[Alexithymia and depression in eating disorders].
Bibliographic record
Abstract
Patients suffering from eating disorder show elevated rates of alexithymia and depression. We compared alexithymia and depression ratings for non-hospitalized women meeting DSM IV criteria for anorexia nervosa (n = 32) and bulimia nervosa (n = 32) to healthy women (n = 74). Alexithymia was evaluated by the Toronto Alexithymia Scale (TAS-20) and depression by the Hospital Anxiety and Depression Scale (HAD). We found that TAS and HAD scores were significantly higher in anorexic compared to bulimic patients, although alexithymia and depression, as evaluated, were significantly and positively correlated with each other (r = 0.53, p = 0.001). Finally, a logistic regression with alexithymia and depression as independent variables showed a strong correlations between the HAD ratings and anorexia, but no correlations between TAS score and the eating disorder subgroups. In eating disorder patients, alexithymia, as evaluated by the Toronto Alexithymia Scale, seems to exhibit a thymo-dependent component which could be secondary to concurrent depression. Through recent studies and results of our research, we analyze and give several interpretations which may explain this correlation between alexithymia and depression.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".