Evidence map›Paper›PMID 41619207›Full record

ArticleHealth promotion practice2026

An Evaluation of a Youth Collaborative Approach to Addressing Nicotine and Tobacco Misinformation on Social Media.

Julia Pengyue Dou, Jaime E Sidani, Christine Larkin, Melina B Martin, Maya I Ragavan

Abstract read
In one paragraph

Article in Health promotion practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Julia Pengyue DouUniversity of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0003-1095-7167
Jaime E SidaniUniversity of Pittsburgh, Pittsburgh, PA, USA.
Christine LarkinUniversity of Pittsburgh, Pittsburgh, PA, USA.
Melina B MartinUniversity of Pittsburgh, Pittsburgh, PA, USA.
Maya I RagavanUniversity of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0003-4443-6829

Funding

Nicotine and Tobacco Misinformation on Youth-Oriented Social Media PlatformsR01MD018543 · NIMHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Jaime Elizabeth Sidani · 2022 to 2026
$3.1M
NIMHD NIH HHS R01 MD018543
6 · The paper itself

Abstract

The MYTH (Misinformation-identifying Youth in Tobacco and Health) Youth Collaborative engages adolescents (ages 13-17) as partners in addressing nicotine and tobacco product (NTP) misinformation on social media through a Youth Participatory Action Research (YPAR) approach. Recognizing youth's unique social media expertise and the growing influence of online NTP marketing, MYTH aims to build critical media literacy skills and empower youth as health advocates. This practice note evaluates participants' experience in MYTH using a mixed-methods approach, combining surveys and a focus group discussion (FGD). Surveys assessed experiences, challenges, and suggestions, analyzed descriptively; the FGD explored in-depth perspectives thematically. Lessons learned highlight the power of participatory learning to shift youth perceptions on NTP misinformation, the importance of an inclusive program environment and consistent logistics for engagement, and opportunities to integrate broader youth development. In conclusion, YPAR initiatives like MYTH offer a promising strategy to empower youth in countering health misinformation and shaping youth-centered public health interventions.

Indexed as

health communicationmedia literacymixed-methods approachNicotine and tobacco products (NTPs)process evaluationsocial media misinformationyouth engagementYouth Participatory Action Research (YPAR)

Identifiers

PMID41619207
PMCPMC13112605

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.