Alexithymia measured with the TAS-20 questionnaire: Determining the validity of the factor structure and its relation to life satisfaction and the Big Five personality traits
Bibliographic record
Abstract
Alexithymia is the inability of an individual to recognize their own or someone else's feelings and to communicate their own emotional states. On the cognitive level, we can observe a decreased ability for imagination and a practical style of thinking, while on the affective level, we can notice a diminished ability of getting in touch with emotions. The most commonly used instrument for measuring alexithymia is the TAS-20 scale that consists of three subscales: Factor 1-the identification of feelings, Factor 2- difficulties describing feelings, Factor 3-externally oriented thinking. The aim of this paper is to determine the factor structure of the TAS-20 questionnaire and its relations to personality traits and life satisfaction. The sample consisted of 601 'nonclinical' and 65 'clinical' participants. The 'clinical' participants have reported in the survey that they had a diagnosed psychiatric disorder. 75% of the 'nonclinical' and 76.9% of the 'clinical' sample participants were female. The average age of the 'nonclinical' sample was 29.47 (SD=7.12), and the average age of the 'clinical' sample was 31.18 (SD=8.44). Confirmatory factor analysis has shown an adequate model fit, but only after the removal of item 20 from the model. The summary score and factor scores showed an expected relationship with the Big Five in the 'nonclinical' sample, except a somewhat weaker correlation with the Openness trait. The summary score and factor scores also had expected relations with life satisfaction, while no significant correlation was detected in the 'clinical' sample. The regression model has shown that personality traits explain 37.6% of the summary score variance. The expected gender differences were not detected.
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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 | 0.001 | 0.003 |
| 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".