Emotion regulation difficulties in anorexia nervosa: associations with improvements in eating psychopathology
Bibliographic record
Abstract
BACKGROUND: Difficulties with emotion regulation have been established as a core deficit in anorexia nervosa (AN). However, limited research has evaluated whether weight gain is associated with improvements in emotion regulation difficulties in AN and whether improvements in emotion regulation are associated with reductions in eating disorder psychopathology. The aims of this study were threefold: 1) to examine the nature and extent of emotion regulation difficulties in AN; 2) to determine whether these difficulties improved during intensive treatment for the eating disorder; and 3) to study whether improvements in emotion regulation were associated with improvements in eating disorder psychopathology. METHOD: The participants were 108 patients who met DSM-IV-TR criteria for AN and were admitted to a specialized intensive treatment program. Self-report measures of eating disorder symptoms and difficulties with emotion regulation were administered at admission to and discharge from the program. RESULTS: Patients with the binge-purge subtype of AN reported greater difficulties with impulse control when upset and more limited access to emotion regulation strategies when experiencing negative emotions than those with the restricting subtype. Among those who completed treatment and became weight restored, improvements in emotion regulation difficulties were observed. Greater pre-to-post treatment improvements in emotional clarity and engagement in goal directed behaviours when upset were associated with greater reductions in eating disorder psychopathology during treatment. CONCLUSIONS: These findings add to growing evidence suggesting that eating disorder symptoms may be related to emotion regulation difficulties in AN and that integrating strategies to address emotion regulation deficits may be important to improving treatment outcome in AN.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".