Evidence map›Paper›PMID 37795944›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2024

Examining the Peer-Reviewed Literature on Tobacco-Related Social Media Data: Scoping Review.

Scott I Donaldson, Allison Dormanesh, Anuja Majmundar, Cindy Pérez, Heather Lopez, Megan Saghian, Trista A Beard, Jennifer B Unger, Jon-Patrick Allem

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Spanish-Language Tobacco-Related Posts on Twitter: Content Analysis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Article
  3. Article
  4. 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

9 authors.

Scott I DonaldsonDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0001-8145-0860
Allison DormaneshDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0001-9060-7356
Anuja MajmundarTobacco Control Research, Surveillance and Health Equity Science, American Cancer Society, Inc., Kennesaw, GA, USA.ORCID 0000-0002-7785-3357
Cindy PérezDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Heather LopezDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Megan SaghianDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Trista A BeardDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0001-5543-4795
Jennifer B UngerDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Jon-Patrick AllemDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0001-9135-8689

Funding

USC Tobacco Center of Regulatory ScienceU54CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Jennifer Beth Unger · 2018 to 2026
$39.0M
California Tobacco Control Branch, Center for Healthy Communities of the California Department of Public Health U54 CA 180905National Cancer Institute and the Food and Drug Administration Center for Tobacco ProductsNCI NIH HHS U54 CA180905University of California T30IR0891
6 · The paper itself

Abstract

introductionTobacco researchers have used social media data to examine tobacco industry marketing practices (eg, influencers), and to document user experience with tobacco products. This study summarized the literature that analyzed tobacco-related social media data, including domain, social media platform, tobacco product type, and themes of findings, among other variables. AIMS AND

methodsPubMed, PsycINFO, Web of Science, and Communication Source were searched between 2004 and 2022. Peer-reviewed articles were included if they were written in English, included at least one tobacco-related term, and one social media-related term, and analyzed a social media post. Two coders screened all-titles and abstracts. The final sample consisted of (n = 255) articles. Studies were coded for domain, social media platform, tobacco product type, data source, type of data, coding and analytic method, and presence of validation procedure, among other variables.

resultsA total of 10 504 820 581 tobacco-related social media posts were assessed across 255 studies. User experience (54.1%) and promotion (23.1%) were the most researched domains. Researchers used data from Twitter the most (42.7%). Text (43.1%) was the most common type of data analyzed. Thematic analysis (80.8%) was the most common analytic technique. Themes of findings from content analyses often pertained to the health effects of tobacco use (61.0%) and promotion (44.2%).

conclusionsResearchers have analyzed billions of tobacco-related social media posts to describe user experience with, and promotions related to, tobacco products like e-cigarettes on platforms like Twitter. Future research may examine tobacco-related social media data from newer platforms like TikTok. IMPLICATIONS: Real-time surveillance of tobacco-related content on social media can keep the tobacco control community abreast of tobacco industry promotional strategies, user experience with tobacco products, and perceived health effects of tobacco use. A framework may be developed to establish best-practices for social media data collection and analysis, including strategies to identify posts from bot accounts and validate methodological approaches used in thematic analysis.

Indexed as

Electronic Nicotine Delivery SystemsSocial MediaTobacco IndustryTobacco ProductsMarketing

Identifiers

PMID37795944
PMCPMC12104493

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.