Catch My Drift: Building Scalable and Sustainable Models for Promoting Clinician Adherence to Evidence-Based Treatments for Eating Disorders

Abstract Lock and colleagues showed promising effects for asynchronous virtual training in family-based treatment for anorexia nervosa paired with expert case-based consultation to promote fidelity. In this commentary, we present two promising directions by which to extend these early findings: (1) using AI to scale fidelity monitoring and prevent clinician drift over time; (2) broadening the reach of virtual training models beyond private practice settings to improve the quality of eating disorders services delivered in community settings and narrow the treatment gap.