Evidence map›Paper›PMID 37790637›Full record

ArticleAJPM focus2023

E-Cigarette-Related Health Beliefs Expressed on Twitter Within the U.S.

Ian Kim, Cynthia Begay, Harrison J Ma, Francis R Orozco, Christopher J Rogers, Thomas W Valente, Jennifer B Unger

Abstract read
In one paragraph

Article in AJPM focus, 2023. 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. Article
  2. Article
  3. Article
  4. Article
  5. Review
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

7 authors.

Ian KimKeck School of Medicine of USC, University of Southern California, Los Angeles, California.
Cynthia BegayKeck School of Medicine of USC, University of Southern California, Los Angeles, California.
Harrison J MaKeck School of Medicine of USC, University of Southern California, Los Angeles, California.
Francis R OrozcoKeck School of Medicine of USC, University of Southern California, Los Angeles, California.
Christopher J RogersCollege of Health and Human Development, California State University Northridge, Los Angeles, California.
Thomas W ValenteKeck School of Medicine of USC, University of Southern California, Los Angeles, California.
Jennifer B UngerKeck School of Medicine of USC, University of Southern California, Los Angeles, California.

Funding

USC Tobacco Center of Regulatory ScienceU54CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Jennifer Beth Unger · 2018 to 2026
$39.0M
NCI NIH HHS U54 CA180905
6 · The paper itself

Abstract

Introduction: This mixed-methods study analyzed English-language U.S.-based Twitter posts related to E-cigarette use from February 2021. Methods: Posts were manually identified as health-related or not and, if health-related, whether they were posted by an E-cigarette user. A random selection of 1,000 health-related tweets from 986 unique E-cigarette users were qualitatively content analyzed for theory of planned behavior constructs as well as nature and tone of each tweet message. Using quantitative semantic network analysis, relationships among the identified topics and sentiment-specific conversation patterns were explored. Results: The most salient health-related conversation topics of E-cigarette users, health beliefs corresponding to each theory of planned behavior construct, and major motivational contexts of E-cigarette use were identified. Seven topics emerged in positive tweets: smoking cessation, social impact generation, controls over addiction, therapeutic effects on physical and mental health, social support, device attachment, and peer influence. Nine topics emerged in negative tweets: side effects on physical health, vaping addiction, lack of E-cigarette regulations, peer pressure, increased risk of COVID-19, side effects on mental health, no help in smoking cessation, social conflict, and polysubstance use. Most assertions for E-cigarette benefits were not substantiated. Jokes in tweets appeared to contribute to the view of vaping as an attractive, enjoyable, safe, and fun activity. Discussions about positive aspects of E-cigarette use were concentrated on a few related topics, whereas tweets discouraging E-cigarette use presented a diverse, less related set of topics. Conclusions: The results provide insights into the drivers of E-cigarette use behaviors. E-cigarette user perspectives gathered from social media may inform research to guide future prevention and cessation interventions.

Indexed as

E-cigarettehealth behaviorhealth beliefsocial mediavaping

Identifiers

PMID37790637
PMCPMC10546567

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.