Susceptibility to smoking and associated factors among the youth in central and eastern European countries.
Bibliographic record
Abstract
Abstract Background Tobacco use among young people still remains a major public health problem. The aim of this study was to examine the association between a variety of factors and susceptibility to smoking initiation and experimentation among the youth from central and eastern European countries. Methods The data used in the current analysis, focusing on current non-smokers, is available from the Global Youth Tobacco Survey, which was performed in five countries (the Czech Republic (2016), n = 3191; Slovakia (2016), n = 3178; Slovenia (2017), n = 2255; Romania (2017), n = 4681; Lithuania (2018), n = 2260). Results Among the never smokers, nearly a quarter of the students were susceptible to smoking in 4 of 5 countries (16% of those susceptible to smoking were identified in Romania). Moreover, 60% of the students in the Czech Republic, Slovakia and Slovenia, and about 50% of the students in Lithuania and Romania were found to be vulnerable to smoking experimentation (an analysis among ever smokers). The multiple regression models provided results that are consistent among all the examined countries, with the following factors identified as significant correlates of smoking initiation and experimentation: being girls, having more money available for own expenses, experiencing exposure to passive smoking in public places, as well as indicating peer smoking. Moreover, adolescents who have declared lack of antismoking education and knowledge on harmful effects of passive smoking, those who saw people using tobacco on TV, in videos or in movies as well as advertising of tobacco products at point of sales were susceptible to smoking. Finally, the students who shared an opinion that smoking helped people feel more comfortable at celebrations, parties or in other social gatherings were at higher risk of smoking susceptibility. Conclusions A high proportion of the youth from central and eastern European countries is susceptible to smoking. Personal and social factors and those related to educational and policy issues were strongly and consistently correlated with smoking susceptibility. These factors should be considered when designing and implementing anti-smoking activities among young people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".