Conference proceeding
Crafting a View of Self-Tracking Data in the Clinical Visit
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, v 2017-, pp 5800-5812
02 May 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
When self-tracking encounters clinical practices, the data is reshaped by goals and expertise that exist within a healthcare framework. To uncover these shaping practices, we provided a Fitbit Zip step-count sensor to nine patients with Parkinson's disease. Each patient wore the sensor for four weeks and then returned for a clinical visit with their neurologist. Our analysis focuses on this first clinical visit after four weeks of data had been collected. Our use of conversation analysis of both talk and action makes visible the practices engaged in by both collaborative members to 'craft a view' of the data toward shared decision making. Our findings reveal the deliberate guiding of attention to specific interpretations of the data through both talk and actions and we explain how our systematic analysis has uncovered tools for the mutually beneficial crafting practices of the clinician and patient.
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Details
- Title
- Crafting a View of Self-Tracking Data in the Clinical Visit
- Creators
- Helena M. Mentis - University of Maryland, Baltimore CountyAnita Komlodi - University of Maryland, Baltimore CountyKatrina Schrader - University of Maryland, BaltimoreMichael Phipps - University of Maryland, BaltimoreAnn Gruber-Baldini - University of Maryland School of Medicine, Baltimore, MD, USAKaren Yarbrough - University of Maryland, BaltimoreLisa Shulman - University of Maryland, BaltimoreACM
- Publication Details
- Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, v 2017-, pp 5800-5812
- Conference
- CHI '17: CHI Conference on Human Factors in Computing Systems
- Series
- ACM Conferences
- Publisher
- ACM
- Number of pages
- 13
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000426970505054
- Scopus ID
- 2-s2.0-85044246199
- Other Identifier
- 991021916516804721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Interdisciplinary Applications