Evidence map›Paper›PMID 35634272›Full record

ArticleTobacco use insights2022

The Longitudinal Impact of Seeing and Posting Tobacco-related Social Media on Tobacco Use Behaviors Among Youth (Aged 12-17): Findings From the 2014-2016 Population Assessment of Tobacco and Health (PATH) Study.

Adriana Pérez, Charles E Spells, Meagan A Bluestein, Melissa B Harrell, Emily T Hébert

Abstract read
In one paragraph

Article in Tobacco use insights, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Social Media Engagement and Quit Intentions Among Youth With Exclusive E-cigarette Use: The Moderating Role of Social Norms.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  4. Article
  5. Article
  6. Young Adults' Exposure to and Engagement With Tobacco-Related Social Media Content and Subsequent Tobacco Use.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Article
  7. Article
  8. 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

5 authors.

Adriana PérezDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston (UTHealth), School of Public Health at the Austin Campus, Austin, TX, USA.ORCID https://orcid.org/0000-0002-6859-9916
Charles E SpellsMichael & Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston (UTHealth), School of Public Health at the Austin Campus, Austin, TX, USA.ORCID https://orcid.org/0000-0003-2623-7893
Meagan A BluesteinMichael & Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston (UTHealth), School of Public Health at the Austin Campus, Austin, TX, USA.ORCID https://orcid.org/0000-0002-7320-7366
Melissa B HarrellMichael & Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston (UTHealth), School of Public Health at the Austin Campus, Austin, TX, USA.
Emily T HébertMichael & Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston (UTHealth), School of Public Health at the Austin Campus, Austin, TX, USA.

Funding

Age of Initiation of Tobacco Products among USA Youth and Young Adults: Administrative SupplementR01CA234205 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI PEREZ, ADRIANA · 2019 to 2021
$1.7M
Using Machine Learning to Develop Just-in-Time Adaptive Interventions for Smoking CessationR00DA046564 · NIDA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HEBERT, EMILY TAYLOR · 2021 to 2023
$747k
NCI NIH HHS R01 CA234205NIDA NIH HHS R00 DA046564
6 · The paper itself

Abstract

Introduction: This study examined the impact of seeing and posting tobacco-related content on social media on tobacco use outcomes in youth. Methods: Longitudinal secondary analyses of youth in the nationally representative 2014-2015 Population Assessment of Tobacco and Health (PATH) study were conducted to examine the association between the interaction of (i) seeing and (ii) posting tobacco-related social media content with previous ever use of each tobacco product, and 3 outcomes in 2015-2016: past 30-day e-cigarette use, past 30-day combustible product use, and past 30-day dual use of e-cigarettes and at least one combustible product. Six weighted multiple logistic regression models (2 interaction exposures*3 outcomes) were used to assess these associations, while adjusting for covariates. Results: Among youth never users in 2014-2015, seeing tobacco-related social media content was significantly associated with past 30-day e-cigarette use (AOR 1.92; 95% CI= 1.36-2.71), and past 30-day dual use of e-cigarettes and at least one combustible product (AOR= 2.11; 95% CI= 1.08- 4.13) in 2015-2016. Among youth ever users in 2014-2015, posting tobacco-related content on social media was significantly associated with all 3 outcomes: past 30-day day e-cigarette use (AOR= 2.09;95%CI=1.23-3.55), past 30-day combustible product use (AOR=2.86; 95%CI=1.67-4.88), and past 30-day dual use of these products (AOR=3.02;95%CI=1.45-6.31), after adjusting for covariates. Conclusions: Seeing and posting tobacco-related content on social media predicts tobacco use among youth, nationwide. Results suggest that interventions and policies prohibiting tobacco-related content on social media are needed to curb the impact of social media on youth tobacco-use.

Indexed as

adolescentscombustible productsdual usee-cigarettespast 30-day use

Identifiers

PMID35634272
PMCPMC9133874

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.