Research Output

How data science can advance mental health research

  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

  • Type:

    Article

  • Date:

    10 December 2018

  • Publication Status:

    Published

  • Publisher

    Springer Nature

  • DOI:

    10.1038/s41562-018-0470-9

  • Cross Ref:

    470

  • ISSN:

    2397-3374

  • Library of Congress:

    RA0421 Public health. Hygiene. Preventive Medicine

  • Dewey Decimal Classification:

    610.7 Medical education, research & nursing

  • Funders:

    Edinburgh Napier Funded

Citation

Russ, T. C., Woelbert, E., Davis, K. A. S., Hafferty, J. D., Ibrahim, Z., Inkster, B., …Data Science Group, M. (2018). How data science can advance mental health research. Nature Human Behaviour, doi:10.1038/s41562-018-0470-9

Contributors

Keywords

Data science, mental health, data mining ,

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