Many mental health problems arise at the start of university life. Students are therefore a high-risk group for issues such as depression and anxiety. Universities are uniquely positioned to test preventive and innovative solutions for student well-being. Bolinski examined how technology can help improve students’ mental health.
Digital help works – but not for everything
Bolinski studied the use of Digital Mental Health Interventions (DMHIs), such as internet- and virtual-reality-based programs. While these interventions have been proven effective in the general population, they often have less impact among students. Another important finding is that improving mental well-being does not automatically lead to better academic results – a common assumption.
A striking outcome of the research 'Innovating Technologies for Improving Student Mental Health' is that relatively few students with mild symptoms were willing to participate in the study. “This shows how important it is to closely align with the needs and motivation of students,” says Bolinski.
Machine learning and VR as research methods
In addition to the effects of the interventions themselves, Bolinski also focused on innovative research methods. He applied Bayesian statistics in controlled studies and meta-analyses, and used machine learning to predict which students are willing to seek help. The results showed that the severity of mental health problems and social factors are decisive. According to the predictive model, international students could benefit from a more tailored approach.
An integrated approach is needed
Bolinski’s research highlights the importance of an integrated approach to mental health in higher education. He argues that digital interventions should not be seen in isolation from broader, structural measures in education: “It is crucial that universities not only invest in innovative technology but also remain attentive to the social and psychological context of students.”