Curating data to build a world-leading resource
‘Anxiety, depression and psychosis can become lifelong, debilitating conditions that hold people back from achieving their life goals and contributing to society’ – Mental Health at Wellcome
Improving our mental health is one of the defining challenges we face today. At the Open Data Institute (ODI), we are working on the ‘Landscaping International Longitudinal Datasets’ project – an exciting and impactful project working with King’s College London Institute of Psychiatry, Psychology & Neuroscience on behalf of Mental Health at Wellcome. The project is identifying the most promising longitudinal datasets for depression, anxiety and psychosis research.
Other partners are MQ Mental Health Research which will lead on organising a workshop to gather the views of various stakeholders on how we can enrich existing datasets; the Centre for Global Mental Health which will help in uncovering datasets from low- and middle-income countries; DATAMIND which will help in discovering different types of datasets; and Wellcome’s lived experience advisors who will provide feedback throughout the whole project.
Read Dr Suzi Gage (Research Lead, Metrics, Wellcome)’s thoughts on the ‘perfect’ mental health dataset: What would the perfect mental health dataset look like?
Creating a step-change in research
A longitudinal study collects data on the same people repeatedly over a period of time. This data can be extremely valuable, as it allows us to examine patterns of change across time.
This project is conducting a global search for existing longitudinal datasets to create a resource that can advance scientific understanding of how the brain, body and environment interact in influencing the course of anxiety, depression and psychosis. In the longer term, this information will help Wellcome with its ultimate aim of finding new and improved ways to predict, identify and intervene as early as possible in ways that reflect the priorities and needs of those who experience mental health problems. The collected datasets and links are listed on the project website.
‘While our knowledge about the development of mental health problems has been steadily increasing over the past few decades, this has failed to curb the rise in the number of people living with mental health problems. Undertaking research to better understand the onset, development and recurrence of disorders such as anxiety, depression and psychosis is crucial for finding rapid and efficient ways to predict, intervene and ultimately stop the harmful outcomes of mental illnesses.’
– Louise Arseneault, Professor of Developmental Psychology, King’s College London
Beyond mental health
The ODI’s mission is to work with companies and governments to build an open, trustworthy data ecosystem. As part of this, we advocate and support data sharing in ways that increase the value of data for everyone while mitigating potential harms. When data is shared across ecosystems we can unlock value beyond that of any individual dataset.
While we are identifying datasets to support mental health research, it is recognised that there are many associated factors, such as physical health, physical activity, social factors and economic circumstances where data collected could be valuable. Research studies and models made from a wider range of compatible datasets, with more up-to-date and accurate data, provide more robust insight. This is why we are identifying datasets from wider spheres beyond just mental health.
Analysing data from a wide range of sources can reveal contributory facts, associations and impacts that can be otherwise missed.
We are starting the project by undertaking a global search for promising large-scale longitudinal datasets. We are using tools that make datasets discoverable, but are also looking for contributions from the wider community.
We are especially interested in hearing from people outside academia to find out what data they find the most useful. We are examining vast amounts of public data from around the world in order to find relevant datasets that could be correlated with information about mental health, leading to insight.
The key criteria for our data search are that the datasets:
- are longitudinal (include multiple observations of the same people over a sustained period of time)
- are active (either ongoing, or planned to start in 3 years or less with funding agreed)
- are powerful (provisionally greater than 8,000 participants).
- monitor subjects at some point between the ages of 14 and 30
If you want more information about how to get involved, or if you are aware of a dataset that you think might be relevant, please get in touch.