Abstract
BackgroundOlder adults who experience pain are more likely to reduce their community and life-space mobility (ie, the usual range of places in an environment in which a person engages). However, there is significant day-to-day variability in pain experiences that offer unique insights into the consequences on life-space mobility, which are not well understood. This variability is complex and cannot be captured with traditional recall-based pain surveys. As a solution, ecological momentary assessments record repeated pain experiences throughout the day in the natural environment.ObjectiveThe aim of this study was to examine the temporal association between ecological momentary assessments of pain and GPS metrics in older adults with symptomatic knee osteoarthritis by using a smartwatch platform called Real-time Online Assessment and Mobility Monitor.MethodsParticipants (n=19, mean 73.1 years, SD 4.8; female: 13/19, 68%; male: 6/19, 32%) wore a smartwatch for a mean period of 13.16 days (SD 2.94). Participants were prompted in their natural environment about their pain intensity (range 0-10) at random time windows in the morning, afternoon, and evening. GPS coordinates were collected at 15-minute intervals and aggregated each day into excursion, ellipsoid, clustering, and trip frequency features. Pain intensity ratings were averaged across time windows for each day. A random effects model was used to investigate the within and between-person effects.ResultsThe daily mean pain intensities reported by participants ranged between 0 and 8 with 40% reporting intensities ≥2. The within-person associations between pain intensity and GPS features were more likely to be statistically significant than those observed between persons. Within-person pain intensity was significantly associated with excursion size, and others (excursion span, total distance, and ellipse major axis) showed a statistical trend (excursion span: P=.08; total distance: P=.07; ellipse major axis: P=.07). Each point increase in the mean pain intensity was associated with a 3.06 km decrease in excursion size, 2.89 km decrease in excursion span, 5.71 km decrease total distance travelled per day, 31.4 km2 decrease in ellipse area, 0.47 km decrease ellipse minor axis, and 3.64 km decrease in ellipse major axis. While not statistically significant, the point estimates for number of clusters (P=.73), frequency of trips (P=.81), and homestay (P=.15) were positively associated with pain intensity, and entropy (P=.99) was negatively associated with pain intensity.ConclusionsIn this demonstration study, higher intensity knee pain in older adults was associated with lower life-space mobility. Results demonstrate that a custom-designed smartwatch platform is effective at simultaneously collecting rich information about ecological pain and life-space mobility. Such smart tools are expected to be important for remote health interventions that harness the variability in pain symptoms while understanding their impact on life-space mobility.
Highlights
The world population of adults aged 65 years or older is rapidly growing [1]
The within-person associations between pain intensity and GPS features were more likely to be statistically significant than those observed between persons
Within-person pain intensity was significantly associated with excursion size, and others showed a statistical trend
Summary
The world population of adults aged 65 years or older is rapidly growing [1]. This phenomenon, unprecedented in history, highlights a need to maintain and promote programs that manage chronic diseases and symptoms causing increased risk of loss of mobility and disability. Rates are higher in those older than 75 years—48.6% have physical impairments, and 27.7% have difficulty walking one quarter-mile (approximately 400 m) These impairments have a significant negative impact on life-space mobility—the daily activities and geographical area in which people engage. Ecological momentary assessments (EMA) record repeated pain experiences throughout the day in a person's natural environment. It minimizes retrospective [6,7] and recent-experience bias [8,9]. There is significant day-to-day variability in pain experiences that offer unique insights into the consequences on life-space mobility, which are not well understood This variability is complex and cannot be captured with traditional recall-based pain surveys. Ecological momentary assessments record repeated pain experiences throughout the day in the natural environment
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