Facilitating Individuals' Sensemaking about Sedentary Behavior via Contextualized Data
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908555917918208 |
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| author | Xu, Kefan Arriaga, Rosa I. |
| author_facet | Xu, Kefan Arriaga, Rosa I. |
| contents | The sedentary lifestyle increases individuals' risks of developing chronic diseases. To support individuals to be more physically active, we propose a mobile system, MotionShift, that presents users with step count data alongside contextual information (e.g., location, weather, calendar events, etc.) and self-reported records. By implementing and deploying this system, we aim to understand how contextual information impacts individuals' sense-making on sensor-captured data and how individuals leverage contextualized data to identify and reduce sedentary activities. The findings will advance the design of context-aware personal informatics systems, empowering users to derive actionable insights from sensor data while minimizing interpretation biases, ultimately promoting opportunities to be more physically active. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_19420 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Facilitating Individuals' Sensemaking about Sedentary Behavior via Contextualized Data Xu, Kefan Arriaga, Rosa I. Human-Computer Interaction The sedentary lifestyle increases individuals' risks of developing chronic diseases. To support individuals to be more physically active, we propose a mobile system, MotionShift, that presents users with step count data alongside contextual information (e.g., location, weather, calendar events, etc.) and self-reported records. By implementing and deploying this system, we aim to understand how contextual information impacts individuals' sense-making on sensor-captured data and how individuals leverage contextualized data to identify and reduce sedentary activities. The findings will advance the design of context-aware personal informatics systems, empowering users to derive actionable insights from sensor data while minimizing interpretation biases, ultimately promoting opportunities to be more physically active. |
| title | Facilitating Individuals' Sensemaking about Sedentary Behavior via Contextualized Data |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.19420 |