ArticleAddiction (Abingdon, England)2019
Predicting vaping uptake, vaping frequency and ongoing vaping among daily smokers using longitudinal data from the International Tobacco Control (ITC) Four Country Surveys.
Article in Addiction (Abingdon, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Understanding the motivational mechanisms for smoking and vaping among dual users and exclusive smokers.Drug and alcohol dependence · 2024Article
- Depressive symptoms and vaping: The mediating effect of outcome expectancies among young adults.Drug and alcohol dependence · 2023Article
- The Australia Smoking and Vaping Model: The Potential Impact of Increasing Access to Nicotine Vaping Products.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023Article
- Article
- A Retrospective Cross-Sectional Study on the Prevalence of E-cigarette Use Among College Students.Journal of community health · 2021Article
- E-Liquid Flavor Preferences and Individual Factors Related to Vaping: A Survey among Dutch Never-Users, Smokers, Dual Users, and Exclusive Vapers.International journal of environmental research and public health · 2019Article
- Predicting the future of smoking in a rapidly evolving nicotine market-place.Addiction (Abingdon, England) · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
aimTo assess (1) how far smoking patterns, depression and smoking-related beliefs and intentions predict vaping uptake, current vaping and vaping frequency among daily smokers; and (2) how far the aforementioned predictors and baseline vaping frequency predict current vaping among those who reported ever vaped.
designAnalysis of data from six waves of a longitudinal survey over 8 years. Longitudinal associations between predictors and outcomes were examined using multi-level models.
settingUnited Kingdom, United States, Canada and Australia.
participantsA total of 6296 daily smokers (53% females) who contributed data to at least two consecutive survey waves. MEASUREMENTS: The outcome variables were vaping uptake, vaping frequency and current vaping at follow-up. The key predictor variables, measured in previous waves, were time to first cigarette, cigarettes smoked per day, depressive symptoms, intention to quit smoking, quitting self-efficacy and worry about adverse health effects of smoking.
findingsNumber of cigarettes smoked daily was associated with (1) subsequent vaping uptake [odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.19, 2.39 for 30+ cigarette per day; reference category: 0-10 cigarettes] and (2) a higher frequency of current vaping (OR = 1.97, 95% CI = 1.36, 2.85 for 30+ cigarettes). Intention to quit was associated with a higher frequency of current vaping (OR = 1.48, 95% CI = 1.21, 1.82). Among those who reported ever vaped, higher baseline vaping frequency (OR = 11.98, 95% CI = 6.00, 23.93 for daily vaping at baseline; reference category: vaped less than monthly) predicted current vaping.
conclusionAmong daily smokers, amount smoked and intention to quit smoking appear to predict subsequent vaping uptake. Vaping frequency at baseline appears to predict current vaping at follow-up.
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