| Literature DB >> 30932051 |
Tom C Russ1,2,3,4,5, Eva Woelbert6, Katrina A S Davis7,8, Jonathan D Hafferty9, Zina Ibrahim10,11, Becky Inkster12, Ann John7, William Lee13,14, Margaret Maxwell15, Andrew M McIntosh16,9, Rob Stewart7,8.
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 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.Entities:
Mesh:
Year: 2018 PMID: 30932051 DOI: 10.1038/s41562-018-0470-9
Source DB: PubMed Journal: Nat Hum Behav ISSN: 2397-3374