Evidence map›Paper›PMID 33284120›Full record

ArticleJMIR public health and surveillance2020

Public Response to a Social Media Tobacco Prevention Campaign: Content Analysis.

Anuja Majmundar, NamQuyen Le, Meghan Bridgid Moran, Jennifer B Unger, Katja Reuter

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. Characteristics Associated with Young Adults' Intentions to Engage with Anti-Vaping Instagram Posts.International journal of environmental research and public health · 2023
    Article
  8. Article
  9. Review
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.

Anuja MajmundarDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-7785-3357
NamQuyen LeSouthern California Clinical and Translational Science Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-5054-5362
Meghan Bridgid MoranDepartment of Health, Behavior & Society, Johns Hopkins University Bloomberg School of Public Health, Balltimore, MD, United States.ORCID 0000-0001-6745-6668
Jennifer B UngerDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0001-9064-6603
Katja ReuterDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-1559-9058

Funding

Southern California Clinical and Translational Science InstituteUL1TR001855 · NCATS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Thomas A Buchanan, Michele D. Kipke · 2016 to 2026
$81.3M
USC Tobacco Center of Regulatory Science (TCORS) for Vulnerable PopulationsP50CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PENTZ, MARY ANN, SAMET, JONATHAN M · 2013 to 2017
$20.1M
NCATS NIH HHS UL1 TR001855NCI NIH HHS P50 CA180905
6 · The paper itself

Abstract

backgroundPrior research suggests that social media-based public health campaigns are often targeted by countercampaigns.

objectiveUsing reactance theory as the theoretical framework, this research characterizes the nature of public response to tobacco prevention messages disseminated via a social media-based campaign. We also examine whether agreement with the prevention messages is associated with comment tone and nature of the contribution to the overall discussion.

methodsUser comments to tobacco prevention messages, posted between April 19, 2017 and July 12, 2017, were extracted from Twitter, Facebook, and Instagram. Two coders categorized comments in terms of tone, agreement with message, nature of contribution, mentions of government agency and regulation, promotional or spam comments, and format of comment. Chi-square analyses tested associations between agreement with the message and tone of the public response and the nature of contributions to the discussions.

resultsOf the 1242 comments received (Twitter: n=1004; Facebook: n=176; Instagram: n=62), many comments used a negative tone (42.75%) and disagreed with the health messages (39.77%), while the majority made healthy contributions to the discussions (84.38%). Only 0.56% of messages mentioned government agencies, and only 0.48% of the comments were antiregulation. Comments employing a positive tone (84.13%) or making healthy contributions (69.11%) were more likely to agree with the campaign messages (P=0.01). Comments employing a negative tone (71.25%) or making toxic contributions (36.26%) generally disagreed with the messages (P=0.01).

conclusionsThe majority of user comments in response to a tobacco prevention campaign made healthy contributions. Our findings encourage the use of social media to promote dialogue about controversial health topics such as smoking. However, toxicity was characteristic of comments that disagreed with the health messages. Managing negative and toxic comments on social media is a crucial issue for social media-based tobacco prevention campaigns to consider.

Indexed as

Public OpinionChi-Square DistributionHumansSocial MediaTobacco UseFacebookhealth campaignhealth communicationInstagraminternetonlinesocial mediatobaccoTwitter

Identifiers

PMID33284120
PMCPMC7752523

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.