Automated Quality Coding for Exposure Therapy Using NLP
Official title: Automated Coding of Exposure Therapy Quality using Natural Language Processing
Funded at Emma Pendleton Bradley Hospital · NIH-11296878 · Data updated 2026-11-12
A research project uses artificial intelligence to automatically measure how well exposure therapy is delivered in anxiety treatment trials and real-world settings, helping clinicians improve care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emma Pendleton Bradley Hospital NIH-funded |
| Lab location | 1 site (Riverside, UNITED STATES) |
| Project start | April 12, 2024 |
| Project end | January 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $563,260 |
| NIH project number | 5R01MH135861-03 |
| Project ID | NIH-11296878 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults and youth who are receiving or have received exposure therapy for anxiety in research trials or community treatment settings.
✕Less likely to help
Patients not receiving exposure therapy or in non-anxiety psychiatric contexts may not directly benefit from this project.
What this research studies
This project aims to develop and test an automated quality coding system powered by natural language processing to streamline how we track adherence to exposure therapy protocols. It builds on pilot work and uses audio data from 1,286 patients across 11,213 therapy sessions in six trials, spanning youth and adults in both research and community settings. By partnering with NIMH researchers, the Exposure Therapy Consortium, and patient and family stakeholders, the study seeks to create practical tools that reduce manual coding burden and enhance fidelity monitoring. The work will inform how quality components influence treatment outcomes and support broader adoption of evidence-based interventions in mental health care.
Why it matters
Potential benefit: If successful, clinicians and researchers could more efficiently ensure exposure therapy is delivered with high quality, potentially improving anxiety treatment outcomes for patients.
How similar studies have gone: Prior pilot work suggests automated quality coding can be feasible, with potential for scalable, real-time monitoring in clinical trials and practice.
Where this research is happening
-
Emma Pendleton Bradley Hospital
Riverside, United States Active
Researchers
- Principal investigator: Benito, Kristen G — Emma Pendleton Bradley Hospital
- Study coordinator: Benito, Kristen G
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.