ArticleJournal of health communication2025
Tweeted, Trolled, Twisted: Battling for Narrative Control in E-Cigarette Use Prevention Campaigns (2014-2020).
Article in Journal of health communication, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interventions to change vaping harm perceptions and associations between harm perceptions and vaping and smoking behaviours: A systematic review.Addiction (Abingdon, England) · 2026Pooled it
- Opposition to Youth e-Cigarette Prevention Campaigns on Twitter and TikTok: Cross-Platform Observational Mixed Methods Analysis.Journal of medical Internet research · 2026Observational
- Structural fragility in digital public health communication.Communications health · 2026Article
- Barriers to Public Health Trust-Building Using Social Media: A Qualitative Analysis.Disaster medicine and public health preparedness · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
This study identifies and analyzes X (formerly Twitter) posts related to 14 e-cigarette use prevention campaigns from 2014 to 2020, assessing message volume, content, sources, potential reach and engagement. Using supervised machine learning, we classified 618,965 tweets, finding 43% contained opposition messaging. Two regional campaigns received the highest levels of opposition, with over 99% of related tweets classified as opposition. However, prevention/neutral messages exhibited 92% higher potential reach than opposition messages. Geolocation analysis suggested that regional campaigns may have struggled to focus their impact within targeted jurisdictions. These findings illustrate the dual role of social media as both an amplifier of prevention messages and a platform for oppositional narratives, underscoring the need for public health practitioners to develop adaptive strategies to enhance the impact of digital campaigns.
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.