Evidence map›Paper›PMID 37578836›Full record

ArticleJournal of medical Internet research2023

Ethical Challenges in AI Approaches to Eating Disorders.

Gemma Sharp, John Torous, Madeline L West

Open access · goldAbstract readEditorial
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
9.7field-weighted citation impact, top 1% of its field
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

21 citing papers in PubMed, 31 citations in OpenAlex.

  1. Trial
  2. Article
  3. Design, Implement, Sustain: Advancing Program-Led Interventions for Binge Eating, a Narrative Review.European eating disorders review : the journal of the Eating Disorders Association · 2026
    Review
  4. Article
  5. Leveraging Technology to Enhance Eating Disorder Treatment Outcomes.The Psychiatric clinics of North America · 2026
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. From statistics to deep learning: Using large language models in psychiatric research.International journal of methods in psychiatric research · 2025
    Review
  18. Large Language Models and Artificial Intelligence in Psychiatry Medical Education: Augmenting But Not Replacing Best Practices.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2025
    Article
  19. Article
  20. Article
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

3 authors at 2 institutions in 2 countries.

Gemma SharpDepartment of Neuroscience, Monash University, Melbourne, Australia.ORCID 0000-0001-9946-518X
John TorousDepartment of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-5362-7937
Madeline L WestDepartment of Neuroscience, Monash University, Melbourne, Australia.ORCID 0000-0002-6590-0486
Monash University · AUBeth Israel Deaconess Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of artificial intelligence (AI) to assist with the prevention, identification, and management of eating disorders and body image concerns is exciting, but it is not without risk. Technology is advancing rapidly, and ensuring that responsible standards are in place to mitigate risk and protect users is vital to the success and safety of technologies and users.

Indexed as

Artificial IntelligenceFeeding and Eating DisordersBody ImageHumansTechnologyAIartificial intelligencebody imagechatboteating disordersethics

Identifiers

PMID37578836
PMCPMC10463082
OpenAlexW4385795914

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.