Evidence map›Paper›PMID 33997888›Full record

ArticleHealth education research2022

Evolution of media frames about e-cigarettes from 2004 to 2019: a content analysis of newspapers in China.

Joanne Chen Lyu, Di Wang, Zhifei Mao, Pamela M Ling

Abstract read
In one paragraph

Article in Health education research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Health Communication through Chinese Media on E-Cigarette: A Topic Modeling Approach.International journal of environmental research and public health · 2022
    Article
  5. Article
  6. 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

4 authors.

Di Wang
Zhifei Mao
Pamela M Ling

Funding

Understanding Smokeless Tobacco MarketingR01CA141661 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LING, PAMELA MAY · 2009 to 2019
$5.4M
Postdoctoral training in tobacco controlT32CA113710 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LING, PAMELA MAY · 2016 to 2020
$2.6M
NCI NIH HHS R01 CA141661NCI NIH HHS T32 CA113710
6 · The paper itself

Abstract

This study conducted a content analysis of 639 news articles about e-cigarettes in China from 2004-2019 to examine longitudinal changes in media frames and media tones about e-cigarettes in Chinese newspapers. Results indicated that policy frame was the most frequently used frame, followed by human impact frame, information frame, and uncertainty frame. Dividing the time period of 2004-2019 into four phases (i.e., 2004-2006, 2007-2010, 2011-2017 and 2018-2019), the study found that the frequency of the information frame significantly decreased over time, while the policy frame and uncertainty frame significantly increased, with the policy frame being the dominant frame in recent years. In contrast, the use of the economic frame and morality frame fluctuated, both reaching peaks in the phase of 2007-2010 and decreasing in the most recent phase. Overall, the tone of the large majority of news articles was unfavorable, and the turning point occurred in the phase of 2007-2010 when the percentage of news articles with negative tone exceeded those with positive tone for the first time. Framing of e-cigarette news articles in China demonstrated the pivotal role of policy makers in defining the e-cigarette issue, and the influence of the international public health community, as an important and reliable information source, on defining the health risk of e-cigarettes, which has implication for not only e-cigarette control, but tobacco control in China in general.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsChinaHumansMass MediaPolicyPublic Health

Identifiers

PMID33997888
PMCPMC9115326

What OpenQuestion holds

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Registered trials

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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.