A lack of social connection is strongly linked to mental health issues such as depression. The overall health impact is comparable to that of smoking and obesity. Interventions that improve social connection and reduce loneliness by bringing people into contact with one another may make an important contribution to reducing mental health complaints. However, there is also a potential risk of “contagion” of depressive symptoms when individuals with mental health issues are brought together.
In this project we will use computational modeling to predict which individuals can best be matched in a social connection intervention. While we aim to minimise the risk of symptom contagion. This is a collaboration of the Centre for Urban Mental Health at the University of Amsterdam (UvA), with the Department of Psychiatry at Amsterdam UMC, the Faculty of Science (FNWI) at UvA, and Arkin,
In the Social Connection Project, we collect empirical data on social connection and potential symptom contagion from approximately 750 participants in ongoing group interventions at Arkin. Using computational analysis, we aim to identify and predict qualitative social connections and reductions in loneliness among patients with depressive symptoms. Subsequently, we will develop both an online and offline social connection intervention for individuals with depression. In this intervention participants will be matched on a personal level, based on computational analysis.
The intervention will be tested in a pilot study at Arkin, and the data will be used to calibrate, validate, and refine the computational model, as well as to further improve the intervention. We hope that this new approach will lead to best practices for social interventions at multiple levels for individuals with mental health disorders.