Evidence map›Paper›PMID 32145496›Full record

ArticleAddictive behaviors2020

Adult perceptions of the relative harm of tobacco products and subsequent tobacco product use: Longitudinal findings from waves 1 and 2 of the population assessment of tobacco and health (PATH) study.

Tara Elton-Marshall, Pete Driezen, Geoffrey T Fong, K Michael Cummings, Alexander Persoskie, Olivia Wackowski, Kelvin Choi, Annette Kaufman, David Strong, Shannon Gravely and 5 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Addictive behaviors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 3 pooled it
5.1field-weighted citation impact, top 4% 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

45 citing papers in PubMed, 3 syntheses or guidelines pooled it, 66 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Developing and Validating Measures of Absolute and Relative E-Cigarette Product Risk Perceptions: Single Items Can Be Surprisingly Comprehensive.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2022
    Pooled it
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Article
  10. Exploring the Underlying Beliefs Shaping Perceptions of E-cigarette Harm Among a Convenience Sample of Adults in the United States.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
    Article
  11. Article
  12. Observational
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  17. Toxicity of waterpipe tobacco smoking: the role of flavors, sweeteners, humectants, and charcoal.Toxicological sciences : an official journal of the Society of Toxicology · 2024
    Review
  18. Article
  19. Article
  20. 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

15 authors at 10 institutions in 2 countries.

Tara Elton-MarshallInstitute for Mental Health Policy Research, Centre for Addiction and Mental Health, London, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Ontario Tobacco Research Unit, Toronto, Ontario, Canada. Electronic address: Tara.EltonMarshall@camh.ca.
Pete DriezenDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada.
Geoffrey T FongDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada; School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada; Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
K Michael CummingsDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
Alexander PersoskieUnited States Food and Drug Administration, Center for Tobacco Products, Silver Spring, MD, USA.
Olivia WackowskiRutgers School of Public Health, Center for Tobacco Studies, Piscataway, NJ, USA.
Kelvin ChoiDivision of Intramural Research, National Institute on Minority Health and Health Disparities, Bethesda, MD, USA.
Annette KaufmanTobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD, USA.
David StrongCancer Prevention Program, Moores Cancer Center, University of California, San Diego, La Jolla, San Diego, CA, USA; Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, San Diego, CA, USA.
Shannon GravelyDepartment of Psychology, University of Waterloo, Waterloo, Ontario, Canada.
Kristie TaylorWestat, Rockville, MD, USA.
Jonathan KwanUnited States Food and Drug Administration, Center for Tobacco Products, Silver Spring, MD, USA.
Maansi Bansal-TraversDepartment of Health Behavior, Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY, USA.
Mark TraversDepartment of Health Behavior, Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY, USA.
Andrew HylandDepartment of Health Behavior, Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY, USA.
Roswell Park Comprehensive Cancer Center · USUniversity of Waterloo · CAUnited States Food and Drug Administration · USCentre for Addiction and Mental Health · CAMedical University of South Carolina · USNational Cancer Institute · USNational Institute on Minority Health and Health Disparities · USRutgers, The State University of New Jersey · USUniversity of California, San Diego · USWestat (United States) · US

Funding

Understanding and reducing tobacco-related health disparities through social and behavioral researchZIAMD000006 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI CHOI, KELVIN · 2015 to 2025
$7.0M
NIDA NIH HHS HHSN271201100027C
6 · The paper itself

Abstract

objectivesTo examine: (1) How perceptions of harm for seven non-cigarette tobacco products predict subsequent use; (2) How change in use is associated with changes in perceptions of product harm; (3) Whether sociodemographic variables moderate the association between perceptions and use.

methodsData are from the adult sample (18+) of the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative longitudinal cohort survey conducted September 2013-December 2014 (Wave 1 (W1) n = 32,320) and October 2014-October 2015 (Wave 2 (W2) n = 28,362).

resultsWave 1 users and non-users of e-cigarettes, filtered cigars, cigarillos, and pipes, who perceived these products as less harmful had greater odds of using the product at W2. For the other products, there was an interaction between W1 perceived harm and W1 use status in predicting W2 product use. At W2, a smaller percentage of U.S. adults rated e-cigarettes as less harmful than cigarettes compared to W1 (41.2% W1, 29.0% W2). Believing non-cigarette products to be less harmful than cigarettes was more strongly associated with subsequent product use in the oldest age group (55+ years) while weaker effects were observed in the youngest age group (18-24 years). This moderating effect of age was significant for e-cigarettes, hookah, traditional cigars, and cigarillos.

conclusionsStrategies to prevent initiation and promote cessation of these products may benefit from understanding and addressing perceptions of these products.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsTobacco Use DisorderAdolescentAdultHumansMiddle AgedPerceptionTobacco UseUnited StatesYoung AdultE-cigarettesHarm perceptionsTobacco products

Identifiers

PMID32145496
PMCPMC7441471
OpenAlexW3005505979

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.