Reliability and factor validity of the hungarian translation of the Toronto Alexithymia Scale in undergraduate students samples
Bibliographic record
Abstract
Alexithymia is the term to describe a constellation of difficulties to identifying feelings, distinguishing between bodily sensations of emotional arousal and describing feelings to others. This construct was examined by assessing the reliability of the factors of the 20-item Toronto Scale (TAS-20). After receiving official approval on the back translation, the Hungarian version of TAS-20 was administered to 275 undergraduate students (172 women and 103 men) of the University of Pécs. In line with the translation of TAS-20 in different languages and cultures, the authors results revealed also good internal reliability for the first two subscales, Difficulty identifying emotion and Difficulty describing emotion. Like in most of non-English mother tongue cultures, the third subscale, Externally oriented thinking lacks strong internal reliability. The exploratory and confirmatory factor analysis proved the validity of the original three factor model on the Hungarian translation. The authors findings suggest that TAS-20 can be a useful tool to assess alexithymia in the Hungarian population and further examinations should be done in order to introduce it in the clinical practice.
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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 | 0.004 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".