Washington: Scientists have developed a web-based tool that optimises your caffeine intake, designing effective strategies to maximise alertness while avoiding excessive tea or coffee consumption.
Using multiple sleep-deprivation and shift-work scenarios, the researchers generated caffeine-consumption guidance using the open-access tool 2B-Alert Web 2.0, and then they compared the results with the US Army guidelines. The research, published in the journal Sleep, found that the solutions suggested by the quantitative caffeine optimisation tool either required on average 40 per cent less caffeine or enhanced alertness by an additional 40 per cent.
"Our 2B-Alert Web tool allows an individual, in our case our service members, to optimise the beneficial effects of caffeine while minimising its consumption," said Jaques Reifman, Senior Research Scientist for Advanced Medical Technology, serving at the US Army Medical Research and Development Command. Caffeine is the most widely consumed stimulant to counter the effects of sleep deprivation on alertness.
However, to be safe and most effective, the right amount must be consumed at the right time. The automated caffeine-guidance algorithm lets users input several factors: the desirable peak-alertness periods within a sleep/wake schedule, the minimum desirable level of alertness, and the maximum tolerable daily caffeine intake.
The 2B-Alert Web 2.0 tool allows users to predict the alertness of an "average" individual as a function of his or her sleep/wake schedule and caffeine schedule. It also enables users to automatically obtain optimal caffeine timing and doses to achieve peak alertness at the desired times, researchers said.
This freely available tool will have practical applications that extend beyond the realms of the military and the research lab, said Reifman. "For example, if you pull an all-nighter, need to be at peak alertness between, say, 9 am and 5 pm, and desire to consume as little caffeine as possible, when and how much caffeine should you consume?" he said. "This is the type of question 2B-Alert was designed to answer," Reifman said.
