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Behavioral Informatics and Computational Modeling in Support of Proactive Health Management and Care

机译:行为信息学和计算模型支持主动式健康管理和护理

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摘要

Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge. In this paper, we describe a vision and an approach to improve health behavior interventions using the tools of behavioral informatics, an emerging transdisciplinary research domain based on system-theoretic principles in combination with behavioral science and information technology. The field of behavioral informatics has the potential to optimize interventions through monitoring, assessing, and modeling behavior in support of providing tailored and timely interventions. We describe the components of a closed-loop system for health interventions. These components range from fine grain sensor characterizations to individual-based models of behavior change. We provide an example of a research health coaching platform that incorporates a closed-loop intervention based on these multiscale models. Using this early prototype, we illustrate how the optimized and personalized methodology and technology can support self-management and remote care. We note that despite the existing examples of research projects and our platform, significant future research is required to convert this vision to full-scale implementations.
机译:与健康相关的行为是健康和生活质量的最重要决定因素。改善健康行为是增强健康结果并缓解人口老龄化和慢性病扩散所带来的日益严峻挑战的有效途径。尽管很难大规模地持续改善健康行为,但技术与行为科学的交汇处的进步可能为应对这一挑战提供了工具。在本文中,我们描述了一种使用行为信息学工具改善健康行为干预措施的愿景和方法,这是一种基于系统理论原理并结合行为科学和信息技术的新兴跨学科研究领域。行为信息学领域具有通过监视,评估和建模行为来优化干预措施的潜力,以支持提供量身定制的及时干预措施。我们描述了用于健康干预的闭环系统的组件。这些组件的范围从细晶粒传感器表征到行为改变的基于个体的模型。我们提供了一个研究健康指导平台的示例,该平台结合了基于这些多尺度模型的闭环干预。使用这个早期的原型,我们说明了优化的个性化方法和技术如何支持自我管理和远程护理。我们注意到,尽管存在研究项目和我们平台的现有示例,但仍需要进行大量的未来研究,才能将这一愿景转化为全面的实施方案。

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