisgender and transgender participants appeared in each of the extracted gender classes, highlighting the limitations of gender labels for people across the gender spectrum. Health disparities also emerged across the gender groups, revealing unique challenges with regard to seeking counselling, microaggression exposure, internalized shame, depressive symptoms, and total lifetime suicide attempts. The results of this study provide a preliminary framework for integrating multiple dimensions into more inclusive subgroups. (PsycInfo Database Record (c) 2026 APA, all rights reserved).