Trial reportSleep2016
A Unified Model of Performance: Validation of its Predictions across Different Sleep/Wake Schedules.
Trial report in Sleep, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05588934 (A Head-to-Head Comparison of the 2B-Alert Caffeine Optimization Algorithm Versus Standard Caffeine Dosing on Performance During Sleep Deprivation), which is not on this map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
A Head-to-Head Comparison of the 2B-Alert Caffeine Optimization Algorithm Versus Standard Caffeine Dosing on Performance During Sleep Deprivation (2B-2)
Who cites it
12 citing papers in PubMed.
- Trial
- Neural indicators of sleep loss and sleep propensity in male military trainees: Insights from dry-electrode EEG-An exploratory study.Physiological reports · 2025Article
- Navigating the night: evaluating and accessing wearable sleep trackers for clinical use.Sleep · 2024Article
- Social dimensions impact individual sleep quantity and quality.Scientific reports · 2023Article
- 2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study.Journal of medical Internet research · 2022Article
- The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing.NPJ digital medicine · 2021Article
- Recent advances in modeling sleep: from the clinic to society and disease.Current opinion in physiology · 2020Article
- 2B-Alert App: A mobile application for real-time individualized prediction of alertness.Journal of sleep research · 2019Article
- Sleep Modelling across Physiological Levels.Clocks & sleep · 2019Review
- Improved Mental Acuity Forecasting with an Individualized Quantitative Sleep Model.Frontiers in neurology · 2017Article
- Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
objectivesHistorically, mathematical models of human neurobehavioral performance developed on data from one sleep study were limited to predicting performance in similar studies, restricting their practical utility. We recently developed a unified model of performance (UMP) to predict the effects of the continuum of sleep loss-from chronic sleep restriction (CSR) to total sleep deprivation (TSD) challenges-and validated it using data from two studies of one laboratory. Here, we significantly extended this effort by validating the UMP predictions across a wide range of sleep/wake schedules from different studies and laboratories.
methodsWe developed the UMP on psychomotor vigilance task (PVT) lapse data from one study encompassing four different CSR conditions (7 d of 3, 5, 7, and 9 h of sleep/night), and predicted performance in five other studies (from four laboratories), including different combinations of TSD (40 to 88 h), CSR (2 to 6 h of sleep/night), control (8 to 10 h of sleep/night), and nap (nocturnal and diurnal) schedules.
resultsThe UMP accurately predicted PVT performance trends across 14 different sleep/wake conditions, yielding average prediction errors between 7% and 36%, with the predictions lying within 2 standard errors of the measured data 87% of the time. In addition, the UMP accurately predicted performance impairment (average error of 15%) for schedules (TSD and naps) not used in model development.
conclusionsThe unified model of performance can be used as a tool to help design sleep/wake schedules to optimize the extent and duration of neurobehavioral performance and to accelerate recovery after sleep loss.
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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.