Drug Addiction in Patients With Chronic Schizophrenia and Its Relation With Psychopathology and Impulsiveness
Bibliographic record
Abstract
BACKGROUND: Using drugs is a common affliction in patients with Schizophrenia affecting their increasing death rate. They have to tolerate longer treatment time and staying in hospital and they further show more violence and their living quality decreases. It also seems that this factor is among the influential factors of unsuccessful results in treating these patients. OBJECTIVES: Despite all this, there is little data about drug consumption, psychopathology and demographic information in patients with chronic schizophrenia in Iran. This paper reviews the relation between drug consumption and the mentioned qualities in patients afflicted by chronic Schizophrenia. METHODS: In this cross-sectional study, 100 patients with Schizophrenia were interviewed based on DSM-IV-TR diagnostic parameters and according to a psychiatrist´s views. The severity of psychopathology was evaluated, using PANSS, (SCID-I) DSM-IV and BARRAT. RESULTS: The results show that in patients with chronic schizophrenia, there is a meaningful relation between cigarette consumption and education, gender, family background and BARRAT. It also has a direct correlation with Attention and Motor. Drug consumption has a meaningful relation with gender and Motor (p<0.05). But it has no relation with BARRAT. Of the variables having a relation with correlation, cigarette and treatment period factors have a predicting effect for drug consumption. CONCLUSIONS: According to the results, drug and cigarette consumption is high among patients with Chronic Schizophrenia. Common cigarette consumption and its relation with impulsiveness increase, and death rate are the reasons which make us take the needed steps to have these patients quit smoking.
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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 | 0.001 |
| 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".