Family and Peer Risk Factors as Predictors of Lifetime Tobacco Use among Iranian Adolescents: Gender Similarities and Differences
Bibliographic record
Abstract
INTRODUCTION: Family and peer risk factors are considered as important predictors of tobacco use in adolescents. Furthermore, information regarding gender differences in lifetime tobacco use of adolescents is essential for designing gender-specific tobacco prevention policies. METHODS: In a cross-sectional population-based study, 870 Iranian adolescents (430 boys and 436 girls) aged 15-18 years old, filled out the adopted form of "Communities That Care Youth Survey". Four family and two peer risk factors were entered in adjusted logistic regression analyses to predict the lifetime tobacco use (cigarette and smokeless tobacco) in boys and girls, separately. RESULTS: Boys reported higher prevalence of lifetime cigarettes use compared to girls (22.8% vs. 17.8%, p = 0.04). However, the prevalence of lifetime smokeless tobacco use in girls was the same as boys, even slightly higher (7.9% vs. 7.1%, P=0.5). "Family history of drug use" and "Friends use of drugs" were common risk factors predicting cigarettes and smokeless tobacco use between both genders. On the other hand, other family risk factors included "Poor family management", "Parental attitude favorable toward drug use" and "Family conflict" were the predictors of lifetime tobacco use only in girls, but not in boys. CONCLUSION: Design and implementation of preventative programs for adolescents tobacco use should be conducted with emphasis on the role of smoker parents at home, and friendship with substance user peers with antisocial behaviors. It seems that family risk factors may have more value in prevention of tobacco use in female adolescents.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".