An Evaluation of the Absolute and Relative Stability of Alexithymia in Patients with Major Depression
Bibliographic record
Abstract
BACKGROUND: Previous studies demonstrating an association between alexithymia and depression have led to the proposal that alexithymia may be a state-dependent phenomenon rather than a stable and enduring personality trait. Several longitudinal studies have provided support for a trait view of alexithymia, but most of these studies evaluated absolute stability only (i.e., the extent to which alexithymia scores change over time) and did not examine the relative stability of alexithymia (i.e., the extent to which relative differences among individuals remain the same over time) in the context of changes in illness symptomatology. The present study evaluated both absolute stability and relative stability of alexithymia in depressed patients who experienced a marked reduction in the severity of depressive symptoms. METHODS: Forty-six psychiatric outpatients with major depression were assessed for alexithymia and depression with the 20-item Toronto Alexithymia Scale and the Hamilton Rating Scale for Depression at the start of treatment (baseline) and after 14 weeks of treatment (follow-up) with antidepressant medication. Paired t tests and correlational analyses were performed to evaluate absolute stability and relative stability in alexithymia. Hierarchical regression analyses were then used to assess the degree to which the relative stability in alexithymia scores was related to the severity of depressive symptoms, and the degree to which changes in alexithymia scores could be attributed to changes in depression scores. RESULTS: Alexithymia scores changed significantly from baseline to follow-up, indicating a general lack of absolute stability. There was, however, strong evidence of relative stability, as alexithymia scores at baseline correlated significantly with alexithymia scores at follow-up and were also a significant predictor of follow-up alexithymia scores, after partialling the effects of depression severity. CONCLUSIONS: Although alexithymia scores may change in the presence of large changes in the severity of depressive symptoms, the finding of relative stability of alexithymia supports the view that this construct is a stable personality trait rather a state-dependent phenomenon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".