LAUSR

OBJECTIVE To identify trends in mobility and daily pain levels among a cohort of patients with clinically diagnosed spine disease. METHODS Participants with spine disease were enrolled from a general neurosurgical clinic and installed a smartphone application (Beiwe) designed for digital phenotyping to their personal smartphone. This application collected passive meta-data on a minute-to-minute basis, including global positioning system (GPS), WiFi, accelerometer, text and telephone logs, and screen on and off time. The application also administered daily visual analog scale pain surveys. A linear mixed model framework was used to test for associations between self-reported pain and mobility and sociability from the passively collected data. RESULTS A total of 105 patients were enrolled, with a median follow-up time of 94.5 days; 55 patients underwent a surgical intervention during the follow-up period. The weekly pain survey response rate was 73.2%. By the end of follow-up, the mean change in pain for all patients was -1.3 points (4.96 at the start of follow-up to 3.66 by the end of follow-up). Increased pain was significantly associated with reduced patient mobility as measured using 3 daily GPS summary statistics (i.e., average flight length, maximum diameter travelled, total distance travelled). CONCLUSIONS Patients with spine disease who reported greater pain had reduced mobility, as measured by the passively collected smartphone GPS data. Smartphone-based digital phenotyping appears to be a promising and scalable approach to assess mobility and quality of life of patients with spine disease.