BACKGROUND GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging. METHODS With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis. RESULTS The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility. CONCLUSION This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

中文翻译：

---

制定一套全面的基于 GPS 的指标，反映日常出行的多维性质，以应用于健康和老龄化研究。

背景技术GPS跟踪越来越多地用于健康和老龄化研究，以客观且不引人注目地评估个人的日常生活活动能力。然而，移动性是一个复杂的概念，基于 GPS 得出的移动性指标对其进行彻底描述仍然具有挑战性。方法 为了反映日常出行中所涉及的各个方面的广度，我们提出了一个概念框架，根据 GPS 衍生的出行指标的特征和分析属性对其进行分类，以应用于健康和老龄化研究。为了演示如何应用分类框架，现有研究中使用的现有流动性指标根据建议的框架进行了分类。然后，我们根据 95 名老年人的真实 GPS 数据提出并计算一组选定的移动性指标，这些指标反映了个人日常移动性的各个方面。为了探索流动性指标背后的潜在维度，我们进行了因子分析。结果 所提出的框架能够根据流动性指标所反映的特征和分析方面对流动性指标进行概念性分类。特征方面告知移动性指示符的内容并且包括与空间、时间、移动范围和属性相关的类别。分析方面告知如何在时间尺度和统计属性方面聚合移动性指标。所提出的类别补充了现有的研究，这些研究通常低估了涉及时间、时间分布和运动的停止-运动分段的流动性指标。因子分析揭示了全面了解老年人日常活动能力所需的以下六个维度：生活空间的范围、外出活动的数量、使用主动交通方式的时间、生活空间的稳定性、寿命的延长移动的空间和时间。结论 本研究主张在未来的健康和老龄化相关研究中纳入基于 GPS 的移动指标，以反映个人日常移动的多维性质。这将有助于更好地了解流动性的哪些方面对于健康老龄化至关重要。