ArticleInternational journal of environmental research and public health2020
Factors Associated with E-Cigarette Use in U.S. Young Adult Never Smokers of Conventional Cigarettes: A Machine Learning Approach.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Comparison of Feature Selection Methods in Machine Learning Models of Cancer Information Seeking Among United States Adults: Cross-Sectional Study.JMIR medical informatics · 2026Article
- Machine learning used to study risk factors for chronic diseases: A scoping review.Canadian journal of public health = Revue canadienne de sante publique · 2026Article
- A portrait of electronic nicotine delivery systems use in Brazil: findings from the 2019-2023 Vigitel survey.Cadernos de saude publica · 2026Article
- Unveiling the Influence of AI on Advancements in Respiratory Care: Narrative Review.Interactive journal of medical research · 2024Review
- Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.International journal of environmental research and public health · 2024Article
- Cardiovascular dysfunction induced by combined exposure to nicotine inhalation and high-fat diet.American journal of physiology. Heart and circulatory physiology · 2024Article
- Adult Electronic Nicotine Delivery System Use in the USA: a Scoping Review Through a Health Equity Lens.Current addiction reports · 2023Article
- Prospective predictors of electronic nicotine delivery system initiation in tobacco naive young adults: A machine learning approach.Preventive medicine reports · 2023Article
- Cross-Sectional Associations of Self-Reported Social/Emotional Support and Life Satisfaction with Smoking and Vaping Status in Adults.International journal of environmental research and public health · 2022Article
- State-specific prevalence of current e-cigarette use by disability status and disability type-United States, BRFSS 2016-2018.Disability and health journal · 2022Article
- E-Cigarette Use in Young Adult Never Cigarette Smokers with Disabilities: Results from the Behavioral Risk Factor Surveillance System Survey.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18-34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.