Bringing new data into mental health research
At Wellcome, we’re interested in making new data sources available for mental health research. Our goal? To unlock research that improves our understanding of anxiety, depression and psychosis.
Mental health problems are complex, and there is unlikely to be one solution or new type of data that provides a fundamental change in our understanding. More likely, a rich tapestry of information — from biological, psychological and social domains — will help us understand how brain, body and environment interact in the trajectory and resolution of anxiety, depression and psychosis.
That’s why we are looking for a supplier to help us identify promising longitudinal datasets that could be used for mental health research in different locations globally. The deadline is the 19th May and the request for proposals is available on the Wellcome website. This post explains more about why we’re doing this work.
People’s trajectories as a key part of mental health research
Longitudinal datasets are a critical resource to help researchers understand the trajectory and resolution of anxiety, depression and psychosis. We know that mental health problems are dynamic, changing over time, and we need ways to capture these changes at the right time scales to understand how mental health relates to other features of a person’s experience and environment.
This will be crucial to finding new and improved ways to predict, identify and intervene as early as possible in these conditions, in ways that reflect the priorities and needs of those who experience them.
Where might this data come from?
We’re interested in both ‘traditional’ and ‘non-traditional’ data sources that could be used for mental health research.
One traditional data source that offers potential is longitudinal population studies or LPS (which Wellcome is also looking into for climate-health research too). LPS collect a broad range of data about individuals over time, providing a powerful existing resource for mental health research. However, traditional LPS collect data much less regularly (annually) than is needed to capture the trajectories of mental health problems, and so there might be an opportunity to enhance these studies with other types of data. We’re also interested in how to help align the field of mental health research around data collection practices (read more on how we are collaborating with other funders to help harmonise the questionnaires researchers are using).
There are other data streams that can (and are) being used to understand mental health problems, which can be collected much more regularly. We also hope to identify these other, non-traditional data sources that may be held outside of academic contexts and could be used for mental health research. These could be held in commercial organisations, health services, schools, social care or academic settings. They might include data like loyalty cards, sleep data and other activity measures, all the way to microbiome data and environmental data like exposure to pollution or heat.
Health data must be effectively (and equitably) governed
A key concern for us is finding data that can support open science whilst also ensuring ethical and equitable use of data and appropriate involvement of those who are represented in it.
MindKind, a 2-year feasibility study commissioned by Wellcome, is exploring how to build a sustainable, fair databank that includes survey data as well as more passively collected data (like social media and location data). MindKind is testing out different ways for contributors to a dataset to understand and control how the data they share is used.
We must think hard about governance of the data. How can we balance the need to protect people’s privacy, ensure their broader rights are protected and that there is appropriate and considered oversight, while maximising the impact of the data resource by opening it up as much as possible? We need to build on existing work, including insights from Understanding Patient Data and the MindKind project, to put in place robust and inclusive governance frameworks that provide clarity and confidence, rather than complexity and confusion.
Different data in different settings
Wellcome’s vision is a world in which no one is held back by mental health problems, and that ambition is global. However, mental health research is currently conducted using data that overwhelmingly comes from high resource settings. Wellcome wants to change that, which is why we’re running the Mental Health Data Prize in South Africa, to support researchers in the country to use existing South African data to understand youth anxiety and depression. It’s also why our current scoping exercise will actively seek out datasets that already exist across different regions and settings — do forward this blog and the RFP to anyone you think may be interested.
These activities are part of a broader goal to improve our understanding of anxiety, depression and psychosis through integrating novel, equitably-sourced and managed data into mental health research. We’ll be doing much more to achieve this goal, so watch this space!
