ArticleJournal of medical Internet research2023
Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Telemonitored sleep quality and daily activity are associated with mental health outcomes among Japanese workers.Scientific reports · 2026Article
- Effect of lemborexant on sleep-wake state discrepancy in participants with insomnia disorder.Psychopharmacology · 2026Article
- Sleep Architecture Alterations Following High-Dose Steroid Pulse Therapy: A Pilot Study Using a Portable Electroencephalogram-Based Device.Neuropsychopharmacology reports · 2025Article
- A bibliometric analysis of wearable device research in sleep science: Trends and hotspots.Medicine · 2025Review
- Revealing sleep and pain reciprocity with wearables and machine learning.Communications medicine · 2025Review
- Validation of a Wireless, Self-Applied Device for Sleep Recording in the Paediatric Population.Nature and science of sleep · 2025Article
- Developing a Sleep Algxorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study.JMIR mental health · 2024Observational
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive.
objectiveThis study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders.
methodsWe analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs.
resultsThe findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments.
conclusionsOur study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.
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