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ViewAttendees 2

Symposia

Technology/Digital Health

Generative Artificial Intelligence in PTSD Treatment: Exploring Different Use Cases of Novel Technologies

2 - (SYM 54) A Generative Ai-based Simulated Patient for Post-workshop Written Exposure Therapy Therapist Practice and Support

Friday, November 15, 2024
2:30 PM – 3:30 PM EST
Location: Liberty B, Level 3, Marriott Downtown
Abstract Body
Post-workshop therapist support or consultation is an important element of evidence-based treatment training and implementation efforts. However in most mental health settings, consultation is unavailable or out of reach due to the time, costs, and access to expert clinicians required. Even when consultation is available, it takes months to attain competence and trainees’ learning opportunities are limited to clinical issues that they encounter with the first one to two cases they see. Additionally, the time required to complete a required number of cases with consultation before successful completion of the training program is often several months. Standardized Patients have been used in training physicians for many years and have been used in some studies to evaluate therapist skill or training success, but the training required to ensure standardization of hired actors and fidelity assessors, and the logistics required to set up and complete these interactions is also often prohibitive. Generative AI-based simulated patient interactions may represent a more feasible and scalable way to provide opportunities to practice, receive feedback and assess fidelity and may reduce or eliminate the need for consultation. They can provide a low-stakes opportunity to practice and develop skills and comfort with both common and increasingly complex clinical scenarios before beginning treatment with actual clients.

In this presentation, we will describe the development and testing of the simulated patient tool. We piloted a prototype of two Written Exposure Therapy (WET) Simulated Patients with therapists who participated in a WET training program (n=10), and conducted evaluation and interviews with these therapists plus an additional sample of therapists as part of a user-centered design process (n=20). We will present qualitative and quantitative results using interview and program evaluation data. Program evaluation data on fidelity and case trajectories will be presented and benchmarked to evaluation data from a standard WET training and consultation program. Additionally, interview data will provide insights into therapists' experiences and suggestions for refinement. We will discuss our findings' implications for training and implementation and consider advantages and limitations of technology for scaling implementation and making post-training practice and support more feasible for therapists working in low resource settings.