Alexithymia in patients with substance use disorders: State or trait?
Bibliographic record
Abstract
Previous research on substance use disorders (SUD) has yielded conflicting results concerning whether alexithymia is a state or trait, raising the question of how alexithymia should be addressed in the treatment of SUD-patients. The absolute and relative stabilities of alexithymia were assessed using the Toronto Alexithymia Scale (TAS-20) and its subscales. In total, 101 patients with SUD were assessed twice during a 3-week inpatient detoxification period while controlling for withdrawal symptoms and personality disorder traits. The relative stability of the total TAS-20 and subscales was moderate to high but showed remarkable differences between baseline low, moderate, and high alexithymic patients.\nA small reduction in the mean levels of the total TAS-20 scores and those of one subscale revealed the absence of absolute stability. The levels of alexithymia were unrelated to changes in withdrawal symptoms, including anxiety- and depression-like symptoms. The differences between low, moderate, and high alexithymic patients in terms of the change in alexithymia scores between baseline and follow-up indicated a strong regression to the mean. The findings suggest that alexithymia in SUD patients as measured using the TAS-20 is both a state and trait phenomenon and does not appear to be related to changes in anxiety- and depression-like symptoms.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".