Evidence map›Paper›PMID 25888422›Full record

ArticleTobacco control2015

Individual and interpersonal triggers to quit smoking in China: a cross-sectional analysis.

Pek Kei Im, Ann McNeill, Mary E Thompson, Geoffrey T Fong, Steve Xu, Anne C K Quah, Yuan Jiang, Lion Shahab

Open access · bronzeAbstract read
In one paragraph

Article in Tobacco control, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed, 26 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

8 authors at 5 institutions in 3 countries.

Pek Kei ImDepartment of Anthropology, University College London, London, UK Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Ann McNeillInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Mary E ThompsonDepartment of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada.
Geoffrey T FongDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada Ontario Institute for Cancer Research, Toronto, Ontario, Canada School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada.
Steve XuDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada.
Anne C K QuahDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada.
Yuan JiangNational Tobacco Control Office, Chinese Center for Disease Control and Prevention, China.
Lion ShahabDepartment of Epidemiology and Public Health, University College London, London, UK.
University of Waterloo · CAChinese Center For Disease Control and Prevention · CNKing's College London · GBUniversity College London · GBUniversity of Cambridge · GB

Funding

Variation in Cigarettes, Tobacco use Behaviors and Exposures in ITC CountriesP01CA138389 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI THOMPSON, MARY · 2009 to 2013
$13.4M
Project 3: Policy Effects on Cigarette Design, Emissions &BehaviorP50CA111236 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI CUMMINGS, KENNETH MICHAEL · 2004 to 2009
$8.2M
Tobacco Control Policy Evaluation in China and South Korea: The ITC Asia ProjectR01CA125116 · NCI · UNIVERSITY OF WATERLOO · PI FONG, GEOFFREY T · 2007 to 2011
$2.8M
CIHR 115016CIHR 57897CIHR 79551Medical Research Council MR/K023195/1NCI NIH HHS P01 CA138389NCI NIH HHS P50 CA111236NCI NIH HHS R01 CA125116
6 · The paper itself

Abstract

aimsTo determine the most prominent individual and interpersonal triggers to quit smoking in China and their associations with sociodemographic characteristics.

methodsData come from Waves 1-3 (2006-2009) of the International Tobacco Control (ITC) China Survey, analysed cross-sectionally as person-waves (N=14,358). Measures included sociodemographic and smoking characteristics. Those who quit between waves (4.3%) were asked about triggers that 'very much' led them to stop smoking, and continuing smokers about triggers that 'very much' made them think about quitting. Triggers covered individual (personal health concerns, cigarette price, smoking restrictions, advertisements, warning labels) and interpersonal factors (family/societal disapproval of smoking, setting an example to children, concerns about secondhand smoke).

resultsOver a third of respondents (34.9%) endorsed at least one trigger strongly; quitters were more likely than smokers to mention any trigger. While similar proportions of smokers endorsed individual (24.4%) and interpersonal triggers (24.0%), quitters endorsed more individual (61.1%) than interpersonal (48.3%) triggers. However, the most common triggers (personal health concerns; setting an example to children) were the same, endorsed by two-thirds of quitters and a quarter of smokers, as were the least common triggers (warning labels; cigarette price), endorsed by 1 in 10 quitters and 1 in 20 smokers. Lower dependence among smokers and greater education among all respondents were associated with endorsing any trigger.

conclusionsIndividual rather than interpersonal triggers appear more important for quitters. Major opportunities to motivate quit attempts are missed in China, particularly with regard to taxation and risk communication. Interventions need to focus on more dependent and less-educated smokers.

Indexed as

AdultChinaCommerceCross-Sectional StudiesFemaleHealth SurveysHumansMaleMiddle AgedMotivationSmokingSmoking CessationSmoking PreventionTaxesTobacco ProductsTobacco Smoke PollutionTobacco Smoke PollutionLow/Middle income countryPackaging and LabellingPricePublic policyTaxation

Identifiers

PMID25888422
PMCPMC4644698
OpenAlexW2027150369

What OpenQuestion holds

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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.