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Engaging with self-tracking applications: how do users respond to their performance data?

by Research Team | May 30, 2022 | Research Publications

Author(s):

  • Alivelu Mukkamala
  • Mimmi Sjöklint
  • Matthias Trier

Abstract:

Self-tracking devices and applications have become popular in recent years and changed user behaviour. Previous research has primarily focused on the adoption of self-tracking devices and their effects on self-assessment. As adoption increases, user engagement becomes prominent for the continuous use of the devices and the applications. In this study, we focus on user engagement with activity tracking applications, e.g., Fitbit Flex and Jawbone Up that offer data on user performance. We collected data from semi-structured interviews with 54 participants. We propose a process model comprising four stages which involve distinct user interactions with data: review, react, reflect, and respond. We advance research in this domain by the proposed process model that explicates user engagement in two cases: when the user encounters satisfactory or unsatisfactory results. In the latter case, we depict four response tactics when users are confronted with unsatisfactory results.

Documentation:

https://doi.org/10.1080/0960085X.2022.2081096

Engaging with Self-Tracking Applications: How do Users Respond to Their Performance Data

by Research Team | May 30, 2022 | Research Publications

Author(s):

  • Ioanna Constantioua
  • Alivelu Mukkamala
  • Mimmi Sjöklint
  • Matthias Trier

Abstract:

Self-tracking devices and applications have become popular in recent years and changed user behaviour. Previous research has primarily focused on the adoption of self-tracking devices and their effects on self-assessment. As adoption increases, user engagement becomes prominent for the continuous use of the devices and the applications. In this study, we focus on user engagement with activity tracking applications, e.g., Fitbit Flex and Jawbone Up that offer data on user performance. We collected data from semi-structured interviews with 54 participants. We propose a process model comprising four stages which involve distinct user interactions with data: review, react, reflect, and respond. We advance research in this domain by the proposed process model that explicates user engagement in two cases: when the user encounters satisfactory or unsatisfactory results. In the latter case, we depict four response tactics when users are confronted with unsatisfactory results.

Documentation:

https://doi.org/10.1080/0960085X.2022.2081096

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