Evidence map›Paper›PMID 40205596›Full record

ReviewJournal of eating disorders2025

Treating the individual: moving towards personalised eating disorder care.

Emma Bryant, Peta Marks, Kristi Griffiths, Stephanie Boulet, Melissa Pehlivan, Sarah Barakat, Stephen Touyz, Sarah Maguire

Abstract readReview
In one paragraph

Review in 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 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  18. Anorexia nervosa: 150 years of critical theory.Journal of eating disorders · 2026
    Review
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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

8 authors.

Emma BryantInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia. emma.bryant@sydney.edu.au.
Peta MarksInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Kristi GriffithsInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Stephanie BouletInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Melissa PehlivanInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Sarah BarakatInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Stephen TouyzInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
Sarah MaguireInsideOut Institute for Eating Disorders, Faculty of Medicine and Health, University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.

Funding

Commonwealth Department of Health, Australia P051002-4GOTT7NX
6 · The paper itself

Abstract

Eating disorders (EDs) are complex and heterogeneous conditions, which are often not resolved with conventional, manualised treatments. Arguments for the development of holistic, person-centred treatments accounting for individual variability have been mounting amongst researchers, clinicians and people with lived experience alike. This review explores the transformative potential of personalised medicine in ED care, emphasising the integration of precision diagnostics and tailored interventions based on individual genetic, biological, psychological and environmental profiles. Building on advancements in genomics, neurobiology, and computational technologies, it advocates for a shift from categorical diagnostic frameworks to symptom-based and dimensional approaches. The paper summarises emerging evidence supporting precision psychiatry, including the development of biomarkers, patient-reported outcomes, predictive modelling, and staging models, and discusses their application in ED research and clinical care. It highlights the utility of machine learning and idiographic statistical methods in optimising therapeutic outcomes and identifies key challenges, such as ethical considerations, scalability and implementation.

Indexed as

Eating disordersHolistic careIdiographicIndividualised medicinePersonalised medicinePerson-centredPrecision diagnosticsPrecision psychiatry

Identifiers

PMID40205596
PMCPMC11983806

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.