Nicotine dependence and gender differences in smokers accessing community mental health services
Bibliographic record
Abstract
Accessible summary • This study explores gender differences in smoking behaviour among individuals accessing community mental health services. • Subjective ratings of tobacco addiction were higher in women than in men, and different variables were associated with nicotine dependence for men and women. • These factors are important for understanding individual differences in tobacco dependence among clients with mental illnesses. Abstract Despite evidence of differences in smoking behaviour between women and men, few studies have assessed these differences in individuals with mental illnesses. In this cross-sectional study, we explored gender differences in smoking behaviour among 298 individuals (60% male) accessing community mental health services. Individuals with a psychotic disorder as compared with a non-psychotic disorder, and individuals using a greater number of substances were more likely to be male. Readiness to change, daily cigarette consumption and level of nicotine dependence did not differ between men and women; however, subjective ratings of tobacco addiction were higher in women than in men. Among women, only scores on the subjective tobacco addiction scale were associated with nicotine dependence, while among men, a variety of variables were associated with nicotine dependence. These factors are important for understanding individual differences in tobacco dependence among clients with mental illnesses, and are expected to inform future studies examining tobacco use in mental health treatment populations.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".