A comparison of tobacco use among Saskatchewan First Nations, Métis, and non-Aboriginal youth: Factors associated with youth tobacco use
Bibliographic record
Abstract
Tobacco use among youth is a serious public health concern because the age of initiation affects \none's subsequent health status. Mounting evidence shows that tobacco use among Aboriginal youth is \nhigher than in the general population; however, differences in prevalence rates between Aboriginal and \nnon-Aboriginal youth have yet to be explained. The purpose of this project was to describe and compare \nthe tobacco use behaviours of First Nations, Métis, and non-Aboriginal youth in the Saskatchewan Youth \nAttitudes Survey (SYAS). \nThis project involved a sub-analysis of data from 2605 Saskatchewan youth who took part in the \n1996 Saskatchewan Youth Attitudes Survey. The purpose of the SYAS was to identify high-risk \nbehaviours, and included two questions on tobacco use. Based on self-reported ethnicity, these youth were \ngrouped into three Aboriginal status categories: non-Aboriginal, First Nations, and Métis. \nChi-square tests and ANOVA were used to compare First Nations, Métis, and non-Aboriginal \nyouth tobacco use on the basis of demographic, social, psychological, behavioural, and spiritual variables. \nLogistic regression was used to develop three models of the factors associated with First Nations, Métis, \nand non-Aboriginal youth tobacco use; these models were compared and contrasted. \nTobacco use significantly differed between the Aboriginal status groups. First Nations youth \nwere more likely to use cigarettes/cigars (79.3%) and chewing tobacco (30.5%), than Métis youth (78.3% \nand 25.0%, respectively), followed by non-Aboriginal (60.1% and 25.3%, respectively). Sexual \nintercourse, parental discipline, school attachment, preoccupation with death, drug use, gang activity, \nalcohol use, and family cohesiveness, were significant factors associated with non-Aboriginal tobacco use, \nwhile age, personal control, alcohol use, preoccupation with death, and drug use were significantly \nassociated with First Nations youth. Only drug use, alcohol use, school attachment and gang activity were \nsignificantly associated with Métis youth tobacco use. \nThe results of this study confirm the importance of ethnicity as a factor associated with tobacco \nuse. Non-Aboriginal, First Nations, and Métis youth share certain factors associated with tobacco use; \nhowever, a number of differences also exist between these groups. These results may inform health \nprofessionals and may guide the development of tobacco reduction programs and interventions that are \nsensitive to ethnic differences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".