Cited by 6Eating Disorders and BehaviorsNutrition, Health and Food BehaviorDigital Mental Health Interventions

Feasibility and acceptability of a digital tele-guided intervention targeting components of the addictive appetite model for bulimia nervosa and binge-eating disorder in Korea

Kwag, Kyung Hwa, Kim, Youl‐Ri, Lee, You Kyung, Lee, Hye Rin, Lee, Ja Youn, Lee, Jihye, Kim, Jione, Kim, Youngkeun +1 more·2022·International Journal of Eating Disorders

Abstract

OBJECTIVE: We aimed to evaluate the feasibility, acceptability, and potential impact of a tele-guided digital-based intervention based on the addictive appetite model of recurrent binge eating. METHOD: Female college students with bulimia nervosa (BN) or binge-eating disorder (BED) (n = 22) received a 6-week guided intervention targeting addictive processes and emotion regulation. The feasibility of the intervention was evaluated, and the outcomes were assessed at baseline, the end of the intervention, and 1-month follow-up. RESULTS: Of the participants, 86.4% (n = 19) completed the intervention. The self-help materials were viewed 6.03 ± 3.06 times per week, and the duration of using the self-help materials was 113.16 ± 160.19 min/week. The intervention group experienced a significant reduction with a moderate effect on binge eating at the end of the intervention (Hedges' g = 0.58), and the effects lasted through follow-up (Hedges' g = 0.82). DISCUSSION: The results suggest that the digital intervention targeting a maintenance mechanism of recurrent binge eating was feasible and acceptable for patients with BN and BED, proving the potential for symptom improvement. PUBLIC SIGNIFICANCE: The addictive appetite model provides the framework for new interventions to improve treatments for BN and BED. This study found that the digital intervention based on the model was feasible and acceptable for patients with BN and BED.

Integrity signals

Registry

Crossref · 10.1002/eat.23754

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Kwag, K. H., Kim, Y., Lee, Y. K., Lee, H. R., Lee, J. Y., Lee, J., Kim, J., Kim, Y., & Treasure, J.
Affiliations
  • Inje University (KR)
  • King's College London (GB)
Corresponding author
Kim, Youl‐Ri
Venue
International Journal of Eating Disorders
Publisher
Wiley
Published
2022-06-10
Volume
55
Issue
7
Pages
977-982
ISSN
  • 0276-3478 (ISSN-L)
  • 1098-108X
OpenAlex
W4281765871
Cited by
6
References
25
Citations by year
2025: 1 · 2024: 2 · 2023: 2 · 2022: 1
FWCI
1.37
Type
journal article
Language
en
Open access
closed
Locations
  • International Journal of Eating Disorders (publishedVersion)
  • PubMed (publishedVersion)
  • Research Portal (King's College London) (submittedVersion)
Funders
  • Korea Health Industry Development Institute (HI18C0956)
  • National Research Foundation of Korea (2021R1A2C2009668)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
  • Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
bulimia nervosa, binge eating disorder, digital interventions, emotion regulation, female university students, feasibility and acceptability, self-help materials
MeSH terms
Appetite, Feasibility Studies, Female, Humans, Bulimia Nervosa, Republic of Korea, Binge-Eating Disorder

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review