Smoking prevalence and correlates among inpatients with schizophrenia or schizoaffective disorder
Bibliographic record
Abstract
Many studies have shown that cigarette smoking prevalence rate is high in patients with schizophrenia. Despite the strong association between smoking and schizophrenia, findings on the relationships between smoking, psychiatric symptoms and cognitive functions remain mixed. Furthermore, the smoking rate among acute inpatients who need tertiary mental health care is still unknown. In this study we investigated the smoking rate in this patient population and examined connections between smoking and cognitive functions, psychiatric symptoms, and clinical and demographic characteristics. A retrospective chart review of patients admitted to a tertiary acute psychiatric facility over a 7-year period was conducted. Information such as patient smoking status, diagnosis, and psychiatric assessment scores, were retrieved. Independent samples t-tests and Chi-squared tests were used to compare variables between smoker and non-smoker groups. The smoking prevalence rate was 72%, approximately four times the smoking rate in the general population in Canada. Compared to the non-smoker group, the smoker group were significantly younger, more likely to be male, had less years of education, shorter illness duration, higher rate of concurrent substance use disorder, and less days of hospital stay. However, the two groups did not show differences in severity of illness, types/numbers of medication used, positive and negative symptoms, and cognitive impairment. Smoking status appeared to be associated with several demographic and clinical features. Smoking did not significantly relate to patients' illness severity, medication use, psychiatric symptoms, or cognitive functioning.
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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 | 0.002 |
| 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) | 0.001 | 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".