The prevalence of smoking among Iranian middle school students, a systematic review
Bibliographic record
Abstract
Objectives: The mean age of cigarette smoking has decreased along with an increase in its prevalence, in developing countries. The aim of this systematic review is to determine the prevalence of lifetime, current and daily smoking among middle school students in Iran . Methods: Various search methods have been used in this study including searching different international databanks such as Pubmed, ISI web of Science, PsychInfo, CINAHL, Embase, as well as domestic databanks including IranPsych and IranMedex. All original studies and researches in Persian or English, which had described any kind of use including lifetime, current and daily use of cigarette, hookah, and pipe among middle school students, were included in the study with no restriction on date of publication, and were qualitatively assessed. Subsequent to data extraction, heterogeneity test was carried out on indicators for which more than two studies were found, and meta-analysis was done using random effects model . Results: The combined prevalence of lifetime, current and daily cigarette smoking were calculated as 14.2% (95% CI: 6.6-21.7), 2.7% (95% CI: 0.5- 5.9) and 1.1% (95% CI: 0.6-2.8), respectively. The combined prevalence of 'current tobacco use of all kinds' was 15% (95% CI: 10.4-19.5), as well. Conclusions: The prevalence of smoking in this age range is lower in Iran compared to other countries. However, a conclusion cannot be made about the changes in the prevalence of smoking in recent years. Moreover, studies carried out to the present have several qualitative limitations, which points to the necessity of high quality repeated surveys
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".