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03766nam a2200685Ia 4500 |
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10.1016-j.jad.2018.08.032 |
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220706s2018 CNT 000 0 und d |
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|a 01650327 (ISSN)
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|a Daytime midpoint as a digital biomarker for chronotype in bipolar disorder
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|b Elsevier B.V.
|c 2018
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|z View Fulltext in Publisher
|u https://doi.org/10.1016/j.jad.2018.08.032
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|a Background: Bipolar disorder (BD) is associated with later sleep and daily activity (evening rather than morning chronotype). Objective chronotype identification (e.g., based on actigraphs/smartphones) has potential utility, but to date, chronotype has mostly been assessed by questionnaires. Given the ubiquity of accelerometer-based devices (e.g. actigraphs/smartphones) worn/used during daytime and tendency to recharge rather than wear at night, we assessed chronotype using daytime (rather than sleep) interval midpoints. Methods: Sixty-one participants with BD type I (BD-I) or II (BD-II) and 61 healthy controls completed 25–50 days of continuous actigraphy. The Composite Scale of Morningness (CSM) was completed by a subset of this group. Daytime activity midpoint was calculated for each daytime interval, excluding naps. Evening chronotype was defined as having a daytime interval midpoint at or after 16:15:00 (4:15:00 PM). Results: BD versus controls had delayed daytime midpoint (mean ± standard deviation) (16:49:07 ± 01:26:19 versus 16:12:51 ± 01:02:14, p < 0.01), and greater midpoint variability (73.3 ± 33.9 min versus 58.1 ± 18.3 min, p < 0.01). Stratifying by gender and age, females and adolescents with BD had delayed and more variable daytime midpoints versus controls. Adults with BD had greater midpoint variability than controls. Within-person mean and standard deviations of daytime midpoints were highly correlated with sleep midpoints (r = 0.99, p < 0.01 and r = 0.86, p < 0.01, respectively). Daytime midpoint mean was also significantly correlated with the CSM (r = -0.56, p < 0.01). Limitations: Small sample size; analyses not fully accounting for daytime napping. Conclusions: Wrist actigraphy for determination of daytime midpoints is a potential tool to identify objective chronotype. Exploration of the use of consumer devices (wearables/smartphones) is needed. © 2018 Elsevier B.V.
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|a Actigraphy
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|a actimetry
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|a adolescent
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|a Adolescent
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|a adult
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|a Adult
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|a Article
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|a biological marker
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|a Biomarkers
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|a bipolar disorder
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|a Bipolar disorder
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|a Bipolar Disorder
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|a bipolar I disorder
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|a bipolar II disorder
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|a Chronobiology Disorders
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|a chronotropism
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|a Chronotype
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|a circadian rhythm
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|a Circadian Rhythm
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|a Composite Scale of Morningness
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|a controlled study
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|a Daytime
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|a female
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|a Female
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|a human
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|a Humans
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|a major clinical study
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|a male
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|a Male
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|a middle aged
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|a Middle Aged
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|a priority journal
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|a psychology
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|a questionnaire
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|a rating scale
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|a sleep
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|a Sleep
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|a sleep disorder
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|a Surveys and Questionnaires
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|a young adult
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|a Young Adult
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|a Depp, C.A.
|e author
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|a Gershon, A.
|e author
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|a Kaufmann, C.N.
|e author
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|a Ketter, T.A.
|e author
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|a Miller, S.
|e author
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|a Zeitzer, J.M.
|e author
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|t Journal of Affective Disorders
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