Longitudinal datasets contain information about a group of people collected repeatedly over time. Research designs that use longitudinal data allow for examination of patterns of change across time and the influence of earlier life circumstances on later outcomes. Longitudinal research can also provide insight into causal mechanisms and processes that is beyond the scope of cross-sectional studies and can be a powerful resource to accelerate mental health research.

Wellcome is interested in developing scientific understanding of how brain, body and environment interact in the trajectory of anxiety, depression and psychosis. We want to understand why and how these problems develop and resolve over time so that we can find better ways to intervene early. Longitudinal datasets are a key tool for answering these questions.

Wellcome are seeking to find the most impactful way to accelerate the development and use of longitudinal data in mental health science to ensure it collects the most relevant data, at the right level of granularity, from relevant diverse populations with sufficiently powered sample sizes. By understanding the current landscape of longitudinal datasets – in terms of both existing data and the possibility to enrich existing studies – we can identify the most powerful opportunities to understand the trajectory of mental health problems.

We considered datasets that collected data over multiple time points.

What about clinical trials? As clinical trials are not the focus of this project, we are not considering datasets with intervention and control groups at this time. Large datasets evaluating population-wide interventions with repeated assessment and without control groups are within the scope of this project.

What about repeated cross-sectional datasets? At this stage, repeated cross-sectional datasets are not within the scope of this project.

What about registries with routinely collected data? These datasets would be considered only if there is an opportunity to enrich these data with other measures that would help accelerate our understanding of anxiety, depression and psychosis.

In order to be considered in this project, there would need to be a willingness to share data beyond the data collectors.

Datasets do not need to have been run in English, but basic information should be easily translatable into English.

No, we are interested in any longitudinal dataset where adding mental health measures would help accelerate our understanding of anxiety, depression and psychosis.