[Relationships between the emotional and cognitive components of alexythymia and PTSD in victims of domestic violence].
Bibliographic record
Abstract
AIM: Alexythymia has been reported in various psychiatric disorders, also in post-traumatic stress disorder (PTSD). The 20-item Toronto Alexythymia Scale (TAS-20) measures three inter-correlated dimensions ofalexythymia: 1. difficulties in identifying feelings, 2. difficulties in describing feelings, 3. externally oriented thinking. The aim of the study was to assess the correlation between factors of TAS-20 and intensification of PTSD symptoms. METHOD: Presence and a degree of alexythymia were estimated using three factorial 20-point self-assessment Toronto Alexythymia Scale. Diagnosis and a degree of intensification of PTSD was based on C.G. Watson's et al. PTSD-I. The study group consisted of 30 women who have experienced domestic violence. Women were residents of hostels for victims of domestic violence or residents of the Lonely Mother House. RESULTS: There was a significant correlation between factor 2 (difficulties describing feelings) scores of TAS-20 and intensification of PTSD (correlation is significant at the 0.05 level, Spearman's correlation coefficient 0.383, p = 0.037). There was no significant relationship between the scores of PTSD-I and the scores of sub-factors 1 and 3. The results emphasize, in addition to the TAS-20 total score, the three sub-factors providing information about whether cognitive and/or affective aspects of alexythymia are associated with posttraumatic stress disorder. CONCLUSION: The most significant factor determining occurrence of PTSD symptoms in the study group of women who have experienced domestic violence was a difficulty in verbalising emotions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".