The relationship between drug craving and psychosomatic symptoms in male patients with heroin dependence
Bibliographic record
Abstract
ObjectiveTo explore the related factors to heroin craving in male patients with heroin dependence(MPHD). Methods218 MPHD (study group) from Hunan province were assessed employing a self-developed data-collecting form, Heroin Craving Questionnaire (HCQ), Symptom Checklist 90 (SCL-90), Toronto Alexithymia Scale (TAS), Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS). ResultsCraving degree became more and more obvious with the prolong of heroin use. Apart from self-control factor, the total score and the other factors of HCQ had significant positive association with the total scores of SDS, SAS, SCL-90 and factors of SCL-90. The value of correlation were from 0.168 to 0.375. Analysis of multiple stepwise regression showed that heroin abusing years, paranoid factor of SCL-90, total score of SAS and cigarette smoking entered the regression equation in turn. ConclusionMPHD suffered from severe drug craving,which was impacted by variety factors.
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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".