Predicting the onset of depression

Researchers from UCL have developed the first online tool that can be used to identify those who are at risk of depression.

PredictD can currently be used by individuals with access to the web but it is hoped that family doctors and local clinics will make use of this new tool as an early detector of depression in their patients.

Depression is a common problem and although there has been much research into treatments, PredictD is the first tool designed to predict the onset of depression. Professor Michael King said: “We have ways of predicting the onset of heart disease or stroke, but none for predicting people’s risk of major depression. Our study is one of the first to develop a risk algorithm for just this purpose.”

Professors Michael King and Irwin Nazareth from UCL led the team who designed the algorithm and extensively tested it across Europe. PredictD was tested on 6,000 people visiting their family doctor in the UK, Spain, Portugal, the Netherlands, Slovenia and Estonia. By tracking the participants at six month intervals the team were able to assess the accuracy of the algorithm. The team plan further tests in randomised trials in Europe and are also exploring the feasibility of using PredictD in China, which would be the first project of its kind in Asia.

Professor King said: “Risk tools such as ours are needed to focus more effort on preventing depression. For example, people identified as at risk by an online tool could be flagged on a GP’s computer. Recognition of those at risk could help with watchful waiting or active support, such as restarting treatment in patients with a history of depression. Patients could also be advised on the nature of depression or on cognitive behaviour therapies to help reduce their risk of developing major depression.”

PredictD can be found on the web at www.ucl.ac.uk/predict-depression
 
By Leila Sattary