A pilot randomized controlled trial of transdiagnostic network-informed personalized treatment for eating disorders versus enhanced cognitive behavioral therapy

Objective: Eating disorders (EDs) are serious mental illnesses with high mortality and relapse rates and carry significant societal and personal costs. Nevertheless, there are few evidence-based treatments available. One aspect that makes treatment difficult is the high heterogeneity in symptom presentation. This heterogeneity makes it challenging for clinicians to identify pertinent treatment targets. Personalized treatment based on idiographic models may be well-suited to address this heterogeneity, and, in turn, presumably improve treatment outcomes. Methods: In the current randomized controlled trial, participants will be randomly assigned to either 20 sessions of enhanced cognitive behavioral therapy (CBT-E) or transdiagnostic network-informed personalized treatment for EDs (T-NIPT-ED). Assessment of ED symptoms, clinical impairment, and quality of life will occur at pre, mid-, posttreatment, and 1-month follow-up. Results: We will examine the acceptability and feasibility of T-NIPT-ED compared to CBT-E. We also will test the initial clinical efficacy of T-NIPT-ED versus CBT-E on clinical outcomes (i.e., ED symptoms and quality of life). Finally, we will test if the network-identified precision targets are the mechanisms of change. Discussion: Ultimately, this research may inform the development and dissemination of evidence-based personalized treatments for EDs and serve as an exemplar for personalized treatment development across the broader field of psychiatry. Public Significance: Current evidence-based treatments for eating disorders result in low rates of recovery, especially for adults with AN. Our study aims to test the feasibility, acceptability, and clinical efficacy of a data-driven, individualized approach to ED treatment, network-informed personalized treatment, compared to the current evidencebased treatment for EDs, Enhanced CBT. Findings have the potential to improve treatment outcomes for EDs by identifying and targeting core symptoms maintaining EDs.