Evidence map›Paper›PMID 27471440›Full record

ArticleTobacco induced diseases2016

The influence of graphic warning labels on efficacy beliefs and risk perceptions: a qualitative study with low-income, urban smokers.

Erin L Mead, Joanna E Cohen, Caitlin E Kennedy, Joseph Gallo, Carl A Latkin

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Managing Fear Responses: A Qualitative Analysis of Pictorial Warning Labels Five Years Post-Plain Packaging.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Responses to Graphic Warning Labels among Low-income Smokers.American journal of health behavior · 2020
    Article
  9. Article
  10. Review
  11. Article
  12. 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.

Erin L MeadDepartment of Health, Behavior and Society, Johns Hopkins University, Bloomberg School of Public Health, 624 N. Broadway, Baltimore, MD 21205 U.S.A. ; Department of Behavioral and Community Health, University of Maryland School of Public Health, Tobacco Center of Regulatory Science, SPH Building (255), 4200 Valley Drive, College Park, MD 20742-2611 U.S.A.
Joanna E CohenDepartment of Health, Behavior and Society, Institute for Global Tobacco Control, Johns Hopkins University, Bloomberg School of Public Health, 2213 McElderry St., Fourth Floor, Baltimore, MD 21205 U.S.A.
Caitlin E KennedyDepartment of International Health, Johns Hopkins University, Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205 U.S.A.
Joseph GalloDepartment of Mental Health, Johns Hopkins University, Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205 U.S.A.
Carl A LatkinDepartment of Health, Behavior and Society, Johns Hopkins University, Bloomberg School of Public Health, 624 N. Broadway, Baltimore, MD 21205 U.S.A.

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Anna Palmer Durbin · 2012 to 2026
$67.0M
A comprehensive approach to secondary HIV prevention and care among positivesR01DA032217 · NIDA · JOHNS HOPKINS UNIVERSITY · PI LATKIN, CARL A · 2011 to 2015
$5.1M
NIAID NIH HHS P30 AI094189NIDA NIH HHS R01 DA032217
6 · The paper itself

Abstract

backgroundHealth communication theories indicate that messages depicting efficacy and threat might promote behavior change by enhancing individuals' efficacy beliefs and risk perceptions, but this has received little attention in graphic warning label research. We explored low socioeconomic status (SES) smokers' perceptions of theory-based graphic warning labels to inform the development of labels to promote smoking cessation.

methodsTwelve graphic warning labels were developed with self-efficacy and response efficacy messages paired with messages portraying high, low, or no threat from smoking. Self-efficacy messages were designed to promote confidence in ability to quit, while response efficacy messages were designed to promote confidence in the ability of the Quitline to aid cessation. From January - February 2014, we conducted in-depth interviews with 25 low SES adult men and women smokers in Baltimore, Maryland, U.S. Participants discussed the labels' role in their self-efficacy beliefs, response efficacy beliefs about the Quitline, and risk perceptions (including perceived severity of and susceptibility to disease). Data were analyzed through framework analysis, a type of thematic analysis.

resultsEfficacy messages in which participants vicariously experienced the characters' quit successes were reported as most influential to self-efficacy beliefs. Labels portraying a high threat were reported as most influential to participants' perceived severity of and susceptibility to smoking risks. Self-efficacy messages alone and paired with high threat were seen as most influential on self-efficacy beliefs. Labels portraying the threat from smoking were most motivational for calling the Quitline, followed by labels showing healthy role models who had successfully quit using the Quitline.

conclusionsRole model-based efficacy messages might enhance the effectiveness of labels by making smokers' self-efficacy beliefs about quitting most salient and enhancing the perceived efficacy of the Quitline. Threatening messages play an important role in enhancing risk perceptions, but findings suggest that efficacy messages are also important in the impact of labels on beliefs and motivation. Our findings could aid in the development of labels to address smoking disparities among low SES populations in the U.S.

Identifiers

PMID27471440
PMCPMC4964038

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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.