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Updated: Sep 16, 2025
Generation of Electronic Cigarette Aerosol by a Third-Generation Machine-Vaping Device: Application to Toxicological Studies
Published on: August 25, 2018
Interdisciplinary perspective-based behavioral prediction of e-cigarette use: A population-based study among Chinese
Yu Chen1, Zining Wang2, Shaoying Jiang3
1School of Art and Communication, Fujian Polytechnic Normal University, Fuqing, China.
Introduction:
E-cigarette use is rising among young adults globally, and college students are particularly vulnerable due to high social media engagement and targeted promotions. Understanding which factors predispose this population to initiate vaping is critical for designing effective prevention strategies.
Methods:
We conducted a cross-sectional survey of 303 never-smoking, never-vaping Chinese college students (aged 18-24 years) recruited via online platforms and referrals. The 25-item questionnaire assessed six domains: demographics, parental smoking, peer e-cigarette use, 'quasi-deviant' behaviors (regular alcohol consumption and bar attendance), social media use and trust, and exposure to e-cigarette marketing across five media channels. A three-item susceptibility scale was combined into a single index via principal component analysis. An Extremely Randomized Trees classifier (n_estimators=60, max_depth=6) with grid-search and five-fold cross-validation on a 75:25 train-test split, identified the strongest predictors of high susceptibility. Model performance was evaluated by accuracy and area under the receiver operating characteristic curve (AUC).
Results:
The model achieved 81% classification accuracy. Feature importance (FI) indicated that bar attendance (FI=0.21), alcohol consumption frequency (FI=0.12), exposure to e-cigarette marketing messages (FI=0.08), social media use (FI=0.08), peer e-cigarette use (FI=0.05), and parental smoking (FI=0.05) were the most influential predictors. Among the participants, 18.8% were classified as high-susceptibility, indicating elevated risk for future vaping initiation.
Conclusions:
'Quasi-deviant' behaviors (regular alcohol use and bar attendance), social media marketing exposure, and social influences (peer and parental smoking) are key predictors of e-cigarette susceptibility in Chinese college students. Multi-level prevention strategies - enforcing digital marketing restrictions, peer-focused education, and integrated substance-use interventions - may effectively reduce susceptibility and avert vaping initiation in this high-risk group.
