Relationship between alexithymia and negative mood in patients with heroin dependence
Bibliographic record
Abstract
Objective:To understand the feature of alexithymia and the relationship between alexithymia and negative mood in patients with heroin dependence(PHD).Method:194 male patients with PHD(study group) were evaluated with a self-developed questionnaire for general status of health,Toronto alexithymia scale(TAS),self-rating depression scale(SDS) and self-rating anxiety scale(SAS).107 healthy men(control group) were also assessed with TAS.Results:Compared with the control group,the patients with PHD had significant higher total and factor scores of TAS(P0.05 or P0.01).There was positive correlation between total score and scores of factorⅠ,Ⅱ,Ⅳ of TAS and total scores of SAS and SDS(r=0.178～ 0.294,all P0.05 or P0.01),and there was negative correlation between factor-Ⅲ score of TAS and total score of SAS(r=-0.147,P0.05).Conclusion:Male patients with PHD have severe alexithymia,which is correlated with negative mood.
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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".