PW01-138 - A Serbian Translation Of The 20-Item Toronto Alexithymia Scale - Development And Validation Of The Factorial Structure
Bibliographic record
Abstract
Introduction Alexithymia represents a personality trait construct encompassing difficulty identifying and describing feelings, distinguishing between feelings and the related physical sensations, and an externally oriented cognition. A self-report 20-item Toronto Alexithymia Scale (TAS-20) is a commonly used tool to measure alexithymia. It has been translated into more than 20 different languages, crossing the cultural and language barriers. TAS-20 has a factorial structure: factor 1 assesses difficulty identifying feelings; factor 2 assesses difficulty describing feelings; factor 3 assesses externally oriented thinking. Objective The objective of the study was to validate a Serbian translation, including the factorial structure, of the TAS-20. Methods TAS-20 was expertly translated from English to Serbian and given to a bilingual non-clinical sample fluent in both English and Serbian (n=47, age 18-60). The subjects were assigned to complete Serbian version (TAS-20-SRB) at week one, and the English version (TAS-20-ENG) at week two (7-14 days apart). The collected data were analysed using a paired samples correlations and paired samples t-test. Results There were no statistically significant differences in paired samples comparisons of means of total score and scores on each of three factors of TAS-20-ENG and TAS-20-SRB (p>0.05). The results of correlations of total scores and scores on factors show the statically significant correlations (p< 0.001), and also that the correlations were very high (from 0.87 to 0.95). Conclusion Bilingual subjects showed temporally and quantitatively congruent scores on both TAS-20 and TAS-20-SRB, suggesting that the Serbian translation of TAS-20 was valid, and that the factorial structure remained stable.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".