A comparative study of alexithymia of depressive patients characterized by somatic symptoms
Bibliographic record
Abstract
Objective:To explore the difference of alexithymia between depressive patients characterized by somatic symptoms and depressive patients characterized by mood symptoms.Method:50 depressive patients characterized by somatic symptoms(somatization symptoms group),50 ones by mood symptoms(mood symptoms group) and 50 normal controls(normal group) were enrolled;assessment were conducted with Toronto alexithymia scale(TAS-26),90 symptoms self-reporting inventory(SCL-90) and Hamilton rating scale for depression(HAMD);the results were compared and analyzed.Results:Somatization symptoms group have more higher average results on the total scores and the factors scores of somatization,anxiety,human being comunication sensitive,phobophobia,paranoid of the SCL-90,on the sorces of anxiety/somatizatuon of the HAMD than mood symptoms group(P0.01 or P0.05);mood symptoms group have more higher average results on the scores of obsession,depression of the SCL-90 and cognitive handicap,thought stoppage,day and night change,somnipathy,feeling of despair of the HAMD than somatization symptoms group(P0.05 or P0.01);there were significant differeces in theⅡfactors scores of the TAS-26 between somatization symptoms group and mood symptoms group(P0.05),and the two groups have more higher average results than normal group in he total scores or the other factors scores of TAS-26(P0.05 or P0.001).Conclusion:Depressive patients characterized by somatic symptoms and depressive patients characterized by mood symptoms have heavy alexithymia,depressive patients characterized by somatic symptoms tend to have more difficuty recognizing emotion and somatic feeling.
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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 | 0.001 | 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".