How data science can advance mental health research

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; MQ Data Science Group

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

Citation

Russ, T. C., Woelbert, E., Davis, K. A. S., Hafferty, J. D., Ibrahim, Z., Inkster, B., John, A., Lee, W., Maxwell, M., McIntosh, A. M., Stewart, R., & MQ Data Science Group. (2018). How data science can advance mental health research. Nature Human Behaviour, https://doi.org/10.1038/s41562-018-0470-9

• Journal Article Type: Article
• Acceptance Date: Oct 11, 2018
• Online Publication Date: Dec 10, 2018
• Publication Date: Dec 10, 2018
• Deposit Date: Dec 11, 2018
• Publicly Available Date: Jun 11, 2019
• Journal: Nature Human Behaviour
• Print ISSN: 2397-3374
• Publisher: Nature Research
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1038/s41562-018-0470-9
• Keywords: Data science, mental health, data mining ,
• Public URL: http://researchrepository.napier.ac.uk/Output/1432811
• Contract Date: Dec 13, 2018