Evidence map›Paper›PMID 39829089›Full record

ArticleThe International journal of eating disorders2025

Current Practices and Perspectives of Artificial Intelligence in the Clinical Management of Eating Disorders: Insights From Clinicians and Community Participants.

Jake Linardon, Claudia Liu, Mariel Messer, Zoe McClure, Cleo Anderson, Hannah K Jarman

Abstract read
In one paragraph

Article in The International journal of eating disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Leveraging Technology to Enhance Eating Disorder Treatment Outcomes.The Psychiatric clinics of North America · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. AI-Readiness in the Eating Disorders Field.The International journal of eating disorders · 2025
    Article
  10. All in the Name of Artificial Intelligence: A Commentary on Linardon (2025).The International journal of eating disorders · 2025
    Article
  11. Article
  12. Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jake LinardonSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.ORCID 0000-0003-4475-7139
Claudia LiuSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Mariel MesserSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.ORCID 0000-0002-7186-7264
Zoe McClureSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.ORCID 0000-0003-3926-8058
Cleo AndersonSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.ORCID 0000-0002-1203-5492
Hannah K JarmanSEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.

Funding

National Health and Medical Research Council Investigator Grant APP1196948
6 · The paper itself

Abstract

objectiveArtificial intelligence (AI) could revolutionize the delivery of mental health care, helping to streamline clinician workflows and assist with diagnostic and treatment decisions. Yet, before AI can be integrated into practice, it is necessary to understand perspectives of these tools to inform facilitators and barriers to their uptake. We gathered data on clinician and community participant perspectives of incorporating AI in the clinical management of eating disorders.

methodA survey was distributed internationally to clinicians (n = 116) with experience in eating disorder treatment (psychologists, psychiatrists, etc.) and community participants (n = 155) who reported occurrence of eating disorder behaviors.

results59% of clinicians reported use of AI systems (most commonly ChatGPT) for professional reasons, compared to 18% of community participants using them for help-related purposes. While more than half of clinicians (58%) and community participants (53%) were open for AI to help support them, fewer were enthusiastic about their integration (40% and 27%, respectively) and believed that they would significantly improve client outcomes (28% and 13%, respectively). Nine in 10 agreed that AI may be improperly used if individuals are not adequately trained, and could pose new data privacy and security concerns. Most agreed that AI will be convenient, beneficial for administrative tasks, and an avenue for continuous support, but will never outperform human clinicians on relational skills.

conclusionWhile many clinicians and community participants are open to the use of AI in eating disorder treatment and recognize its possible wide-ranging benefits, most remain cautious and uncertain about its implementation.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelFeeding and Eating DisordersAdultFemaleHumansMaleMiddle AgedSurveys and Questionnairesartificial intelligenceclinical practiceeating disorderstechnology

Identifiers

PMID39829089
PMCPMC11969028

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.