Improving the quality of cognitive behavioral therapy using AI feedback
Enhancing the quality of CBT in community mental health through AI-generated fidelity feedback
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 ID | NIH-10885113 on NIH RePORTER |
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.
Who could benefit from this research
Good fit: Ideal candidates for this research are adults receiving cognitive behavioral therapy for mental health issues in community settings.
Not a fit: Patients who are not receiving cognitive behavioral therapy or those under 21 years old may not benefit from this research.
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 performed: 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
Seattle, United States
- Lyssn.io, INC. — Seattle, United States (Active)
Researchers
- Principal investigator: Atkins, David Charles — Lyssn.io, INC.
- Study coordinator: Atkins, David Charles
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 below.