Evidence map›Paper›PMID 33447117›Full record

ArticleTobacco use insights2020

Predictors of E-Cigarette Initiation: Findings From the Youth and Young Adult Panel Study.

Navitha Jayakumar, Shawn O'Connor, Lori Diemert, Robert Schwartz

Open access · goldAbstract read
In one paragraph

Article in Tobacco use insights, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 pooled it
1.2field-weighted citation impact, top 21% 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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Sharing Antivaping Social Media Messages.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2025
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  14. Remote Versus In-Person Learning During COVID-19: Comparison of E-Cigarette Susceptibility and Ever Use Among a Diverse Cohort of 6th-Grade Students in Texas.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023
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  16. Determinants of E-Cigarette and Cigarette Use among Youth and Young Adults in Poland-PolNicoYouth Study.International journal of environmental research and public health · 2022
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  18. A machine learning approach to predict e-cigarette use and dependence among Ontario youth.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2022
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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

4 authors at 1 institution in 1 country.

Navitha JayakumarDalla Lana School of Public Health, Ontario Tobacco Research Unit, University of Toronto, Toronto, ON, Canada.
Shawn O'ConnorDalla Lana School of Public Health, Ontario Tobacco Research Unit, University of Toronto, Toronto, ON, Canada.
Lori DiemertDalla Lana School of Public Health, Ontario Tobacco Research Unit, University of Toronto, Toronto, ON, Canada.
Robert SchwartzDalla Lana School of Public Health, Ontario Tobacco Research Unit, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-7838-0769
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAlthough previous studies have identified reasons why youth try e-cigarettes, longitudinal research is needed to identify predictors of e-cigarette initiation. This study assesses predictors of e-cigarette initiation among youth and young adults in the 2018-2019 Youth and Young Adult Panel Study.

methodsThis study examined the proportion of Canadian participants aged 16 to 25 (n = 137) reporting never use of e-cigarettes at baseline in 2018. Individuals were categorized as not initiated and initiated at 12-month follow-up. We examined demographic characteristics, substance use, health status, social influences and perception by initiation category. Adjusted odds ratios (AORs) were calculated using logistic regression models and multivariable logistic regression model.

resultsAmong the 137 never e-cigarette users at baseline, 59% remained never users while 41% initiated use of e-cigarettes during the 12-month follow-up. The results of multivariable logistic regression analysis showed that regularly seeing anyone use e-cigarettes (AOR: 4.11; 95% CI: 1.04, 16.31) and seeing anyone use e-cigarettes very often or always at baseline (AOR: 4.54; 95% CI: 1.21, 17.01) is associated with initiating e-cigarette use among youth and young adults.

conclusionThe results revealed social influences to be the most important predictors of initiation among youth and young adults. Interventions to prevent youth and young adults from initiating e-cigarette use should expand from only focusing on peer use to reducing use in public space such as parks and recreational facilities.

Indexed as

adolescentse-cigarettepeer usesocial influencesVapingyoung adultsyouth

Identifiers

PMID33447117
PMCPMC7780163
OpenAlexW3113639145

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.