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Background

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 behaviour 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.

The Brighten research team has conducted two NIMH-funded randomized clinical trials and collected data (actively and passively) related to real-world behaviour and depression from over 2000 study participants. The manuscript thoroughly describes a dataset collected over the course of the two Brighten studies. The data is made available to qualified researchers through Sage Bionetwork’s qualified researcher data-sharing program via the Synapse platform. 

We believe the dataset will provide a timely and significant long-term value for researchers interested in developing robust and transparently validated digital biomarkers of mental health using real-world data (RWD).

We share and describe one of the largest and most diverse real-world behaviour 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 behavioural data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioural markers and understand the effectiveness of mental health care delivered continuously and remotely.

Brighten V1 - hhttps://doi.org/10.1136/bmjinnov-2015-000098

Brighten V2 - https://doi.org/10.2196/10130