Smoking and Predictors of Nicotine Dependence in a Homeless Population
Bibliographic record
Abstract
OBJECTIVE: To assess prevalence rates of tobacco use and dependence in a sample of homeless individuals and to investigate trends for demographic and clinical characteristics across different levels of nicotine dependence (nonsmokers vs. lowly dependent smokers vs. highly dependent smokers). METHODS: A cross-sectional study of 489 homeless men and women in 3 Canadian cities. Each subject was assessed using structured clinical interviews and the Fagerström Test for Nicotine Dependence (FTND). Cochran-Armitage trend tests were applied to determine unadjusted trends in sociodemographic and clinical variables across levels of nicotine dependence. A generalized logit model was computed to adjust for potential confounding. RESULTS: The mean age was 37.9 years; 39.2% of the participants were women. About 80.8% were current smokers; the mean FTND score was 5.0. Although no significant differences were found between nonsmokers and smokers with low nicotine dependence, smokers with high nicotine dependence were only half as likely as nonsmokers to be Aboriginal, were 2.39 times more likely to have ever been incarcerated, and 2.44 times more likely to have current drug dependence. There were significant trends for the use of cocaine, opioids, and alcohol, with nonsmokers having the lowest and highly dependent smokers having the highest rates of using these substances. CONCLUSIONS: Available public health smoking cessation treatment opportunities should be made available within health care services for the homeless. There is also a need for developing and implementing tobacco dependence treatment programs, which are accessible and tailored to meet the needs of this specific population, accounting for polysubstance use and concurrent substance dependence and mental health disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".