The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults With Knee Osteoarthritis: A Smartwatch-Based Demonstration Study (Preprint)

The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults With Knee Osteoarthritis: A Smartwatch-Based Demonstration Study (Preprint)

BACKGROUND Older 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. OBJECTIVE The 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. METHODS Participants (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. RESULTS The 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. CONCLUSIONS In 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.

背景 经历疼痛的老年人更有可能减少其社区活动和生活空间移动性（即一个人在环境中通常活动的场所范围）。然而，疼痛体验存在显著的日常变异性，这为生活空间移动性的影响提供了独特的见解，但人们对此了解甚少。这种变异性很复杂，无法通过传统的基于回忆的疼痛调查来捕捉。作为一种解决方案，生态瞬时评估在自然环境中记录一天中反复出现的疼痛体验。 目的 本研究的目的是通过使用一个名为实时在线评估和移动监测器的智能手表平台，检验有症状的膝骨关节炎老年人的疼痛生态瞬时评估与全球定位系统（GPS）指标之间的时间关联。 方法 参与者（n = 19，平均年龄73.1岁，标准差4.8；女性：13/19，68%；男性：6/19，32%）佩戴智能手表的平均时长为13.16天（标准差2.94）。在自然环境中，参与者在上午、下午和晚上的随机时间窗口被提示报告其疼痛强度（范围0 - 10）。每隔15分钟收集一次GPS坐标，并将每天的数据汇总为出行、椭球体、聚类和出行频率等特征。每天对各个时间窗口的疼痛强度评分进行平均。使用随机效应模型来研究个体内和个体间的效应。 结果 参与者报告的每日平均疼痛强度在0到8之间，40%的人报告强度≥2。疼痛强度与GPS特征之间的个体内关联比个体间观察到的关联更有可能具有统计学意义。个体内疼痛强度与出行规模显著相关，其他指标（出行跨度、总距离和椭圆长轴）呈现出统计学趋势（出行跨度：P = 0.08；总距离：P = 0.07；椭圆长轴：P = 0.07）。平均疼痛强度每增加1分，出行规模减少3.06千米，出行跨度减少2.89千米，每天行驶的总距离减少5.71千米，椭圆面积减少31.4平方千米，椭圆短轴减少0.47千米，椭圆长轴减少3.64千米。虽然不具有统计学意义，但聚类数量（P = 0.73）、出行频率（P = 0.81）和在家停留时间（P = 0.15）的点估计值与疼痛强度呈正相关，熵（P = 0.99）与疼痛强度呈负相关。 结论 在这项示范研究中，老年人较高强度的膝痛与较低的生活空间移动性相关。结果表明，定制设计的智能手表平台能有效地同时收集有关生态疼痛和生活空间移动性的丰富信息。此类智能工具对于远程健康干预措施非常重要，这些干预措施可以利用疼痛症状的变异性，同时了解其对生活空间移动性的影响。