ArticleNPJ digital medicine2021
Trait-like nocturnal sleep behavior identified by combining wearable, phone-use, and self-report data.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The trial behind it
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
20 citing papers in PubMed.
- Human Circadian Rhythm Through the Lens of GIScience: A Systematic Review.Research square · 2026Article
- Prediction of cognitive performance by demographics, sleep, and brain morphometry: machine learning findings from ENIGMA-Sleep Working Group.Research square · 2026Article
- The Digital Exposome: A Life Course Framework for Health in the Digital Age.Journal of medical Internet research · 2026Article
- Predicting daily cognition and lifestyle behaviors for older adults using smart home data and ecological momentary assessment.The Clinical neuropsychologist · 2026Article
- Bedtime electronic device use and sleep quality in Chinese young adults: a longitudinal study.BMC public health · 2026Article
- Full-day sleep pattern analysis in common mental disorders: Leveraging highly discrepant recordings from two consumer tracking devices.PloS one · 2026Article
- Article
- Sleep, Well-Being, and Cognition in Medical Interns on a Float or Overnight Call Schedule.JAMA network open · 2024Observational
- Five million nights: temporal dynamics in human sleep phenotypes.NPJ digital medicine · 2024Article
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- Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study.JMIR formative research · 2023Article
- Quality of Sleep Data Validation From the Xiaomi Mi Band 5 Against Polysomnography: Comparison Study.Journal of medical Internet research · 2023Article
- Smartphone Keyboard Interaction Monitoring as an Unobtrusive Method to Approximate Rest-Activity Patterns: Experience Sampling Study Investigating Interindividual and Metric-Specific Variations.Journal of medical Internet research · 2023Article
- Early morning university classes are associated with impaired sleep and academic performance.Nature human behaviour · 2023Article
- Smartphone-Tracked Digital Markers of Momentary Subjective Stress in College Students: Idiographic Machine Learning Analysis.JMIR mHealth and uHealth · 2023Article
- Associations of smartphone usage patterns with sleep and mental health symptoms in a clinical cohort receiving virtual behavioral medicine care: a retrospective study.Sleep advances : a journal of the Sleep Research Society · 2023Article
- Working-from-home persistently influences sleep and physical activity 2 years after the Covid-19 pandemic onset: a longitudinal sleep tracker and electronic diary-based study.Frontiers in psychology · 2023Article
- Psychological Research on Sleep Problems and Adjustment of Working Hours during Teleworking in the COVID-19 Pandemic: An Exploratory Study.International journal of environmental research and public health · 2022Article
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Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using polysomnography over multiple weeks to characterize an individual's habitual sleep behavior while accurate, is difficult to upscale. As an alternative, we integrated sleep measurements from a consumer sleep-tracker, smartphone-based ecological momentary assessment, and user-phone interactions in 198 participants for 2 months. User retention averaged >80% for all three modalities. Agreement in bed and wake time estimates across modalities was high (rho = 0.81-0.92) and were adrift of one another for an average of 4 min, providing redundant sleep measurement. On the ~23% of nights where discrepancies between modalities exceeded 1 h, k-means clustering revealed three patterns, each consistently expressed within a given individual. The three corresponding groups that emerged differed systematically in age, sleep timing, time in bed, and peri-sleep phone usage. Hence, contrary to being problematic, discrepant data across measurement modalities facilitated the identification of stable interindividual differences in sleep behavior, underscoring its utility to characterizing population sleep and peri-sleep behavior.
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Registered trials
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.