Reliability and Factor Structure in an Adolescent Sample of the Dutch 20-Item Toronto Alexithymia Scale
Bibliographic record
Abstract
This study investigated the psychometric properties of the 20-item Toronto Alexithymia Scale (TAS-20) in an adolescent sample (N = 406, ages 12 to 17). This is rarely done even though the TAS-20 is used in adolescent research. Five published factor models were tested. For good fitting models, a second-order model with alexithymia as a higher-order factor and metric invariance across sex and age groups was tested. Confirmatory factor analyses showed that the original three-factor model and a four-factor model provided acceptable fit. Both models were invariant across sex, but not across age. Second-order models did not provide good fit. Reliability was good for the "Difficulty identifying feelings" subscale and acceptable for the "Difficulty describing feelings" subscale, but not for the "Externally oriented thinking" subscale. Measuring alexithymia with the TAS-20 in adolescents thus seems problematic, especially in younger age groups.
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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 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".