Evidence map›Paper›PMID 38695345›Full record

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

Quantifying Cigarette and e-Cigarette Marketing Exposure Among Chinese Adolescents Using Ecological Momentary Assessment.

Lauren Czaplicki, Hannah E Barker, Johannes Thrul, Yuxian Cui, Tingzhong Yang, Joanna E Cohen

Open access · hybridAbstract read
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
1.3field-weighted citation impact, top 20% of its field
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, 4 citations in OpenAlex.

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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 at 2 institutions in 3 countries.

Lauren CzaplickiDepartment of Health, Behavior and Society, Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-7496-0990
Hannah E BarkerDepartment of Health, Behavior and Society, Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-0405-2209
Johannes ThrulDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-8929-9579
Yuxian CuiDepartment of Health, Behavior and Society, Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Tingzhong YangCenter for Tobacco Control Research/Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID 0000-0001-8234-0938
Joanna E CohenDepartment of Health, Behavior and Society, Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-3869-3637
Johns Hopkins University · USWomen's Hospital, School of Medicine, Zhejiang University · CN

Funding

Bloomberg Philanthropies
6 · The paper itself

Abstract

introductionAddressing cigarette and e-cigarette use in China is key to reducing the global tobacco epidemic. Marketing exposure is one causal factor for adolescent smoking and e-cigarette use. Currently, China restricts cigarette and e-cigarette ads in public places and online; however, there may not be full policy compliance. We collected real-time data in the natural environment to estimate how much and where Chinese adolescents-a group susceptible to smoking and e-cigarette use-are exposed to cigarette and e-cigarette marketing to inform policy responses. AIMS AND

methodsIn June 2022, we conducted a 7-day ecological momentary assessment (EMA) study with 15-16-year-olds (n = 96) across eight Chinese cities. Participants completed up to 42 EMA surveys (six per day), sent at random intervals outside of school hours. In each survey, participants reported whether they saw (1) displays and (2) ads in the past hour (none, cigarette, e-cigarette, both) in the past hour. We also captured the source of cigarette/e-cigarette ad exposure.

resultsMost participants were exposed to cigarette and/or e-cigarette displays (89.6%) or ads (79.2%) more than 7 days. On average, participants reported past-hour exposure to displays 12.7 times and past-hour exposure to ads 10.8 times over the week. The most common sources of cigarette ads were public places (eg, kiosks, supermarkets); the most common sources of e-cigarette ad exposure were social media/internet or e-cigarette stores.

conclusionsFindings highlight the need to enhance enforcement of restrictions on cigarette and e-cigarette ads in public places and online in China and extend restrictions to ban displays. IMPLICATIONS: Marketing exposure is a causal factor in youth smoking and e-cigarette use. We used EMA to estimate cigarette and e-cigarette display and ad exposure among Chinese adolescents. On average, participants reported past-hour exposure to cigarette and/or e-cigarette displays 13 times and past-hour exposure to cigarette and/or e-cigarette ads 11 times more than 1 week. Most saw ads in public places and online. Results suggest strengthening implementation of China's ban on cigarette and e-cigarette ads in public places and online and banning product displays. These are policy responses that can contribute to reducing adolescent cigarette and e-cigarette uptake in China.

Indexed as

Ecological Momentary AssessmentElectronic Nicotine Delivery SystemsMarketingAdolescentAdolescent BehaviorAdvertisingChinaCigarette SmokingFemaleHumansMaleSurveys and QuestionnairesTobacco ProductsVaping

Identifiers

PMID38695345
PMCPMC11494615
OpenAlexW4396583067

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.