Influence of social environment in smoking among adolescents in Turkey
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine the social determinants of smoking among adolescents attending school and/or work. METHODS: A survey was carried out on 6012 adolescents aged between 13 and 17 years in 15 cities, recruited from schools, vocational training centres and work places. A self-completed questionnaire was used for data collection. Single- and multi-level regression analyses were run to estimate models. RESULTS: Ever smoking and current smoking rates were 41.1% and 10.5% among girls, and 57.5% and 25.2% among boys. These rates were 47.0% and 13.3% among those who only attended school, 62.2% and 31.7% among those who attended school and worked simultaneously, and 67.5% and 43.0% among those who worked and did not attend school. In multi-level analysis, the major predictors of current smoking were close friends smoking [odds ratio (OR) 3.48; 95% confidence interval (CI) 1.93-6.27], no knowledge of harmful effects of short-term smoking (OR 2.15; 95% CI 1.74-2.67), vulnerability to peer pressure (OR 1.90; 95% CI 1.48-2.46), negative self-perception (OR 1.69; 95% CI 1.31-2.18) and male sex (OR 1.68; 95% CI 1.30-2.16). Mothers higher education was a predictor for girls' smoking, while mother's lower education was a predictor for boys' smoking. At the school level, smoking prevalence was a predictor of current smoking (OR 1.07; 95% CI 1.05-1.08). CONCLUSIONS: Smoking patterns were similar to Western countries in several aspects, while male prevalence rates were higher and the impact of gender-related predictors was significant. Our findings suggest that youth smoking prevention policies should address personal, familial and educational environmental level requirements, taking into consideration the gender differences in addition to international guidelines.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".