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Self-tracking technologies empower people to build self-knowledge and insights across many domains and individual user contexts. However, individuals with severe motor disabilities are largely excluded from personal informatics systems. To bridge this gap, we designed and developed a first-of-a-kind power wheelchair (PWC) based multi-modal self-tracking system to support individuals with a recent spinal cord injury to track their pressure reliefs---a very frequent self-care activity to prevent pressure ulcers. We deployed this system with nine inpatient participants of a rehabilitation hospital and qualitatively evaluated the feasibility through their interactions with audio, visual, and haptic reminder modalities through observations and interviews. Our deployment and evaluation demonstrate the feasibility of creating chairable self-tracking systems to help facilitate independence and self-awareness of their self-care activity and the potential for personal informatics systems to be effectively designed so that they are useful for this population.
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A Model of Socially Sustained Self-Tracking for Food and Diet
Studies of personal informatics systems primarily examine people's use or non-use, but people often leverage other technology towards their long-term behavior change processes such as social platforms. We explore how tracking technologies and social platforms together help people build healthy eating behaviors by interviewing 18 people who use Chinese food journaling apps. We contribute a Model of Socially Sustained Self-Tracking in personal informatics, building on the past model of Personal Informatics and the learning components of Social Cognitive Theory. The model illustrates how people get advice from social platforms on when and how to track, transfer data to and apply knowledge from social platforms, evolve to use social platforms after tracking, and occasionally resume using tracking tools. Observational learning and enactive learning are central to these processes, with social technologies helping people to gain deeper and more reliable domain knowledge. We discuss how lapsing and abandoning of tracking can be viewed as evolving to social platforms, offering recommendations for how technology can better facilitate this evolution.
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- Award ID(s):
- 1850389
- PAR ID:
- 10602789
- Publisher / Repository:
- Association for Computing Machinery (ACM)
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 5
- Issue:
- CSCW2
- ISSN:
- 2573-0142
- Format(s):
- Medium: X Size: p. 1-32
- Size(s):
- p. 1-32
- Sponsoring Org:
- National Science Foundation
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