Please use this identifier to cite or link to this item:
Appears in Collections:Faculty of Health Sciences and Sport Journal Articles
Peer Review Status: Refereed
Title: How data science can advance mental health research
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
Contact Email:
Keywords: Data science
mental health
data mining
Issue Date: 2019
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.
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.
DOI Link: 10.1038/s41562-018-0470-9
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted for publication in Nature Human Behaviour 3, pages 24–32 (2019) published by SpringerNature:
Notes: Additional co-authors: MQ Data Science group

Files in This Item:
File Description SizeFormat 
Data science and mental health FINAL.pdfFulltext - Accepted Version458.62 kBAdobe PDFView/Open

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.