Cognitive Remediation and Emotion Skills Training (CREST) for anorexia nervosa in individual format: self-reported outcomes
Bibliographic record
Abstract
BACKGROUND: To evaluate self-reported outcomes after a brief course of skills-based individual therapy for inpatients with anorexia nervosa (AN). METHODS: In this case series study 37 adults with AN participated in cognitive remediation and emotion skills training (CREST) sessions, and completed social anhedonia, alexithymia and motivational measures before and after the intervention. RESULTS: The CREST primary outcome measures were total scores on the Revised Social Anhedonia Scale (RSAS), which decreased significantly (p = 0.03) with an effect size of 0.31, and the Toronto Alexithymia Scale (TAS), which also decreased significantly (p = 0.05) with an effect size of 0.35. The secondary outcome measures focused on motivation: perceived 'importance to change' and 'ability to change'; the second of which increased significantly (p < 0.001) with a medium effect size (d = 0.71). CONCLUSIONS: The individual format of CREST led to a decrease in patients' self-reported social anhedonia, an improvement in the ability to label their emotions, and increased confidence in their ability to change. Considering the limited number of individual sessions, this is a promising preliminary finding which warrants further research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".