Abstract
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.
Original language | English |
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Pages (from-to) | 2763-2775 |
Journal | IEEE Transactions on Biomedical Engineering |
Volume | 62 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2016 |
MoE publication type | A1 Journal article-refereed |
Keywords
- behavioral informatics
- computational models
- health behavior change
- multiscale
- self-management
- wearable sensors