Tobacco cessation drug therapy among Canada's Aboriginal people
Bibliographic record
Abstract
The smoking rate among Aboriginal people is more than double the rate of the rest of the Canadian population, and smoking is a major source of morbidity and mortality within this population. Tobacco cessation drug therapy use among Aboriginal smokers is very low. We administered a cross-sectional questionnaire to Aboriginal and non-Aboriginal smokers or recent ex-smokers in 12 First Nations communities in two Canadian provinces from September to December 2004. Participants were asked about smoking cessation advice and perceptions of three drug therapy agents. The overall response rate was 82% (407 Aboriginal and 102 non-Aboriginal smokers or ex-smokers). A substantial proportion reported tobacco cessation or reduction in the previous year (Aboriginal 46% vs. non-Aboriginal 32%). Aboriginal participants were less likely to seek physician services (prevalence OR [pOR] = 0.45, 95% CI = 0.27-0.74, p = .001) and less willing to use nicotine patch (pOR = 0.6, 95% CI = 0.38-0.96, p = .03) or bupropion (pOR = 0.50, 95% CI = 0.29-0.84, p = .008). Among First Nations participants, who receive a drug therapy subsidy, lack of awareness of the subsidy were associated with less willingness to use drug therapy; further, the requirement for a physician prescription was perceived as a barrier. Among all participants, utilization of physician services (pOR = 2.2, 95% CI = 1.50-3.20, p<.001) and receiving drug therapy advice from a physician (pOR = 7.7, 95% CI = 4.17-14.3, p<.001) was associated with willingness to use drug therapy. In conclusion, many Aboriginal smokers are interested in and attempt cessation, but underutilization of physician services and low willingness to use drug therapy may explain their lower use of drug therapy. Physicians need to provide advice on drug therapy, and policy makers should eliminate the need for a physician prescription. Future studies can explore cultural attitudes toward cessation drug therapy and physician services.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".