Novel Guided Self-Help for the treatment of Binge Eating Disorder: Feasibility, Acceptability, and Preliminary Efficacy
Bibliographic record
Abstract
Purpose: Binge eating disorder (BED) is a prevalent eating disorder. Many individuals with BED do not receive evidence-based care due to many barriers. This preliminary study evaluated the feasibility, acceptability, and potential efficacy of a manualized guided self-help (GSH) intervention with support in the form of a culturally adapted manual for a French-Canadian population. Method: Twenty-two women with overweight or obesity meeting the BED diagnostic criteria participated in an 8-week open trial. The GSH programme combined a self-help book and weekly support phone calls. Participants were assessed at baseline, at week 4, postintervention, and 12 weeks following its end. Feasibility was measured by attrition rates, participation, and satisfaction. Acceptability was measured by a questionnaire based on the Theoretical Framework of Acceptability. Potential efficacy outcomes were objective binge eating days, eating disorder symptomatology, depressive symptoms, and propensity to eat intuitively. Results: The GSH programme has proven feasible (4.5% attrition, 91% completion, 95.5% satisfaction) and acceptable. Potential efficacy results showed promising improvements on all outcomes (19% abstinence, 70.9% reduction in objective binge eating days). Conclusion: Although preliminary, this programme warrants further study as it may be an efficient and cost-effective way to deliver GSH for BED patients with accessibility barriers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".