Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression.
Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression.
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DOI：
10.1038/s41597-022-01633-7
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发表时间：
2022-08-27
期刊：
影响因子：
9.8
通讯作者：
Arean, Pat
中科院分区：
文献类型：
--
作者：
Pratap, Abhishek;Homiar, Ava;Waninger, Luke;Herd, Calvin;Suver, Christine;Volponi, Joshua;Anguera, Joaquin A.;Arean, Pat
尽管医疗保健系统花费了数十亿美元，但大多数患有精神健康障碍的人仍无法获得及时和基于证据的护理。研究人员一直在探索使用数字健康技术来衡量现实世界中的行为，但结果不一。有必要创建可访问和可计算的数字心理健康数据集，以推进包容性和透明验证的研究，从而创建强大的现实世界心理健康数字生物标记。在这里，我们分享并描述了来自美国各地两千多人的最大、最多样化的现实世界行为数据集之一。这些数据是由 NIMH 资助的两项随机临床试验的一部分生成的，该试验旨在评估持续远程提供心理健康护理的有效性。纵向数据集包括对情绪、抑郁、焦虑的自我评估以及在现实世界中被动收集的基于手机的行为数据流。该数据集将提供及时和长期的数据资源，以评估开发数字行为标记的分析方法，并了解持续远程提供的心理保健的有效性。
Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. Researchers have been exploring using digital health technologies to measure behavior in real-world settings with mixed results. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.
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