PocketPPD：使用被动式智能手机传感技术筛查产后抑郁风险
PocketPPD: Screening for Postpartum Depression Risk Using Passive Smartphone Sensing
AI总结：
研究针对产后抑郁筛查难题，提出基于被动智能手机传感的PocketPPD方法，利用产妇情境特征检测风险。通过对61名产后女性的四周可行性研究，给出不同模型AUC结果，发现重要数字生物标志物，为低负担筛查及围产期心理健康监测提供依据。
AI中文摘要：
产后抑郁（PPD）是一种严重的围产期心理健康状况，影响全球约20%的新妈妈。常见筛查方法依赖用户输入，负担重。近期被动移动传感（PMS）方法可利用机器学习和多模态传感器数据检测抑郁症状，但产后行为模式独特，能否用于PPD存疑。为此提出PocketPPD，利用智能手机收集的产妇情境特征检测PPD风险。在对61名产后女性进行的为期四周的可行性研究中，仅PMS模型的AUC为0.75，整合PMS数据和自我报告特征的最佳模型AUC为0.83。还发现早晚日常波动是重要数字生物标志物，受婴儿发育阶段和就业状况等产妇情境动态调节。该研究为低负担PPD风险筛查提供了实证依据，为围产期心理健康持续监测奠定了基础。
英文摘要：
Postpartum depression (PPD) is a serious perinatal mental health condition affecting approximately 20% of new mothers worldwide. Common screening approaches for PPD, such as self-report questionnaires and active digital logs, rely heavily on user input and thus impose a substantial burden on participants, limiting their feasibility for long-term use. Recent passive mobile sensing (PMS) approaches have enabled low-burden detection of depressive symptoms using machine learning methods with multi-modal sensor data from off-the-shelf mobile devices including smartphones. However, the postpartum period entails distinct behavioral patterns, raising uncertainty about whether sensing-based indicators for general depression and mental disorders generalize to PPD. To address this gap, we propose PocketPPD, a PMS-based PPD screening method that detects PPD risk using maternal contextual features, such as disruptions in behavioral rhythms and shifts in stability, collected through a smartphone. In our exploratory four-week feasibility study with 61 postpartum women, the PMS-only model achieved an AUC of 0.75, while the best-performing model, integrating PMS-oriented data and self-report features, achieved an AUC of 0.83. Moreover, we find that morning and late-night routine volatility ranks among the top digital biomarkers, dynamically moderated by maternal contexts such as infant developmental stage and employment status. This work provides empirical evidence for low-burden PPD risk screening and our findings lay the groundwork for continuous perinatal mental health monitoring.
