The measurement of alexithymia in children and adolescents: Psychometric properties of the Alexithymia Questionnaire for Children and the twenty-item Toronto Alexithymia Scale in different non-clinical and clinical samples of children and adolescents
Bibliographic record
Abstract
This study had two aims. Firstly, the psychometric properties of the 20-item Toronto Alexithymia Scale (TAS-20) and the Alexithymia Questionnaire for Children (AQC) that measure the three dimensions of alexithymia (DIF, difficulty identifying feelings; DDF, difficulty describing feelings; EOT, externally-oriented thinking) were explored in various samples of children, adolescents or young adults to detect the best factor-structure and to examine if the Externally-Oriented Thinking (EOT) factor must be deleted or not. Secondly, the capacity for adolescents to distinguish between alexithymia and depression was studied using factorial analyses of items of self-report of alexithymia and depression scales. Four groups were examined (80 healthy children, 105 adolescents with various psychiatric disorders, 333 healthy older adolescents and 505 young adults recruited from universities). The first two groups filled out the AQC and the latter two the TAS-20. Confirmatory factorial analyses (CFA) showed that the two-factor model (DIF, DDF) provided acceptable fits and had significant advantages over the three-factor model (DIF, DDF, EOT). Low alpha coefficients for the EOT subscale were reported (range from 0.18-0.61). Except for the children sample, exploratory factorial analyses (EFA) were performed on the items of the TAS-20 or AQC without the EOT items and the Beck depression inventory-II (BDI-II) or the Zung Self-Rating Depression Scale (SDS). The items of the AQC and BDI-II or items of the TAS-20 and SDS loaded on separate factors with only a minor overlap suggesting that adolescents were able to differentiate alexithymia and depression when self-assessments were used. Alexithymia can be reliably assessed in adolescents using the TAS-20 or AQC without the eight items rating the EOT dimension.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".