Electronic cigarettes: adolescent health and wellbeing
Bibliographic record
Abstract
We read with interest John N Newton and colleagues' Comment (Feb 6, p 639),1Newton JN Dockrell M Marczylo T Making sense of the latest evidence on electronic cigarettes.Lancet. 2018; 391: 639-642Summary Full Text Full Text PDF PubMed Scopus (18) Google Scholar in which they incorrectly state that “experimentation with ECs [electronic cigarettes] has had no detectable effect on youth smoking rates and increased availability of ECs has not interrupted declining trends in youth smoking in many countries”. We believe that this statement is incorrect and is not supported by evidence in the literature. Studies clearly show that experimenting with ECs is reversing the previous long-term reduction in teenage smoking.2Barrington-Trimis JL Urman R Leventhal AM et al.E-cigarettes, cigarettes, and the prevalence of adolescent tobacco use.Pediatrics. 2016; (published online July 11.)DOI:10.1542/peds.2015-3983Google Scholar Additionally, findings from a systematic review suggest that adolescents and young children who start with ECs are more likely to smoke cigarettes later in life than those who have not previously used ECs.3Soneji S Barrington-Trimis JL Wills TA et al.Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis.JAMA Pediatr. 2017; 171: 788-797Crossref PubMed Scopus (511) Google Scholar The study authors3Soneji S Barrington-Trimis JL Wills TA et al.Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis.JAMA Pediatr. 2017; 171: 788-797Crossref PubMed Scopus (511) Google Scholar also found consistent and strong evidence that EC use is associated with increased odds of subsequent initiation of cigarette smoking and current cigarette smoking status in adolescents. In the first-ever study designed to control susceptibility to cigarette smoking, adolescents who initiated EC use were more likely to smoke conventional cigarettes 1 year later and become daily smokers.4Hammond D Reid JL Cole AG Leatherdale ST Electronic cigarette use and smoking initiation among youth: a longitudinal cohort study.CMAJ. 2017; 189: e1328-e1336Crossref PubMed Scopus (78) Google Scholar Meanwhile, a congressionally mandated review by the National Academies of Sciences, Engineering, and Medicine of more than 800 peer-reviewed scientific studies on the health effects of ECs on adolescents concluded that “There is substantial evidence that e-cigarette use by youth and young adults increases their risk of ever using conventional cigarettes”.5National Academies of Sciences and Engineering and MedicinePublic health consequences of e-cigarettes. The National Academies Press, Washington, DC2018Google Scholar Therefore, the National Academies of Sciences, Engineering, and Medicine's recommendation should be appropriately reflected in future paediatric clinical guidelines for EC use to prevent a future global tobacco epidemic. This online publication has been corrected. The corrected version first appeared at thelancet.com on September 6, 2018 This online publication has been corrected. The corrected version first appeared at thelancet.com on September 6, 2018 Making sense of the latest evidence on electronic cigarettesIn the UK, 2·85 million people (5·7% of adults) regularly use electronic cigarettes (ECs), almost all of whom are smokers or ex-smokers.1 Prevalence of EC use is similar in the USA2 but is lower in other European Union (EU) countries (average 2%).1 ECs produce an estimated 18 000 additional long-term ex-smokers in England each year;3 a recent update suggests that figure might be as high as 57 000.1 Full-Text PDF Electronic cigarettes: adolescent health and wellbeing – Authors' replyWe thank all correspondents for their interest in our Comment.1 Full-Text PDF Electronic cigarettes: adolescent health and wellbeingThe Comment by John N Newton and colleagues1 would have been more credible if it had been consistently based on evidence. The authors claim that the findings of the National Academies of Sciences, Engineering, and Medicine report2 are generally in line with the Public Health England evidence review,3 but differences of emphasis exist. Full-Text PDF Department of ErrorBandara AN, Mehrnoush V. Electronic cigarettes: adolescent health and wellbeing. Lancet 2018; 392: 473. In this Correspondence, the corresponding author's email address was incorrect. This has been corrected online as of Sept 6, 2018. Full-Text PDF
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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 | 0.013 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.030 | 0.054 |
| Insufficient payload (model declined to judge) | 0.021 | 0.013 |
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".