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How data science can advance mental health research

Author

Listed:
  • Tom C. Russ

    (University of Edinburgh
    University of Edinburgh
    University of Edinburgh
    University of Edinburgh)

  • Eva Woelbert

    (MQ: Transforming Mental Health)

  • Katrina A. S. Davis

    (King’s College London
    South London and Maudsley NHS Foundation Trust)

  • Jonathan D. Hafferty

    (University of Edinburgh)

  • Zina Ibrahim

    (King’s College London
    University College London)

  • Becky Inkster

    (University of Cambridge)

  • Ann John

    (King’s College London)

  • William Lee

    (University of Plymouth
    Devon Partnership NHS Trust)

  • Margaret Maxwell

    (University of Stirling)

  • Andrew M. McIntosh

    (University of Edinburgh
    University of Edinburgh)

  • Rob Stewart

    (King’s College London
    South London and Maudsley NHS Foundation Trust)

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.

Suggested Citation

  • Tom C. Russ & Eva Woelbert & Katrina A. S. Davis & Jonathan D. Hafferty & Zina Ibrahim & Becky Inkster & Ann John & William Lee & Margaret Maxwell & Andrew M. McIntosh & Rob Stewart, 2019. "How data science can advance mental health research," Nature Human Behaviour, Nature, vol. 3(1), pages 24-32, January.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:1:d:10.1038_s41562-018-0470-9
    DOI: 10.1038/s41562-018-0470-9
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    Cited by:

    1. C. Potts & R. R. Bond & J-A. Jordan & M. D. Mulvenna & K. Dyer & A. Moorhead & A. Elliott, 2023. "Process mining to discover patterns in patient outcomes in a Psychological Therapies Service," Health Care Management Science, Springer, vol. 26(3), pages 461-476, September.
    2. Drydakis, Nick, 2022. "M-Health Apps and Physical and Mental Health Outcomes of Sexual Minorities," GLO Discussion Paper Series 1121, Global Labor Organization (GLO).

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