Youth mental health meets big data analytics: Hype or Hope?
Depression and anxiety disorders among youth are causing major problems worldwide. The mechanisms involved are still unknown, however. Moji Aghajani – Assistant Professor at the Institute of Education and Child Studies - aims to provide new insights with his research "Youth mental health meets big data analytics: Hype or Hope?
Globally, millions of adolescents face major emotional, social and economic problems due to depression and anxiety disorders. However, we don’t know what neural, biological and psychosocial mechanisms underpin these mood disorders. This lack of understanding complicates effective prevention and intervention.
Experts hence warrant an urgent paradigm shift, focusing more on the individual patient and personalized analysis through the use of artificial intelligence (AI) and large-scale datasets (big data). Moji Aghajani's work tests this desired paradigm shift by deploying AI and big data within an existing clinical consortium with over 10,000 participants, including mood disorders and psychologically healthy youth. In doing so, Moji Aghajani aims to either confirm or refute the relevance and feasibility of the earlier mentioned paradigm shift.
NWO SGW grant
Aghajani's proof of concept study is funded by a grant within the SGW Open Competition program of the Netherlands Organization for Scientific Research (NWO). With the Open Competition - SGW, NWO aims to give social sciences and humanities scientists the opportunity to conduct innovative research on topics with potentially major public impact. The unique aspect of these grants is that there is no need to know in advance whether the intended objectives will be achieved. So, there is plenty of scope for experimentation and innovation. Read more about the NWO SGW grant ››
Lecture dies for alumni
On Saturday February 11th, Moji Aghajani gave a lecture on his project during the dies for alumni in honor of the 448th anniversary of Leiden University. He informed alumni how he plans to use AI and big data to map mental disorders among young people in a personalized way, so to inform diagnostics, prognostics and risk assessment.