Assessing alexithymia in forensic settings: Psychometric properties of the 20‐item Toronto Alexithymia Scale among incarcerated adult offenders
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Alexithymia is a trait involving difficulty identifying feelings (DIF), difficulty describing feelings (DDF) and externally orientated thinking (EOT). It is a risk factor for criminal behaviour. It is commonly assessed with the Toronto Alexithymia Scale (TAS-20), but the psychometrics of the TAS-20 have not been tested across the range of offender populations, and it has been suggested it might be unsuitable in incarcerated offenders. AIM: To establish the psychometrics of the TAS-20 among incarcerated offenders. METHODS: Factorial validity was examined using confirmatory factor analyses, and the invariance of this factor structure was tested against a published community sample. Reliability coefficients were calculated. RESULTS: One hundred and forty six incarcerated offenders were recruited. The factor structure of the TAS-20 was invariant across the samples. The intended factor structure composed of DIF, DDF and EOT factors performed well overall (with a reverse-scored method factor added), but six EOT items had low factor loadings. The total scale score and DIF and DDF subscales had acceptable reliability, but EOT did not. CONCLUSIONS: Our results suggest that the TAS-20 functions similarly in offender and community samples. Its total scale score, and DIF and DDF subscale scores can be used confidently, but the assessment of externally oriented thinking may not be adequate with this scale alone. In sum, the TAS-20 can facilitate robust assessment of alexithymia in closed criminal justice settings as well as in the wider community.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 it