The researchers — led by Philip I. Chow, PhD, a psychology researcher at the University of Virginia in Charlottesville — identified 72 undergraduate students from a university in the United States. They determined baseline depression and social anxiety symptoms using self-report instruments and installed an app on students’ mobile phones to collect GPS location data along with self-reported emotions.
The researchers found that higher social anxiety was correlated with more time at home, and more negative emotions were associated with longer homestay. Among those with higher social anxiety at baseline, more negative emotions within one day was also associated with a high likelihood of spending time at home the next day.
These “results demonstrate the feasibility and utility of modeling the relationship between affect and homestay using fine-grained GPS data,” according to the researchers. They concluded that using continuous GPS data can help other researchers understand how homestay is related to daily symptoms.
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