Evidence map›Paper›PMID 29320344›Full record

ArticleAmerican journal of health behavior2018

A Profile of Individuals with Anti-tobacco Message Fatigue.

Jiyeon So, Lucy Popova

Abstract read
In one paragraph

Article in American journal of health behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Perceptions of Prevention and Cessation Ads among US Youth Who Use Multiple Tobacco Products: A Qualitative Study.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

2 authors.

Jiyeon SoUniversity of Georgia, Department of Communication Studies, Athens, GA, USA.
Lucy PopovaGeorgia State University, Atlanta, GA, USA.

Funding

Communicating harm of new tobacco productsR00CA187460 · NCI · GEORGIA STATE UNIVERSITY · PI POPOVA, LYUDMILA · 2016 to 2018
$738k
NCI NIH HHS R00 CA187460
6 · The paper itself

Abstract

objectivesMessage fatigue, a phenomenon of being tired of repeated exposure to messages promoting the same health behavior, may reduce the effectiveness of anti-tobacco messages, such as warning labels. As an initial step towards understanding the phenomenon, we examined predictors of anti-tobacco message fatigue.

methodsAn online study (N = 1838) involving a non-probability sample of nonsmokers and smokers in the United States assessed anti-tobacco message fatigue and individual-level factors including demographic variables and smoking status. General linear models were used to analyze the data.

resultsThe multivariable results show that individuals who were younger, male, and had higher income and education reported higher levels of anti-tobacco message fatigue. African Americans reported significantly lower levels of message fatigue than other racial groups. Current smokers reported greater message fatigue than transitioning smokers and nonsmokers. Among current smokers, those with greater nicotine dependence reported higher levels of anti-tobacco message fatigue.

conclusionsThese findings underscore the importance of segmenting the audience based on their levels of message fatigue and using more novel message strategies and delivery methods to influence populations with relatively higher levels of anti-tobacco message fatigue.

Indexed as

Product LabelingSmoking PreventionAdultFemaleHumansMaleMiddle AgedSmokersSmokingSmoking CessationUnited States

Identifiers

PMID29320344
PMCPMC5772987

What OpenQuestion holds

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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.