Dataset Information

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project.

ABSTRACT:

Objective

To provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research.

Summary of key points

Groups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian and Ethnic minority groups, people living with obesity, people who are socioeconomically deprived and people living in care homes. All these groups are under-served by clinical research, and there is an urgent need to rectify this if COVID-19 research is to deliver relevant evidence for these groups who are most in need. We provide a framework and checklists for addressing key issues when designing and delivering inclusive COVID-19 research, based on the National Institute for Health Research INnovations in CLinical trial design and delivery for the UnDEr-served project roadmap. Strong community engagement, codevelopment and prioritisation of research questions and interventions are essential. Under-served groups should be represented on funding panels and ethics committees, who should insist on the removal of barriers to participation. Exclusion criteria should be kept to a minimum; intervention delivery and outcome measurement should be simple, flexible and tailored to the needs of different groups, and local advice on the best way to reach and engage with under-served communities should be taken by study delivery teams. Data on characteristics that allow identification of under-served groups must be collected, analyses should include these data to enable subgroup comparisons and results should be shared with under-served groups at an early stage.

Conclusion

Inclusive COVID-19 research is a necessity, not a luxury, if research is to benefit all the communities it seeks to serve. It requires close engagement with under-served groups and attention to aspects of study topic, design, delivery, analysis and dissemination across the research life cycle.

SUBMITTER: Witham MD

PROVIDER: S-EPMC7646322 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project.

Witham Miles D MD Anderson Eleanor E Carroll Camille B CB Dark Paul M PM Down Kim K Hall Alistair S AS Knee Joanna J Maher Eamonn R ER Maier Rebecca H RH Mountain Gail A GA Nestor Gary G O'Brien John T JT Oliva Laurie L Wason James J Rochester Lynn L

BMJ open 20201105 11

<h4>Objective</h4>To provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research.<h4>Summary of key points</h4>Groups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian an ...[more]

PMID: 33154065

Similar Datasets

Project description:BackgroundRacially marginalised groups are underserved in healthcare and underrepresented in health research. Patient and public involvement and engagement (PPIE) is established as the method to ensure equity in health research. However, methods traditionally employed in PPIE can lead to the exclusion of some communities and exacerbation of existing inequalities, highlighting the need to develop inclusive processes for more inclusive community involvement in health research. We aimed to produce guidance to promote good practice for inclusive involvement of racially marginalised community groups in health research via public and community involvement and engagement.MethodsThe CHecklist for Inclusive COmmunity involvement in health research (CHICO) was co-produced by researchers and three Bristol-based community organisations: Dhek Bhal, My Friday Coffee Morning-Barton Hill, and Malcolm X Elders. After initial conversations and link building with community leaders to develop relationships, researchers attended at least three meetings with each community group to discuss preferred approaches to involvement. Each community group had a different format, and discussions were open and tailored to fit the groups preferences. The meetings were held in the community groups' usual meeting venue. Notes from meetings were reviewed by researchers to identify key themes, which were used to inform the creation of a draft illustration which was then taken back to the community groups for refinement and used to inform the development of written guidance and the final illustration.ResultsChecklist items were structured into three stages: (1) building relationships, (2) reciprocal relationships and (3) practicalities. Stage 1 highlights the importance of building trust with the community group over time through regular visits to community venues and talking to people informally to understand the history of the group, their preferences and needs, and topics that are likely to be of interest to them. Stage 2 focusses on maintaining a reciprocal relationship and understanding how to best to give back to the community. Stage 3 provides guidance on the practicalities of designing and running inclusive community-based involvement activities, including consideration of the venue, format, communication-style, language requirements, social activities, and provision of food.ConclusionsOur co-produced checklist can guide researchers in how to involve people from different ethnicities in health research that is relevant to their community.

Dataset Information

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project.

Objective

Summary of key points

Conclusion

Publications

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project.

Similar Datasets

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