The dynamic interplay between sleep and mood: an intensive longitudinal study of individuals with bipolar disorder

Lewis, K. J. S., Tilling, K., Gordon-Smith, Katherine ORCID: https://orcid.org/0000-0003-4083-1143, Saunders, K. E. A., Di Florio, A., Jones, Lisa ORCID: https://orcid.org/0000-0002-5122-8334, Jones, I., O' Donovan, M. C. and Heron, J. (2022) The dynamic interplay between sleep and mood: an intensive longitudinal study of individuals with bipolar disorder. Psychological Medicine. pp. 1-10. ISSN Print: 0033-2917 Online: 1469-8978

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Abstract

Background
Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations.

Methods
Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed.

Results
Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling.

Conclusions
Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.

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