Prevalence and Risk Factors of Cigarette Consumption among the University of Sharjah Students
Bibliographic record
Abstract
OBJECTIVE: Smoking is considered a major public health problem throughout the world. Although the burden of a disease attributable to smoking occurs among adults yet, the problem originates in the teenage and adolescence when the majority of smokers have their first experience with cigarettes. The objective of this study was to estimate prevalence of cigarette consumption among the University of Sharjah students. SETTING: University of Sharjah, Sharjah campus.PARTICIPANTS: The total undergraduate student population registered at University of Sharjah (UoS) during the period of study.DESIGN: A cross-sectional design was followed and included a sample of the University of Sharjah students based on the assumption of a prevalence of 15% and a degree of precision of 5% at the 95% confidence interval for each of the two campuses within the University city (Medical and Health Sciences campus and Non-Medical campus). The designed data collection tool was distributed based on the stratified sampling technique.RESULTS: The overall prevalence was 28.2% for both sexes. The prevalence of smoking among males accounted for 44.6%, while the prevalence of smoking accounted for 13% in females. The highest percentage of type of smoking was cigarettes 52.2% in males and 78.5% in females followed by medwakh 30.2% in males and water-pipe in females 21.5%. A student at a non-medical college, being a non-national, and having parents who were smokers were the common logistic regression predictors of smoking for both sexes in the sample under study.CONCLUSION: Tobacco control strategies and preventive measures in the UAE should start as early as preparatory and high school education and be directed towards school students as it seems that the problem is escalating in prevalence and magnitude.
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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 | 0.001 |
| 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".