ArticleAJPM focus2023
E-Cigarette-Related Health Beliefs Expressed on Twitter Within the U.S.
Article in AJPM focus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Bidirectional Associations Between Engagement with Tobacco Information on Social Media and Young Adults' Depressive Symptoms: A Longitudinal Cross-Lagged Analysis.Behavioral sciences (Basel, Switzerland) · 2026Article
- Response to the Netflix Docuseries "Big Vape: The Rise and Fall of JUUL": Mixed Methods Analysis of YouTube Comments Using Qualitative Coding and Topic Modeling.JMIR formative research · 2025Article
- Online Illicit Drug Distribution in the Thai Language on X: Exploratory Qualitative Content Analysis.JMIR infodemiology · 2025Article
- Stanford Screenomics: An Open-source Platform for Unobtrusive Multimodal Digital Trace Data Collection from Android Smartphones.medRxiv : the preprint server for health sciences · 2025Article
- Why and how should children be protected from the deluge of vaping related media and marketing overexposure?Breathe (Sheffield, England) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Introduction: This mixed-methods study analyzed English-language U.S.-based Twitter posts related to E-cigarette use from February 2021. Methods: Posts were manually identified as health-related or not and, if health-related, whether they were posted by an E-cigarette user. A random selection of 1,000 health-related tweets from 986 unique E-cigarette users were qualitatively content analyzed for theory of planned behavior constructs as well as nature and tone of each tweet message. Using quantitative semantic network analysis, relationships among the identified topics and sentiment-specific conversation patterns were explored. Results: The most salient health-related conversation topics of E-cigarette users, health beliefs corresponding to each theory of planned behavior construct, and major motivational contexts of E-cigarette use were identified. Seven topics emerged in positive tweets: smoking cessation, social impact generation, controls over addiction, therapeutic effects on physical and mental health, social support, device attachment, and peer influence. Nine topics emerged in negative tweets: side effects on physical health, vaping addiction, lack of E-cigarette regulations, peer pressure, increased risk of COVID-19, side effects on mental health, no help in smoking cessation, social conflict, and polysubstance use. Most assertions for E-cigarette benefits were not substantiated. Jokes in tweets appeared to contribute to the view of vaping as an attractive, enjoyable, safe, and fun activity. Discussions about positive aspects of E-cigarette use were concentrated on a few related topics, whereas tweets discouraging E-cigarette use presented a diverse, less related set of topics. Conclusions: The results provide insights into the drivers of E-cigarette use behaviors. E-cigarette user perspectives gathered from social media may inform research to guide future prevention and cessation interventions.
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What OpenQuestion holds
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.