Evidence map›Paper›PMID 39631065›Full record

Observational studyJMIR formative research2024

Public Perceptions of Very Low Nicotine Content on Twitter: Observational Study.

Zidian Xie, Xinyi Liu, Xubin Lou, Dongmei Li

Abstract readObservational Study
In one paragraph

Observational study in JMIR formative research, 2024. 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

4 authors.

Zidian XieDepartment of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, United States.ORCID 0000-0002-5149-7710
Xinyi LiuGoergen Institute for Data Science, University of Rochester, Rochester, NY, United States.ORCID 0009-0004-5974-7990
Xubin LouGoergen Institute for Data Science, University of Rochester, Rochester, NY, United States.ORCID 0009-0009-6227-3913
Dongmei LiDepartment of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, United States.ORCID 0000-0001-9140-2483

Funding

Vaporized Nicotine Product Initiation Among Youth in the US, Canada, and England: Methods to Predict Uptake and Policy EfficacyP01CA200512 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI FONG, GEOFFREY T · 2016 to 2025
$25.3M
WNY Center for Research on Flavored Tobacco Products (CRoFT)U54CA228110 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI GONIEWICZ, MACIEJ LUKASZ · 2018 to 2022
$19.8M
Artificial Intelligence for effective communication to promote vaping cessation on social mediaR01CA285482 · NCI · UNIVERSITY OF ROCHESTER · PI Dongmei Li · 2024 to 2026
$1.7M
NCI NIH HHS P01 CA200512NCI NIH HHS R01 CA285482NCI NIH HHS U54 CA228110
6 · The paper itself

Abstract

backgroundNicotine is a highly addictive agent in tobacco products. On June 21, 2022, the US Food and Drug Administration (FDA) announced a plan to propose a rule to establish a maximum nicotine level in cigarettes and other combusted tobacco products.

objectiveThis study aimed to understand public perception and discussion of very low nicotine content (VLNC) on Twitter (rebranded as X in July 2023).

methodsFrom December 12, 2021, to January 1, 2023, we collected Twitter data using relevant keywords such as "vln," "low nicotine," and "reduced nicotine." After a series of preprocessing steps (such as removing duplicates, retweets, and commercial tweets), we identified 3270 unique noncommercial tweets related to VLNC. We used an inductive method to assess the public perception and discussion of VLNC on Twitter. To establish a codebook, we randomly selected 300 tweets for hand-coding, including the attitudes (positive, neutral, and negative) toward VLNC (including its proposed rule) and major topics (13 topics). The Cohen κ statistic between the 2 human coders reached over 70%, indicating a substantial interrater agreement. The rest of the tweets were single-coded according to the codebook.

resultsWe observed a significant peak in the discussion of VLNC on Twitter within 4 days of the FDA's announcement of the proposed rule on June 21, 2022. The proportion of tweets with a negative attitude toward VLNC was significantly lower than those with a positive attitude, 24.5% (801/3270) versus 37.09% (1213/3270) with P<.001 from the 2-proportion z test. Among tweets with a positive attitude, the topic "Reduce cigarette consumption or help smoking cessation" was dominant (1097/1213, 90.44%). Among tweets with a negative attitude, the topic "VLNC leads to more smoking" was the most popular topic (227/801, 28.34%), followed by "Similar toxicity of VLNC as a regular cigarette" (223/801, 27.84%), and "VLNC is not a good method for quitting smoking" (211/801, 26.34%).

conclusionsThere is a more positive attitude toward VLNC than a negative attitude on Twitter, resulting from different opinions about VLNC. Discussions around VLNC mainly focused on whether VLNC could help people quit smoking.

Indexed as

NicotinePublic OpinionSocial MediaHumansTobacco ProductsUnited StatesUnited States Food and Drug AdministrationNicotinecontent analysisobservational studypublic perceptionTwittervery low nicotine

Identifiers

PMID39631065
PMCPMC11656502

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Registered trials

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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.