Self-reported addiction to and perceived behavioural control of waterpipe tobacco smoking and its patterns in Egypt: policy implications
Bibliographic record
Abstract
BACKGROUND: Studies on waterpipe tobacco dependency are currently limited. AIMS: This study assessed self-reported addiction to waterpipe tobacco smoking among Egyptian waterpipe smokers and identified the associated sociodemographic factors, perceived behavioural control and patterns of waterpipe tobacco smoking. METHODS: Cross-sectional surveys were conducted on Egyptian adults in 2015 and 2017. Data on 1490 current waterpipe smokers were analysed including: sociodemographic characteristics, waterpipe tobacco smoking behaviour (age at starting, frequency, amount, company and place of smoking, and expenditure), perceived harm of waterpipe tobacco smoking, and self-reported addiction to and perceived behavioural control of waterpipe smoking (ability to quit, difficulty in quitting, quit attempts and intention to quit). RESULTS: A quarter (25.8%) of the participants self-reported addiction to waterpipe tobacco smoking (males 27.1%, females 11.6%). Participants who considered themselves addicted reported less confidence in their ability to quit, fewer quit attempts, less intention to quit and less perceived harm of waterpipe smoking than those not addicted (P < 0.001). Variables associated with self-reported addiction were: younger age at starting waterpipe tobacco smoking (ORa = 2.2, 95% CI: 1.7-2.9), daily waterpipe tobacco smoking (ORa = 2.0, 95% CI: 1.1-3.5), smoking alone (ORa = 2.0, 95% CI: 1.4-2.8), being married (ORa = 1.8, 95% CI: 1.2-2.9), and monthly spending on waterpipe smoking of ≥ 150 Egyptian pounds (US$ 8.6) (ORa = 4.1, 95% CI: 2.9-5.6). CONCLUSIONS: Comprehensive waterpipe-specific policies are needed including education on waterpipe tobacco smoking dependency, increased taxation to decrease affordability of waterpipe tobacco and cessation programmes addressing perceived self-efficacy and addiction to waterpipe tobacco smoking.
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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 | 0.001 | 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".