Evidence map›Paper›PMID 29622781›Full record

ArticleJournal of public health policy2018

Presenting models to policymakers: intention and perception.

Elena N Naumova, Erin Hennessy

Abstract readComment
PubMed Publisher
In one paragraph

Article in Journal of public health policy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Elena N NaumovaFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Avenue, Jaharis-269F, Boston, MA, 02111, USA. elena.naumova@tufts.edu.
Erin HennessyFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Avenue, Jaharis-269F, Boston, MA, 02111, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Seifu et al. article is a start to a timely inquiry on policymakers' perceptions of mathematical modeling and simulations aimed to guide obesity prevention programs. These computational tools have the potential to transform the fields of public health policy. Yet, to be effective, a broad Data and Information Literacy Initiative is needed to instill policymakers with the willingness to become life-long learners, to adapt and accept new technologies, attitudes, information, and creative ways of thinking.

Indexed as

Pediatric ObesityBaltimoreChildHumansIntentionPolicy MakingResearchDecision makingLiteracyObesityPublic health policySimulation modeling

Identifiers

PMID29622781

What OpenQuestion holds

Textmetadata
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.