Alexithymia and facial emotion recognition in patients with eating disorders
Bibliographic record
Abstract
OBJECTIVE: Patients with anorexia or bulimia nervosa are reported to show high levels of alexithymia and to have difficulties recognizing facially displayed emotions. The current study tested whether it could be that facial emotion recognition is a basic skill that is independent from alexithymia. METHOD: We assessed emotion recognition skills and alexithymia in a group of 79 female inpatients with eating disorders and compared them with a group of 78 healthy female controls. Instruments used were the Toronto Alexithymia Scale, the Facially Expressed Emotion Labeling (FEEL) test, and the revised Symptom Check List (SCL-90-R). RESULTS: There were no significant differences between patients and controls in their emotion recognition scores, but patients with eating disorders displayed significantly more alexithymia and psychopathology. Emotion recognition in patients was not related to alexithymia, psychopathology, or clinical symptoms. CONCLUSION: We suggest that the reported alexithymia of patients with eating disorders is complex and independent from basic facial emotion recognition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".