The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder

Background: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD...

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Detalles Bibliográficos
Autores: Matcham F, Carr E, Meyer N, White KM, Oetzmann C, Leightley D, Lamers F, Siddi S, Cummins N, Annas P, de Girolamo G, Haro JM, Lavelle G, Li Q, Lombardini F, Mohr DC, Narayan VA, Penninx BWHJ, Coromina M, Riquelme Alacid G, Simblett SK, Nica R, Wykes T, Brasen JC, Myin-Germeys I, Dobson RJB, Folarin AA, Ranjan Y, Rashid Z, Dineley J, Vairavan S, Hotopf M
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Fundació Sant Joan de Déu
Repositorio:r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
OAI Identifier:oai:fsjd.fundanetsuite.com:p26571
Acceso en línea:https://fsjd.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=26571
Access Level:acceso abierto
Palabra clave:Major Depressive Disorder
Sleep
Longitudinal
Wearable technology
Descripción
Sumario:Background: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. Methods: Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). Results: Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %. Limitations: Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected.

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