Current and former smokers among adolescents aged 12–17 years in Iran: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Smoking, especially among adolescents, is considered a serious public health concern worldwide being associated with increased mortality. The present study was designed as the first systematic review and meta-analysis of the prevalence of current and former smoking behavior among adolescents in Iran. METHODS: Seven international scholarly databases, namely Scopus, Embase, Pubmed/Medline, ISI/Web of Science (WOS), the Cochrane Library, Psyc Info and Cinahl, were extensively searched from January 2000 to September 18, 2019. Google Scholar was also mined. Iranian databases were searched as well (namely, MagIran, Scientific Information Database (SID), and Barakatkns). The DerSimonian-Laird's approach, via the Freeman-Tukey double arcsine method, was used to synthesize the prevalence estimates. RESULTS: The prevalence of current smokers among Iranian adolescents was estimated to be 9% (95% CI: 7 to 10). Stratifying based on gender, the prevalence was 12% among boys (95% CI: 10 to 14) and 6% among girls (95% CI: 5 to 8). The prevalence of former smokers among Iranian adolescents using the random-effect model was computed to be 24% (95% CI: 21 to 27). CONCLUSION: The findings of this study showed that the prevalence of current and former smoking behavior among Iranian adolescents is a relevant public health concern. The country's young population should be given more attention by health policy- and decision-makers and implementation of ad hoc prevention and control policies should be on their agenda.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".