Get your head together: designing an adaptive digital intervention that improves the emotion regulation of students

Abstract

Stress among students has become a hot topic in the news lately. Counselors and therapists that work for universities have seen quite an increase in students visiting them. Many students suffer from stress, anxiety, depression and burn-outs. The amount of students experiencing these issues has increased so much, that even universities have noticed this and are starting Mental Health awareness weeks or mindfulness workshops. Utrecht University (UU) is one of these universities. The UU has recently hired an extra counselor for students and PhD'ers, because waiting times were increasing fast. Waiting time for a person to get therapy in the Netherlands has now increased to approximately 2 months. It can already be quite a challenge to admit to oneself you need help, however, waiting another two months after taking this big step, might discourage many people to actually seek help. Perhaps technology might be able to already provide some help and support in these two months, or in general at all. Previous researches have shown that digital applications can help people monitor and improve their behaviour, for example in fitness and for people suffering from chronic disease. The goal of this thesis was to design a digital intervention (in the form of an algorithm) that helps and improves student's ability regulate their emotions. This digital intervention uses a well-researched and popular emotion regulation technique: mindfulness. Seven different studies were done, in which the stressors students experience were collected, an expert and students gave their opinion on what mindfulness exercises one should advise based on stressor and personality, and finally the algorithm was designed. In this research, the algorithm is not tested for it's effectiveness. However, the perceived effectiveness was tested among students and showed some interesting results. Some exercises were perceived as effective, while others were not. There were a few different explanations possible, as to why some exercises were perceived as effective, and some were not. However, more research is needed on the effectiveness of this algorithm, before it can be implemented.