Group cognitive remediation therapy for adolescents with anorexia nervosa: Outcomes before, after, and during follow-up in a real-world setting in Japan
Bibliographic record
Abstract
Objective: Cognitive remediation therapy (CRT) can be used as an adjunct treatment for adolescents with severe and complex anorexia nervosa (AN) requiring inpatient treatment. However, there has been only one study on CRT for adolescents with AN in Japan. This study explored group CRT as an adjunct to inpatient treatment for Japanese adolescents with severe and complex AN requiring inpatient care. Methods: Thirty-one adolescents with AN underwent group CRT. Neuropsychological (set-shifting and central coherence) and psychological assessments (motivation, self-esteem, and depressive symptoms) were measured before and after the intervention. Weight and AN symptoms were measured before and after the intervention and at follow-up, and the adolescents completed post-intervention and follow-up questionnaires. Results: Set-shifting led to medium to large effect size improvements. Medium effect size improvements in central coherence and depressive symptoms were also observed. The feedback from the adolescents was mainly positive, and the treatment completion rate was high. The patients also reported that the skills learned through group CRT could be applied in daily life. Conclusion: Group CRT may be beneficial for adolescents with severe and complex AN who require inpatient care.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".