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Article

How data science can advance mental health research

Citation
Russ TC, Woelbert E, Davis KAS, Hafferty JD, Ibrahim Z, Inkster B, John A, Lee W, Maxwell M, McIntosh AM & Stewart R (2019) How data science can advance mental health research. Nature Human Behaviour, 3, pp. 24-32. https://doi.org/10.1038/s41562-018-0470-9

Abstract
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 article 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.

Keywords
Data science; mental health; data mining;

Notes
Additional co-authors: MQ Data Science group

Journal
Nature Human Behaviour: Volume 3

StatusPublished
Author(s)Russ, Tom C; Woelbert, Eva; Davis, Katrina A S; Hafferty, Jonathan D; Ibrahim, Zina; Inkster, Becky; John, Ann; Lee, William; Maxwell, Margaret; McIntosh, Andrew M; Stewart, Rob
FundersBiotechnology and Biological Sciences Research Council
Publication date31/12/2019
Publication date online10/12/2018
Date accepted by journal11/10/2018
URLhttp://hdl.handle.net/1893/27961
eISSN2397-3374
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