5 - (SYM 9) Web-based and Ai-supported Provider Trainings for Written Exposure Therapy

Written exposure therapy (WET) is a brief, exposure-based, evidence-based treatment (EBT) for PTSD with demonstrated non-inferiority to existing gold-standard treatments. Traditional WET training models involve a 2-day, live workshop followed by ongoing clinical consultation, which has been shown to solidify competency development. Despite high demand for training in WET, implementation efforts are hindered by the high cost and provider time requirements of engaging in workshops and consultation and a shortage of consultants. Asynchronous and automated training solutions which can be completed flexibly around the provider’s schedule, and which do not require consultant time, may help increase training capacity in WET. Given the demonstrated value of competency-based training, solutions which allow providers to engage in real-time practice of delivering WET while receiving high-fidelity feedback on their practice hold promise for increasing provider competency and patient outcomes. In response to the need for such training solutions, this presentation discusses the development of a fully virtual, modular, web-based training course for providers to learn WET. Large language model (LLM) based components will be embedded in the web-based training and will allow providers to practice delivering WET in a session-by-session manner via role play practice with an AI-patient while receiving high-fidelity feedback from an AI-consultant. The LLM-based components also allow providers to engage in repeat practice of WET skills providers often find challenging, like delivering feedback on the patient’s trauma narrative, as well as to ask questions and get help with patients on their caseload. As part of a randomized clinical trial, we will compare these asynchronous and automated training strategies to training as usual, comparing provider competency, training efficiency, cost-effectiveness, and patient outcomes. Asynchronous and automated training tools hold promise to dramatically increase the reach of evidence-based treatments.