Using sleep and circadian rhythms data to understand trajectories and clinical outcomes in bipolar disorder
Our vision is to work closely with the bipolar disorder community in Scotland to optimise the use of innovative ambient and passive data collection methods for sleep and circadian rhythms. To inform future approaches early intervention, clinical practice and personalised medicine in bipolar disorder.
Assessing methods for collecting sleep, circadian and light exposure data
We will be using novel methods of collecting information on sleep, circadian rhythms and light exposure over an extended period of time. This will provide a greater picture of the complexity about sleep and circadian rhythms in bipolar than previous studies.
Co-production of clinical and functional outcomes, and testing methods of data collection
We will be working closely with Bipolar Scotland and individuals with bipolar disorder to identify which clinical and functional outcomes we should prioritise in our other workstreams.
Development of a Data Management System to support data collection and optimise sharing opportunities
We will develop research data management (RDM) and reporting that supports individual-focused and long-term ambient and passive data collection, using best practices for FAIR research data (Findable, Accessible, Interoperable, Re-Usable) and guidance on sleep and circadian informatics data harmonization.
Study of the relationships between sleep, circadian rhythms, light exposure and outcomes in people with bipolar disorder
This is a prospective study to investigate the longer-term associations between activity, daylight , sleep and circadian measures and mental health (and vice versa) at an individual level. The long-term nature of this work will allow for causal mechanisms to be assessed and identified.
Co-production and delivery of knowledge exchange and dissemination programme: "Sleep and circadian rhythms in bipolar disorder"
This workstream will engage with the bipolar community to create innovative musical compositions and performances driven by sleep and circadian data from the study. This will be achieved using game-engine technologies that allow for real-time, data-driven generation of music. The music will be accompanied by visualisations of the same data and shared in the format of online music videos and a live performances.
Workstream 4 In Numbers
PERIODS OF 9 WEEK ACTIGRAPHY
MONTHS RADAR TECHNOLOGY MONITORING