# Applying Computational Phenotypes To Assess Mental Health Disorders Among Transgender Patients in the United States

> **NIH NIH F31** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $41,011

## Abstract

PROJECT SUMMARY
Transgender (TG) individuals have high prevalence of depression (64%) and are nearly nine times as likely to
attempt suicide compared to the general population. Studies have not consistently collected data related to TG
identity nor have they used the recommended two-step method of asking for assigned sex at birth and current
gender identity. This population is largely overlooked in epidemiologic studies due to small sample size. With
inconsistent and inaccurate ascertainment of TG patients in real-world data sources, TG people are missed
and their health trends over time are understudied. Researchers are unable to identify and meaningfully
address mental health inequities for this population, which can further exacerbate and perpetuate psychiatric
conditions. It remains unclear what the health care utilization trends are for TG patients with psychiatric
disorders and their adherence and persistence to psychiatric medications over time. Understanding this
population’s mental health using large datasets is imperative in order to optimize the care management of
psychiatric conditions experienced by TG people.
The objectives of this proposal are to: (1) apply and evaluate the performance of existing computational
phenotypes (CPs) to identify TG patients with depressive disorders (DD), anxiety, and attention deficit
disorders (ADD), (2) assess adherence and prevalence of psychiatric medications among TG patients
diagnosed with psychiatric disorders compared to cisgender patients with these diagnoses, and (3)
examine the risk of non-fatal self-harm among TG patients with psychiatric disorders receiving
psychotherapy compared to TG patients not receiving psychotherapy. For all aims, IBM MarketScan from
years 2008 to 2020 will be used, which is a large, longitudinal medical claims database that includes
inpatient and outpatient visits and prescription medication use. The completion of the proposed aims will
provide real-world evidence on mental health care for TG individuals in the United States.
The training plan outlined in this proposal will equip the applicant with critical knowledge and necessary
skills in social and pharmacoepidemiology and transgender mental health. This plan will prepare him to
successfully complete the proposed aims and to progress into a role as an independent, interdisciplinary
researcher studying the intersection of pharmacoepidemiology and transgender health equity in the US.
The applicant is extremely well supported by an interdisciplinary group of social, psychiatric, and
pharmacoepidemiology faculty, health disparities researchers, and pharmaceutical researchers with the
requisite expertise to support his doctoral research and prepare him for the next phase of his career.

## Key facts

- **NIH application ID:** 10828306
- **Project number:** 5F31MH132187-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Theo Beltran
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $41,011
- **Award type:** 5
- **Project period:** 2023-08-01 → 2025-03-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10828306

## Citation

> US National Institutes of Health, RePORTER application 10828306, Applying Computational Phenotypes To Assess Mental Health Disorders Among Transgender Patients in the United States (5F31MH132187-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10828306. Licensed CC0.

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