AI-based Simulated Patients to Train Therapists in Written Exposure Therapy for PTSD
Official title: Evaluation of a Multiagent LLM-Based Simulated Patient to Train Therapists in Written Exposure Therapy for PTSD
Funded at Stanford University · NIH-11392704 · Data updated 2026-11-12
A Stanford-led project uses an AI-powered simulated patient system to help therapists learn Written Exposure Therapy for PTSD more effectively than workshops alone.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | August 8, 2025 |
| Project end | July 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $131,900 |
| NIH project number | 5P50MH139450-02 |
| Project ID | NIH-11392704 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable to patient participation; the study targets clinician training and implementation contexts.
✕Less likely to help
Patients will not be directly enrolled as participants in this training-focused grant.
What this research studies
This project aims to strengthen PTSD care by teaching therapists how to deliver Written Exposure Therapy through an AI-assisted training tool that simulates real patient interactions and provides real-time feedback. Therapists practice WET with virtual patients and a simulated consultant, using scenarios of varying difficulty to build skills without needing live clients. The approach blends cutting-edge AI with hands-on practice to improve clinical outcomes and reduce barriers to expert consultation. The study will compare this mixed training model to traditional training methods in people who would normally train clinicians in WET. Partnerships with health systems will support implementation and evaluation in real-world settings.
Why it matters
Potential benefit: If successful, therapists will gain more effective and scalable training in WET, potentially increasing access to PTSD treatment for patients.
How similar studies have gone: Previous experiential training approaches with simulated practice have shown promise, but this AI-driven SIT represents a novel integration for WET.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Kaysen, Debra L — Stanford University
- Study coordinator: Kaysen, Debra L
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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.