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Knowledge translation within a population health study: how do you do it?
BACKGROUND: Despite the considerable and growing body of knowledge translation (KT) literature, there are few methodologies sufficiently detailed to guide an integrated KT research approach for a population health study. This paper argues for a clearly articulated collaborative KT approach to be emb...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3674953/ https://www.ncbi.nlm.nih.gov/pubmed/23694753 http://dx.doi.org/10.1186/1748-5908-8-54 |
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author | Kitson, Alison Powell, Kathryn Hoon, Elizabeth Newbury, Jonathan Wilson, Anne Beilby, Justin |
author_facet | Kitson, Alison Powell, Kathryn Hoon, Elizabeth Newbury, Jonathan Wilson, Anne Beilby, Justin |
author_sort | Kitson, Alison |
collection | PubMed |
description | BACKGROUND: Despite the considerable and growing body of knowledge translation (KT) literature, there are few methodologies sufficiently detailed to guide an integrated KT research approach for a population health study. This paper argues for a clearly articulated collaborative KT approach to be embedded within the research design from the outset. DISCUSSION: Population health studies are complex in their own right, and strategies to engage the local community in adopting new interventions are often fraught with considerable challenges. In order to maximise the impact of population health research, more explicit KT strategies need to be developed from the outset. We present four propositions, arising from our work in developing a KT framework for a population health study. These cover the need for an explicit theory-informed conceptual framework; formalizing collaborative approaches within the design; making explicit the roles of both the stakeholders and the researchers; and clarifying what counts as evidence. From our deliberations on these propositions, our own co-creating (co-KT) Framework emerged in which KT is defined as both a theoretical and practical framework for actioning the intent of researchers and communities to co-create, refine, implement and evaluate the impact of new knowledge that is sensitive to the context (values, norms and tacit knowledge) where it is generated and used. The co-KT Framework has five steps. These include initial contact and framing the issue; refining and testing knowledge; interpreting, contextualising and adapting knowledge to the local context; implementing and evaluating; and finally, the embedding and translating of new knowledge into practice. SUMMARY: Although descriptions of how to incorporate KT into research designs are increasing, current theoretical and operational frameworks do not generally span a holistic process from knowledge co-creation to knowledge application and implementation within one project. Population health studies may have greater health impact when KT is incorporated early and explicitly into the research design. This, we argue, will require that particular attention be paid to collaborative approaches, stakeholder identification and engagement, the nature and sources of evidence used, and the role of the research team working with the local study community. |
format | Online Article Text |
id | pubmed-3674953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36749532013-06-07 Knowledge translation within a population health study: how do you do it? Kitson, Alison Powell, Kathryn Hoon, Elizabeth Newbury, Jonathan Wilson, Anne Beilby, Justin Implement Sci Debate BACKGROUND: Despite the considerable and growing body of knowledge translation (KT) literature, there are few methodologies sufficiently detailed to guide an integrated KT research approach for a population health study. This paper argues for a clearly articulated collaborative KT approach to be embedded within the research design from the outset. DISCUSSION: Population health studies are complex in their own right, and strategies to engage the local community in adopting new interventions are often fraught with considerable challenges. In order to maximise the impact of population health research, more explicit KT strategies need to be developed from the outset. We present four propositions, arising from our work in developing a KT framework for a population health study. These cover the need for an explicit theory-informed conceptual framework; formalizing collaborative approaches within the design; making explicit the roles of both the stakeholders and the researchers; and clarifying what counts as evidence. From our deliberations on these propositions, our own co-creating (co-KT) Framework emerged in which KT is defined as both a theoretical and practical framework for actioning the intent of researchers and communities to co-create, refine, implement and evaluate the impact of new knowledge that is sensitive to the context (values, norms and tacit knowledge) where it is generated and used. The co-KT Framework has five steps. These include initial contact and framing the issue; refining and testing knowledge; interpreting, contextualising and adapting knowledge to the local context; implementing and evaluating; and finally, the embedding and translating of new knowledge into practice. SUMMARY: Although descriptions of how to incorporate KT into research designs are increasing, current theoretical and operational frameworks do not generally span a holistic process from knowledge co-creation to knowledge application and implementation within one project. Population health studies may have greater health impact when KT is incorporated early and explicitly into the research design. This, we argue, will require that particular attention be paid to collaborative approaches, stakeholder identification and engagement, the nature and sources of evidence used, and the role of the research team working with the local study community. BioMed Central 2013-05-21 /pmc/articles/PMC3674953/ /pubmed/23694753 http://dx.doi.org/10.1186/1748-5908-8-54 Text en Copyright © 2013 Kitson et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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 cited. |
spellingShingle | Debate Kitson, Alison Powell, Kathryn Hoon, Elizabeth Newbury, Jonathan Wilson, Anne Beilby, Justin Knowledge translation within a population health study: how do you do it? |
title | Knowledge translation within a population health study: how do you do it? |
title_full | Knowledge translation within a population health study: how do you do it? |
title_fullStr | Knowledge translation within a population health study: how do you do it? |
title_full_unstemmed | Knowledge translation within a population health study: how do you do it? |
title_short | Knowledge translation within a population health study: how do you do it? |
title_sort | knowledge translation within a population health study: how do you do it? |
topic | Debate |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3674953/ https://www.ncbi.nlm.nih.gov/pubmed/23694753 http://dx.doi.org/10.1186/1748-5908-8-54 |
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