Relationship between tobacco and cannabis use status in outpatients with schizophrenia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: While high prevalence of tobacco and cannabis use are well established in schizophrenia, reports on their co-morbid use is limited. We explored the links between tobacco and cannabis use in an outpatient population meeting DSM-IV criteria for schizophrenia. METHODS: Cigarette smoking behaviors were assessed in an outpaitent population with schizophrenia (N=54) with current (n=18), former (n=24), and no lifetime cannabis dependence (n=12). RESULTS: We found significant differences in cigarettes per day (CPD) across groups: current dependent patients smoked less CPD than patients with former dependence and those with no history of dependence; former dependent patients smoked significantly less than patients with no history of cannabis dependence. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Preliminary results support an effect of cannabis use status on tobacco consumption. In the absence of cannabis, patients may increase cigarette smoking, suggesting state-dependent effects of cannabis on tobacco. Prospective designs should further examine this relationship between cannabis and tobacco in schizophrenia versus non-psychiatric controls.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".