Dialectical behavior therapy self‐help for binge‐eating disorder: A randomized controlled study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare the relative effectiveness of dialectical behavior therapy guided self-help (DBT-GSH) and DBT unguided self-help (DBT-USH) with an unguided self-help control condition in the treatment of binge-eating disorder (BED). METHOD: Seventy-one participants who met diagnostic criteria for BED based on Eating Disorder Examination (EDE) interview were randomly assigned to DBT-GSH, DBT-USH or active control USH for 12 weeks. Assessments took place at baseline, 12 weeks and 3-month follow-up. Outcome measures included the EDE to assess binge frequency, the EDE-Questionnaire (EDE-Q), the Brief Symptom Inventory, and the Short Form 6D. RESULTS: The overall completion rate was 65% at post-treatment and 63% at 3-month follow-up. Intention to treat analyses showed that participants in all three conditions reported significant reductions in binge frequency with large effect sizes. A similar pattern emerged for secondary outcome variables including eating disorder psychopathology, general psychological distress, and health-related quality of life. DISCUSSION: Self-help may be an effective way to disseminate DBT for BED. However, future research should evaluate DBT self-help using a larger sample size, possibly in a multisite design.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".