Evidence map›Paper›PMID 26238566›Full record

ArticleHealth research policy and systems2015

Using conjoint analysis to develop a system of scoring policymakers' use of research in policy and program development.

Steve R Makkar, Anna Williamson, Tari Turner, Sally Redman, Jordan Louviere

Abstract read
In one paragraph

Article in Health research policy and systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

5 authors.

Steve R MakkarThe Sax Institute, Level 13, Building 10, 235 Jones Street, Ultimo, NSW, 2007, Australia. steve.makkar@saxinstitute.org.au.
Anna WilliamsonThe Sax Institute, Level 13, Building 10, 235 Jones Street, Ultimo, NSW, 2007, Australia. anna.williamson@saxinstitute.org.au.
Tari TurnerWorld Vision Australia, 1 Vision Drive, Burwood East, Melbourne, Victoria, 3151, Australia. tari.turner@worldvision.com.au.
Sally RedmanThe Sax Institute, Level 13, Building 10, 235 Jones Street, Ultimo, NSW, 2007, Australia. sally.redman@saxinstitute.org.au.
Jordan LouviereSchool of Marketing, University of South Australia, Level 4, Yungondi Building, North Terrace, Adelaide, South Australia, 5000, Australia. jordan.louviere@unisa.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe importance of utilising the best available research evidence in the development of health policies, services, and programs is increasingly recognised, yet few standardised systems for quantifying policymakers' research use are available. We developed a comprehensive measurement and scoring tool that assesses four domains of research use (i.e. instrumental, conceptual, tactical, and imposed). The scoring tool breaks down each domain into its key subactions like a checklist. Our aim was to develop a tool that assigned appropriate scores to each subaction based on its relative importance to undertaking evidence-informed health policymaking. In order to establish the relative importance of each research use subaction and generate this scoring system, we conducted conjoint analysis with a sample of knowledge translation experts.

methodsFifty-four experts were recruited to undertake four choice surveys. Respondents were shown combinations of research use subactions called profiles, and rated on a 1 to 9 scale whether each profile represented a limited (1-3), moderate (4-6), or extensive (7-9) example of research use. Generalised Estimating Equations were used to analyse respondents' choice data, which calculated a utility coefficient for each subaction. A large utility coefficient indicated that a subaction was particularly influential in guiding experts' ratings of extensive research use.

resultsUtility coefficients were calculated for each subaction, which became the points assigned to the subactions in the scoring system. The following subactions yielded the largest utilities and were regarded as the most important components of each research use domain: using research to directly influence the core of the policy decision; using research to inform alternative perspectives to deal with the policy issue; using research to persuade targeted stakeholders to support a predetermined decision; and using research because it was a mandated requirement by the policymaker's organisation.

conclusionsWe have generated an empirically derived and context-sensitive means of measuring and scoring the extent to which policymakers used research to inform the development of a policy document. The scoring system can be used by organisations to not only quantify the extent of their research use, but also to provide them with insights into potential strategies to improve subsequent research use.

Indexed as

Evidence-Based MedicineHealth PolicyHealth Services ResearchPolicy MakingProgram DevelopmentTranslational Research, BiomedicalAdministrative PersonnelChecklistHumans

Identifiers

PMID26238566
PMCPMC4523001

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.