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Ambient and passive collection of sleep and circadian data in bipolar disorder to understand symptom trajectories and clinical outcomes (AMBIENT-BD): study protocol

Raahat Manrai*, Duncan Swiffen, Cathy A. Wyse, Debbie Gray, Amy C. Ferguson, Lorna Lopez, Iain Campbell, Aja L. Murray, Emma Louise Gale, Livia C. T. Scorza, Katie F. M. Marwick, Athanasios Tsanas, Andrew N. Coogan, Manuel Spitschan, Andrew J. Miller, Reneta L. Riha, Maja Mitchell Grigorjeva, Daniel Thedie, Maria Gardani, Thomas ZienlinskiHeather C. Whalley, Daniel J. Smith

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Bipolar disorder is defined by extreme variability in mood, activity and sleep/wake patterns. To date, studies of sleep and circadian parameters in bipolar disorder have predominantly relied on short term monitoring over 1-2 weeks, leaving a need for approaches that can assess individual-level changes in sleep, activity and mood with high levels of temporal granularity. In the AMBIENT-BD study, we will optimise low intensity ambient and passive data collection techniques. These methods will allow us to infer sleep and circadian timing patterns over extended time periods while developing novel data collection, sharing and analytical methods. In parallel, we will develop data management systems to streamline and optimise data sharing. At its core, our project involves an 18-month prospective study focused on the assessment of sleep/wake patterns and clinical and functional outcomes in individuals with bipolar disorder. Furthermore, in collaboration with Bipolar Scotland, we will deliver a knowledge exchange programme on the theme of ‘Sleep, circadian rhythms and bipolar disorder’. AMBIENT-BD will advance our understanding of symptom trajectories and mechanisms contributing to relapse in bipolar disorder, providing new insights for innovations in clinical management.
Original languageEnglish
Article number254
Pages (from-to)1-19
Number of pages19
JournalWellcome Open Research
Volume10
DOIs
Publication statusPublished - 18 Jun 2025

Keywords

  • Bipolar disorder
  • Digital technology
  • Sleep
  • Circadian rhythms
  • Co-production

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