How can we balance equity and empowerment with open mental health science?

Wellcome is working towards a world in which no-one is held back by mental health problems. This has never been more urgent. Mental health problems are set to become the largest burden of disease globally by 2030, but although there is an ever-growing range of treatments and prevention initiatives, there have been limited improvements in outcomes over the past few decades. We still know very little about what drives clinical impact, or the interplay between biological, psychological, and social factors in anxiety, depression, and psychosis.

We need new, more personalised interventions. But to develop them in a way that benefits everyone and not just the minority, we need to address some of the fundamental challenges that currently shape mental health research.

This post is about what these challenges are, and some of the work we are doing to start addressing them.

Balancing openness with equity

Mental health disciplines are currently highly siloed. Different disciplines use different metrics and measurements, which means findings rarely inform research in other fields. For example, cellular neuroscience rarely has crossover with clinical psychology. Accordingly, datasets tend to focus on only one area relevant to mental health outcomes, whether biological, psychological, or social.

Existing data can be very hard to access for re-use in research. Funding often isn’t available for re-analysis of existing datasets, or for the curation of data which would make access easier. In addition, we tend to treat all mental health data with the same high level of protection despite there being a spectrum of sensitivity. This can often be restrictive for the research community. Embedding sustained societal oversight into decisions about research data holds opportunities for developing a more nuanced approach to data collection and use. But that’s not as easy as it sounds to setup, especially as there’s little funding for this kind of sustained engagement.

There is a huge deficit of data representing non-WEIRD (Western, Educated, Industrialized, Rich and Democratic) populations. The intersection between biological, psychological, and social factors for mental health problems will vary significantly across different cultures and contexts. But much research relies on small datasets gathered primarily from populations already in contact with health services who come from WEIRD contexts. Inevitably, findings drawn from these data have limited global applicability.

Even when data is collected in non-WEIRD contexts the value rarely finds its way back to research participants or the local research community. Researchers outside of high-income contexts often have to contend with scarce resource and less advanced technical infrastructure, putting them at a disadvantage in effectively accessing and using the data. This commonly results in available data being “vacuumed up” by western researchers who use it to drive findings and publications that draw further resource towards themselves. This is often referred to as ‘data colonialism’.

What we are doing

Looking at these issues together shows why we need to balance openness with equity. An open science community may mean more researchers can work together, accessing more data. But without addressing the additional barriers researchers in low and middle income countries commonly face, we run the risk of making personalised interventions that only work for certain types of people.

It’s clear that to address these issues, we need to collect new data in new ways and make better use of existing data. Here are two projects Wellcome is doing to work towards this. Both encourage a more open, more collaborative approach to the use of data in mental health science. They are both operating in multiple global regions in ways that respond to the needs of different communities, and both projects are foregrounding the perspectives of people with lived experience in the way data is collected and used.

The MindKind Study: Collecting new data in new ways

The MindKind Study is a 2-year feasibility study led by Sage Bionetworks alongside a network of researchers and young people with lived experience in UK, South Africa and India.

They are testing different approaches of collecting data related to psychological, behavioural and environmental factors in ways that give various levels of agency to the people providing the data. In practice they are:

1. Building a prototype databank that collects data related to sleep, bodily movement, social connections and positive activities, and using it to test different forms of data stewardship with 4500 participants in UK, India and South Africa.
2. Running international deliberative democracy exercises to gather feedback on what data should get collected and how it should be used.
3. Co-designing the entire feasibility study with professional youth advisors and panels of lived experience advisors.

From this process we are learning:

• How to bring together different types of research data in a form that is useful to researchers.
• What technical, regulatory, ethical and cultural factors need to be accounted for to ensure data can be collected and accessed globally.
• The relative preference and acceptability of different data stewardship approaches that allow for research participants to be more involved in decisions about what data is collected and how it is used.
• How to embed the perspective of people with lived experience of mental health problems into every level of global research.

Find out more

The Wellcome Data Prize: Making better use of existing data

In early 2022 we will launch the first Wellcome Data Prize in Mental Health to improve access to data collected via cohort studies, private and third sector organisations in the UK and South Africa. This work is being led by Social Finance & DataKind UK.

The prize will incentivise and support mental health researchers and data scientists to access and analyse data to further our understanding. It is designed to:

• Make use of existing data drawing on longitudinal, NGO and private data sources
• Address impactful research questions related to ‘what works’ in preventing or treating youth anxiety and depression.
• Involve young people with lived experience in the design of the prize and all the projects funded through the prize
• Build multi-disciplinary teams with academics, data scientists and young people with lived experience
• Raise awareness of the opportunities for computational innovation in mental health
• Provide seed funding to enable the broadest possible participation.
• Ensure team leads are based in the same country as the data sources to address risks of data colonialism.

Find out more

These projects are the start of a long process of building a strong, interdisciplinary field around mental health data, and we are undertaking them with a view to learning as much as we can about effective ways of challenging old habits. We’d love to hear your ideas and feedback.