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The relationship between chronotype and depressive symptoms: A meta-analysis.

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BACKGROUND Expanding our understanding of the factors that influence depression is crucial for prognosis and treatment. In light of increasing evidence of an association between disrupted circadian rhythms and affective… Click to show full abstract

BACKGROUND Expanding our understanding of the factors that influence depression is crucial for prognosis and treatment. In light of increasing evidence of an association between disrupted circadian rhythms and affective symptoms, a meta-analysis was used to examine the relationship between an eveningness chronotype and depression. METHODS Electronic searches of the PsycINFO, Medline, Scopus, and Google Scholar databases were conducted in February 2016. Relevant reviews, related journals, and reference lists were manually searched. Statistical data were reported or transformed to a Fisher's z correlational coefficient for effect size analysis. RESULTS Data from 36 studies (n =15734) met the inclusion criteria and were analysed under a random effects model. Nearly all included studies utilised the Composite Scale of Morningness (CSM) or the Morningness-Eveningness Questionnaire (MEQ) as a measure of chronotype. Overall effect size from 58 effect sizes was small (z=-.20; 95% CI: -.18 to -.23). Effect sizes based on the CSM were significantly larger than those based on the MEQ. There was no evidence of publication bias. LIMITATIONS The number of studies comparing different mood disorders or the potential moderating effects of gender and age were too few to draw conclusions regarding their respective effect sizes. Future research should utilise longitudinal designs to draw causal inferences on the directionality of this relationship. CONCLUSIONS Findings from this meta-analysis indicate an eveningness orientation is somewhat associated with more severe mood symptoms. Chronobiological approaches may contribute to the prevention and treatment of depressive disorders.

Keywords: chronotype; analysis; effect; symptoms meta; relationship; meta analysis

Journal Title: Journal of affective disorders
Year Published: 2017

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