Predicting the risk of young people developing anxiety and depression
Theme Mental health
Workstream Biological interventions, trial recruitment and safety
Status: This project is ongoing
The number of adolescents experiencing anxiety and depression is increasing. We need to find better ways to identify people at high risk of developing anxiety and depression so they can be offered help. If we can offer help to high-risk individuals early on in childhood, this could prevent symptoms getting worse or lessen the impact on their lives. We also need to better understand what causes anxiety and depression and what puts people at high risk, so we can develop new ways to prevent and treat it.
Project aims
The aims of this project are:
- To look at how anxiety and depression develop in childhood and identify long-term patterns over childhood and adolescence
- To investigate how problems with the immune system can put people at risk of developing anxiety and depression in childhood, adolescence and early adulthood
- To review previous studies that have explored ways to predict who will experience persistent anxiety and depression
- To develop a risk calculator which can predict risk of depression and anxiety in childhood and adolescence, to use in a community setting
- To test whether the risk calculator can accurately predict risk of depression and anxiety in different UK populations
This research will use information already gathered as part of three UK studies: Born in Bradford (BiB), the Avon Longitudinal study of Parents and Children (ALSPAC) and the Millennium Cohort Study (MCS).
Our work so far
We performed a systematic review of risk calculators for forecasting depression and anxiety over the course of life.
We found 9 studies of risk calculators to predict how depression and anxiety change over the course of life. Of these studies:
- 7 focused on adults
- 2 focused on children and adolescents
Only 1 study looked at anxiety levels – the others looked at depression.
The most common factor used in the risk calculators to predict a person’s long-term levels of depression and anxiety was their past mental health, and that of their family.
We noted that the risk calculators using a large number of different factors, or specialised factors like brain scans, didn’t always provide more accurate predictions.
Our review shows that effective models for predicting the risk of persistent or worsening depression and anxiety are needed. This is particularly important for children and adolescents, who could be offered help while they are young, to prevent their symptoms continuing or worsening.
What we hope to achieve
This project will develop and test a risk calculation tool to predict anxiety and depression in childhood and adolescence.
Community settings need a tool that can predict adolescent depression and anxiety using information accessible to them. But can such a tool accurately predict future risk of anxiety and depression? This project aims to answer this question. If successful, the tool could be adopted in clinics or community settings, for example GP practices.
