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Arxiv
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Investigating the Relationship Between Physical Activity and Tailored Behavior Change Messaging: Connecting Contextual Bandit with Large Language Models
- Machine learning approaches, such as contextual multi-armed bandit algorithms, are being employed to reduce sedentary behavior by delivering personalized interventions to encourage physical activity.
- A hybrid approach combining contextual multi-armed bandit for selecting intervention types with large language models for personalizing message content is proposed in the study.
- Four intervention types, such as behavioral self-monitoring, gain-framed, loss-framed, and social comparison, are evaluated through motivational messages to increase motivation for physical activity and daily step count.
- The study assesses the effectiveness of different models in delivering daily messages, including contextual multi-armed bandit alone, large language models alone, combined contextual multi-armed bandit with large language model personalization, and equal randomization.
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