The predictive value of emotion regulation difficulties and negative mood on short and long‐term treatment outcomes in an online guided self‐help programme for adults with binge‐eating disorder

The clinical trial register number is not given in this version of the manuscript due to anonymisation.

Authors

Institutions

Publication Details

Journal
European Eating Disorders Review
Published
2024-09-20
DOI
https://doi.org/10.1002/erv.3135
Citations
1
Primary Topic
Eating Disorders and Behaviors
Type
article
Field-Weighted Citation Impact
0.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The predictive value of emotion regulation difficulties and negative mood on short and long‐term treatment outcomes in an online guided self‐help programme for adults with binge‐eating disorder

Andrea Wyssen, Simone Munsch, Andrea H. Meyer, Felicitas Forrer et al.
1 citations
European Eating Disorders Review
Eating Disorders and Behaviors
0.64
article

The predictive value of emotion regulation difficulties and negative mood on short and long‐term treatment outcomes in an online guided self‐help programme for adults with binge‐eating disorder

Andrea Wyssen, Simone Munsch, Andrea H. Meyer, Felicitas Forrer, Marius Rubo
article en
1 citations

Abstract

The clinical trial register number is not given in this version of the manuscript due to anonymisation.

European Eating Disorders ReviewVol. 33(1)
University of Bern (CH), University of Fribourg (CH), University of Basel (CH)
Schweizerische Anorexia Nervosa Stiftung
Openalex Percentile: Top 28%
Eating Disorders and Behaviors
0.64
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.