Self-Tracking for Chronic Condition Management: Exploring User Agency in Sensor-Connected Diabetes Apps

Tunis, Rachel

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https://hdl.handle.net/2142/115179 Copy

Description

Title

Self-Tracking for Chronic Condition Management: Exploring User Agency in Sensor-Connected Diabetes Apps

Author(s)

Tunis, Rachel

Contributor(s)

Sanfilippo, Madelyn

Issue Date

2022-10-29

Keyword(s)

• self-tracking
• users
• agency
• accessibility

Abstract

Digital self-tracking has received a great deal of both praise and criticism over the past several years as uptake of selftracking applications and devices has grown rapidly. Academics, technologists, and health professionals alike have pointed out the potential for self-tracking devices to engage patients in their healthcare in a more meaningful way and provide new tools that could positively impact their strategies for managing their health. Further, since self-tracking devices collect large amounts of data in real-time, self-trackers present opportunities for more personalized care; that is, they could identify unique patterns in individuals’ health profiles that could be targeted for more effective health management. However, particularly in academic literature and the media, a variety of concerns related to self-trackers have surfaced. For example, critical analyses describe concerns with the wide-reaching data collection practices of companies that develop self-trackers, enabling them to make advanced predictions and classifications about users with relatively few guardrails and regulations protecting this sensitive consumer data. Critics, including health experts, also point out that the accuracy and reliability of self-tracking apps and devices are often questionable. Further, there is often a lack of transparency about how algorithms, personalized features, predictions, and classifications are constructed and determined.

Type of Resource

text

Language

en

Handle URL

https://hdl.handle.net/2142/115179

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