Cargando…

Predicting research use in a public health policy environment: results of a logistic regression analysis

BACKGROUND: Use of research evidence in public health policy decision-making is affected by a range of contextual factors operating at the individual, organisational and external levels. Context-specific research is needed to target and tailor research translation intervention design and implementat...

Descripción completa

Detalles Bibliográficos
Autores principales: Zardo, Pauline, Collie, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212120/
https://www.ncbi.nlm.nih.gov/pubmed/25297813
http://dx.doi.org/10.1186/s13012-014-0142-8
_version_ 1782341655098032128
author Zardo, Pauline
Collie, Alex
author_facet Zardo, Pauline
Collie, Alex
author_sort Zardo, Pauline
collection PubMed
description BACKGROUND: Use of research evidence in public health policy decision-making is affected by a range of contextual factors operating at the individual, organisational and external levels. Context-specific research is needed to target and tailor research translation intervention design and implementation to ensure that factors affecting research in a specific context are addressed. Whilst such research is increasing, there remain relatively few studies that have quantitatively assessed the factors that predict research use in specific public health policy environments. METHOD: A quantitative survey was designed and implemented within two public health policy agencies in the Australian state of Victoria. Binary logistic regression analyses were conducted on survey data provided by 372 participants. Univariate logistic regression analyses of 49 factors revealed 26 factors that significantly predicted research use independently. The 26 factors were then tested in a single model and five factors emerged as significant predictors of research over and above all other factors. RESULTS: The five key factors that significantly predicted research use were the following: relevance of research to day-to-day decision-making, skills for research use, internal prompts for use of research, intention to use research within the next 12 months and the agency for which the individual worked. CONCLUSIONS: These findings suggest that individual- and organisational-level factors are the critical factors to target in the design of interventions aiming to increase research use in this context. In particular, relevance of research and skills for research use would be necessary to target. The likelihood for research use increased 11- and 4-fold for those who rated highly on these factors. This study builds on previous research and contributes to the currently limited number of quantitative studies that examine use of research evidence in a large sample of public health policy and program decision-makers within a specific context. The survey used in this study is likely to be relevant for use in other public health policy contexts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-014-0142-8) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4212120
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-42121202014-10-30 Predicting research use in a public health policy environment: results of a logistic regression analysis Zardo, Pauline Collie, Alex Implement Sci Research BACKGROUND: Use of research evidence in public health policy decision-making is affected by a range of contextual factors operating at the individual, organisational and external levels. Context-specific research is needed to target and tailor research translation intervention design and implementation to ensure that factors affecting research in a specific context are addressed. Whilst such research is increasing, there remain relatively few studies that have quantitatively assessed the factors that predict research use in specific public health policy environments. METHOD: A quantitative survey was designed and implemented within two public health policy agencies in the Australian state of Victoria. Binary logistic regression analyses were conducted on survey data provided by 372 participants. Univariate logistic regression analyses of 49 factors revealed 26 factors that significantly predicted research use independently. The 26 factors were then tested in a single model and five factors emerged as significant predictors of research over and above all other factors. RESULTS: The five key factors that significantly predicted research use were the following: relevance of research to day-to-day decision-making, skills for research use, internal prompts for use of research, intention to use research within the next 12 months and the agency for which the individual worked. CONCLUSIONS: These findings suggest that individual- and organisational-level factors are the critical factors to target in the design of interventions aiming to increase research use in this context. In particular, relevance of research and skills for research use would be necessary to target. The likelihood for research use increased 11- and 4-fold for those who rated highly on these factors. This study builds on previous research and contributes to the currently limited number of quantitative studies that examine use of research evidence in a large sample of public health policy and program decision-makers within a specific context. The survey used in this study is likely to be relevant for use in other public health policy contexts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-014-0142-8) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-09 /pmc/articles/PMC4212120/ /pubmed/25297813 http://dx.doi.org/10.1186/s13012-014-0142-8 Text en © Zardo and Collie; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), 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
Zardo, Pauline
Collie, Alex
Predicting research use in a public health policy environment: results of a logistic regression analysis
title Predicting research use in a public health policy environment: results of a logistic regression analysis
title_full Predicting research use in a public health policy environment: results of a logistic regression analysis
title_fullStr Predicting research use in a public health policy environment: results of a logistic regression analysis
title_full_unstemmed Predicting research use in a public health policy environment: results of a logistic regression analysis
title_short Predicting research use in a public health policy environment: results of a logistic regression analysis
title_sort predicting research use in a public health policy environment: results of a logistic regression analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212120/
https://www.ncbi.nlm.nih.gov/pubmed/25297813
http://dx.doi.org/10.1186/s13012-014-0142-8
work_keys_str_mv AT zardopauline predictingresearchuseinapublichealthpolicyenvironmentresultsofalogisticregressionanalysis
AT colliealex predictingresearchuseinapublichealthpolicyenvironmentresultsofalogisticregressionanalysis