Background: The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. Objective: We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. Methods: Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. Results: This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=−0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, P<.001) the subsequent periodicity of mobility. Conclusions: Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.

中文翻译：

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抑郁症状严重程度与手机测量活动能力之间的纵向关系：动态结构方程模型研究


背景：通过手机收集的位置数据测量的个人移动性已被发现与抑郁症相关；然而，抑郁症状严重程度与手机测量的活动能力之间的纵向关系（关系的时间方向）尚未得到充分探索。目的：我们的目的是探讨随着时间的推移，抑郁症状严重程度与手机测量的活动能力之间的关系和关系方向。方法：本文使用的数据来自一项名为“疾病和复发 - 重度抑郁症远程评估”的欧盟主要项目，该项目在 3 个欧洲国家进行。每两周通过手机进行 8 项患者健康问卷 (PHQ-8) 测量抑郁症状的严重程度。参与者的位置数据由手机中的 GPS 和网络传感器每 10 分钟记录一次，并从 PHQ-8 评估前 2 周的位置数据中提取 11 个移动特征。动态结构方程模型用于探索抑郁症状严重程度与手机测量的活动能力之间的纵向关系。结果：本研究包含 290 名参与者（年龄：中位数 50.0 IQR 34.0、59.0）岁的 2341 条 PHQ-8 记录和相应的电话收集位置数据；其中 215 人（74.1%）为女性，149 人（51.4%）有工作。抑郁症状严重程度与手机测量的活动能力之间存在显着负相关，并且这些相关性在个体内部水平比个体间水平更显着。对于关系随时间的变化方向，Homestay（在家的时间）（φ=0.09， P =.01）、位置熵（不同地点的时间分布）（φ=−0.04， P =.02）和居住位置计数（反映出行）（φ=0.05， P =.02）与随后的变化显着相关PHQ-8 得分，而 PHQ-8 得分的变化显着影响（φ=−0.07， P <.001）随后的流动性周期性。结论：一些基于手机的移动功能有可能预测未来的抑郁症，这可能为未来的临床应用、复发预防和现实环境中的远程心理健康监测实践提供支持。