Large-scale data collation and use can be a double-edged sword – with potential to create huge value, but also with potential to reinforce systemic injustice.
As a commissioner on The Lancet & Financial Times Commission for Governing health futures 2030, I am excited by the thinking we’ve been doing around 'data solidarity'. This could be a model to address structural inequities in global heath data infrastructures that leave huge populations unaccounted for and without a voice. Crucially, these models aim to set a new balance between important concerns over personal privacy and the imperative for open science.
Wellcome’s vision of a world in which no one is held back by mental health problems can only be met if we find ways to harness the power of new forms of large-scale data collection, discovering what works for whom, in what contexts, and why.
Mental health research to date has too often focused on limited data sets, representing limited populations of which limited questions have been asked. For example, international longitudinal research studies suggest that most people will experience mental health problems before middle age. Few will access professional help, and will instead address or manage difficulties through a range or approaches not mediated by professionals, from religious engagement to exercise. Despite this, most research to date has focused almost exclusively on the professionally mediated experiences of a small population, from a limited demographic, who do access treatment.
In particular, mental health science data is collected predominantly in contexts that can be characterised as Western, Educated, Industrialised, Rich and Democratic (WEIRD). The lack of data infrastructure in low- and middle-income countries, combined with a lack of research funding focused on those who live outside of WEIRD contexts, mean there is less data from those populations and fewer ways to collect new data. This is a particular issue for mental health research, where considering cultural context for both understanding and intervention is vital. There is so much for us still to learn and so many new questions to be asked.
To address this, we need to structure projects so that places without established research data infrastructures can benefit, while taking into account the range of cultures in which data is being collected. Wellcome has set out to test the feasibility of developing a new form of mental health data collection across varied geographies, starting with India, South Africa, and the United Kingdom.
Through open tender in late 2020, we commissioned Sage Bionetworks and their consortium partners from Walter Sisulu University, the Indian Law Society, the University of Cambridge, the University of Oxford, and the University of Washington to test the overall feasibility and best approaches to build a new mental health databank. This consortium brings expertise that encompasses clinical psychology, psychiatry, mental health law and policy, behavioural sciences, and epidemiology.
They are running an 18-month feasibility trial to test the development of a databank that allows young people to bank information about aspects of their life (from the biological to the behavioural), illuminating what for them are the 'active ingredients' to help prevent or treat anxiety or depression.
Using both qualitative and quantitative methods, the team are gathering empirical evidence to evaluate both acceptability and preference for novel data governance structures that give real voice to those banking their data. This will allow us to build data governance systems that balance community data sharing preferences with the open science ambitions of researchers.
Key to this work is the embedding of lived experience via advisory panels. The team has established a panel of young people with lived experience in every country and a panel of researchers who can contribute to key decisions in the design of the study and databank. Shuranjeet Takhar, one of Wellcome’s lived experience consultants, has written more about this.
Drawing on Sage Bionetworks, the project has developed a new taxonomy of data governance models to test. In consultation with the lived experience and researcher groups, the team have developed a methodology for trialling, testing, and evaluating these models, pulling both from quantitative data collection and a deliberative democracy exercise to ensure rich and contextualised insights. They have also scoped and started the significant task of gaining ethical and regulatory approval for carrying out the study in all four jurisdictions in which the team is operating (no mean feat).
At the end of the feasibility study, we are aiming to have a minimal viable product along with a wealth of evidence with which to evaluate whether it is feasible to create a community-led databank that enables an open science community. Such a resource has the potential to enable a diverse community of researchers to ask a more diverse set of questions of more diverse populations.
The team is aiming to start the data collection phase by June 2021. Myself and colleagues are writing regular progress updates on the Wellcome Digital blog, so keep an eye out for more updates soon.
This article was first published on Governing health futures 2030 on 23 March 2021