ArticleJournal of affective disorders2018
Daytime midpoint as a digital biomarker for chronotype in bipolar disorder.
Article in Journal of affective disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- A systematic review and meta-analysis of sleep and circadian rhythms disturbances in individuals at high-risk of developing or with early onset of bipolar disorders.Neuroscience and biobehavioral reviews · 2022Pooled it
- Toward a Digital Future in Bipolar Disorder Assessment: A Systematic Review of Disruptions in the Rest-Activity Cycle as Measured by Actigraphy.Frontiers in psychiatry · 2022Pooled it
- Rest-Activity Timing Phenotypes and Mental Health: A Longitudinal Analysis of 24-Hour Accelerometry in Population-Based Cohorts.Health data science · 2026Article
- Metabolic plasticity: an evolutionary perspective on metabolic and circadian dysregulation in bipolar disorder.Molecular psychiatry · 2025Review
- Chronotype, cognitive outcomes, and neural dynamics: recent evidence and potential mechanisms with implications for perioperative period.Frontiers in neuroscience · 2025Review
- Underlying biological mechanisms of emotion dysregulation in bipolar disorder.Frontiers in psychiatry · 2025Review
- Characterisation of the genetic relationship between the domains of sleep and circadian-related behaviours with substance use phenotypes.Addiction biology · 2022Article
- Chronotype, circadian rhythm, and psychiatric disorders: Recent evidence and potential mechanisms.Frontiers in neuroscience · 2022Review
- Registration of 24-hour accelerometric rest-activity profiles and its application to human chronotypes.Biological rhythm research · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundBipolar 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.
methodsSixty-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).
resultsBD 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.
conclusionsWrist 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.