Unraveling the rhythm of depression: exploring physical activity, sleep, and circadian markers for depression detection and prediction

Depressive disorders pose a substantial public health challenge, contributing to morbidity and mortality of those affected. While effective treatments exist, the varying success in individuals calls for a deeper understanding of the mechanisms of depression. This dissertation focuses on the connection between circadian rhythms, also known as bio-rhythms, and depression, investigating disturbances in sleep, physical activity, and rest-activity rhythms in depressed and non-depressed individuals.
To address knowledge gaps, objective and subjective measures were combined to identify depression more accurately. The results showed that subjective momentary affect measures outperformed objective movement data in distinguishing depressed from non-depressed individuals. Also, in depressed individuals, negative moods linger more at night, which is worsened by poor sleep but lessened by good sleep. Movement data revealed lower physical activity levels and dampened activity peaks in depressed individuals, particularly during current episodes. Surprisingly, recent, not current, depression correlated with the complexity of activity patterns. We found circadian rhythm changes close to transitions in depressive symptoms for some individuals but not for others, highlighting the necessary shift from a group- to individual-level approach. Lastly, exploring circadian rhythms in severely depressed patients undergoing chronotherapy, a treatment targeting circadian rhythm reset, revealed individual-level improvements in circadian rhythm disturbances, supporting the therapy's potential clinical application.
This dissertation improves our understanding of the link between depression and circadian rhythms. By combining various measures and adopting a personalized approach, we may identify and treat depression better in the future, providing hope for individuals suffering from this mental health condition.