ArticleThe International journal of eating disorders2026
Artificial Intelligence in Eating Disorder Treatment: A Qualitative Analysis of Clinical Opportunities, Barriers, and Ethical Considerations From Multi-Disciplinary Focus Groups.
Article in The International journal of eating disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Clinicians' Attitudes and Perceptions on the Adoption of AI in Mental Health Care: Scoping Review.Journal of medical Internet research · 2026Article
- AI and machine learning for early identification of eating disorders: a narrative review and Indian contextual insights.Eating and weight disorders : EWD · 2026Review
- Artificial Intelligence in Eating Disorder Treatment: A Qualitative Analysis of Clinical Opportunities, Barriers, and Ethical Considerations From Multi-Disciplinary Focus Groups.The International journal of eating disorders · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectiveThis study explored eating disorder and Artificial Intelligence (AI) professionals' perspectives on how AI might support eating disorder treatment. Successful implementation requires insight into implementation partners' perspectives.
methodThis study is an explorative qualitative analysis of two interdisciplinary focus groups (consisting of 22 eating disorder and AI professionals in total). Qualitative analysis with ATLAS.ti using a hybrid thematic analysis approach combined deductive coding with inductive theme development. The groups discussed (1) the opportunities and challenges-including ethical and safety considerations-of AI in eating disorder care, and (2) the types of evidence and evaluation frameworks required for adoption in practice.
resultsThemes were categorized into "opportunities," "challenges," "concerns," "solutions," and "evidence needed." Opportunities focused on AI's potential to enhance efficiency, support treatment delivery and monitoring, and reduce human error. Challenges concerned barriers to adoption in clinical practice, responsibility, and explainability. Concerns included ethical and legal risks, also related to data sharing. Proposed solutions emphasized the need for human oversight, cross-sector collaboration, and clinician training. With regard to evidence needed, participants mentioned safety and accuracy, and the need for scientific testing and validation. DISCUSSION: This study highlighted the potential and complexity of integrating AI into eating disorder care from the viewpoint of eating disorder and AI professionals. While there is value in AI in improving efficiency and clinical support, successful implementation requires addressing ethical concerns, legal uncertainty, and infrastructural barriers. Collaboration across disciplines, rigorous validation, and clinician involvement are essential to ensure that AI applications are safe, meaningful, and ethically sound.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.