Verteilung des Persönlichkeitsmerkmals Alexithymie bei Patienten in stationärer psychosomatischer Behandlung - gemessen mit TAS-20 und LEAS
Bibliographic record
Abstract
Preliminary findings of an ongoing study of the distribution of alexithymia in different diagnostic-groups of psychosomatically ill in-patients (n = 240, will be increased to n = 400) are reported. Alexithymiea is measured simultaneousely by the Levels of Emotional Awareness Scale (LEAS, a performance-test) and the 20-item Toronto Alexithymia Scale (TAS 20, a self-report-scale). Measured by the LEAS and compared with other diagnostic groups (affective, anxiety and compulsive-obsessive disorders; adjustment disorders; eating disorders), patients with somatoform disorders showed a decreased ability to be aware of and to communicate their emotional states. This finding which meets theoretical considerations about the origin of alexithymia could not be found with the TAS 20. The TAS 20 did not differentiate between the diagnostic groups, but showed - in accordance with two other self-report-scales (STAI for self reported anxiety as a personality trait and SCL-90-R for self reported somatic und psychic complaints) - higher mean scores at the onset than at the end of treatment. Methodical implications of the different findings of the two alexithymia scales are discussed.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".