Improving the quality of cognitive behavioral therapy using AI feedback
Official title: Enhancing the quality of CBT in community mental health through AI-generated fidelity feedback
Funded at Lyssn.io, INC. · NIH-10885113 · Data updated 2026-11-12
This study is testing a new AI tool that listens to therapy sessions to help therapists improve their skills, making cognitive behavioral therapy even better for people in community mental health settings.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Lyssn.io, INC. NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project start | August 5, 2021 |
| Project end | July 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $697,475 |
| NIH project number | 5R42MH128101-04 |
| Project ID | NIH-10885113 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults receiving cognitive behavioral therapy for mental health issues in community settings.
✕Less likely to help
Patients who are not receiving cognitive behavioral therapy or those under 21 years old may not benefit from this research.
What this research studies
This research aims to enhance the quality of cognitive behavioral therapy (CBT) by developing an AI-based software system that evaluates the fidelity of therapy sessions. By analyzing audio recordings of CBT sessions, the system will provide real-time feedback to therapists, helping them improve their techniques and effectiveness. This innovative approach seeks to make quality assessment scalable and accessible in community mental health settings, where traditional methods are often impractical. The project builds on previous successes in using AI for evaluating therapy practices, ensuring a robust methodology.
Why it matters
Potential benefit: If successful, this research could lead to higher quality mental health care through improved therapy practices, ultimately benefiting patients' treatment outcomes.
How similar studies have gone: Previous research has shown success in using AI algorithms to evaluate therapy fidelity, indicating a promising approach for this project.
Where this research is happening
-
Lyssn.io, INC.
Seattle, United States Active
Researchers
- Principal investigator: Atkins, David Charles — Lyssn.io, INC.
- Study coordinator: Atkins, David Charles
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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.