JMIR Publications

ABSTRACT

Background:

One-third of the U.S. population experiences sleep loss, with the potential to impair physical and cognitive performance, and result in reduced 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 the 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:

Here, we aimed to enhance the capability of the 2B-Alert Web by providing the means for the tool 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, 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 U.S. 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 four simulated conditions, the 2B-Alert Web-proposed interventions increased average 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 U.S. 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/rest schedules. 2B-Alert Web is accessible at: .