Evidence map›Paper›PMID 37651169›Full record

ArticleJMIR formative research2023

Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis.

Page D Dobbs, Allison Ames Boykin, Nnamdi Ezike, Aaron J Myers, Jason B Colditz, Brian A Primack

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Observational
  3. 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

6 authors at 3 institutions in 1 country.

Page D Dobbs *Health, Human Performance and Recreation Department, University of Arkansas, Fayetteville, AR, United States.ORCID https://orcid.org/0000-0003-1913-6488
Allison Ames Boykin *Education Statistics and Research Methods, University of Arkansas, Fayetteville, AR, United States.ORCID https://orcid.org/0000-0002-1512-9830
Nnamdi Ezike *Education Statistics and Research Methods, University of Arkansas, Fayetteville, AR, United States.ORCID https://orcid.org/0000-0001-8379-7243
Aaron J Myers *Education Statistics and Research Methods, University of Arkansas, Fayetteville, AR, United States.ORCID https://orcid.org/0000-0001-5075-3914
Jason B Colditz *Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-2811-841X
Brian A Primack *College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States.ORCID https://orcid.org/0000-0002-5962-0939
University of Arkansas at Fayetteville · USOregon State University · USUniversity of Pittsburgh · US

Funding

Leveraging Twitter to monitor nicotine and tobacco-related cancer communicationR01CA225773 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PRIMACK, BRIAN A. · 2018 to 2022
$1.9M
Loopholes, Enforcement Challenges, and Tobacco Industry Interference with Tobacco Control PoliciesK01CA267967 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI Page D. Dobbs · 2022 to 2026
$799k
NCI NIH HHS K01 CA267967NCI NIH HHS R01 CA225773
6 · The paper itself

Abstract

backgroundOn December 20, 2019, the US "Tobacco 21" law raised the minimum legal sales age of tobacco products to 21 years. Initial research suggests that misinformation about Tobacco 21 circulated via news sources on Twitter and that sentiment about the law was associated with particular types of tobacco products and included discussions about other age-related behaviors. However, underlying themes about this sentiment as well as temporal trends leading up to enactment of the law have not been explored.

objectiveThis study sought to examine (1) sentiment (pro-, anti-, and neutral policy) about Tobacco 21 on Twitter and (2) volume patterns (number of tweets) of Twitter discussions leading up to the enactment of the federal law.

methodsWe collected tweets related to Tobacco 21 posted between September 4, 2019, and December 31, 2019. A 2% subsample of tweets (4628/231,447) was annotated by 2 experienced, trained coders for policy-related information and sentiment. To do this, a codebook was developed using an inductive procedure that outlined the operational definitions and examples for the human coders to annotate sentiment (pro-, anti-, and neutral policy). Following the annotation of the data, the researchers used a thematic analysis to determine emergent themes per sentiment category. The data were then annotated again to capture frequencies of emergent themes. Concurrently, we examined trends in the volume of Tobacco 21-related tweets (weekly rhythms and total number of tweets over the time data were collected) and analyzed the qualitative discussions occurring at those peak times.

resultsThe most prevalent category of tweets related to Tobacco 21 was neutral policy (514/1113, 46.2%), followed by antipolicy (432/1113, 38.8%); 167 of 1113 (15%) were propolicy or supportive of the law. Key themes identified among neutral tweets were news reports and discussion of political figures, parties, or government involvement in general. Most discussions were generated from news sources and surfaced in the final days before enactment. Tweets opposing Tobacco 21 mentioned that the law was unfair to young audiences who were addicted to nicotine and were skeptical of the law's efficacy and importance. Methods used to evade the law were found to be represented in both neutral and antipolicy tweets. Propolicy tweets focused on the protection of youth and described the law as a sensible regulatory approach rather than a complete ban of all products or flavored products. Four spikes in daily volume were noted, 2 of which corresponded with political speeches and 2 with the preparation and passage of the legislation.

conclusionsUnderstanding themes of public sentiment-as well as when Twitter activity is most active-will help public health professionals to optimize health promotion activities to increase community readiness and respond to enforcement needs including education for retailers and the general public.

Indexed as

attitudeattitudeslawlawsmixed methodsopinionopinionspoliciespolicyregulationregulationssentimentsmokesmokersmokingsocial mediatobaccoTobacco 21tobacco policytweettweetsTwitter

Identifiers

PMID37651169
PMCPMC10502593
OpenAlexW4386306224

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.