Developing pathways for community-led research with big data: a content analysis of stakeholder interviews
Abstract Background Big data (BD) informs nearly every aspect of our lives and, in health research, is the foundation for basic discovery and its tailored translation into healthcare. Yet, as new data resources and citizen/patient-led science movements offer sites of innovation, segments of the popu...
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doaj-cb32f618a80d4912b4d0d59e2260ef8e2020-11-25T03:44:42ZengBMCHealth Research Policy and Systems1478-45052020-07-0118111210.1186/s12961-020-00589-7Developing pathways for community-led research with big data: a content analysis of stakeholder interviewsShira Grayson0Megan Doerr1Joon-Ho Yu2Sage BionetworksSage BionetworksInstitute for Public Health Genetics, University of WashingtonAbstract Background Big data (BD) informs nearly every aspect of our lives and, in health research, is the foundation for basic discovery and its tailored translation into healthcare. Yet, as new data resources and citizen/patient-led science movements offer sites of innovation, segments of the population with the lowest health status are least likely to engage in BD research either as intentional data contributors or as ‘citizen/community scientists’. Progress is being made to include a more diverse spectrum of research participants in datasets and to encourage inclusive and collaborative engagement in research through community-based participatory research approaches, citizen/patient-led research pilots and incremental research policy changes. However, additional evidence-based policies are needed at the organisational, community and national levels to strengthen capacity-building and widespread adoption of these approaches to ensure that the translation of research is effectively used to improve health and health equity. The aims of this study are to capture uses of BD (‘use cases’) from the perspectives of community leaders and to identify needs and barriers for enabling community-led BD science. Methods We conducted a qualitative content analysis of semi-structured key informant interviews with 16 community leaders. Results Based on our analysis findings, we developed a BD Engagement Model illustrating the pathways and various forces for and against community engagement in BD research. Conclusions The goal of our Model is to promote concrete, transparent dialogue between communities and researchers about barriers and facilitators of authentic community-engaged BD research. Findings from this study will inform the subsequent phases of a multi-phased project with the ultimate aims of organising fundable frameworks and identifying policy options to support BD projects within community settings.http://link.springer.com/article/10.1186/s12961-020-00589-7Big Datacommunity engagementcommunity-led researchpatient-led researchpublic healthqualitative analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shira Grayson Megan Doerr Joon-Ho Yu |
spellingShingle |
Shira Grayson Megan Doerr Joon-Ho Yu Developing pathways for community-led research with big data: a content analysis of stakeholder interviews Health Research Policy and Systems Big Data community engagement community-led research patient-led research public health qualitative analysis |
author_facet |
Shira Grayson Megan Doerr Joon-Ho Yu |
author_sort |
Shira Grayson |
title |
Developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
title_short |
Developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
title_full |
Developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
title_fullStr |
Developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
title_full_unstemmed |
Developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
title_sort |
developing pathways for community-led research with big data: a content analysis of stakeholder interviews |
publisher |
BMC |
series |
Health Research Policy and Systems |
issn |
1478-4505 |
publishDate |
2020-07-01 |
description |
Abstract Background Big data (BD) informs nearly every aspect of our lives and, in health research, is the foundation for basic discovery and its tailored translation into healthcare. Yet, as new data resources and citizen/patient-led science movements offer sites of innovation, segments of the population with the lowest health status are least likely to engage in BD research either as intentional data contributors or as ‘citizen/community scientists’. Progress is being made to include a more diverse spectrum of research participants in datasets and to encourage inclusive and collaborative engagement in research through community-based participatory research approaches, citizen/patient-led research pilots and incremental research policy changes. However, additional evidence-based policies are needed at the organisational, community and national levels to strengthen capacity-building and widespread adoption of these approaches to ensure that the translation of research is effectively used to improve health and health equity. The aims of this study are to capture uses of BD (‘use cases’) from the perspectives of community leaders and to identify needs and barriers for enabling community-led BD science. Methods We conducted a qualitative content analysis of semi-structured key informant interviews with 16 community leaders. Results Based on our analysis findings, we developed a BD Engagement Model illustrating the pathways and various forces for and against community engagement in BD research. Conclusions The goal of our Model is to promote concrete, transparent dialogue between communities and researchers about barriers and facilitators of authentic community-engaged BD research. Findings from this study will inform the subsequent phases of a multi-phased project with the ultimate aims of organising fundable frameworks and identifying policy options to support BD projects within community settings. |
topic |
Big Data community engagement community-led research patient-led research public health qualitative analysis |
url |
http://link.springer.com/article/10.1186/s12961-020-00589-7 |
work_keys_str_mv |
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