Evidence map›Paper›PMID 29236531›Full record

ArticleHealth communication2019

Communication Regulatory Science: Mapping a New Field.

Seth M Noar, Joseph N Cappella, Simani Price

Abstract read
In one paragraph

Article in Health communication, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. 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

3 authors.

Seth M Noara School of Media and Journalism , University of North Carolina at Chapel Hill.
Joseph N Cappellac Annenberg School for Communication , University of Pennsylvania.
Simani Pricee Coordinating Center for Tobacco Centers of Regulatory Science , Rockville , Maryland.

Funding

Training & Education Program p294-308P50CA180907 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RIBISL, KURT M. · 2013 to 2017
$20.2M
UPENN TCORS: Tobacco Product Messaging in a Complex Communication EnvironmentP50CA179546 · NCI · UNIVERSITY OF PENNSYLVANIA · PI HORNIK, ROBERT C. · 2013 to 2017
$18.7M
NCI NIH HHS P50 CA179546NCI NIH HHS P50 CA180907
6 · The paper itself

Abstract

Communication regulatory science is an emerging field that uses validated techniques, tools, and models to inform regulatory actions that promote optimal communication outcomes and benefit the public. In the opening article to this special issue on communication and tobacco regulatory science, we 1) describe Food and Drug Administration (FDA) regulation of tobacco products in the US; 2) introduce communication regulatory science and provide examples in the tobacco regulatory science realm; and 3) describe the special issue process and final set of articles. Communication research on tobacco regulatory science is a burgeoning area of inquiry, and this work advances communication science, informs and potentially guides the FDA, and may help to withstand legal challenges brought by the tobacco industry. This research has the potential to have a major impact on the tobacco epidemic and population health by helping implement the most effective communications to prevent tobacco initiation and increase cessation. This special issue provides an example of 10 studies that exemplify tobacco regulatory science and demonstrate how the health communication field can affect regulation and benefit public health.

Indexed as

Government RegulationHealth CommunicationInterdisciplinary CommunicationUnited States Food and Drug AdministrationCommerceHumansMarketingPublic HealthTobacco IndustryUnited States

Identifiers

PMID29236531
PMCPMC6053339

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.