HCJan 14, 2021

Data Engagement Reconsidered: A Study of Automatic Stress Tracking Technology in Use

arXiv:2101.05450v11 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the issue of ineffective stress management for users of wearable or mobile tracking technologies, but it is incremental as it builds on existing self-tracking research by focusing on data engagement practices.

The paper tackles the problem of limited understanding of how automatic stress-tracking technologies are used in everyday life by conducting an empirical study with 17 users in China, identifying three key challenges: lack of immediate awareness, pre-required knowledge, and communal support that hinder effective usage.

In today's fast-paced world, stress has become a growing health concern. While more automatic stress tracking technologies have recently become available on wearable or mobile devices, there is still a limited understanding of how they are actually used in everyday life. This paper presents an empirical study of automatic stress-tracking technologies in use in China, based on semi-structured interviews with 17 users. The study highlights three challenges of stress-tracking data engagement that prevent effective technology usage: the lack of immediate awareness, the lack of pre-required knowledge, and the lack of corresponding communal support. Drawing on the stress-tracking practices uncovered in the study, we bring these issues to the fore, and unpack assumptions embedded in related works on self-tracking and how data engagement is approached. We end by calling for a reconsideration of data engagement as part of self-tracking practices with technologies rather than simply looking at the user interface.

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