2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study.

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 sch...

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Publicado en:Journal of Medical Internet Research Vol. 24; no. 1
Autores principales: Reifman, Jaques, Kumar, Kamal, Hartman, Luke, Frock, Andrew, Doty, Tracy J, Balkin, Thomas J, Ramakrishnan, Sridhar, Vital-Lopez, Francisco G
Formato: research Journal Article
Publicado: JMIR Publications Inc. Jan2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2022
      vid: 24
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      pub: JMIR Publications Inc.
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        atl: 2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study.
      aug:
        au:
          Reifman, Jaques
          Kumar, Kamal
          Hartman, Luke
          Frock, Andrew
          Doty, Tracy J
          Balkin, Thomas J
          Ramakrishnan, Sridhar
          Vital-Lopez, Francisco G
        affil: 1 Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, United States
      sug:
        subj:
          Social Media
          Caffeine Pharmacodynamics
          Sleep
          Psychomotor Performance
          Human
          Attention
          Wakefulness
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Validation Studies
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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