Research undertaken at the Institute of Psychiatry, Psychology and Neuroscience at Kings College London and commissioned by Wellcome has identified 19 “pockets of value” in data for transformative mental health research, with the aim of providing a resource for researchers to identify longitudinal data that may be of use to them.
3,068 datasets from 146 countries were identified in the published report. Findings indicated that “some of the richest datasets for mental health research included strong measures of depression and anxiety, mental health data across the life course, and biological and genetic data”. In addition, the pockets of value include data from wearables and phone apps; neuroimaging data; and well-connected data with strong links to other datasets.
The report also identifies limitations to many of the datasets, such as small sample sizes, a lack of overall focus on mental health, and under-representation of low- and middle-income countries. The report highlights how existing datasets can be bettered by “improving retention of minoritised and marginalised participants, expanding existing samples, improving measurement methods and collection, improving discoverability and encouraging the involvement of lived experience experts”.
Professor Louise Arseneault, professor of developmental psychology and project leader, noted that there is “not one perfect source of data for studying mental health – instead researchers could analyse multiple datasets to increase research value. If researchers coordinate their approach to conducting longitudinal research and improve the discoverability of existing datasets, we can maximise on the huge financial, time, and resource investment that has been made in longitudinal research so far.”
In related news, we covered the launch of DATAMIND, the Health Data Research and Medical Research Council hub designed to provide expert data resources, services, tools and expertise to support mental health research and innovation, back in 2021. One of the ways DATAMIND supports mental health research is in the collection of data from “diverse sources” including health records, schools, research trials and longitudinal studies, before making it discoverable through the UK Health Data Research Innovation Gateway.
In a HTN Now webinar from December, we talked with Professor Ann John on DATAMIND and how mental health data can be harnessed. Ann talked about the importance of increasing the visibility and interoperability of datasets, citing the issues arising from a lack of standardisation in data collection and understanding what the differences are. She also noted the difficulties regarding data in “challenge areas”, such as under-served groups and children and young people, as well as in collecting data on mental health specifically, since “people with poor mental health often don’t take part in studies”.
In addition, last year we hosted a webinar on the challenges and benefits of validating data in mental health featuring Katy Lethbridge, Ideal Health’s marketing director at the time, and Basil Badi, practice director for data management. Katy emphasised how “good data management is really a golden thread that needs to run throughout transformation, in order to make it work”; whilst Basil provided insight into how data validation helps “map a patient’s journey from beginning to end”.