Emotion‐focused therapy in a case of anorexia nervosa
Bibliographic record
Abstract
Abstract An emotion‐focused approach to the treatment of eating disorders and to case formulation is described in an individual with anorexia nervosa (AN). The basic theory of emotion‐focused therapy (EFT), the steps of case formulation and an outline of the tasks and course of treatment of an individual recently hospitalized on an inpatient unit for eating disorders highlight key aspects of the approach. The transformation in this individual, in terms of gaining access to her internal experience, understanding and tolerating her emotions, and working through her core themes of insecure attachment and worthlessness, is described. Weight and scores on self‐report measures at the outset of treatment and at 18 months are provided. Copyright © 2009 John Wiley & Sons, Ltd. Key Practitioner Message: Guidelines for treating eating disorders are tenuous and new approaches showing promise must be developed. Emotion‐focused therapy (EFT) shows promise in the treatment of eating disorders. Description of the case shows the application of EFT to anorexia nervosa and illustrates the change in the individual in terms of recognizing and coping with emotional experience.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| 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".