Digital Phenotype for Childhood Internalizing Disorders: Less Positive Play and Promise for a Brief Assessment Battery.
Digital Phenotype for Childhood Internalizing Disorders: Less Positive Play and Promise for a Brief Assessment Battery.
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DOI：
10.1109/jbhi.2021.3053846
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发表时间：
2021-08
影响因子：
7.7
通讯作者：
McGinnis RS
中科院分区：
文献类型：
--
作者：
McGinnis EW;Scism J;Hruschak J;Muzik M;Rosenblum KL;Fitzgerald K;Copeland W;McGinnis RS
童年时期的内化障碍，如焦虑和抑郁，是常见的、有害的且难以察觉的。建议进行全民儿童心理健康筛查，但需要新技术来提供客观检测。仪器化的情绪诱导任务旨在迫使儿童做出特定的行为反应，已成为检测儿童内化精神病理学的手段。在我们之前的工作中，我们利用机器学习，从负价任务（焦虑和恐惧的压力）期间收集的运动和声音数据中识别童年内化精神病理学的数字表型。在这项工作中，我们根据儿童玩泡泡的正价任务记录的可穿戴惯性传感器数据，开发了一种儿童内化障碍的数字表型。我们发现，源自捕获奖励反应性特征的表型能够准确检测具有潜在内化精神病理学的儿童（AUC = 0.81）。在此过程中，我们探索了部署到两个身体位置的可穿戴传感器计算出的各种特征集对任务两个阶段的表型性能的影响。我们在之前的负价数字表型的背景下进一步考虑这种新颖的数字表型，并发现每个任务都为检测儿童内化精神病理学、捕获不同问题和障碍亚型的问题带来了独特的信息。总的来说，这些结果为情绪诱导任务组提供了初步证据，以开发一种新的儿童内化障碍诊断方法。
Childhood internalizing disorders, like anxiety and depression, are common, impairing, and difficult to detect. Universal childhood mental health screening has been recommended, but new technologies are needed to provide objective detection. Instrumented mood induction tasks, designed to press children for specific behavioral responses, have emerged as means for detecting childhood internalizing psychopathology. In our previous work, we leveraged machine learning to identify digital phenotypes of childhood internalizing psychopathology from movement and voice data collected during negative valence tasks (pressing for anxiety and fear). In this work, we develop a digital phenotype for childhood internalizing disorders based on wearable inertial sensor data recorded from a Positive Valence task during which a child plays with bubbles. We find that a phenotype derived from features that capture reward responsiveness is able to accurately detect children with underlying internalizing psychopathology (AUC=0.81). In so doing, we explore the impact of a variety of feature sets computed from wearable sensors deployed to two body locations on phenotype performance across two phases of the task. We further consider this novel digital phenotype in the context of our previous Negative Valence digital phenotypes and find that each task brings unique information to the problem of detecting childhood internalizing psychopathology, capturing different problems and disorder subtypes. Collectively, these results provide preliminary evidence for a mood induction task battery to develop a novel diagnostic for childhood internalizing disorders.