# Development and Preliminary Trial of a Digital Transdiagnostic CBT Intervention for Transgender Adolescents

> **NIH NIH R34** · LURIE CHILDREN'S HOSPITAL OF CHICAGO · 2024 · $249,765

## Abstract

PROJECT SUMMARY
The proposed study will develop and evaluate a transdiagnostic gender-affirmative CBT-based digital mental
health intervention for transgender and nonbinary (TNB) adolescents. TNB adolescents are at profound mental
health risk. Compared to cisgender (non-TNB) adolescents, TNB adolescents have a two- to three-fold increased
risk for depression, anxiety, and suicidality. Moreover, TNB adolescents experience unique stressors related to
their gender minority identities that contribute to the development of psychological distress, including depression
and anxiety. Yet very little research has focused on adapting evidence-based interventions that are known to be
effective in treating depression and anxiety for TNB adolescents by incorporating minority stress considerations,
and none have been developed specifically for mobile delivery. Leveraging technology to deliver culturally
tailored, evidence-based mental health interventions to TNB adolescents holds great promise to reduce health
disparities and improve mental health outcomes in this health disparity population with documented barriers
accessing competent mental health care.

## Key facts

- **NIH application ID:** 10868380
- **Project number:** 1R34MH133768-01A1
- **Recipient organization:** LURIE CHILDREN'S HOSPITAL OF CHICAGO
- **Principal Investigator:** Diane Chen
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $249,765
- **Award type:** 1
- **Project period:** 2024-05-01 → 2025-03-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10868380

## Citation

> US National Institutes of Health, RePORTER application 10868380, Development and Preliminary Trial of a Digital Transdiagnostic CBT Intervention for Transgender Adolescents (1R34MH133768-01A1). Retrieved via AI Analytics 2026-06-03 from https://api.ai-analytics.org/grant/nih/10868380. Licensed CC0.

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