London, January 24-Researchers have developed a new tool that can predict the risk of depression in young adults years in advance, a finding that may pave the way for new methods to monitor mental illness risk in teens.
Described in the Journal of the American Academy of Child and Adolescent Psychiatry, the predictive tool can help identify young people who may go on to experience a major depressive disorder when they reach 18 years of age. In the study, the researchers, including those from King’s College London in the UK, evaluated the performance of the tool in samples of adolescents from New Zealand and the UK.
They found differences in its ability to predict depression across these countries, highlighting the need to consider local variations when developing predictive tools.
“This research marks an important first step in developing an accessible tool that could help screen adolescents for depression and improve mental health worldwide,” said Valeria Mondelli, study co-author from King’s College London.
“Depression can have debilitating lifelong impacts and adolescents are especially vulnerable to its onset. Identification of those at high risk of developing depression in later adolescence could be valuable in devising effective early-intervention strategies to help prevent this illness,” she added.
To develop the tool, the researchers identified 11 variables that could be combined into a single score to recognise those adolescents at risk of developing depression.
“In our study we tried to go beyond more traditional ways of identifying youths at high risk of depression and learn from other medical specialties that combine multiple variables to generate composite risk scores, such as the Framingham cardiovascular risk score,” explained Christian Kieling, lead author on the study from Universidade Federal do Rio Grande do Sul in Brazil.
The researchers compared the tool’s ability to predict depression in a sample of 1,144 British 12 year olds, and 739 New Zealand 15 year olds. According to the study, the predictive ability of the tool was not as strong in the UK and New Zealand samples.
“The existence of these discrepancies does not discount the value of our tool but provides important insight into adapting the score according to where it will be used,” Kieling said.
“Adaptation is necessary for most predictive tools; for instance, tools used to assess the risk of cardiovascular disease developed in the US require adjustments when used in other countries,” he added
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