What’s BOThering You?

Poor student mental well-being (StMWB) is increasingly recognized as a major public health burden. Due to a lack of understanding how different aspects of StMWB overlap and dynamically evolve over time within persons, interventions to prevent or treat poor StWB have only limited success. Our research goal is to take a network-oriented modelling approach to identify the network structure of StMWB components over time, and to model this dynamic network computationally. This way, we aim to uncover and provide novel insights in the complex networks of StWB components of higher education students over time, leading to a multidimensional, dynamic, and personalized network model of StMWB. The model serves as input for the development and evaluation of personalized and engaging conversational agents (i.e., chatbots) that can support students in their well-being. Such chatbots can lower the threshold for young people to seek help for their mental health problems, using technology they already have experience with.