Trends of electronic cigarette use among adolescents: A bibliometric analysis
Bibliographic record
Abstract
INTRODUCTION: The use rate of electronic cigarettes (e-cigarettes) among adolescents is continuously rising globally, posing new challenges to public health and negatively impacting adolescent health. This study employs bibliometric methods to systematically present the current state and evolving trends in global research on adolescent e-cigarette use. METHODS: This study uses CiteSpace to conduct a bibliometric analysis of articles related to adolescent e-cigarette use from the Web of Science (WoS) Core Collection database. Firstly, performance analysis and collaboration network analysis were utilized to clarify the basic publication status, main knowledge producers, and knowledge collaboration networks in adolescent e-cigarette use research. Secondly, a co-citation network analysis was performed to visually analyze the disciplinary characteristics and 'hot topics' in this field. Finally, keyword burst detection and clustering techniques were employed to further explain the development trends and frontiers of research on adolescent e-cigarette use. RESULTS: A total of 2063 research articles and review articles were included in this study. Research on adolescent e-cigarette use has significantly increased from 2002 to 2024. The United States, the United Kingdom and Canada are the main contributors, with their institutions and researchers playing key roles in the international collaborative network. Current research increasingly adopts interdisciplinary approaches. Keyword co-occurrence and burst identified current research 'hotspots' including vaping, substance use, public policy, prevention, advertising, and cessation. Co-citation cluster analysis revealed promising research areas such as attractiveness, environment and health, accessibility and smoking behavior, and mental health. CONCLUSIONS: Through data mining and visualization techniques, this study provides a comprehensive bibliometric analysis of published work on e-cigarettes and adolescence. The results of this work offer references for researchers in future investigations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.054 | 0.128 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".