Philip I. Chow

TL;DR: Empirical studies identified 207 studies that had tracked changes in measures of personality traits during interventions, including true experiments and prepost change designs, and found that personality traits changed the most, and patients being treated for substance use changed the least.

TL;DR: Results demonstrate the feasibility and utility of modeling the relationship between affect and homestay using fine-grained GPS data and suggest that integrating repeated state affect assessments in situ with continuous GPS data can increase understanding of how actual Homestay is related to affect in everyday life and to symptoms of anxiety and depression.

TL;DR: A feasibility study leveraging non-invasive mobile sensing technology to passively assess college students' social anxiety, one of the most common disorders in the college student population, demonstrated that social anxiety level is significantly correlated with places students' visited and location transitions.

TL;DR: In this article, the DemonicSalmon dataset was used to investigate how social anxiety and depression symptoms manifest in the daily life of 72 students over a two-week study period, and the collected data enhances understanding of how students' social anxiety, depression and affect levels are associated with their mobility, activity levels, and communication patterns.

TL;DR: The different relationships between mobility and social anxiety were explored to build a predictive model that assessed social anxiety from passively generated Global Positioning System (GPS) data and indicate that extracting and analyzing mobility features may help to reveal how social anxiety symptoms manifest in the daily lives of college students.