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New treatment targets for mental health disorders can be identified by using data collected from wearables and mobile phones.

Dr Kate Saunders, Director of Medical Studies at the Department of Psychiatry and Honorary Consultant Psychiatrist, was speaking at the Women in Data Science conference hosted by the Alan Turing Institute. Research analyst and features editor for DataIQ, Toni Sekinah, wrote up this inspiring talk.

Read an edited extract here:

Saunders began to use a computerised approach to classify mood and so got patients to record how they felt on a more regular basis, rather than every time they went to the clinic. “We can target something that is meaningful to patients that we can objectively measure,”  said Saunders.

What’s clear is that instability is the hallmark of bi-polar disorder.
- Dr Kate Saunders

She found that there could be an impact on the way that disorders are diagnosed in the future. Bi-polar disorder has been classically described as periods of depression, of mania, and of “being OK.” However, Saunders saw that, in real life, things aren’t as simple. “The reality is completely different. What’s clear is that instability is the hallmark of this disorder,” she said.

Saunders and her fellow researchers found that certain patterns of behaviour are present in several different conditions. “We’ve got something [a pattern] that we think characterises a disorder, but it probably characterises many others.”

The honorary consultant psychiatrist also looked at the activity of people with borderline personality disorder and found their sleeping patterns were very irregular. “They are not sleeping for any particular period of time. It’s absolutely clear that they have a very, very significant problem with sleep,” noted Saunders.

Sleep could potentially be a new treatment target, given its importance to general wellbeing.

She also found that impulsivity and mood instability directly correlate with chaotic sleep. This led her to think that sleep could potentially be a new treatment target, given its importance to general wellbeing and health outcomes.


Read the full article on DataIQ.


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