Active Mental Health Public Health & Healthcare

International longitudinal datasets made discoverable with an interactive online platform

Funder Wellcome Charity-funded
Recipient organisation King's College London
Funding £1.3M
Period Oct 2023 — Sept 2028

In plain English

AI plain-English summary

Mental health researchers have mapped more than 3,000 longitudinal datasets from around the world—studies that track the same people over years or decades—and now plan to turn that list into a searchable online platform. The problem is that these datasets are scattered across different sectors and countries, often invisible to researchers who could use them. Without a central directory, valuable data on depression, anxiety, and psychosis goes underused. The team identified these datasets in just nine months, and the raw list already generated global enthusiasm on social media. The proposed platform would make each dataset discoverable by extracting key information: who was studied, what was measured, and how to access the data. An automated updating system would keep the platform accurate over time. The project also includes a toolkit for involving people with lived experience of mental health conditions in longitudinal research. If successful, the platform could transform how mental health scientists reuse existing data, enabling large-scale meta-analyses without new data collection. This would accelerate discovery of risk factors, treatment responses, and long-term outcomes for common mental disorders—improving research infrastructure rather than directly changing daily life.

View original technical description
Commissioned by Wellcome, we landscaped the world for longitudinal datasets with the objective of finding the most promising opportunities for transformative research on depression, anxiety and psychosis. In the space of 9 months, we identified more than 3,000 international longitudinal datasets across different sectors and with a range of different foci. The list of datasets, posted on the Landscaping project’s website, generated great enthusiasm around the world on social media. Here, we propose to convert this list into an interactive platform for increasing the discoverability of longitudinal datasets, maximising the use of already collected data and generating new knowledge based on meta-data. We plan to review all identified datasets to extract information about their discoverability, the populations they cover and the data they collected. We propose to develop an automated updating system for ensuring the accuracy and relevance of this new platform in the years to come. We aim to offer a toolkit about Lived Experience Expert (LEEs) involvement in longitudinal mental health research. We envision to disseminate the platform to wide audience and targeted stakeholders. We intend to analyse meta-data to identify strengths and gaps of longitudinal datasets for mental health research.

View the original record at the funder ↗

Researchers

Louise Arseneault (EPMC Awardee)

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Original classification

Discretionary Award

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