Generation smoke-free: Protective factors for never smoking among young First Nations peoples aged 10–15 years in the Next Generation Youth Wellbeing Study
Bibliographic record
Abstract
In Australia, smoking accounts for half of all Aboriginal and Torres Strait Islander (First Nations) deaths aged ≥45 years. Regular smoking is more common among First Nations than non-Indigenous peoples in Australia. Smoking primarily commences during adolescence and young adulthood. Preventing uptake is important for long-term health outcomes. This study aimed to identify the protective factors that support young people to be smoke-free, to inform prevention programs and strategies. The ‘Next Generation Youth Wellbeing Study’ is a mixed-methods cohort study. It includes First Nations adolescents aged 10–24 years and living in urban, rural and remote communities in central Australia, Western Australia and New South Wales. This study analysed self-reported data on smoking from young people aged 10–15 years, collected during 2018–20, using Poisson regression to investigate the relation of various factors to never-smoking. Among 682 participants, 54% were female, 90% had never smoked tobacco and 79% lived in smoke-free homes. Factors independently associated with never smoking were: having friends who did not smoke (prevalence ratio [PR] 1.22, 95% confidence interval [CI] 1.15–1.30); daily school attendance (PR 1.14, 1.06–1.22), never drinking (PR 1.84, 1.38–2.46), self-reported good/excellent health (PR 1.12, 1.00–1.26), good mental health (PR 1.12, 1.04–1.20), never been questioned by police (PR 1.24, 1.14–1.34) and never interacting with the justice system (PR 1.23, 1.13–1.33), compared with participants without these exposures. There was no association between never smoking and sex, available money or physical activity. Most First Nations young people had never smoked; this was related to multiple smoke-free influences, good health and wellbeing and positive social engagement and experiences. Alongside opportunities in home, school and community settings to support smoke-free behaviours, broader system-wide changes are required. • Most young people had never smoked. This was related to good health and wellbeing and positive social engagement and experiences. • There are opportunities in home, school and community settings to support smoke-free behaviours with broader system-wide changes also required. • Community programs must support wellbeing – keeping people physically healthy, in good mental health and engaged and active, centring family, community and culture. • Bigger systemic changes are needed. No negative interactions with the police was one of the strongest predictors of being a never smoker. The culture of over-policing and systemic racism that targets young Aboriginal people is directly impacting their health.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".