DemonicSalmon: Monitoring mental health and social interactions of college students using smartphones

Abstract

Abstract Mental health problems are a leading cause of disease burden and disability worldwide. Social anxiety and depression are highly prevalent among college students. The current methods for detecting symptoms are based on client self-report via questionnaires and interviews in traditional clinical settings, but self-report is subject to recall bias and visiting a clinic requires a high level of motivation. Assessment methods that use both actively and passively collected data hold promise for detecting and monitoring social anxiety and depression symptoms as individuals go about their daily lives. The present study, named DemonicSalmon, investigates how social anxiety and depression symptoms manifest in the daily life of 72 students over a two-week study period. Results show a number of significant correlations between the automatic objective sensor data from smartphones and indicators of mental health. The collected data enhances understanding of how students’ social anxiety, depression and affect levels are associated with their mobility, activity levels, and communication patterns. The DemonicSalmon dataset has been made publicly available on the web to enhance collaborations in this important area of research.