The rise in narghile (shisha, hookah) waterpipe tobacco smoking: A qualitative study of perceptions of smokers and non smokers
Bibliographic record
Abstract
BACKGROUND: The prevalence of waterpipe tobacco smoking (WTS) in the Middle East region and worldwide is increasing. There is evidence to indicate both short term and long term health effects of WTS, resulting in the issuance of an advisory note by the World Health Organization. METHODS: This research aimed at gaining an in-depth understanding of the factors contributing to the rise in WTS in Lebanon. Qualitative focus groups (25) and in-depth interviews (9) were conducted with adults in Lebanon in 2007. Participants were recruited to represent diversity in smoking status, gender, age groups and urban/rural residence. The interviews and focus groups were thematically analyzed, and recurrent themes noted and summarized. RESULTS: The main themes identified were availability, affordability, innovation, influence of media, lack of a policy framework, and the sensory characteristics evoked from WTS. Men and women, smokers and non-smokers, and younger and older participants differed in their emphases on the above themes. These themes, though specific to waterpipe, are similar to themes manipulated by the cigarette industry, and eventually controlled through tobacco control policies. CONCLUSIONS: Understanding reasons behind the rise in waterpipe tobacco use is important if appropriate prevention, cessation, and policy interventions are to be formulated. Strict adherence to the FCTC is warranted, with careful and vigilant attention that all tobacco products are covered by laws in both high as well as middle to lower income countries.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".