Improving the measurement of alexithymia in autistic adults: a psychometric investigation and refinement of the twenty-item Toronto Alexithymia Scale
Bibliographic record
Abstract
Abstract Background Alexithymia, a personality trait characterized by difficulties interpreting one’s own emotional states, is commonly elevated in autistic adults, and a growing body of literature suggests that this trait underlies a number of cognitive and emotional differences previously attributed to autism, such as difficulties in facial emotion recognition and reduced empathy. Although questionnaires such as the twenty-item Toronto Alexithymia Scale (TAS-20) are frequently used to measure alexithymia in the autistic population, few studies have attempted to determine the psychometric properties of these questionnaires in autistic adults, including whether differential item functioning (I-DIF) exists between autistic and general population adults. Methods We conducted an in-depth psychometric analysis of the TAS-20 in a large sample of 743 verbal autistic adults recruited from the Simons Foundation SPARK participant pool and 721 general population controls enrolled in a large international psychological study (the Human Penguin Project). The factor structure of the TAS-20 was examined using confirmatory factor analysis, and item response theory was used to further refine the scale based on local model misfit and I-DIF between the groups. Correlations between alexithymia and other clinical outcomes such as autistic traits, anxiety, and quality-of-life were used to assess the nomological validity of the revised alexithymia scale in the SPARK sample. Results The TAS-20 did not exhibit adequate global model fit in either the autistic or general population samples. Empirically driven item reduction was undertaken, resulting in an eight-item unidimensional scale (TAS-8) with sound psychometric properties and practically ignorable I-DIF between diagnostic groups. Correlational analyses indicated that TAS-8 scores meaningfully predict autistic trait levels, anxiety and depression symptoms, and quality of life, even after controlling for trait neuroticism. Limitations Limitations of the current study include a sample of autistic adults that was overwhelmingly female, later-diagnosed, and well-educated; clinical and control groups drawn from different studies with variable measures; and an inability to test several other important psychometric characteristics of the TAS-8, including sensitivity to change and I-DIF across multiple administrations. Conclusions These results indicate the potential of the TAS-8 as a psychometrically robust tool to measure alexithymia in both autistic and non-autistic adults. A free online score calculator has been created to facilitate the use of norm-referenced TAS-8 latent trait scores in research applications (available at http://asdmeasures.shinyapps.io/TAS8_Score ).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.058 | 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".