Conversational Agents in Behavioral Sleep Medicine: Designing Self-Report and Analytics Tools
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917237591375872 |
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| author | Mahmood, Amama Kim, Bokyung Zhao, Honghao Atwood, Molly E. Buenaver, Luis F. Smith, Michael T. Huang, Chien-Ming |
| author_facet | Mahmood, Amama Kim, Bokyung Zhao, Honghao Atwood, Molly E. Buenaver, Luis F. Smith, Michael T. Huang, Chien-Ming |
| contents | The sleep diary is a widely used clinical tool for understanding and treating sleep disorders in Behavioral Sleep Medicine (BSM); 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 explore conversational agents (CAs) as an alternative to traditional diary methods by designing a voice-based sleep diary and a specialist-facing analytics tool, and using them as design probes to understand how CAs might support BSM more broadly. Our multi-stage study with specialists comprised: (1) interviews to identify shortcomings of current text-based diaries, (2) iterative co-design of the conversational diary and analytics tool, and (3) focus groups to examine broader opportunities for CAs in BSM. This work offers empirical insights into how specialists envision CAs in clinical care and outlines design implications for integrating them into existing self-report practices and behavioral interventions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15378 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Conversational Agents in Behavioral Sleep Medicine: Designing Self-Report and Analytics Tools Mahmood, Amama Kim, Bokyung Zhao, Honghao Atwood, Molly E. Buenaver, Luis F. Smith, Michael T. Huang, Chien-Ming Human-Computer Interaction The sleep diary is a widely used clinical tool for understanding and treating sleep disorders in Behavioral Sleep Medicine (BSM); 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 explore conversational agents (CAs) as an alternative to traditional diary methods by designing a voice-based sleep diary and a specialist-facing analytics tool, and using them as design probes to understand how CAs might support BSM more broadly. Our multi-stage study with specialists comprised: (1) interviews to identify shortcomings of current text-based diaries, (2) iterative co-design of the conversational diary and analytics tool, and (3) focus groups to examine broader opportunities for CAs in BSM. This work offers empirical insights into how specialists envision CAs in clinical care and outlines design implications for integrating them into existing self-report practices and behavioral interventions. |
| title | Conversational Agents in Behavioral Sleep Medicine: Designing Self-Report and Analytics Tools |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.15378 |