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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jul 14, 2026
Date Accepted: Jul 16, 2026

The final, peer-reviewed published version of this preprint can be found here:

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

Goldschmidt AB, Graham AK

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

J Med Internet Res 2026;28:e107039

DOI: 10.2196/107039

PMID: 42585573

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

  • Andrea Beth Goldschmidt; 
  • Andrea Kass Graham

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 extending from these early findings: 1) using artificial intelligence to scale fidelity monitoring and prevent clinician drift over time; 2) extending the reach of virtual training models beyond private practice settings to improve the quality of eating disorder services delivered in community settings and narrow the treatment gap.


 Citation

Please cite as:

Goldschmidt AB, Graham AK

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

J Med Internet Res 2026;28:e107039

DOI: 10.2196/107039

PMID: 42585573

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