Evidence map›Paper›PMID 38525334›Full record

Trial reportFrontiers in public health2024

Effectively communicating with local policymakers: a randomized trial of policy brief dissemination to address obesity.

Elizabeth A Dodson, Renee G Parks, Rebekah R Jacob, Ruopeng An, Amy A Eyler, Nathan Lee, Alexandra B Morshed, Mary C Politi, Rachel G Tabak, Yan Yan and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

11 authors.

Elizabeth A DodsonPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Renee G ParksPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Rebekah R JacobPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Ruopeng AnBrown School, Washington University in St. Louis, St. Louis, MO, United States.
Amy A EylerPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Nathan LeeCivicPulse, Portland, OR, United States.
Alexandra B MorshedPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Mary C PolitiDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States.
Rachel G TabakPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Yan YanDivision of Public Health Sciences, Department of Surgery, Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States.
Ross C BrownsonPrevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States.

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI TIMOTHY J. EBERLEIN · 2001 to 2026
$128.0M
Washington University Nutrition Obesity Research CenterP30DK056341 · NIDDK · WASHINGTON UNIVERSITY · PI Dominic N Reeds · 1999 to 2026
$30.2M
Washington University Center for Diabetes Translation Research P30DK092950 · NIDDK · WASHINGTON UNIVERSITY · PI Ross C Brownson, Debra Haire-Joshu · 2011 to 2026
$11.7M
Washington University Implementation Science Center for Cancer Control (WU-ISCCC)P50CA244431 · NCI · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C, COLDITZ, GRAHAM A. · 2019 to 2023
$8.0M
The Retain Study: Recruiting and Engaging with Technology Older Adults to Increase NeurocognitionU48DP006395 · DP · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C · 2018 to 2023
$4.8M
NCCDPHP CDC HHS U48 DP006395NCI NIH HHS P30 CA091842NCI NIH HHS P50 CA244431NIDDK NIH HHS P30 DK056341NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

Introduction: Evidence-based policies are a powerful tool for impacting health and addressing obesity. Effectively communicating evidence to policymakers is critical to ensure evidence is incorporated into policies. While all public health is local, limited knowledge exists regarding effective approaches for improving local policymakers' uptake of evidence-based policies. Methods: Local policymakers were randomized to view one of four versions of a policy brief (usual care, narrative, risk-framing, and narrative/risk-framing combination). They then answered a brief survey including questions about their impressions of the brief, their likelihood of using it, and how they determine legislative priorities. Results: Responses from 331 participants indicated that a majority rated local data (92%), constituent needs/opinions (92%), and cost-effectiveness data (89%) as important or very important in determining what issues they work on. The majority of respondents agreed or strongly agreed that briefs were understandable (87%), believable (77%), and held their attention (74%) with no brief version rated significantly higher than the others. Across the four types of briefs, 42% indicated they were likely to use the brief. Logistic regression models showed that those indicating that local data were important in determining what they work on were over seven times more likely to use the policy brief than those indicating that local data were less important in determining what they work on (aOR = 7.39, 95% CI = 1.86,52.57). Discussion: Among local policymakers in this study there was no dominant format or type of policy brief; all brief types were rated similarly highly. This highlights the importance of carefully crafting clear, succinct, credible, and understandable policy briefs, using different formats depending on communication objectives. Participants indicated a strong preference for receiving materials incorporating local data. To ensure maximum effect, every effort should be made to include data relevant to a policymaker's local area in policy communications.

Indexed as

CommunicationHealth PolicyHumansObesityPublic HealthSurveys and Questionnairescommunicationdisseminationevidence-based policylocal policyobesity policy

Identifiers

PMID38525334
PMCPMC10957535

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.