Co-producing data-intensive research with an underserved group: a case study and evaluation identifying pathways to impact

IntroductionCo-production of research, where researchers and experts by experience work as equal partners throughout a research project, can improve the quality, relevance, implementation and impact of research. However, there is limited evidence on methods for successful co-production in data-intensive research with underserved groups. In partnership with the charity Voice of Young People in Care (VOYPIC) and a group of care experienced young people, the Administrative Data Research Centre Northern Ireland (ADRC NI) piloted and evaluated a co-production approach in a research project that used linked administrative data to examine the association between care experience and mental ill health and mortality. ObjectiveThe aim of this paper is to report the impact of co-production using the pilot as a case study, and assess the mechanisms involved against published principles of co-production. Additionally, we consider if co-production in this context is a special case that warrants bespoke guidance. MethodsTwo participatory workshops and three semi-structured 1-1 interviews were conducted to collect the perspectives of pilot participants. Deductive thematic analysis was used to sort data into three predetermined categories: 1) impact; 2) barriers; and 3) enablers. To formally assess pathways to implementing co-production and achieving impact, mechanisms were mapped against the five National Institute for Health and Care Research (NIHR) principles of co-production. ResultsPositive impacts were identified for individuals, the research and organisations involved. Common barriers to co-production, like representativeness and resource constraints were identified, alongside challenges specific to data-intensive research, such as balancing power-sharing with data access constraints. Key enablers included genuine power sharing, valuing diverse knowledge, and partnership working. Special considerations needed to support successful co-production in this context include extra effort to achieve inclusion and address support needs. Partnerships with voluntary and community organisations support an inclusive, trauma-informed approach. ConclusionThis case study and evaluation can be utilised to support co-production with underserved groups in other data-intensive research contexts. Embedding co-production of data research with underserved groups will require changes to the broader research eco-system, including tailored guidance and resources, and funding partnerships rather than only pre-specified research projects.