The Discrepancies Between Researchers and the Community When Identifying Intervention Targets for Eating Disorders

Findings suggest a marked discrepancy between lived experience and researcher perspectives on what is important to target in interventions for eating disorders. We encourage researchers to lean into this dissent to support rigorous best practice in the development and refinement of mental health interventions.

Authors

Institutions

Publication Details

Journal
International Journal of Eating Disorders
Published
2025-11-28
DOI
https://doi.org/10.1111/eat.70009
Primary Topic
Eating Disorders and Behaviors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Discrepancies Between Researchers and the Community When Identifying Intervention Targets for Eating Disorders

Tracey Wade, Jamie‐Lee Pennesi, Mia L. Pellizzer
International Journal of Eating Disorders
Eating Disorders and Behaviors
article

The Discrepancies Between Researchers and the Community When Identifying Intervention Targets for Eating Disorders

Tracey Wade, Jamie‐Lee Pennesi, Mia L. Pellizzer
article en

Abstract

Findings suggest a marked discrepancy between lived experience and researcher perspectives on what is important to target in interventions for eating disorders. We encourage researchers to lean into this dissent to support rigorous best practice in the development and refinement of mental health interventions.

International Journal of Eating Disorders
Flinders University (AU)
Openalex Percentile: Top 51%
Eating Disorders and Behaviors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.