Evidence map›Paper›PMID 39531640›Full record

ArticleJournal of medical Internet research2024

Concurrent Mentions of Vaping and Alcohol on Twitter: Latent Dirichlet Analysis.

Lynsie R Ranker, David Assefa Tofu, Manyuan Lu, Jiaxi Wu, Aruni Bhatnagar, Rose Marie Robertson, Derry Wijaya, Traci Hong, Jessica L Fetterman, Ziming Xuan

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lynsie R RankerCommunity Health Sciences, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0001-7928-2781
David Assefa TofuDepartment of Computer Science, Boston University, Boston, MA, United States.ORCID 0009-0002-3836-5008
Manyuan LuDepartment of Computer Science, Boston University, Boston, MA, United States.ORCID 0009-0000-7850-3423
Jiaxi WuAnnenberg School of Communication, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0001-5004-9492
Aruni BhatnagarDepartment of Medicine, University of Louisville, Louisville, KY, United States.ORCID 0000-0001-6818-0384
Rose Marie RobertsonAmerican Heart Association Tobacco Regulation and Addiction Center, Dallas, TX, United States.ORCID 0000-0002-8855-0933
Derry WijayaDepartment of Computer Science, Boston University, Boston, MA, United States.ORCID 0000-0002-0848-4703
Traci HongCollege of Communication, Boston University, Boston, MA, United States.ORCID 0000-0001-9107-1880
Jessica L FettermanEvans Department of Medicine and Whitaker Cardiovascular Institute, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States.ORCID 0000-0002-9286-7538
Ziming XuanCommunity Health Sciences, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0001-6139-4785

Funding

ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
Relations of Mitochondrial Genetic Variation and Function with Atrial FibrillationK01HL143142 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI FETTERMAN, JESSICA L · 2019 to 2023
$757k
NHLBI NIH HHS K01 HL143142NHLBI NIH HHS U54 HL120163
6 · The paper itself

Abstract

backgroundCo-use of alcohol and e-cigarettes (often called vaping) has been linked with long-term health outcomes, including increased risk for substance use disorder. Co-use may have been exacerbated by the COVID-19 pandemic. Social networking sites may offer insights into current perspectives on polysubstance use.

objectiveThe aims of this study were to investigate concurrent mentions of vaping and alcohol on Twitter (subsequently rebranded X) during a time of changing vaping regulations in the United States and the emergence of the COVID-19 pandemic.

methodsTweets including both vape- and alcohol-related terms posted between October 2019 and September 2020 were analyzed using latent Dirichlet allocation modeling. Distinct topics were identified and described.

resultsThree topics were identified across 6437 tweets: (1) flavors and flavor ban (n=3334, 51.8% of tweets), (2) co-use discourse (n=1119, 17.4%), and (3) availability and access regulation (n=1984, 30.8%). Co-use discussions often portrayed co-use as positive and prosocial. Tweets focused on regulation often used alcohol regulations for comparison. Some focused on the perceived overregulation of vaping (compared to alcohol), while others supported limiting youth access but not at the expense of adult access (eg, stronger age verification over product bans). Across topics, vaping was typically portrayed as less harmful than alcohol use. The benefits of flavors for adult smoking cessation were also discussed. The distribution of topics across time varied across both pre- and post-regulatory change and pre- and post-COVID-19 pandemic declaration periods, suggesting shifts in topic focus salience across time.

conclusionsCo-use discussions on social media during this time of regulatory change and social upheaval typically portrayed both vaping and alcohol use in a positive light. It also included debates surrounding the differences in regulation of the 2 substances-particularly as it related to limiting youth access. Emergent themes from the analysis suggest that alcohol was perceived as more harmful but less regulated and more accessible to underage youth than vaping products. Frequent discussions and comparisons of the 2 substances as it relates to their regulation emphasize the still-evolving vaping policy landscape. Social media content analyses during times of change may help regulators and policy makers to better understand and respond to common concerns and potential misconceptions surrounding drug-related policies and accessibility.

Indexed as

COVID-19Social MediaVapingAlcohol DrinkingElectronic Nicotine Delivery SystemsHumansPandemicsSARS-CoV-2United Statesalcoholalcohol useco-usee-cigarettesinsightregulationsocial mediasocial networking sitesubstance use disordertweetvapevapingvaping policyyouth

Identifiers

PMID39531640
PMCPMC11599884

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.