Skip to main content
11th WCCBT Congress Main banner
Final Program


Icon Legend
This session is not in your schedule.
This session is in your schedule. Click again to remove it.
Presentation Icons
Recorded Session
Recorded Session
Ticketed Session
Ticketed Session

Symposium

Artificial Intelligence and Technology-based Interventions

From Innovation to Implementation: Uses of Artificial Intelligence to Support Training and Skill in CBT

3 - (SYM 20) Supporting Evidence-based Therapy Skills and Implementation with Llm-based Simulation and Consultation

Friday, June 26, 2026
4:41 PM - 5:00 PM PDT
Location: Yerba Buena Salon 13, B3 Level
Keywords: Implementation, Training / Training Directors, Technology / Mobile Health
Abstract Body
Nearly 7% of the U.S. population experiences post-traumatic stress disorder (PTSD), which has a substantial impact on quality of life and physical health, and results in high costs to society. While several evidence-based psychotherapies (EBPs) have demonstrated effectiveness in treating PTSD, most individuals with PTSD do not receive these treatments. Access to EBPs is very limited in public and rural mental health contexts that grapple with severe financial constraints while treating a high volume of individuals with PTSD. Innovation is needed to promote the uptake and effective delivery of EBPs in such settings.

Large language models (LLMs) are promising tools to support EBP delivery. They have the potential to provide scalable and just-in-time support to administrators seeking to implement EBPs, therapists who use them, and to support patients between sessions. LLMs also have the potential to detect and activate key mechanisms of change. The CREATE center is a U.S National Institute of Mental Health-funded center that is developing and testing a suite of LLM-based tools to support effective and engaging EBP delivery across the care delivery continuum in under-resourced treatment settings. CREATE uses common frameworks and a user-centered approach to guide the discovery, design and build phases.

In this presentation, we will describe the suite of tools and initial use cases, and provide data on feasibility and acceptability of these tools as well as the initial evaluation results for the quality of LLM-based guidance. The first tool, ImpleMentor, is designed to facilitate the development of an implementation plan and support teams as they implement EBPs in public and under-resourced treatment settings. TherapyTrainer is an LLM-based tool to support therapists as they learn new EBPs through simulation after initial workshop training. COACH-AI provides ongoing consultation and support on clinical cases and clinical challenges. Finally, the worksheet helper tool provides support for patients as they complete EBP homework between sessions and can support quality and efficient care. We will describe the process of development, refinement, and evaluation of these tools and evidence of feasibility for the therapy support tools. Considerations for deployment and integration into training and care delivery, including safety, privacy, effectiveness, engagement, equity, and readiness for implementation will be discussed.