LAUSR

The recent popularization of smart technology presents new opportunities for continual, digital-monitoring of patient status. In this project, we used a smartphone app to track the mood, sleep, and activity levels of 159 outpatients with bipolar disorder (BD). The participants were asked to report their daily wake/sleep time and emotional status in the app, while daily activity data were automatically collected via GPS. We performed repeated-measures correlation analysis to examine possible correlations between the readouts. Mood, sleep and activity levels all showed intra-variable correlations with readings on the next day, in the next week, and in the next month. Furthermore, mood and sleep at the reference time were positively correlated with activity in subsequent weeks or months, and activity was positively correlated with mood and sleep in the same time ranges. Thus, our results were in line with previous studies, showing that mood, sleep, and activity levels are interdependent in patients with BD. With the association between mood on future activity level was most significant, and the correlations between each readout and the others were dependent on time frame. Our findings suggest our smartphone app has potential to provide an informative and reliable means for real-time tracking of BD status.