Adaptive System Architecture for Health Behavior Change: Harnessing the Power of Large Language Models

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dc.contributor.author Bhavsar, Maitry
dc.contributor.author Patel, Sachin
dc.date.accessioned 2023-12-26T18:40:30Z
dc.date.available 2023-12-26T18:40:30Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 9c4f41e5-d6d9-4218-a6a3-006a57a0fc4d
dc.identifier.uri https://hdl.handle.net/10125/106802
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Health Behavior Change Support Systems
dc.subject adaptive system
dc.subject architecture
dc.subject health behavior change
dc.subject large language model
dc.title Adaptive System Architecture for Health Behavior Change: Harnessing the Power of Large Language Models
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract In this paper, we present a novel adaptive system architecture for positive health behavior change. Leveraging an advanced large language model as a knowledgebase, the system automatically generates personalized behavior change plans based on individual needs. It utilizes established health behavior change theories to provide timely, context-specific interventions and nudges. We outline the system’s key components and functionality, demonstrating its adaptability through a structured walkthrough of ”Achieve healthy weight” and ”Manage Job-Related Stress” scenarios. We demonstrate that system dynamically adapts its recommendations based on users’ evolving behaviors, intentions, circumstances, and stage in the behavior change process, ensuring ongoing relevance and effectiveness. The paper highlights the potential of a large language model to serve as a knowledge base in health behavior change support systems.
dcterms.extent 10 pages
prism.startingpage 3464
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