Factors Influencing Smoking Among Indigenous Adolescents Aged 10–24 Years Living in Australia, New Zealand, Canada, and the United States: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Smoking rates are higher among Indigenous populations in most high-income countries with initiation primarily occurring in adolescence for all population groups. This review aims to identify protective and risk factors for smoking behavior among Indigenous adolescents and young adults. AIMS AND METHODS: We searched Medline, Embase, and Psychinfo for all original research published between January 2006 and December 2016 that reported influences on smoking for Indigenous adolescents or young adults aged 10-24 living in Australia, New Zealand, Canada, and the United States (US). Extracted data were coded to individual, social, and environmental level categories using a modified Theory of Triadic Influence framework. RESULTS: A total of 55 studies were included, 41 were descriptive quantitative and 14 qualitative, and 26 included Indigenous participants only. The majority were from the US (32). Frequently reported influences were at the individual and social levels such as increasing age; attitudes and knowledge; substance use; peer and family relationships; smoking norms; mental health; physical activity. At the environmental level, smoke-free spaces; second-hand smoke exposure; high community level prevalence; and social marketing campaigns were also frequently reported. Some studies referenced price, access, and traditional tobacco use. Few reported historical and cultural factors. CONCLUSIONS: Young Indigenous people experience similar influences to other populations such as smoking among family and friends. Greater youth smoking is related to broader community level prevalence, but few studies explore the distal or historical contributing factors such as traditional tobacco use, colonization, experiences of intergenerational trauma and discrimination, or the role of cultural connection. IMPLICATIONS: This review identified a range of factors that influence Indigenous youth smoking and contributes to an understanding of what prevention measures may be effective. Youth tobacco use occurs alongside other substance use and may also serve as an indicator of mental health. Comprehensive community-based programs that work more broadly to address the risk factors related to tobacco, including improving youth mental health, will be important for other behaviors as well. This research highlights the importance of social influence and need for ongoing denormalization of smoking. Future Indigenous led and community owned research is needed to identify likely protective cultural factors.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".