Introduction
Novel digital footprint data have opened up a new era in population health and wellbeing research. A lot of information is being generated as we traverse our daily lives, touching on behaviours from financial wellbeing (e.g. banking data) to eating habits (e.g. shopping records). Forecasting of population level outcomes through such data is of increasing relevance in policy making. Whilst having a great potential, standalone digital footprint data do not contain information about health and wellbeing outcomes.
Explaining the science
Until now the use of novel ‘digital footprint’ data has mostly been limited to private companies. Companies have been using aggregates of these data to track sales of their products, to understand the factors that impact sales levels, and to target marketing and promotions. Changes in Data Protection law in the UK, i.e. General Data Protection Regulation, mean the public can now access and donate their data for academic research. For example, shopping history data, recorded through loyalty cards by retailers, are an extremely useful source of information for population health research as it can provide granular, objective data on real world choices and behaviours (e.g. painkillers, food, alcohol consumption). This information is often hard to obtain in the health research domain.
Links between lifestyle choices and health outcomes are commonly studied through self-report questionnaires that ask people to remember their everyday choices and behaviours, which can bias results: responses about behaviours do not always reflect the reality of what people actually do. If and when novel digital footprint data are used in a privacy preserving and ethical manner, these data can be utilised for public good, benefiting health research (e.g. helping to understand how everyday behaviours and lifestyle choices impact health and social outcomes). For example, what are the exact levels of alcohol consumption that lead to irreversible health damage for unborn babies accounting for moderating factors (e.g. age, gender, genetic makeup, etc.)? Under which conditions do different types of ready meals contribute to obesity? Do chemicals in household products lead to higher risks of cancer and other adverse health outcomes in children?
Aims
This interest group brings multidisciplinary and multi sector communities together to identify, explore and optimise opportunities for linking novel digital footprint data to health and wellbeing outcomes. Such linkages, whether on individual or aggregate level, facilitate insights into a variety of behaviours associated with physical and mental health, serve as a ground truth to validate patterns in the data and provide testbeds for identifying environmental exposures of risk factors for adverse health outcomes.
The Novel data linkages interest group main objective is to create a community of practice that brings together researchers in data science, artificial intelligence, social & medical sciences and other relevant disciplines from the UK and beyond to work on digital footprint linkages and research frameworks with linked data. We meet regularly, both in person and hybrid. The meetings are a mix of roundtables, research and non-academic stakeholders-led presentations and workshops. We actively identify opportunities for collaborative outputs and exchange of ideas (e.g., through workshops, joint funding proposals, papers, policy submissions or by organising a special issue in an academic journal).
This interest group is a platform for engagement between academic researchers and key non-academic stakeholders (e.g. policy-makers, industry, third sector). We promote work of early career researchers in relevant domains, provide mentorship and networking opportunities. Please get in touch with us if you are working or have interest in this area.
How to get involved
Organisers
