The association between alexithymia and two dimensions of major depressive disorder: cognitive and somatic-affective
Bibliographic record
Abstract
Aim: To explore the association between alexithymia and two dimensions of major depressive disorder (MDD): cognitive and somatic-affective. Patients and methods. Unicentric, cross-sectional study included consecutive sample of 63 patients at the Department of Psychiatry (DoP), Sestre Milosrdnice University Hospital Centre, Zagreb, Croatia. Target population included outpatients with diagnosed MDD (F32 and F33, according to ICD-10). Inclusion criteria were: confirmed MDD diagnosis, age between 18 and 65 years, both genders, outpatient treatment at the DoP. The main outcome was the association between alexithymia, measured by total score on 20-item Toronto-Alexithymia scale (TAS-20), with two dimensions of MDD, cognitive and somatic-affective, measured by Beck Depression Inventory-II (BDI-II). Results: Both dimensions of BDI-II and the total severity of MDD symptoms were statistically significantly, although low, associated with alexithymia, and the differences between these two correlations were not (statistically) significant. However, in the multivariable model, the cognitive dimension (b = 0.64; β = 0.48; p = 0.002; statistically significant at the false discovery rate of 0.05) was primarily associated with alexithymia, and the somatic-affective was not, after all cognitive aspects were controlled for (b = -0.19; β = 0-0.14; p = 0.491; not statistically significant, with the false discovery rate of 0.05). Conclusion: Alexithymia is primarily associated with a pure cognitive dimension of MDD after somatic-affective elements are excluded. Somatic-affective dimension of MDD is not associated with alexithymia after the cognitive elements were controlled for. Both dimensions, as well as the overall severity of MDD, are associated with alexithymia, but this association is relatively low.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".