A Study of Factor Structure of the Korean Version of the 20-Item Toronto Alexithymia Scale
Bibliographic record
Abstract
Background: The purpose of this study is to examine the factor structure of the Korean version of the 20-Item Toronto Alexithymia Scale. The TAS-20 (source of the TAS-20K) has been supported the three-factor correlated model. However, some factor structure studies of the TAS-20 rejected the three-factor correlated model and adopted alternative models. Methods: In study 1, we conducted a comparison study of the alternative measurement models by using CFA. In study 2, we examined scale reliability and gender measurement invariance of the factor structure. To examine the alternative models and scale reliability, we using the bifactor model reliability indices. Results: As a result, the DIF and DDF factors have a close relationship but the EOT factor has some differences with DIF and DDF. So we adopted a two-factor correlated model with group factor. And the adopted factor structure has partial measurement invariance. Therefore we can compare gender differences of the TAS-20K. Conclusions: This study has significance that examining TAS-20K’s factor structure and examining measurement invariance in gender.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".