Evidence map›Paper›PMID 31709136›Full record

ArticlePreventive medicine reports2019

Use of research evidence in state health policymaking: Menu labeling policy in California.

Denise D Payán, LaVonna B Lewis

Abstract read
In one paragraph

Article in Preventive medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
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  8. Global Research on Coronaviruses: An R Package.Journal of medical Internet research · 2020
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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.

Denise D PayánDepartment of Public Health, School of Social Sciences, Humanities and Arts, University of California, Merced, Merced, CA, USA.
LaVonna B LewisSol Price School of Public Policy, University of Southern California, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Addressing the translational gap between research evidence and state health policy requires an understanding of the current use of research evidence in the state policymaking process. In this study, we explore the use of research evidence to inform the legislative debate about restaurant nutrition labeling policy in California. In 2008, California was the first state to enact a mandatory menu calorie labeling policy in the U.S. Using a qualitative approach, we examine data sources and types of evidence used in legislative documents (n = 87) related to six menu labeling bills introduced in California's state legislature between 2003 and 2008. Federal- and state-level government agency reports were the most frequently cited sources of technical knowledge. Advocacy coalition members who were active participants involved in the policy debate were also cited as experts. Five of the six bills included evidence in related legislative documents. While documents included considerable evidence on the magnitude and severity of the obesity problem to justify policy enactment, there were a limited number of statements referring to policy effectiveness and only one statement identified attesting to implementation context and acceptability. Reference to evidence on related policy suggests policy precedence may also play an important role in policy decision making. There is a need to improve the dissemination of obesity policy effectiveness and implementation studies in a politically time sensitive manner to influence state health policy debates. Strategies are discussed to effectively integrate the use of research evidence in the state health policymaking process.

Indexed as

Evidence-based health policyMenu labelingObesityQualitative researchState policy

Identifiers

PMID31709136
PMCPMC6831831

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.