Maintenance treatment for anorexia nervosa: A comparison of cognitive behavior therapy and treatment as usual
Bibliographic record
Abstract
Abstract Objective The aim of this study was to compare two maintenance treatment conditions for weight‐restored anorexia nervosa (AN): individual cognitive behavior therapy (CBT) and maintenance treatment as usual (MTAU). Method This study was a nonrandomized clinical trial. The participants were 88 patients with AN who had achieved a minimum body mass index (BMI) of 19.5 and control of binge eating and purging symptoms after completing a specialized hospital‐based program. Forty‐six patients received 1 year of manualized individual CBT and 42 were in an assessment‐only control condition (i.e., MTAU) for 1 year. This condition was intended to mirror follow‐up care as usual. Participants in both the conditions were assessed at 3‐month intervals during the 1‐year study. The main outcome variable was time to relapse. Results When relapse was defined as a BMI ≤ 17.5 for 3 months or the resumption of regular binge eating and/or purging behavior for 3 months, time to relapse was significantly longer in the CBT condition when compared with MTAU. At 1 year, 65% of the CBT group and 34% of the MTAU group had not relapsed. Discussion The current findings provide preliminary evidence that CBT may be helpful in improving outcome and preventing relapse in weight‐restored AN. © 2008 by Wiley Periodicals, Inc. Int J Eat Disord 2009
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".