Peer-Reviewed Journal Details
Mandatory Fields
Russ, TC;Woelbert, E;Davis, KAS;Hafferty, JD;Ibrahim, Z;Inkster, B;John, A;Lee, W;Maxwell, M;McIntosh, AM;Stewart, R;Anderson, M;Aylett, K;Bourke, S;Burhouse, A;Callard, F;Chapman, K;Cowley, M;Cusack, J;Delgadillo, J;Dix, S;Dobson, R;Donohoe, G;Dougall, N;Downs, J;Fisher, H;Folarin, A;Foley, T;Geddes, J;Globerman, J;Hassan, L;Hayes, J;Hodges, H;Jacob, E;Jacobs, R;Joyce, C;Kaur, S;Kerz, M;Kirkbride, J;Leavey, G;Lewis, G;Lloyd, K;Matcham, W;McCloskey, E;McQuillin, A;Delgado, TN;Newsome, C;Nicodemus, K;Porteous, D;Ray, D;Sanhu, S;Smith, D;Stewart, R;Tutu, L;Ullah, A;Vance, B;Wolpert, M;Wyse, C;Zammit, S
2019
January
Nature Human Behaviour
How data science can advance mental health research
Published
Optional Fields
BIG DATA PSYCHOLOGICAL TREATMENT DEFAULT-MODE DATA LINKAGE PRIMARY-CARE DISORDERS DEPRESSION BIOBANK RISK SERVICES
3
24
32
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.
2397-3374
10.1038/s41562-018-0470-9
Grant Details
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