Alexithymia and pain experience in depressive patients
Bibliographic record
Abstract
Introduction Alexithymia appears as an inhibition of recognizing and describing the mental conditions. It is often connected with psychosomatic illness or depression. Aims The aim of this study was to compare depressive patients with healthy persons in terms of the prevelence and level of the alexithymia and pain feeling. Methods The examined group (E) consists of 16 patients with diagnosed depression (11 women, 44,6±11,6 year old).The control group (C) consists of 14 randomly chosen persons (10 women, 40,0+/-15,3 year old) who achieved < 11 points in the Beck's Depression Inventory (BDI).The alexithymia level was examined with TAS - 26 questionnaire (difficulty of recognizing the feelings and somatic senses (ODR), concrete thinking (MK), difficulty of expressing the feelings (TRW) and the lack of imagination (U)). The intensity of pain was examined with the questionnaire SF-MPQ. The scale BPCQ was used to examine beliefs about pain control. Results No statistical differences about age, sex, the U feature in TAS-26 scale and the results of BPCQ test were shown. The differences beetween groups E and C appeared in the alexithymia intensity range (75,3 ± 14,4 v.62,4 ± 8,2pts, p = 007), the ODR feature (23,7 ± 6,7 v. 13,0 ± 4,1pts, p< 0,001), MK (18,9 ± 4 v.23,1 ± 5,3pts, p = 0,036) and TRW (13,4 ± 2,6 v. 9,6 ± 2,8pts, p = 0,001). The E group featured significantly higher pain intensity(p = 0,012). Conclusions The patients with depression suffer from alexithymia very often. The prevalence of upper difficulties and great intensity of pain could suggest a psychotomatic component of pain affections.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".