Attitude towards cigarette or e-cigarette use and the smoking initiation year among young European adults
Bibliographic record
Abstract
The attitudes towards smoking are changing. More and more European are reaching for first cigarette under 15 years old. The aim of the study was to assess the prevalence of ever cigarette and e-cigarette usae and smoking initiation among young European adults. A cross-sectional study was carried out among students from five European countries: Belarus (BY), Lithuania (LT), Poland (PL), Russia (RU) and Slovakia (SK). A self-prepared, previously validated questionnaire focused on attitudes toward cigarettes and e-cigarette use was used. This study is a part of YoUng People E-Smoking Study (YUPESS). Completed questionnaires were obtained from 14,352 young adults (70.4% female), aged 20.9±2.4 y-old: BY:3895; LT:1128; PL: 7324; RU:1290; SK:715, the overall response rate: 72.2%. Ever cigarette use was declared by 66.1% of respondents, mean age cigarette start: 16.0 ± 2.5 y-old. Among respondents, 43.7% had ever used e-cigarette, mean age e-smoking start: 18.2 ± 2.2. The proportion of Europeans, who had ever used a cigarettes or e-cigarette, significantly differed (p<0.001) between the research centres. Females were less (p<0.001) likely to try either cigarette (64.7%) or e-cigarette (40.5%) compared to male (69.5% and 51.3% respectively). The average age of smoking and e-smoking initiation significantly differed (p=0.001) across Eastern and Central Europe. The earliest nicotine initiation was observed in non EU members; for cigarette in Russia: 15.3 ± 2.6 y-old, and for e-cigarette in Belarus: 17.3 ± 2.0. Europeans reach for cigarettes at an earlier age than e-cigarettes. Attitudes towards cigarette and e-cigarette use differ between EU and non-EU 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 | 0.001 | 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) | 0.001 | 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".