Abstract

Abstract Introduction Hypersomnolence is commonly reported in Major Depressive Disorder with Seasonal Pattern (Seasonal Affective Disorder; SAD). However, self-reported hypersomnolence may conflate long sleep duration, daytime sleepiness, fatigue, increased time in bed, or maladaptive sleep cognitions, undermining treatment efforts. Methods Eighty-eight participants ages 18-65 years old were recruited during the winter (SAD = 43, Control = 45). Depression severity was assessed by a clinician rated interview, and self-reported hypersomnolence was determined by assessing self-reported sleep duration. Participants wore an Actiwatch for 4-14 days and completed self-report measures of daytime sleepiness and fatigue. We performed a hierarchical linear regression to determine which factors best explain self-reported winter hypersomnolence: actigraphic total sleep time (TST), time in bed (TIB), depression severity, sleepiness, or fatigue. Due to collinearity of TST and TIB, we separated those variables into two models predicting hypersomnolence. Results SAD participants endorsed greater hypersomnolence than controls during the winter (B = .714; p < .001). In model 1, TST (OR(1,14) = .024, p <.001) and daytime sleepiness (OR(1,14) = .208, p = .03) significantly predicted the presence of self-reported winter hypersomnolence above and beyond age, gender, depression, and fatigue. In model 2, only TIB (OR(1, 14) = .021, p = .001) was a significant predictor. Post-hoc analyses indicated that fatigue and depression severity significantly predicted self-reported hypersomnolence when entered separately into the model. Sleepiness accounted for the largest change in pseudo-R2 in bth models. Conclusion We found evidence for the multifaceted etiology of self-reported hypersomnolence. Daytime sleepiness, sleep duration, time in bed, and the shared variance between fatigue and depression severity all explained self-reported hypersomnolence. Treatment of hypersomnolence should include actigraphy, and should be individually tailored based on presentation. Support NIMH K.A.R. MH103303

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