Evidence map›Paper›PMID 23616548›Full record

Trial reportThe Journal of neuroscience : the official journal of the Society for Neuroscience2013

Content matters: neuroimaging investigation of brain and behavioral impact of televised anti-tobacco public service announcements.

An-Li Wang, Kosha Ruparel, James W Loughead, Andrew A Strasser, Shira J Blady, Kevin G Lynch, Dan Romer, Joseph N Cappella, Caryn Lerman, Daniel D Langleben

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04279483 (Geo Smoking Study and Neural and Geospatial Examination of Smokers' Exposure to Retail Environments), which is not on this map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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.

NCT04279483 nacompletednot on this mapstarted 2019, after this paper: background citation

Geo Smoking Study and Neural and Geospatial Examination of Smokers' Exposure to Retail Environments

TypeinterventionalSponsorAbramson Cancer Center at Penn MedicineRan2019 to 2024Enrolled343ConditionsSmoking, Tobacco, Smoking, Smoking, CigaretteArmsTobacco retailer, Non-tobacco retailer
3 · Its place in the literature

Who cites it

48 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Brain system integration and message consistent health behavior change.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2022
    Article
  8. The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Review
  9. Article
  10. Social networks and neural receptivity to persuasive health messages.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

10 authors.

An-Li WangAnnenberg Public Policy Center, Department of Psychiatry, and Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Kosha Ruparel
James W Loughead
Andrew A Strasser
Shira J Blady
Kevin G Lynch
Dan Romer
Joseph N Cappella
Caryn Lerman
Daniel D Langleben

Funding

Brain and behavioral effects of graphic cigarette warning labelsR01DA036028 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI LANGLEBEN, DANIEL D · 2013 to 2017
$2.9M
Functional MRI of anti-tobacco public service announcementsR21DA024419 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI LANGLEBEN, DANIEL D · 2007 to 2010
$1.5M
NIDA NIH HHS R01 DA036028NIDA NIH HHS R21 DA024419
6 · The paper itself

Abstract

Televised public service announcements are video ads that are a key component of public health campaigns against smoking. Understanding the neurophysiological correlates of anti-tobacco ads is an important step toward novel objective methods of their evaluation and design. In the present study, we used functional magnetic resonance imaging (fMRI) to investigate the brain and behavioral effects of the interaction between content ("argument strength," AS) and format ("message sensation value," MSV) of anti-smoking ads in humans. Seventy-one nontreatment-seeking smokers viewed a sequence of 16 high or 16 low AS ads during an fMRI scan. Dependent variables were brain fMRI signal, the immediate recall of the ads, the immediate change in intentions to quit smoking, and the urine levels of a major nicotine metabolite cotinine at a 1 month follow-up. Whole-brain ANOVA revealed that AS and MSV interacted in the inferior frontal, inferior parietal, and fusiform gyri; the precuneus; and the dorsomedial prefrontal cortex (dMPFC). Regression analysis showed that the activation in the dMPFC predicted the urine cotinine levels 1 month later. These results characterize the key brain regions engaged in the processing of persuasive communications and suggest that brain fMRI response to anti-smoking ads could predict subsequent smoking severity in nontreatment-seeking smokers. Our findings demonstrate the importance of the quality of content for objective ad outcomes and suggest that fMRI investigation may aid the prerelease evaluation of televised public health ads.

Indexed as

TelevisionAdolescentAdultFemaleHealth PromotionHumansMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingPrefrontal CortexPsychomotor PerformanceSmokingSmoking CessationSocial BehaviorSurveys and Questionnaires

Identifiers

PMID23616548
PMCPMC3773220

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.