# Investigating the Portability of an Automated Coding System of the Two-Step Method of Gender

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $164,083

## Abstract

ABSTRACT
The proposed study brings together a team of researchers and leverages already collected data within the
American College Health Association National College Health Assessment (ACHA-NCHA) to examine the
portability of an automated method of classifying gender groupings using the two-step method and expanded
options for gender identity. While the two-step method has been recommended as the gold standard for
assessing sex assigned at birth and gender identity, there is a lack of clarity as to how to classify and identify
gender expansive individuals (i.e., individuals whose identities are not masculine or feminine alone) via that
method. This is important as gender expansive individuals do not identify with the binary framework imposed
when assigning gender identity based on discordance between sex assigned at birth and gender identity.
Additionally, research indicates that there are differences in the health status (such as substance use) and
social determinants of health of individuals who identify as transgender versus individuals who identify as
gender expansive. Our team has created an automated coding method developed with sexual and gender
minority (SGM) people that takes into account multiple gender selections, write-in gender responses, and sex
assigned at birth. In this study we will refine and expand that coding method to use on a sample that includes
both SGM and non-SGM people: the ACHA-NCHA. We expect that our refined automated coding method can
be expanded to a non-SGM data set and can improve classification of people who use write-in responses over
the ACHA-NCHA recommended method. We also expect that our method will significantly reduce the number
of people classified as missing when compared to the ACHA-NCHA recommended method. We will also test
the capability of our method to better predict substance use involvement over the ACHA-NCHA recommended
method. This study will lay the groundwork for rigorous and replicable SGM health research with robust gender
identity methods.

## Key facts

- **NIH application ID:** 10796807
- **Project number:** 3R01DA052016-04S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Annesa Flentje
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $164,083
- **Award type:** 3
- **Project period:** 2020-09-30 → 2025-03-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10796807

## Citation

> US National Institutes of Health, RePORTER application 10796807, Investigating the Portability of an Automated Coding System of the Two-Step Method of Gender (3R01DA052016-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10796807. Licensed CC0.

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