Evidence map›Paper›PMID 27299656›Full record

ArticleCancer causes & control : CCC2016

Framing research for state policymakers who place a priority on cancer.

Ross C Brownson, Elizabeth A Dodson, Jon F Kerner, Sarah Moreland-Russell

Abstract read
In one paragraph

Article in Cancer causes & control : CCC, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Ross C BrownsonDepartment of Surgery and Alvin J. Siteman Cancer Center, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO, USA. rbrownson@wustl.edu.
Elizabeth A DodsonPrevention Research Center in St. Louis, Brown School, Washington University in St. Louis, St. Louis, MO, 63130, USA.
Jon F KernerCanadian Partnership Against Cancer, Toronto, ON, Canada.
Sarah Moreland-RussellPrevention Research Center in St. Louis, Brown School, Washington University in St. Louis, St. Louis, MO, 63130, USA.

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI TIMOTHY J. EBERLEIN · 2001 to 2026
$128.0M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
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 Institute of Clinical and Translational SciencesKL2TR000450 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$8.8M
Cancer Control Dissemination Research Among State-Level Policy MakersR01CA124404 · NCI · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C · 2007 to 2011
$2.5M
Mentored Training for Dissemination and Implemention Research in CancerR25CA171994 · NCI · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C · 2013 to 2017
$1.5M
NCATS NIH HHS KL2 TR000450NCATS NIH HHS UL1 TR000448NCI NIH HHS P30 CA091842NCI NIH HHS R01 CA124404NCI NIH HHS R25 CA171994NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

purposeDespite the potential for reducing the cancer burden via state policy change, few data exist on how best to disseminate research information to influence state legislators' policy choices. We explored: (1) the relative importance of core framing issues (source, presentation, timeliness) among policymakers who prioritize cancer and those who do not prioritize cancer and (2) the predictors of use of research in policymaking.

methodsCross-sectional data were collected from US state policymakers (i.e., legislators elected to state houses or senates) from January through October 2012 (n = 862). One-way analysis of variance was performed to investigate the association of the priority of cancer variable with outcome variables. Multivariate logistic regression models examined predictors of the influence of research information.

resultsLegislators who prioritized cancer tended to rate characteristics that make research information useful higher than those who did not prioritize cancer. Among differences that were statistically significant were three items in the "source" domain (relevance, delivered by someone respected, supports one's own position), one item in the "presentation" domain (telling a story related to constituents) and two items in the "timeliness" domain (high current state priority, feasible when information is received). Participants who prioritized cancer risk factors were 80 % more likely to rate research information as one of their top reasons for choosing an issue on which to work.

conclusionsOur results suggest the importance of narrative forms of communication and that research information needs to be relevant to the policymakers' constituents in a brief, concise format.

Indexed as

Health PolicyNeoplasmsPolicy MakingResearchCross-Sectional StudiesHumansCancer controlEvidenceHealth policyPolicy makingResearch

Identifiers

PMID27299656
PMCPMC5116371

What OpenQuestion holds

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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.