Visual Attention to Ambiguous Emotional Faces in Eating Disorders: Role of Alexithymia
Bibliographic record
Abstract
Eating disorders (EDs) are often accompanied by social-emotional problems. Recently, alexithymia has been suggested to explain objective emotion processing deficits in EDs. We tested if elevated levels of alexithymia may explain emotional face-processing problems in a mixed ED group (N = 24, 19 with anorexia and five with bulimia), comparing them with high-alexithymic (N = 25) and low-alexithymic healthy controls (N = 25). Participants judged the mixture ratio of clear and ambiguous facial emotion blends while eye movements were recorded. The ED group was less accurate judging ambiguous blends containing anger or disgust and attended less to the faces compared with low-alexithymic controls. Reduced attention to faces, in particular the eye region, was linked to confusion with ambiguous anger and disgust in the ED group only. Although significant group differences only emerged compared with low-alexithymic controls, the visual attention patterns underlying the ED group's problems with subtle anger and disgust expressions were not driven by alexithymia. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.
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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".