Assessing alexithymia in chronic pain: psychometric properties of the Toronto Alexithymia Scale-20 and Perth Alexithymia Questionnaire
Bibliographic record
Abstract
Introduction: Alexithymia is elevated in chronic pain and relates to poor pain-related outcomes. However, despite concerns from other clinical populations, the psychometric properties of alexithymia measures have not been rigorously established in chronic pain. Objective: This study examined the psychometric properties of the Toronto Alexithymia Scale-20 Item (TAS-20) and the Perth Alexithymia Questionnaire (PAQ) in adults with chronic pain. Methods: An online sample of adults with chronic pain across the United States (N = 1453) completed the TAS-20, PAQ, and related questionnaires at baseline, 3-month follow-up, and 12-month follow-up. Results: Both measures showed good temporal stability, convergent validity (with emotion regulation scores), divergent validity (with depression and anxiety scores), and criterion validity. Some concerns were raised about the TAS-20: the original 3-factor structure showed a poor model fit; the Externally Oriented Thinking subscale of the TAS-20 had poor factor loadings and unacceptable internal consistency; and, we identified several TAS-20 items that may slightly inflate the predictive validity of the TAS-20 on pain-related outcomes. The original 5-factor structure of the PAQ showed a good fit; each PAQ subscale had good factor loadings and excellent internal consistency. Conclusions: Both the TAS-20 and PAQ had psychometric strengths. Our data raised some concern for the use of TAS-20 subscales; the PAQ may be a psychometrically stronger option, particularly for investigators interested in alexithymia subscale analysis in people with chronic pain.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".