Evidence map›Paper›PMID 28289369›Full record

ArticleTobacco induced diseases2017

Associations of attitudes towards electronic cigarettes with advertisement exposure and social determinants: a cross sectional study.

Benjamin Reinhold, Rebecca Fischbein, Surya Sruthi Bhamidipalli, Jennifer Bryant, Deric R Kenne

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  6. Review
  7. Article
  8. The association of adolescent e-cigarette harm perception to advertising exposure and marketing type.Archives of public health = Archives belges de sante publique · 2022
    Article
  9. Article
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  12. Knowledge about E-Cigarettes and Tobacco Harm Reduction among Public Health Residents in Europe.International journal of environmental research and public health · 2019
    Article
  13. Article
  14. E-Cigarette Marketing and Communication: How E-Cigarette Companies Market E-Cigarettes and the Public Engages with E-cigarette Information.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2019
    Review
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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

5 authors.

Benjamin ReinholdCollege of Public Health, Kent State University, 800 E. Summit St, Kent, 44240 OH USA.
Rebecca FischbeinHealth Policy and Management, College of Public Health, Kent State University, 800 E. Summit St, Kent, 44240 OH USA.
Surya Sruthi BhamidipalliCollege of Public Health, Kent State University, 800 E. Summit St, Kent, 44240 OH USA.
Jennifer BryantCollege of Public Health, Kent State University, 800 E. Summit St, Kent, 44240 OH USA.
Deric R KenneCollege of Public Health, Kent State University, 800 E. Summit St, Kent, 44240 OH USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe exposure of young adults to electronic cigarette (e-cigarette) advertisements has risen rapidly. E-cigarette ads have been shown to increase short term perceived acceptability of using e-cigarettes in places where traditional cigarettes are banned. We set out to investigate if advertising exposure was related to perceptions of harm, addictiveness, and acceptability of use of e-cigarettes in places where traditional cigarettes are banned.

methodsUsing a cross-sectional design, 6037 students at a large Midwestern university between the ages of 18-24 were surveyed about e-cigarette use and smoking status. Bivariate analyses were performed associating perception of harm, addictiveness, and acceptability of e-cigarette use in places where smoking is banned with demographic and other background factors, and e-cigarette advertising exposure through different media channels. Logistic regression analyses were used to explore the relationship of these factors on perceptions of harm, addictiveness and acceptability of e-cigarette use in places where smoking is banned.

resultsMore than a quarter (27.4%) of respondents had used an e-cigarette, greater than half (53.2%) had seen an advertisement on TV and 42.0% had seen an advertisement on the Internet. Logistic regressions revealed that being white, male, an e-cigarette user, a smoker, having a mother who smoked, and Internet advertisement exposure were associated with lower perceived harm of e-cigarettes. The same factors, plus having seen advertisements on TV, were associated with increased likelihood of perceiving e-cigarette use in bars, stores, at work and in a dorm as acceptable. Perceiving use of e-cigarettes as acceptable in classrooms was also associated with the aforementioned factors and also included race. Only being male and an e-cigarette user were associated with lower perceived addictiveness of e-cigarettes.

conclusionsE-cigarette use is increasing in adolescents and young adults, as is exposure to e-cigarette advertising. Independent of nicotine use and demographics factors, e-cigarette advertising is associated with increased beliefs in acceptability of e-cigarette use in places where cigarettes are banned. E-cigarette advertisements may be responsible for normalizing e-cigarette use. Exposure to internet e-cigarette advertisements was associated with lower perceived harm; this may be due to the false health claims often made in internet advertisements.

Indexed as

AdolescentsAdvertisingE-cigarettesElectronic CigarettesHarmNicotinePerceptionsTransitional youth

Identifiers

PMID28289369
PMCPMC5307872

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.