Age and gender effect on alexithymia in large, Japanese community and clinical samples: a cross-validation study of the Toronto Alexithymia Scale (TAS-20)
Bibliographic record
Abstract
BACKGROUND: The construct validity of alexithymia and its assessment using the 20-item Toronto Alexithymia Scale (TAS-20) in Japan is unknown. Low reliability has been found for the third factor of the TAS-20 in some cultures, and the factor structure for psychosomatic disorder patients has not been adequately investigated. Although alexithymia most likely has certain developmental aspects, this has infrequently been investigated. METHODS: The newly-developed Japanese TAS-20 was administered to a normative sample (n = 2,718; 14-84 y.o.), along with the NEO Five-Factor Inventory (NEO-FFI) for cross validation. Psychosomatic patients (n = 1,924, 12-87 y.o.) were tested to evaluate the factor structure in a clinical sample. College students (n = 196) were used for a test-retest study. Internal reliability and consistency were assessed, and the factorial structure was evaluated using confirmatory and exploratory factor analyses for both the normative and the clinical samples. The correlations between the TAS-20 and the NEO-FFI factor scores were evaluated. Age-related and gender differences in the TAS-20 were explored using analysis of variance in the normative sample. RESULTS: The original three-factor model of the TAS-20 was confirmed to be valid for these Japanese samples, although a 4-factor solution that included negatively keyed items (NKI) as an additional factor was more effective. Significant correlations of the TAS-20 with the NEO-FFI were found, as has been previously reported. Factor analyses of the normative and patient samples showed similar patterns. The TAS-20 total, difficulty in identifying feelings (DIF), and difficulty in describing feelings (DDF) scores were high for teenagers, decreased with age, and from 30s did not change significantly. In contrast, externally oriented thinking (EOT) scores showed an almost linear positive correlation with age. DIF scores were higher for females, while EOT scores were higher for males, without any interaction between gender and age differences. CONCLUSION: The original three-factor concept of the TAS-20 was generally supported for practical use. Age-related differences in TAS-20 scores indicate developmental aspects of alexithymia. Alexithymia is made up of two components with different developmental paths: DIF/DDF and EOT.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".