Expresión emocional en los trastornos de la conducta alimentaria: alexitimia y asertividad
Bibliographic record
Abstract
Background: Alexithymia and lack of assertiveness are common characteristics eating disorders disorders (ED) and interfere in emotional expression.Aim: To assess the presence of alexithymia and assertiveness in different subtypes of ED.Method: The Eating Attitudes Test (EAT-40), the Eating Disorders Inventory (EDI), the Toronto Alexithymia Scale (TAS-20) and Rathus Assertiveness Schedule) (RAS) were administered to 108 ED patients (28 anorectics, 36 with ED not otherwise specified (EDNOS) and 44 bulimics).Results: All the subgroups scored within the pathological range of alexithymia, especially anorexics (57.1%), the highest (52.9 ± 14.3), although not statistically significant (NS).Bulimics showed more difficulty to discriminate emotional signals (23.3 ± 8.7) and anorexics more thoughts oriented to external details (15.1 ± 7.1) (NS).Bulimics scored negative in RAS (-0.6 ± 25.8), mainly exhibiting more submissive and dependant behaviors (-2.6 ± 7.4) (NS).In bulimic (r = 0.795; p < 0.001) and EDNOS (r = 0.623; p < 0.001) subgroups, the lower interoceptive consciousness, the more difficulty to discriminate emotional signals were observed.The higher interpersonal distrust in anorexic (r = 0.617; p = 0.001) and EDNOS subgroups (r = 0.590; p < 0.001), the more difficulty to express emotions verbally; the more difficulty to discriminate emotional signals, the more deficit behaviors in bulimics (r = -0.715;p < 0.001; r = 0.707; p < 0.001) and ineffectiveness in anorexics (r = 0.593; p = 0.001) were observed.Conclusions: The presence of alexithymia and lack of assertiveness in all the ED subgroups were verified.The most alexiyhimic were the anorexics and bulimics were less assertive and showed more difficulty to identify emotions and anorexics to describe them.
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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 | 0.000 |
| 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) | 0.001 | 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".