Wearable Meets LLM for Stress Management: A Duoethnographic Study Integrating Wearable-Triggered Stressors and LLM Chatbots for Personalized Interventions
Journal:
arXiv
Published Date:
Feb 24, 2025
Abstract
We use a duoethnographic approach to study how wearable-integrated LLM
chatbots can assist with personalized stress management, addressing the growing
need for immediacy and tailored interventions. Two researchers interacted with
custom chatbots over 22 days, responding to wearable-detected physiological
prompts, recording stressor phrases, and using them to seek tailored
interventions from their LLM-powered chatbots. They recorded their experiences
in autoethnographic diaries and analyzed them during weekly discussions,
focusing on the relevance, clarity, and impact of chatbot-generated
interventions. Results showed that even though most events triggered by the
wearable were meaningful, only one in five warranted an intervention. It also
showed that interventions tailored with brief event descriptions were more
effective than generic ones. By examining the intersection of wearables and
LLM, this research contributes to developing more effective, user-centric
mental health tools for real-time stress relief and behavior change.
