Crowd-Powered Discovery of Mental Health Self-Care Techniques in Higher Education

Mental disorders deteriorate well-being in many ways. Clinical mental health care is insufficient and struggles to keep up with the growing demand for services in many parts of the world. Human-Computer Interaction researchers have focused on building different interactive systems that support mental well-being. In our work we focus on collecting, peer-assessing, and assisting in the discovery of mental health self-care techniques through an online tool. Our target demographic is the higher education community. The implemented tool can offer new self-care techniques to its users, and our user studies validate its usefulness in capturing and offering valuable mental health care information. Further, we study how source disclosure affects the perception of the discovered techniques, finding no major differences in the measured variables. Finally, we discuss how user-generated self-care suggestions in this context warrants caution and the implications of our study.