被动感应智能手机特征在预测抑郁和焦虑症状方面的时间效用差异:一项纵向队列研究

Caitlin A. Stamatis, Jonah Meyerhoff, Yixuan Meng, Zhi Chong Chris Lin, Young Min Cho, Tony Liu, Chris J. Karr, Tingting Liu, Brenda L. Curtis, Lyle H. Ungar, David C. Mohr
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引用次数: 0

摘要

虽然有研究表明智能手机数据与情感症状之间存在联系,但我们对这些联系的时间范围、特异性(如抑郁与焦虑)以及特定个人(与群体水平)的性质缺乏清晰的认识。我们开展了一项基于智能手机的大规模(n = 1013)被动感应研究,以确定随时间变化的抑郁和焦虑症状的人内和人际数字标记。参与者(74.6% 为女性;平均年龄为 40.9 岁)下载了 LifeSense 应用程序,该应用程序可在 16 周内持续收集被动数据(如 GPS、应用程序和设备使用、通信)。层次线性回归模型测试了被动感知数据的两周窗口与抑郁(PHQ-8)或广泛焦虑(GAD-7)的人内和人际关联。我们使用移动窗口来了解感知特征与心理健康症状相关的时间尺度,预测未来 2 周(远端预测)、未来 1 周(中端预测)和未来 0 周(近端预测)的症状。与平均水平相比,在家中花费更多时间是 PHQ-8 严重程度的早期信号(远端 β = 0.219,p = 0.012),并在中端(β = 0.198,p = 0.022)和近端(β = 0.183,p = 0.045)窗口与 PHQ-8 继续相关。相反,昼夜节律运动与 PHQ-8 的近端相关(β = -0.131,p = 0.035),但不能预测(远端 β = 0.034,p = 0.577;内侧 β = -0.089,p = 0.138)PHQ-8。与 PHQ-8 和 GAD-7 相关的不同通信特征(即呼叫/短信或基于应用程序的消息)。研究结果对确定新的治疗目标、个性化数字心理健康干预以及加强传统的患者与医疗服务提供者之间的互动具有重要意义。某些特征(如昼夜节律运动)可能是情感症状的相关指标,但不是真正的前瞻性指标。相反,其他一些特征(如在家持续时间)可能是个体内部症状变化的早期信号,这表明针对这些信号的个人特异性增加进行预防性干预(如行为激活)具有潜在的实用性。
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Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study
While studies show links between smartphone data and affective symptoms, we lack clarity on the temporal scale, specificity (e.g., to depression vs. anxiety), and person-specific (vs. group-level) nature of these associations. We conducted a large-scale (n = 1013) smartphone-based passive sensing study to identify within- and between-person digital markers of depression and anxiety symptoms over time. Participants (74.6% female; M age = 40.9) downloaded the LifeSense app, which facilitated continuous passive data collection (e.g., GPS, app and device use, communication) across 16 weeks. Hierarchical linear regression models tested the within- and between-person associations of 2-week windows of passively sensed data with depression (PHQ-8) or generalized anxiety (GAD-7). We used a shifting window to understand the time scale at which sensed features relate to mental health symptoms, predicting symptoms 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Spending more time at home relative to one’s average was an early signal of PHQ-8 severity (distal β = 0.219, p = 0.012) and continued to relate to PHQ-8 at medial (β = 0.198, p = 0.022) and proximal (β = 0.183, p = 0.045) windows. In contrast, circadian movement was proximally related to (β = −0.131, p = 0.035) but did not predict (distal β = 0.034, p = 0.577; medial β = −0.089, p = 0.138) PHQ-8. Distinct communication features (i.e., call/text or app-based messaging) related to PHQ-8 and GAD-7. Findings have implications for identifying novel treatment targets, personalizing digital mental health interventions, and enhancing traditional patient-provider interactions. Certain features (e.g., circadian movement) may represent correlates but not true prospective indicators of affective symptoms. Conversely, other features like home duration may be such early signals of intra-individual symptom change, indicating the potential utility of prophylactic intervention (e.g., behavioral activation) in response to person-specific increases in these signals.
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