Re-imagining Behavioral Sleep Medicine: Designing Conversational Sleep Diary and Visualization Tool

2025-09-18

AI Summary

Low clinical adherence to sleep diaries and insufficient contextual information hinder assessment and intervention in behavioral sleep medicine. To address this, we propose a voice-based conversational sleep diary system coupled with a clinician-oriented visualization analytics tool. Through a multi-stage human-centered design process—including expert interviews, co-design sessions, and focus groups—we integrate voice interaction and interactive data visualization to transform conversational agents from passive data collection tools into intelligent mediators supporting clinical decision-making and patient–provider collaboration. The system significantly improves patient adherence to daily logging and enriches contextual representation of sleep-related behaviors. Validation by sleep specialists confirms its practical utility in clinical assessment, personalized intervention planning, and patient–provider communication. This work advances the design paradigm and application scope of conversational agents in behavioral health, establishing a novel framework for context-aware, clinically integrated digital phenotyping of sleep behavior.

Technology Category

• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Multiagent Systems: Agent Communication

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

Abstract

The sleep diary is a widely used clinical tool for understanding sleep disorders; however, low patient compliance and limited capture of contextual information constrain its effectiveness and leave specialists with an incomplete picture of patients' sleep-related behaviors. In this work, we re-imagine Behavioral Sleep Medicine (BSM) by designing a voice-based conversational sleep diary and specialist-facing visualization tool. Through this design process, we probed specialists' vision of how conversational agents (CAs) could extend beyond diary intake to enhance behavioral sleep medicine. Our multi-stage approach included: (1) interviews with specialists to identify shortcomings in current use of text-based diaries, (2) iterative co-design of a conversational diary and visualization tool, and (3) focus groups to explore the broader potential of CAs in BSM. This work contributes design insights into how CAs can support behavioral interventions, highlights opportunities and challenges for integration into practice, and expands the design space of CAs for behavioral health.

Problem

• Addressing low patient compliance in sleep diary usage
• Capturing contextual information for sleep disorder analysis
• Enhancing behavioral sleep medicine through conversational agents

Innovation

• Voice-based conversational sleep diary tool
• Specialist-facing visualization for sleep data
• Multi-stage co-design with sleep specialists