Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial.
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The MQ Data Science group was set up by the UK mental health research charity MQ in 2015 and includes UK-based researchers from a range of disciplines working the field of mental health data science. The authors of this article are all members of the MQ Data Science group and the article stemmed from discussions at a previous meeting of the wider group. T.C.R. is a member of the Alzheimer Scotland Dementia Research Centre funded by Alzheimer Scotland. T.C.R. and A.M.M. are both members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (G0700704/ 84698). Funding from the Biotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, and Medical Research Council is gratefully acknowledged. K.A.S.D., Z.I. and R.S. are part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. W.L. is supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South West Peninsula (NIHR CLAHRC South West Peninsula). A.M.M. has received funding from the Sackler Trust, the Wellcome Trust, and an MRC Mental Health Data Pathfinder award (MC_PC_17209). R.S. has received research funding in the last three years from Janssen, Roche and GSK. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health and Social Care, or any other funder. MQ sponsored the meetings from which this paper emerged. Other than one of the authors (E.W.) being employed by MQ, the charity had no role in the preparation of the manuscript and the final decision to publish was made by the corresponding author.
The MQ Data Science group:
Margaret Anderson16, Kate Aylett17, Suzy Bourke18, Anna Burhouse19, Felicity Callard20, Kathy Chapman21, Matt Cowley22, James Cusack23, Katrina A. S. Davis24, Jaime Delgadillo25, Sophie Dix6, Richard Dobson26, Gary Donohoe27, Nadine Dougall28, Johnny Downs26, Helen Fisher26,29, Amos Folarin8,26, Thomas Foley30, John Geddes31, Joardana Globerman22, Jonathan D. Hafferty2, Lamiece Hassan32, Joseph Hayes33, Helen Hodges34, Zina Ibrahim9, Becky Inkster11, Eddie Jacob22, Rowena Jacobs35, Ann John36, Cynthia Joyce6, Suky Kaur37, Maximilian Kerz26, James Kirkbride33, Gerard Leavey38, Glyn Lewis33, Keith Lloyd36, Wendy Matcham39, Margaret Maxwell40, Erin McCloskey6, Andrew M. McIntosh1,2, Andrew McQuillin33, Tamsin Newlove Delgado41, Catherine Newsome42, Kristin Nicodemus43, David Porteous43, Daniel Ray44, Tom C. Russ1,2,3,4,5, Simran Sanhu45, Daniel Smith46, Robert Stewart7, Laura Tutu6, Ayath Ullah47, Bill Vance32, Eva Woelbert6, Miranda Wolpert48, Cathy Wyse46 and Stanley Zammit49
The authors declare no competing interests.
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Russ, T.C., Woelbert, E., Davis, K.A.S. et al. How data science can advance mental health research. Nat Hum Behav 3, 24–32 (2019). https://doi.org/10.1038/s41562-018-0470-9
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