The 20‐item Toronto Alexithymia Scale: Validation of factor solutions using confirmatory factor analysis on physiotherapy out‐patients
Bibliographic record
Abstract
OBJECTIVE: Whilst the 20-item Toronto Alexithymia Scale (TAS-20) was developed to measure three intercorrelated dimensions, there is some debate as to whether the scale is best served by a two- or three-factor construct. In particular, there is some doubt as to whether clinical data exhibit the third factor. This study uses data from a sample of physiotherapy (physical therapy) out-patients in the UK to validate the factorial structure of a set of models postulated in the literature, including the three-factor model hypothesized by Bagby et al. (1994). METHOD: Data were collected from a sample of physiotherapy out-patients (N=242). Specialist factor analysis software (LISREL 8.54) was used to perform confirmatory factor analyses on a range of models proposed in the literature. RESULTS: The analysis supports the three-factor model assumed by Bagby et al. (1994), as well as most of the two-factor models suggested in the literature. CONCLUSIONS: This new set of clinical data supports most of the two- and three-factor models postulated in the recent literature, including the three-factor model advocated by Bagby et al. (1994).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".