Vaping among French adolescents aged 17: results from the ESCAPAD 2017 survey (n = 39 115)
Bibliographic record
Abstract
Introduction Electronic nicotine delivery systems (ENDS) use has spread out in France since 2010, including among adolescents. However, its use in relation to smoking and other factors is not well understood today. Methods The data used come from the ESCAPAD 2017 survey, a nationally representative cross-sectional survey taking place at a 1-day session of civic and military information compulsory for all French nationals around 17 (39 115 respondents). Descriptive analyses and multivariate regressions (Poisson with robust variance) were undertaken to describe the recent use of ENDS at 17 and it associated factors. Results ENDS were experimented by 52.4 % of 17 years old, and used by 16.8 % in the preceding month, 1,9 % daily. Most recent users were also daily smokers (62.5 %), and only 7.6 % never experimented smoking before. They were mostly boys (PR=1.39). No difference related to the parental socioeconomic status was highlighted. Recent vapers were more likely to have retaken a school year (PR=1,25) and were less likely out of school (PR=0,80). The associate uses of other products were the most striking factors: daily smoking (PR=2,73), regular alcohol drinking (PR=1,20), cannabis use in the last year (PR=1,60), ever use of hookah (PR=2,31) and ever use of another illicit drug (PR=1,11). Conclusions Those robust and representative results about vaping among French adolescents are essential to understand this trend. Although most French adolescents experiment with vaping, they are fewer to use it regularly and most of regular vapers are also daily smokers. The relationship between smoking and vaping will have to be further investigated. Funding This work was supported by the French Cancer League as part of the PETAL research program on adolescent 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".