Emotion-processing deficits in eating disorders
Bibliographic record
Abstract
OBJECTIVE: First, we measured both emotional awareness and alexithymia to understand better emotion-processing deficits in eating disorder patients (EDs). Second, we increased the reliability of the measures by limiting the influence of confounding factors (negative affects). METHOD: Seventy females with eating disorders were compared with 70 female controls. Participants completed the Beck Depression Inventory (BDI; depression), the Hospital and Anxiety Depression Scale (HADS; anxiety), the Toronto Alexithymia Scale (TAS; alexithymia), and the Level of Emotional Awareness Scale (LEAS). RESULTS: EDs exhibited higher alexithymia scores and lower LEAS scores, with an inability to identify and describe their own emotions, as well as an impairment in mentalizing others' emotional experience. Whereas alexithymia scores were related to depression scores, LEAS scores were not. After controlling for depression, alexithymia scores were similar in EDs and controls. DISCUSSION: The marked impairment in emotion processing found in EDs is independent of affective disorders. Thus, the joint use of TAS and LEAS suggests a global emotion-processing deficit in EDs.
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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 | 0.001 |
| 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".