Using Big Data to Understand Mental Health
Using Big Data to Understand Mental Health
This research is a great example of not only the power of Big Data in improving the research of mental health but also its diagnosis and treatment.
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Mental health has been given a welcome dose of publicity in recent months as various campaigners have attempted to remove the stigma attached to it and encourage people to talk more about their mental wellbeing. Given that it’s believed one in four of us are affected by mental illness, it’s long overdue. It’s especially challenging for young people, with mental health issues often starting when we’re young.
Researchers from the Farr Centre at Swansea University are working to better understand the issues surrounding the impact mental health has on young people.
Mental Health in the Young
The team took a Big Data approach to their work and analyzed data from 358,000 people aged between six and 18 years of age living in Wales between 2003 and 2013. The data was gleaned from GPS and NHS primary care services.
The data revealed that antidepressant use rose significantly, with depression symptoms doubling in that time. Interestingly, however, actual diagnoses of depression fell by roughly a quarter.
"These findings add to the growing debate over increasing prescribing of anti-depressants to children and young people. The main issue is whether they were being prescribed appropriately. However, it’s worth remembering that there has been historical under-treatment of mental disorders in young people. It’s important that each individual young person is listened to and gets the right kind of help for their problem," the researchers say.
"We need to ensure GPs are trained to really understand the lives and moods of young people, as well as knowing what warning signs they should look out for. For some young people, reassurance that this is within the range of normal human experience may be appropriate. For others, talking therapies may be the best option, as they have a proven track record of improving symptoms for those with mild and moderate depression. In more serious cases, anti-depressants should be used together with talking therapies. They do work. Improving access to talking therapies is very important."
The paper recommends new strategies for prescribing and treating depression in children and young people. The HAPPEN project, for which this research was a part, aims to better understand the health and wellbeing of young people.
Previous work suggests that 70% of children who have mental health problems don’t receive the right interventions at an early enough age. The project aims to improve that by working with nine to 11-year-old school children in Swansea, Wales.
The cohort of 3,500 children provided data on their sleep, concentration, physical activity, nutrition, and well-being. The data was then linked anonymously to GP records, hospital admissions, and educational achievement.
Researchers then analyzed this data before reporting back to schools and other local health stakeholder groups, including public health professionals, sports clubs, and local charities.
“This research aims to improve our understanding of child mental health difficulties, explore the effectiveness of school-based interventions and provide an insight into the relationships between health, wellbeing and education outcomes,” the team says. “The project offers advice and support to schools via a host of resources which they can access to improve health and wellbeing interventions and ensure curriculum needs are also being met. The use of consultation, engagement, and collaboration has enabled the network’s success to date and the number of schools joining and the data collected for our research is continuing to grow.”
It’s a great example of not only the power of Big Data in improving the research of mental health but also its diagnosis and treatment. Hopefully, it will add to the dialog and improve matters for young people both across the UK and further afield.
Published at DZone with permission of Adi Gaskell , DZone MVB. See the original article here.
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