Nicotine use among patients with schizophrenia
Bibliographic record
Abstract
Objective: The frequency of nicotine use among patients with schizophrenia is reported to be 2.5-4.5-fold that of the general population. Studies on the relation between nicotine use and psychopathology, sociodemographic characteristics, symptoms and biological markers among patients with schizophrenia are limited in Turkey. In these surveys nicotine use was found to be correlated with a decrease in severity of negative symptoms, and an increase in cognitive functioning. On the other hand it is probable that patients with schizophrenia tend to use nicotine for decreasing side effects of their drugs. In this study we aim to evaluate relation of nicotine use with symptomatology, drug use and other clinical characteristics. Methods: A total of 156 patients with diagnosis of schizophrenia enrolled into the study. The demographic characteristics of patients, nicotine use and disease symptomatology were evaluated. Brief Psychiatric Rating Scale (BPRS), Scale of Assessment for the Positive Symptoms (SAPS), Scale of Assessment for the Negative Symptoms (SANS) and Calgary Depression Scale were used to evaluate symptomatology. Chi-square and t-tests are used for statistical analysis. Results: 59.6% (93) of patients were male and 40.4% (63) patients were female. Mean age was calculated as 34.96±11.95. 53.8% (84) of patients had nicotine use. Nicotine use prevalence among male patients was 73.1% (68) while it was 25.4% (16) in female patients. Clinical features, SANS, SAPS, BPRS and Calgary Depression Scale rates were similar in nicotine user and non-user groups. Mean equivalent antipsychotic dosage for nicotine user group was 697.61 while it is calculated as 520.55 for the non-user group. The difference was statistically significant (t=3.288, df=154, p=0.001). Correlations of daily smoke amount, pack-years of cigarette smoking and symptomatology were evaluated. Pack-years of cigarette smoking were found negatively correlated with total SANS score, SANS affective flattening, SANS anhedonia subscale and SAPS inappropriate affect subscale. Conclusion: Results of our study are similar to other studies’ in terms of nicotine use and showed higher nicotine use rates than in the general population. Correlations of nicotine use and clinical scales were supporting results of previous studies. Although clinical rating scale scores are similar, the difference in equivalent doses of antipsychotics is statistically significant. This may be related with nicotine’s effect on the metabolism of antipsychotics, but the issue needs further assessment.
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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".