Youth Smoking Behavior and Policy Attitudes: A Study of High-School Students in the Maldives
Bibliographic record
Abstract
Background: Tobacco use significantly impacts health and economic sectors. In the Maldives, 4 out of 10 men smoke daily, despite anti-tobacco policies. The Maldives Global Youth Tobacco Survey (GYTS) shows fluctuating cigarette smoking prevalence among secondary school students: 6.9% (2004), 3.8% (2007), 4.3% (2011), and 4.7% (2019). No studies have investigated smoking prevalence and attitudes toward anti-smoking policies among higher-secondary students in Addu City. This study examines smoking habits, susceptibility, and attitudes toward anti-smoking regulations to support policy development. Methods: We conducted an observational cross-sectional study using a self-administered survey based on the GYTS and the Canadian Student Tobacco, Alcohol and Drugs Survey (CSTADS), involving 335 high school students in Addu City. Variables included sociodemographic factors, ever-smokers, current smokers, age at first cigarette, smoking dependency, use of other tobacco products, smoking susceptibility, willingness to quit, and reasons to quit or not smoke. Results with p-values < 0.05 were statistically significant. Results: 22.8% of the students had tried smoking, with 4.74% currently smoking, predominantly males. Additionally, 32.2% had tried e-cigarettes. Smoking susceptibility was 44.2%. Seven students showed smoking dependency, with a significant gender difference (75.4% boys vs 33.3% girls, p < 0.05). Among smokers, 20% wanted to quit, and 70% cited cost as a deterrent. Only 20% of smokers supported a total ban on smoking in media compared to 49.8% of non-smokers (p = 0.03). Non-smokers significantly supported anti-smoking measures (73% vs 12.5% of smokers). Conclusion: Cigarette smoking among high school students in Addu is below the national average, but the high number of ever-smokers and interest in smoking and e-cigarettes suggest potential future increases. Policymakers should enact stronger legislation, enforce age restrictions, raise tobacco taxes, and implement comprehensive smoking cessation programs to address tobacco use effectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".