Mental health and pain problems could be better understood through AI

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By Jessica Taylor

There are around 740 million people living in Europe today. About 140 million of those people are living in chronic pain, according to pain specialist Dr Chris Eccleston of Bath University.

Dr Eccleston is known in his field for researching how the human brain processes pain and the psychological impacts of being in constant pain.

How can we possibly access and treat all the people suffering from chronic pain across the world? Especially people in countries where there are only one or two trained pain specialists.

Dr Eccleston believes this is where AI could be the solution.

“We can’t possibly train doctors and psychologists to reach that many people,” he says.

He then looks at the ways we currently assess and treat people for mental health problems. He describes them as “Victorian” – and indeed they are. The so called “talking cure” of psychotherapy was developed by Sigmund Freud in the 1800s.

“We have a Victorian approach to psychotherapy.

“We ask somebody to visit [the patient] from afar and sit with them. We ask people to remember what happened in their life and we give them a set of things to change. When they come back a week later we ask them ‘how was it?’.”

But Dr Eccleston thinks our own data can inform how mental health services are offered in future. By feeding large volumes of data about human behaviour – both individually and collectively – into a computer, we should be able to teach the machine to be able to differentiate between behaviours and spot ‘triggers’ that could cause someone to have a mental health crisis.

He describes people as fairly inept at being able to spot warning signs of a mental health problem in those around us, and so he believes a computer solution should be able to fill in that gap. He wants to be able to bring the data together to build a “prevention model” – so health professionals can intervene before someone is dealing with a mental health problem.

However, in a system that provides solutions by learning from huge data samples, concerns will always be raised about how secure and reliable that system will be. Dr Eccleston admits there are always worries that a new technology could have adverse effects; most importantly when dealing with privacy. But he also points out this is not a new issue.

When it comes to trust, he is optimistic that people will be able to get on board with the idea of trusting a machine with their thoughts and symptoms from pilot studies that are already being trialled.

“The work that has been done in that area is promising. When people know there isn’t a real person there they are engaging with it. I think the work is showing that they are able to engage therapeutically.”

One of the biggest challenges in treating pain is being able to measure the severity and type of pain a person is feeling. Dr Eccleston’s research has led him to study people who cannot communicate by mouth. In the past, he has worked with people suffering from degenerative illnesses to study pain.

“They are in pain but they can’t tell us. But the face can show pain through expression.”

He believes there is a space for a detection system to be built which would recognise the indicators of pain from having received data from other patients who are suffering, to understand the nature and extent of someone’s pain. He also admits this is a challenge, as it is so difficult to describe the intensity of a person’s pain.

With so many people across the world suffering from chronic pain, Dr Eccleston knows it is impossible for trained specialists to have personal contact with every single patient. But with an AI system that has collected millions of data samples, it is possible to give pain sufferers access to an expert system that could transform pain perception all around the world. Admittedly, this has not happened yet, and there are not currently any AI-focused trials in the areas of mental health and pain. But Dr Eccleston is confident the technology is on its way.

“It’s like science fiction,” he says.

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