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

BACKGROUND: The 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 s...

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Autores principales: Makkar, Steve R, Williamson, Anna, Turner, Tari, Redman, Sally, Louviere, Jordan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523001/
https://www.ncbi.nlm.nih.gov/pubmed/26238566
http://dx.doi.org/10.1186/s12961-015-0022-y
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author Makkar, Steve R
Williamson, Anna
Turner, Tari
Redman, Sally
Louviere, Jordan
author_facet Makkar, Steve R
Williamson, Anna
Turner, Tari
Redman, Sally
Louviere, Jordan
author_sort Makkar, Steve R
collection PubMed
description BACKGROUND: The 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. METHODS: Fifty-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. RESULTS: Utility 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. CONCLUSIONS: We 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12961-015-0022-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-45230012015-08-04 Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development Makkar, Steve R Williamson, Anna Turner, Tari Redman, Sally Louviere, Jordan Health Res Policy Syst Research BACKGROUND: The 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. METHODS: Fifty-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. RESULTS: Utility 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. CONCLUSIONS: We 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12961-015-0022-y) contains supplementary material, which is available to authorized users. BioMed Central 2015-08-04 /pmc/articles/PMC4523001/ /pubmed/26238566 http://dx.doi.org/10.1186/s12961-015-0022-y Text en © Makkar et al. 2015 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Makkar, Steve R
Williamson, Anna
Turner, Tari
Redman, Sally
Louviere, Jordan
Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title_full Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title_fullStr Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title_full_unstemmed Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title_short Using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
title_sort using conjoint analysis to develop a system of scoring policymakers’ use of research in policy and program development
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523001/
https://www.ncbi.nlm.nih.gov/pubmed/26238566
http://dx.doi.org/10.1186/s12961-015-0022-y
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