Data science for mental health: a UK perspective on a global challenge

Andrew M. McIntosh; Robert Stewart; Ann John; Daniel J. Smith; Katrina Davis; Cathie Sudlow; Aiden Corvin; Kristin K. Nicodemus; David Kingdon; Lamiece Hassan; Matthew Hotopf; Stephen M. Lawrie; Tom C. Russ; John R. Geddes; Miranda Wolpert; Eva Wölbert; David J. Porteous

doi:10.1016/S2215-0366(16)30089-X

Data science for mental health: a UK perspective on a global challenge

Andrew M. McIntosh^*
, Robert Stewart
, Ann John
, Daniel J. Smith
, Katrina Davis
, Cathie Sudlow
, Aiden Corvin
, Kristin K. Nicodemus
, David Kingdon
, Lamiece Hassan
, Matthew Hotopf
, Stephen M. Lawrie
, Tom C. Russ
, John R. Geddes
, Miranda Wolpert
, Eva Wölbert
, David J. Porteous

^*Corresponding author for this work

University of Edinburgh
Swansea University
University of Glasgow
Trinity College Dublin
University of Southampton
University of Manchester
University of Oxford
UCL University College London
MQ: Transforming Mental Health

Research output: Contribution to journal › Article › peer-review

48 Citations (Scopus)

530 Downloads (Pure)

Abstract

Data science uses computer science and statistics to extract new knowledge from high-dimensional datasets (ie, those with many different variables and data types). Mental health research, diagnosis, and treatment could benefit from data science that uses cohort studies, genomics, and routine health-care and administrative data. The UK is well placed to trial these approaches through robust NHS-linked data science projects, such as the UK Biobank, Generation Scotland, and the Clinical Record Interactive Search (CRIS) programme. Data science has great potential as a low-cost, high-return catalyst for improved mental health recognition, understanding, support, and outcomes. Lessons learnt from such studies could have global implications.

Original language	English
Pages (from-to)	993-998
Number of pages	6
Journal	The Lancet Psychiatry
Volume	3
Issue number	10
Early online date	28 Sept 2016
DOIs	https://doi.org/10.1016/S2215-0366(16)30089-X
Publication status	Published - 1 Oct 2016

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Data science for mental health_MCINTOSH_Firstonline28September2016_GREEN AAMAccepted author manuscript, 601 KBLicence: CC BY-NC-ND

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McIntosh, A. M., Stewart, R., John, A., Smith, D. J., Davis, K., Sudlow, C., Corvin, A., Nicodemus, K. K., Kingdon, D., Hassan, L., Hotopf, M., Lawrie, S. M., Russ, T. C., Geddes, J. R., Wolpert, M., Wölbert, E., & Porteous, D. J. (2016). Data science for mental health: a UK perspective on a global challenge. The Lancet Psychiatry, 3(10), 993-998. https://doi.org/10.1016/S2215-0366(16)30089-X

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title = "Data science for mental health: a UK perspective on a global challenge",

abstract = "Data science uses computer science and statistics to extract new knowledge from high-dimensional datasets (ie, those with many different variables and data types). Mental health research, diagnosis, and treatment could benefit from data science that uses cohort studies, genomics, and routine health-care and administrative data. The UK is well placed to trial these approaches through robust NHS-linked data science projects, such as the UK Biobank, Generation Scotland, and the Clinical Record Interactive Search (CRIS) programme. Data science has great potential as a low-cost, high-return catalyst for improved mental health recognition, understanding, support, and outcomes. Lessons learnt from such studies could have global implications.",

author = "McIntosh, \{Andrew M.\} and Robert Stewart and Ann John and Smith, \{Daniel J.\} and Katrina Davis and Cathie Sudlow and Aiden Corvin and Nicodemus, \{Kristin K.\} and David Kingdon and Lamiece Hassan and Matthew Hotopf and Lawrie, \{Stephen M.\} and Russ, \{Tom C.\} and Geddes, \{John R.\} and Miranda Wolpert and Eva W{\"o}lbert and Porteous, \{David J.\}",

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McIntosh, AM, Stewart, R, John, A, Smith, DJ, Davis, K, Sudlow, C, Corvin, A, Nicodemus, KK, Kingdon, D, Hassan, L, Hotopf, M, Lawrie, SM, Russ, TC, Geddes, JR, Wolpert, M, Wölbert, E & Porteous, DJ 2016, 'Data science for mental health: a UK perspective on a global challenge', The Lancet Psychiatry, vol. 3, no. 10, pp. 993-998. https://doi.org/10.1016/S2215-0366(16)30089-X

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AU - Corvin, Aiden

AU - Nicodemus, Kristin K.

AU - Kingdon, David

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AU - Hotopf, Matthew

AU - Lawrie, Stephen M.

AU - Russ, Tom C.

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AU - Wolpert, Miranda

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AU - Porteous, David J.

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Data science for mental health: a UK perspective on a global challenge

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