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Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression.


ABSTRACT: 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.

SUBMITTER: Pratap A 

PROVIDER: S-EPMC9420101 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression.

Pratap Abhishek A   Homiar Ava A   Waninger Luke L   Herd Calvin C   Suver Christine C   Volponi Joshua J   Anguera Joaquin A JA   Areán Pat P  

Scientific data 20220827 1


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  ...[more]

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