Delivering Brief Cognitive Behavioral Therapy (CBT‐T) for Eating Disorders: Examining Real‐World Outcomes of a Large‐Scale Training Program
Bibliographic record
Abstract
OBJECTIVE: Cognitive Behavioral Therapy-Ten (CBT-T) is a 10-session manualized eating disorder (ED) treatment protocol for nonunderweight EDs. CBT-T was developed to increase access to treatment and reduce wait times, as it can be delivered in half the time as existing CBT approaches for EDs. To improve access to treatment, the Nova Scotia Eating Disorder Provincial Service trained 36 clinicians through a 10-month CBT-T training program and offered CBT-T provincially. This study examines changes in ED psychopathology, binge eating, compensatory behaviors, anxiety, and depression in a transdiagnostic cohort of adult patients treated with CBT-T. Further, an exploratory analysis of predictors of treatment outcome was conducted. METHODS: A retrospective chart review was conducted on adults who began CBT-T between July 2022 and March 2024. Participants completed routine outcome measures per the CBT-T manual. Mixed-effects models examined symptom changes over time, along with predictors of treatment outcome, dropout, and extension. RESULTS: A total of 267 patients started CBT-T. Significant reductions in ED psychopathology, binge eating, and compensatory behaviors, anxiety, and depression were observed throughout treatment. Effect sizes were large to very large at the end of treatment for primary and secondary outcomes. Early change in ED psychopathology predicted better outcomes, whereas diagnoses of anorexia nervosa and atypical anorexia nervosa were associated with higher dropout rates. DISCUSSION: Findings support that CBT-T may be an effective, scalable treatment associated with significant symptom reductions corresponding to large effect sizes. Future research should explore adaptations to improve retention, especially for those with anorexia nervosa and atypical anorexia nervosa.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".