Evidence map›Paper›PMID 33394529›Full record

ArticleAddiction (Abingdon, England)2021

Trends in electronic cigarette use and conventional smoking: quantifying a possible 'diversion' effect among US adolescents.

Arielle S Selya, Floe Foxon

Abstract read
In one paragraph

Article in Addiction (Abingdon, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. A Decision-Theoretic Public Health Framework for Heated Tobacco and Nicotine Vaping Products.International journal of environmental research and public health · 2022
    Article
  15. Article
  16. Article
  17. Rural disparities in adolescent smoking prevalence.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2022
    Article
  18. Article
  19. Article
  20. Review
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

2 authors.

Arielle S SelyaBehavioral Sciences Group, Sanford Research, Sioux Falls, SD, USA.ORCID 0000-0001-7026-6988
Floe FoxonPinneyAssociates, Pittsburgh, PA, USA.ORCID 0000-0002-4893-9178

Funding

Transdisciplinary approaches to American Indian and rural population health researchP20GM121341 · NIGMS · SANFORD RESEARCH/USD · PI ANGAL, JYOTI · 2017 to 2022
$11.8M
NIGMS NIH HHS P20 GM121341
6 · The paper itself

Abstract

BACKGROUND AND

aimsThe impact of electronic cigarettes (ECs) on nicotine use is hotly debated: some fear that ECs are a 'catalyst' to conventional smoking, while others argue that they divert adolescents from the more harmful product. This study used simulation modeling to evaluate the plausibility of catalyst and diversion hypotheses against real-world data.

designA simulation model represented life-time exclusive EC use, exclusive conventional smoking and dual use as separate subpopulations. The 'catalyst' effect was modeled as EC use increasing dual use initiation (i.e. EC users also start smoking). The 'diversion' effect was modeled as EC use decreasing exclusive cigarette initiation. The model was calibrated using data from the US National Youth Tobacco Survey (NYTS). The plausibility of each scenario was evaluated by comparing simulated trends with NYTS data. This is the first study, to our knowledge, to estimate the magnitude of a diversion effect through simulation.

settingUnited States. PARTICIPANTS AND MEASUREMENTS: Adolescents aged 12-17 years in NYTS, a cross-sectional study from 2000 to 2019 (n = 12 500 to 31 000 per wave). Exclusive cigarette use, exclusive EC use and dual use of both products were defined using cumulative life-time criteria (100+ cigarettes smoked and/or > 100 days vaped).

findingsA null model (no catalyst or diversion) over-predicts NYTS smoking by up to 87%. Under the conservative assumption that the catalyst effect accounts for all dual use, an exponential decay constant of 19.6% EC users/year initiating smoking is required; however, this further over-predicts actual smoking by up to 109%. A diversion effect with an exponential decay constant of 55.4%/year or 65.4%/year, with the maximum possible opposing catalyst effect also active, is required optimally to match NYTS smoking trends (root mean square error = 286 632 versus 391 396 in the null model).

conclusionsA simulation model shows that a substantial diversion effect is needed to explain observed nicotine use trends among US adolescents, and it must be larger than any possible opposing catalyst effect, if present.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsVapingAdolescentCross-Sectional StudiesHumansSmokingUnited StatesAdolescentscigarettesdiversionelectronic cigarettesnicotine usesimulation modeling

Identifiers

PMID33394529
PMCPMC8172422

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.