The global prevalence of E-cigarettes in youth: A comprehensive systematic review and meta-analysis
Bibliographic record
Abstract
Objectives: Smoking, especially cigarettes, is known as one of the most common social and health problems among people. E-cigarettes are another form of tobacco that has been an ordinary daily occurrence.Study Design: systematic review and meta-analysis. Methods: Systematic searching of databases was performed in Scopus, Web of Science, PubMed, Science Direct, MagIran, IranDoc, SID and Google search engine based on the PRISMA 2020 guideline. This search was conducted by the end of May 2021. Following full-text assessments, the related data were extracted from the papers. Newcastle-Ottawa scale was also used to evaluate the quality of methodology of the articles. Finally, study analysis was performed using Comprehensive Meta-Analysis software (version 2) based on the random effect model. Results: Global prevalence of E-cigarette in younger individuals was 16.8 (95 % CI: 10.6-25.6) and 4.8 (95 % CI: 3-7.6) in the Ever and Current modes of E-cigarette, respectively. We also found that E-cigarettes were used more common in young boys than young girls in both Ever and Current modes. In young boys, the prevalence of E-cigarette were 18.8 (95 % CI: 8.4-36.8) and 4.9 (95 % CI: 3-8) in both modes of Ever and Current, respectively. In young girls, these factors were 9.9 (95 % CI: 5-18.6) and 1.6 (95 % CI: 1-3.1) in both modes of Ever and Current, respectively. Conclusions: The global prevalence of e-cigarettes among young people, especially young boys, is increasing. Based on this, the prevention and management of the damage of this social phenomenon requires comprehensive global study, planning and policy.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".