Exploring how to improve the involvement of Polish and South Asian communities around big data research. A qualitative study using COM-B model

• Published in: International journal of population data science 2023-01, Vol.8 (1), p.2130-2130
• Main Authors: Teodorowski, Piotr, Rodgers, Sarah E., Fleming, Kate, Tahir, Naheed, Ahmed, Saiqa, Frith, Lucy
• Format: Article
• Language: English
• Subjects: big data; ethnic minorities; Population Data Science; PPI; public involvement; qualitative
• ISSN: 2399-4908; 2399-4908
• DOI: 10.23889/ijpds.v8i1.2130

IntroductionInvolving public contributors helps researchers to ensure that public views are taken into consideration when designing and planning research, so that it is person-centred and relevant to the public. This paper will consider public involvement in big data research. Inclusion of different communities is needed to ensure everyone's voice is heard. However, there remains limited evidence on how to improve the involvement of seldom-heard communities in big data research. ObjectivesThis study aims to understand how South Asians and Polish communities in the UK can be encouraged to participate in public involvement initiatives in big data research. MethodsForty interviews were conducted with Polish (n=20) and South Asian (n=20) participants on Zoom. The participants were living in the United Kingdom and had not previously been involved as public contributors. Transcribed interviews were analysed using reflexive thematic analysis. ResultsWe identified eight themes. The 'happy to reuse data' theme sets the scene by exploring our participants' views towards big data research and under what circumstances they thought that data could be used. The remaining themes were mapped under the capability-opportunity-motivation-behaviour (COM-B) model, as developed by Michie and colleagues. This allowed us to discuss multiple factors that could influence people's willingness to become public contributors. ConclusionsOur study is the first to explore how to improve the involvement and engagement of seldom-heard communities in big data research using the COM-B model. The results have the potential to support researchers who want to identify what can influence members of the public to be involved. By using the COM-B model, it is possible to determine what measures could be implemented to better engage these communities.