Examining emotion regulation in binge-eating disorder
Bibliographic record
Abstract
Abstract Background Inefficient mechanisms of emotional regulation appear essential in understanding the development and maintenance of binge-eating disorder (BED). Previous research focused mainly on a very limited emotion regulation strategies in BED, such as rumination, suppression, and positive reappraisal. Therefore, the aim of the study was to assess a wider range of emotional regulation strategies (i.e. acceptance, refocusing on planning, positive refocusing, positive reappraisal, putting into perspective, self-blame, other-blame, rumination, and catastrophizing), as well as associations between those strategies and binge-eating-related beliefs (negative, positive, and permissive), and clinical variables (eating disorders symptoms, both anxiety, depressive symptoms, and alexithymia). Methods Women diagnosed with BED (n = 35) according to the DSM-5 criteria and healthy women (n = 41) aged 22–60 years were assessed using: the Eating Attitudes Test-26, the Eating Beliefs Questionnaire-18, the Hospital Anxiety and Depression Scale, the Toronto Alexithymia Scale-20, the Cognitive Emotion Regulation Questionnaire, and the Difficulties in Emotion Regulation Scale. Statistical analyses included: Student t - tests or Mann–Whitney U tests for testing group differences between BED and HC group, and Pearson’s r coefficient or Spearman’s rho for exploring associations between the emotion regulation difficulties and strategies, and clinical variables and binge-eating-related beliefs in both groups. Results The BED group presented with a significantly higher level of emotion regulation difficulties such as: nonacceptance of emotional responses, lack of emotional clarity, difficulties engaging in goal-directed behavior, impulse control difficulties, and limited access to emotion regulation strategies compared to the healthy controls. Moreover, patients with BED were significantly more likely to use maladaptive strategies (rumination and self-blame) and less likely to use adaptive strategies (positive refocusing and putting into perspective). In the clinical group, various difficulties in emotion regulation difficulties occurred to be positively correlated with the level of alexithymia, and anxiety and depressive symptoms. Regarding emotion regulation strategies, self-blame and catastrophizing were positively related to anxiety symptoms, but solely catastrophizing was related to the severity of eating disorder psychopathology. Conclusions Our results indicate an essential and still insufficiently understood role of emotional dysregulation in BED. An especially important construct in this context seems to be alexithymia, which was strongly related to the majority of emotion regulation difficulties. Therefore, it might be beneficial to pay special attention to this construct when planning therapeutic interventions, as well as to the maladaptive emotion regulation strategies self-blame and catastrophizing, which were significantly related to BED psychopathology.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".