Research Library

open-access-imgOpen Access2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study
Author(s)
Jaques Reifman,
Kamal Kumar,
Luke Hartman,
Andrew Frock,
T J Doty,
Thomas J. Balkin,
Sridhar Ramakrishnan,
Francisco G. Vital-Lopez
Publication year2022
Publication title
journal of medical internet research
Resource typeJournals
PublisherJMIR Publications
Background One-third of the US population experiences sleep loss, with the potential to impair physical and cognitive performance, reduce productivity, and imperil safety during work and daily activities. Computer-based fatigue-management systems with the ability to predict the effects of sleep schedules on alertness and identify safe and effective caffeine interventions that maximize its stimulating benefits could help mitigate cognitive impairment due to limited sleep. To provide these capabilities to broad communities, we previously released 2B-Alert Web, a publicly available tool for predicting the average alertness level of a group of individuals as a function of time of day, sleep history, and caffeine consumption. Objective In this study, we aim to enhance the capability of the 2B-Alert Web tool by providing the means for it to automatically recommend safe and effective caffeine interventions (time and dose) that lead to optimal alertness levels at user-specified times under any sleep-loss condition. Methods We incorporated a recently developed caffeine-optimization algorithm into the predictive models of the original 2B-Alert Web tool, allowing the system to search for and identify viable caffeine interventions that result in user-specified alertness levels at desired times of the day. To assess the potential benefits of this new capability, we simulated four sleep-deprivation conditions (sustained operations, restricted sleep with morning or evening shift, and night shift with daytime sleep) and compared the alertness levels resulting from the algorithm’s recommendations with those based on the US Army caffeine-countermeasure guidelines. In addition, we enhanced the usability of the tool by adopting a drag-and-drop graphical interface for the creation of sleep and caffeine schedules. Results For the 4 simulated conditions, the 2B-Alert Web–proposed interventions increased mean alertness by 36% to 94% and decreased peak alertness impairment by 31% to 71% while using equivalent or smaller doses of caffeine as the corresponding US Army guidelines. Conclusions The enhanced capability of this evidence-based, publicly available tool increases the efficiency by which diverse communities of users can identify safe and effective caffeine interventions to mitigate the effects of sleep loss in the design of research studies and work and rest schedules.
Subject(s)alertness , astronomy , cognition , computer science , environmental health , evening , human–computer interaction , medicine , operating system , physics , population , psychiatry , psychological intervention , sleep deprivation , sleep restriction , usability , workload
Language(s)English
SCImago Journal Rank1.446
H-Index142
eISSN1439-4456
pISSN1438-8871
DOI10.2196/29595

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