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Informatics 2017, 4(1), 5; doi:10.3390/informatics4010005

Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables

1
Academy for Digital Entertainment, NHTV Breda University of Applied Sciences, Breda 4817 JT, The Netherlands
2
Business Management Division, Universidad Carlos III de Madrid, Madrid 28903, Spain
3
Experience Dynamics, Inc., Portland, OR 97213, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Francisco Javier Falcone Lanas
Received: 11 October 2016 / Revised: 11 January 2017 / Accepted: 19 January 2017 / Published: 22 January 2017
(This article belongs to the Special Issue Smart Health 2016)
View Full-Text   |   Download PDF [1250 KB, uploaded 24 January 2017]   |  

Abstract

Wearable fitness trackers have gained a new level of popularity due to their ambient data gathering and analysis. This has signalled a trend toward self-efficacy and increased motivation among users of these devices. For consumers looking to improve their health, fitness trackers offer a way to more readily gain motivation via the personal data-based insights the devices offer. However, the user experience (UX) that accompanies wearables is critical to helping users interpret, understand, gain motivation and act on their data. Despite this, there is little evidence as to specific aspects of fitness tracker user engagement and long-term motivation. We report on a 4-week situated diary study and Healthcare Technology Self-efficacy (HTSE) questionnaire assessment of 34 users of two popular American fitness trackers: JawBone and FitBit. The study results illustrate design implications and requirements for fitness trackers and other self-efficacy mobile healthcare applications. View Full-Text
Keywords: fitness tracking; mobile healthcare; user engagement; motivation; self-efficacy; wearable technology; mHealth heuristics fitness tracking; mobile healthcare; user engagement; motivation; self-efficacy; wearable technology; mHealth heuristics
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Asimakopoulos, S.; Asimakopoulos, G.; Spillers, F. Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables. Informatics 2017, 4, 5.

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