Mobility, well-being, and community participation among people with depression: an observation study using geographically-explicit ecological momentary assessment (GEMA) (Preprint)

BACKGROUND Globally, more than 300 million people suffer from depressive disorders. Despite a wide range of conducted research, information on the mobility and daily routines of persons with depression remains lacking. OBJECTIVE To describe a preliminary explication of the association between mobility, well-being, and community participation of people with depression as they occur in real-time settings. METHODS We used a multivariate, time-series, single-subject, repeated measures (MRSRM) design. People with depression (N=33) were invited to use a GPS device for over two weeks for continuous mobility tracking, while information on their well-being was collected with paper surveys before and after two-weeks periods. The tracking records from 32 participants were imported into Geographical Information Systems (GIS) to extract the specific mobility information. Socio-demographic and environmental information (building density, greenness index and PM2.5) was derived for statistical analysis to explore the relationship between mobility, community participation and mental health using correlation coefficients and logistic regression analysis. RESULTS The more hours participants stayed at home, the more often they had depressive symptoms (r=0.47, P CONCLUSIONS Our study showed that having signs of depression is associated with mobility area and time spent at home among persons with depression, which may mean that their activity level in society is limited. Staying home may be a solution for avoiding extra stress, problems with self-esteem and maintaining satisfaction with life. Low-threshold access to health services should be tailored for each person based on their needs. More information based on studies using robust design, bigger sample size, and more accurate measurement methods, however, is required before individualized services can be fully achieved. Although using GPS may be a feasible data collection method, more effort should be put into collecting the data with easy-to-use technology to avoid extra stress in the participants.