Owlstown Text-Only

Elizabeth W. Lampe

Go to full site
Home
Publications
Projects
Courses
Mentorship

From Skepticism to Support: Addressing Clinician and Patient Concerns About AI in Eating Disorder Care.

Journal article

Nicholas C. Jacobson, E. Lampe, Ellen E. Fitzsimmons-Craft
International Journal of Eating Disorders, 2025
Semantic Scholar DOI PubMed
Cite

Cite

APA   Click to copy
Jacobson, N. C., Lampe, E., & Fitzsimmons-Craft, E. E. (2025). From Skepticism to Support: Addressing Clinician and Patient Concerns About AI in Eating Disorder Care. International Journal of Eating Disorders.

Chicago/Turabian   Click to copy
Jacobson, Nicholas C., E. Lampe, and Ellen E. Fitzsimmons-Craft. “From Skepticism to Support: Addressing Clinician and Patient Concerns About AI in Eating Disorder Care.” International Journal of Eating Disorders (2025).

MLA   Click to copy
Jacobson, Nicholas C., et al. “From Skepticism to Support: Addressing Clinician and Patient Concerns About AI in Eating Disorder Care.” International Journal of Eating Disorders, 2025.

BibTeX   Click to copy 

@article{nicholas2025a,
  title = {From Skepticism to Support: Addressing Clinician and Patient Concerns About AI in Eating Disorder Care.},
  year = {2025},
  journal = {International Journal of Eating Disorders},
  author = {Jacobson, Nicholas C. and Lampe, E. and Fitzsimmons-Craft, Ellen E.}
}

Abstract

While Linardon and colleagues reveal cautious attitudes toward artificial intelligence (AI) in eating disorder care, our recent empirical evidence suggests that specialized, expert-developed AI interventions can effectively support individuals at risk for eating disorders. However, unlike specialized AI, general-purpose AI (systems designed for broad tasks without specific clinical fine-tuning) often produces harmful content for eating disorder-related prompts, highlighting the need for specialized systems with strong ethical guardrails. Responsible AI integration requires balancing legitimate clinical concerns with evidence-based implementation, positioning AI not as a replacement for human providers, but as a complementary tool to expand access to quality care for the many individuals unable to receive traditional treatment.