Evidence map›Paper›PMID 31912873›Full record

ArticleTranslational behavioral medicine2021

Instagram's #JUUL: who's posting what.

Kar-Hai Chu, Sara J Matheny, Jaime E Sidani, Jon-Patrick Allem, Jennifer B Unger, Tess Boley Cruz

Abstract read
In one paragraph

Article in Translational behavioral medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Instagram Memes of Oral Nicotine Pouches: Content Analysis Study.Online journal of public health informatics · 2026
    Article
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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

6 authors.

Kar-Hai ChuCenter for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, USA.
Sara J MathenyCenter for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, USA.
Jaime E SidaniCenter for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, USA.
Jon-Patrick AllemKeck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Jennifer B UngerKeck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Tess Boley CruzKeck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Funding

USC Tobacco Center of Regulatory ScienceU54CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Jennifer Beth Unger · 2018 to 2026
$39.0M
USC Tobacco Center of Regulatory Science (TCORS) for Vulnerable PopulationsP50CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PENTZ, MARY ANN, SAMET, JONATHAN M · 2013 to 2017
$20.1M
Leveraging mobile applications to maximize tobacco cessationK07CA222338 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHU, KAR-HAI · 2018 to 2021
$585k
NCI NIH HHS K07 CA222338NCI NIH HHS P50 CA180905NCI NIH HHS U54 CA180905
6 · The paper itself

Abstract

Exposure to e-cigarette (e-cig) marketing through traditional and online media can increase the risk of e-cig use among adolescents. Though popular e-cig brand JUUL has scaled back its social media promotions, outside vendors and individual users create posts about JUUL unregulated. Instagram's image-focus offers an opportunity to document promotions that may appeal to adolescents. To assess the visual representation of JUUL on social media, we systematically classified discussion topics and themes of posts to Instagram. Of 25,428 unique Instagram images using the hashtag #JUUL retrieved between June 18 and July 18, 2018, a random subsample of 3,000 images (approximately 12% of the full data set) was drawn for human coding and analyses. Coded categories included relevance to JUUL, type of image, image appeal, and user type. Based on the number of relevant images, percentages of image type and appeal for each user type were calculated. There were 583 images that were coded as relevant. The majority of image types (64%) were classified as product (n =; 374). The most frequently coded type of appeal was flavors, found in 54% of images with appeal (n =; 149), followed by cartoons, found in 21% (n =; 57). Vendors were responsible for posting most of the images (n =; 291), followed by e-cig enthusiasts (n =; 99). Continued surveillance of e-cig products, such as JUUL, remains necessary to provide a foundation for potential regulatory protections against marketing and promotions that may appeal to youth.

Indexed as

Electronic Nicotine Delivery SystemsSocial MediaTobacco ProductsVapingAdolescentHumansMarketingE-cigaretteInstagramJUULNicotineSocial media

Identifiers

PMID31912873
PMCPMC7877305

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.