Evidence map›Paper›PMID 31079033›Full record

ArticleTobacco control2020

Measuring e-cigarette addiction among adolescents.

Erin A Vogel, Judith J Prochaska, Mark L Rubinstein

Abstract read
In one paragraph

Article in Tobacco control, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 3 pooled it
–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

60 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. What is the Addictive Potential from Vaping?Nordisk alkohol- & narkotikatidskrift : NAT · 2026
    Article
  10. Article
  11. Observational
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Influence of electronic cigarette vapour on theBiomaterial investigations in dentistry · 2025
    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

3 authors.

Erin A VogelDepartment of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0002-7193-8720
Judith J ProchaskaStanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, California, USA.
Mark L RubinsteinDivision of Adolescent Medicine, University of California, San Francisco, San Francisco, California, USA Mark.Rubinstein@ucsf.edu.

Funding

Retail Environment for Tobacco and Marijuana in California: Impact on College Student UseR01CA217165 · NCI · STANFORD UNIVERSITY · PI HENRIKSEN, LISA ANNE · 2018 to 2023
$2.7M
Adolescent ENDS Use, Nicotine Metabolism and Toxicant ExposureR21DA040718 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RUBINSTEIN, MARK L · 2016 to 2017
$436k
NCI NIH HHS R01 CA217165NIDA NIH HHS R21 DA040718
6 · The paper itself

Abstract

BACKGROUND AND

objectivesWith high rates of use and uncertain consequences, valid electronic cigarette (e-cigarette) use frequency and addiction measures for adolescents are needed. This cross-sectional study examined correlations for multiple measures of adolescent e-cigarette use with nicotine exposure quantified with salivary cotinine levels.

methodsAdolescents (N=173, age 13-18) who reported past-month e-cigarette use were recruited from the San Francisco Bay Area. Participants self-reported: (1) days of e-cigarette use in a typical month, (2) number of e-cigarette sessions in a typical day (sessions per day; SPD) and the (3) E-Cigarette Addiction Severity Index (EASI). Participants also completed the 10-item Penn State Electronic Cigarette Dependence Index (ECDI), which we examined in full and as a 2-item Heaviness of Vaping Index (HVI; the sum of the ECDI items on use frequency and time to first vaping on wakening). Sessions per month (SPM) were calculated using days per month and SPD. Cotinine levels, SPD and SPM were log-transformed.

resultsAmong frequency measures, SPM correlated most strongly with cotinine (r=0.59), followed closely by days per month (r=0.58) and SPD (r

conclusionsAdolescents' reports of frequency of e-cigarette use and degree of addiction correlated significantly with cotinine as a biomarker of nicotine exposure. We recommend the EASI and days per month as brief general measures. SPM and the ECDI are more extensive measures that may yield a more nuanced understanding of use.

Indexed as

Electronic Nicotine Delivery SystemsAdolescentBehavior, AddictiveBiomarkersCotinineCross-Sectional StudiesFemaleHumansMaleNicotineSalivaSan FranciscoSelf ReportSeverity of Illness IndexSmokingSubstance-Related DisordersBiomarkersCotinineNicotineaddictionadolescentdependencee-cigaretteENDSfrequency

Identifiers

PMID31079033
PMCPMC7738215

What OpenQuestion holds

Textmetadata
LicenceTDM
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.