An Automated Algorithm for Classifying Expansive Responses for Gender Identity.

ABSTRACT: Current two-step measures of gender identity do not prescribe methods for using expanded responses (e.g., multiple selections) among sexual and gender minority (SGM) people, though they want the opportunity to provide these responses. To increase statistical power using expanded gender identity responses, we created an automated algorithm to generate analyzable categories. Participants' expanded gender identity responses and sex assigned at birth were used to create five categories (i.e., cisgender men, cisgender women, gender expansive individuals, transgender men, and transgender women) from a cohort of SGM people (N = 6,312, 53% cisgender individuals). Data was collected from June 2020 to June 2021. Chi-square tests were performed to assess the association between the algo

SUBMITTER: Ceja A 

PROVIDER: S-EPMC12629618 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature