Evidence map›Paper›PMID 30698815›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2020

Longitudinal Analysis of Associations Between Reasons for Electronic Cigarette Use and Change in Smoking Status Among Adults in the Population Assessment of Tobacco and Health Study.

Eric K Soule, Andrew D Plunk, Paul T Harrell, Rashelle B Hayes, Kathryn C Edwards

Abstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  12. Dual Use of Nicotine and Cannabis Through Vaping Among Adolescents.American journal of preventive medicine · 2022
    Article
  13. Substance Use Among Collegiate Athletes Versus Non-athletes.Athletic training & sports health care · 2021
    Article
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  15. Article
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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.

Eric K SouleDepartment of Health Education and Promotion, East Carolina University, Greenville, NC.
Andrew D PlunkDepartment of Pediatrics, Eastern Virginia Medical School, Norfolk, VA.
Paul T HarrellDepartment of Pediatrics, Eastern Virginia Medical School, Norfolk, VA.
Rashelle B HayesDepartment of Psychiatry, Virginia Commonwealth University, Richmond, VA.
Kathryn C EdwardsWestat, Behavioral Health Group, Rockville, MD.

Funding

Project 4: Using a prospective cohort survey to test population-level predictions generated by Projects 1-3U54DA036105 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI BRELAND, ALISON · 2018 to 2022
$20.8M
Training and Education Core p270-287P50DA036105 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI EISSENBERG, THOMAS EVAN · 2013 to 2017
$19.2M
Measure Development for Prediction of E-cigarette InitiationR03CA195124 · NCI · EASTERN VIRGINIA MEDICAL SCHOOL · PI HARRELL, PAUL TRUMAN · 2015 to 2016
$166k
NCI NIH HHS R03 CA195124NIDA NIH HHS P50 DA036105NIDA NIH HHS U54 DA036105
6 · The paper itself

Abstract

introductionElectronic cigarette (ECIG) use and changes in cigarette smoking status may be influenced by self-reported reasons for using ECIGs.

methodsWe analyzed adult current and former cigarette smokers who were also current or former ECIG users at wave 1 (n = 3044) using wave 1 and wave 2 Population Assessment of Tobacco and Health Study data (2013-2015). Prevalence of reporting 13 reasons for ECIG use at wave 1 was examined and weighted logistic regressions were conducted predicting smoking status changes from wave 1 to wave 2.

resultsReasons for ECIG use ranged from 18.1% (people in the media or public figures use them) to 82.5% (they might be less harmful to people around me than cigarettes). From wave 1 to wave 2, 27.2% of former smokers (n = 249) became current smokers and 11.6% of current smokers (n = 246) became former smokers. Among wave 1 former smokers, using ECIGs because of the availability of flavors (AOR = 0.57, 95% CI = 0.39-0.85) or because they don't smell (AOR = 0.64, 95% CI = 0.42-0.97) was associated with lower odds of relapse to smoking, but using ECIGs because using them helps people quit smoking (AOR = 1.55, 95% CI = 1.01-2.38) was associated with greater odds of relapse. Among wave 1 current smokers, using ECIGs because they can be used where smoking is not allowed (AOR = 0.56, 95% CI = 0.38-0.85) was associated with reduced odds of quitting cigarettes.

conclusionsSome reasons for ECIG use are associated with changes in self-reported smoking status. Researchers should examine ECIG user characteristics when assessing associations between ECIG use and smoking status transitions. IMPLICATIONS: Given that certain reasons for ECIG use, such as using ECIGs in locations are where smoking is not allowed, may inhibit smoking reduction, policies may be developed to prevent ECIG use in locations where smoking is banned. In addition, because certain reasons for ECIG use may aid in relapse prevention, such as availability of desired flavors, efforts should be made to identify ECIG device characteristics that are appealing to smokers but not youth or nontobacco users. These results provide support for future research on reasons for ECIG use to inform regulatory policies.

Indexed as

AdolescentAdultAgedCigarette SmokingElectronic Nicotine Delivery SystemsFemaleFlavoring AgentsHumansLongitudinal StudiesMaleMiddle AgedPrevalenceSelf ReportSmokersSmoking CessationUnited StatesFlavoring Agents

Identifiers

PMID30698815
PMCPMC7171285

What OpenQuestion holds

Textmetadata
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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.