Edinburgh poised to make significant advances in mental health research based upon data science ‘unparalleled in UK’.

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From Andrew McIntosh Professor of Biological Psychiatry at the University of Edinburgh in DIGIT yesterday:

Our vision is to make meaningful links between ongoing research studies spanning the whole lifespan and anonymised health records to better understand the causes and consequences of mental health conditions. We hope that this will enable more effective treatments and ultimately pave the way for improving resilience to common mental health disorders. This combination of resources means Edinburgh is poised to make significant advances in mental health research based upon rapidly developing resources for data science that are unparalleled in the UK.’

Researchers at Edinburgh University are to get Medical Research Council funding of £2.2 million to develop:

‘[A] new approach using big data, an emerging area of research, to understand mental health could potentially pave the way for new and more effective treatment. Big data will be used to draw more meaningful insights from vast amounts of information pooled from several sources including anonymised health records, genetics and psychological studies. This will help to build a more nuanced and complete picture of the disease’s development and progression, which will hopefully make it more treatable.’

https://digit.fyi/funding-mental-health-research/

This announcement follows several reported here, highlighting the leading role many of Scotland’s universities are playing. See, for example:

British Ecological Society praises Scottish Government for enabling ‘a unique opportunity to closely link policy to research’

Scottish research to be used in $1.2 billion initiative to help poor Indian farmers

Scottish scientists part of breakthrough in cystic fibrosis research

Scottish Veterinary researchers working to improve the health and productivity of farmed animals in sub-Saharan Africa.

Scottish university research to help developing nations remove arsenic from water supplies

Scotland’s world-leading expertise to the fore again in India and Bangladesh

Scotland’s tidal energy expertise to help poor communities in South-East Asia

‘Unparalleled in UK’? I like the sound of that. Will BBC Scotland?

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3 thoughts on “Edinburgh poised to make significant advances in mental health research based upon data science ‘unparalleled in UK’.

  1. Alasdair Macdonald April 7, 2018 / 12:34 pm

    While I welcome this research, I hope that it’s outcomes are not focussed solely on the concept that the ‘fault/weakness/affliction/condition’ lies solely with the individual and that the treatment will be focussed on individuals. I am not, here, arguing that we should not be using better techniques to remove distress in individuals – of course we should. However, probably, most people who are experiencing what are called mental health issues are experiencing these because of the socioeconomic circumstances in which we find ourselves. This is the way RD Laing and others framed mental health – it was Society that was the problem, not the person.

    The huge amount of anonymised data which will be available to this project should enable pretty strong correlations to be drawn between mental health conditions and socioeconomic circumstance. Of course, as David Hume pointed out, a correlation is not a cause, but correlations indicate fairly strongly where the causes can be found and that appropriate changes can be made.

    There are many examples of this in public health, from the introduction of clean water supplies and effective sewage disposal to ‘the cod liver oil and the orange juice.’

    Improved working conditions, living wages, citizens’ incomes, early years education, greater empowerment of communities are all ways in which the ‘mental health’ of the population can be improved, as well as by specific approaches, including pharmacological ones, for individuals.

    The media will focus on the ‘failing humans’ paradigm, rather than the ‘alienating society’.

    Like

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