ArticleAddictive behaviors reports2019
Relationship between social media engagement and e-cigarette policy support.
Article in Addictive behaviors reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Smokers' Likelihood to Engage With Information and Misinformation on Twitter About the Relative Harms of e-Cigarette Use: Results From a Randomized Controlled Trial.JMIR public health and surveillance · 2021Trial
- Tobacco control policies discussed on social media: a scoping review.Tobacco control · 2026Article
- Advancing Support for Electronic Cigarette Control Policies in the United States: The Impact of Theory-Based Messaging Strategies.Preventive medicine reports · 2025Article
- The role of social media messages and content creators in shaping COVID-19 vaccination intentions.Frontiers in digital health · 2025Article
- Social Media Data Mining of Antitobacco Campaign Messages: Machine Learning Analysis of Facebook Posts.Journal of medical Internet research · 2023Article
- Sampling Twitter users for social science research: evidence from a systematic review of the literature.Quality & quantity · 2023Article
- Describing Memes Referencing Vaping: Thematic Analysis.Substance use & misuse · 2023Article
- Do Longitudinal Trends in Tobacco 21-Related Media Coverage Correlate with Policy Support? an Exploratory Analysis Using Supervised and Unsupervised Machine Learning Methods.Health communication · 2022Article
- Public Response to a Social Media Tobacco Prevention Campaign: Content Analysis.JMIR public health and surveillance · 2020Article
- The World Health Organization's World No Tobacco Day 2020 Campaign Exposes Tobacco and Related Industry Tactics to Manipulate Children and Young People and Hook a New Generation of Users.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionGiven increasing efforts to regulate e-cigarettes, it is important to understand factors associated with support for tobacco regulatory policies. We investigate such factors found in social media and hypothesize that greater online engagement with tobacco content would be associated with less support for e-cigarette regulatory policies.
methodsWe constructed social networks of Twitter users who tweet about tobacco and categorized them using a combination of social network and Twitter metrics. Twitter users were identified as representing leaders, followers or general users in online discussions of tobacco products, and invited to complete an online survey. Participants responded to questions about their engagement with tobacco-related content online, degree of support for e-cigarette regulations, exposure to tobacco marketing, e-cigarette use and other demographic information. We examined links between their reported engagement with tobacco-related content and support for e-cigarette regulatory policies using structural equation modelling.
resultsThe analytic sample consisted of 470 participants. The conceptualized structural equation model had a good fit (χ
conclusionsFindings suggest that our hypothesis was supported. Twitter users engaging with tobacco-related content and harboring negative attitudes toward e-cigarette regulatory policies could be an important audience segment to reach with tailored e-cigarette policy education messages.
Indexed as
Identifiers
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.