ArticleJournal of the American Medical Informatics Association : JAMIA2019
Electronic cigarette usage patterns: a case study combining survey and social media data.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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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.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Features of disposable e-cigarettes and their association with pricing and consumer preference: Evidence from web data of US online stores.Addiction (Abingdon, England) · 2025Article
- Twitter users perceptions of AI-based e-learning technologies.Scientific reports · 2024Article
- Tweet topics and sentiments relating to distance learning among Italian Twitter users.Scientific reports · 2022Article
- COVID-19 Pandemic: Identifying Key Issues Using Social Media and Natural Language Processing.Journal of healthcare informatics research · 2022Article
- Covid-19 vaccines in Italian public opinion: Identifying key issues using Twitter and Natural Language Processing.PloS one · 2022Article
- Health, Psychosocial, and Social Issues Emanating From the COVID-19 Pandemic Based on Social Media Comments: Text Mining and Thematic Analysis Approach.JMIR medical informatics · 2021Article
- Doing what matters most.Journal of the American Medical Informatics Association : JAMIA · 2019Article
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 at 3 institutions in 2 countries.
Funding
Abstract
Objective: To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions. Materials and Methods: We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. We analyzed online forum participation patterns using survey data. We compared e-cigarette use patterns, including brand and flavor types, ratings, and purchase approaches, between the 2 datasets. We used logistic regression to study intentions to use e-cigarettes using both datasets. Results: Male and younger e-cigarette users were the most likely to participate in e-cigarette-related discussion forums. Forum active survey participants were hardcore vapers. The e-cigarette use patterns were similar in the online survey data and the social media data. Intention to use e-cigarettes was positively related to e-liquid ratings and flavor ratings. Social media provided a valuable source of information on users' ratings of e-cigarette refill liquids. Discussion: For hardcore vapers, social media data were consistent with online survey data, which suggests that social media may be useful to study e-cigarette use behaviors and can serve as a useful complement to online survey research. We proposed an innovative framework for social media data triangulation in public health studies. Conclusion: We illustrated how social media data, combined with online survey data, can serve as a new and rich information source for public health research.
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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.