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Updated: Dec 30, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Beyond novelty effect: a mixed-methods exploration into the motivation for long-term activity tracker use
Grace Shin1, Yuanyuan Feng2, Mohammad Hossein Jarrahi1
1School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Activity trackers can help manage health, but novelty effects may hinder long-term use. This study analyzed Fitbit data and user interviews to understand sustained engagement beyond the initial 3-month novelty period.
Area of Science:
- Consumer Health Informatics
- Human-Computer Interaction
- Digital Health
Background:
- Activity trackers offer quantified measurements for self-health management.
- Short-term studies often overlook the novelty effect and long-term usage motivations.
- Understanding sustained use is crucial for effective health technology development.
Purpose of the Study:
- To explore the impact of the novelty effect on activity tracker adoption.
- To identify motivations for sustained use of activity trackers beyond the novelty period.
- To provide design implications for future health-monitoring technologies.
Main Methods:
- Mixed-methods approach combining quantitative Fitbit log analysis and qualitative interviews.
- Study included 23 Fitbit users with a minimum of 2 months of device usage (69-1073 days).
- Behavioral understanding was developed through in-depth analysis of user data and experiences.
Main Results:
- Activity tracker usage exhibited two distinct stages: a novelty period and a long-term use period.
- The novelty period for Fitbit users in this study lasted approximately 3 months.
- Qualitative data revealed factors influencing continuous device use across different stages.
Conclusions:
- Long-term activity tracker use involves important dynamics beyond initial adoption.
- Findings contribute new knowledge to consumer health informatics and human-computer interaction.
- Design implications are provided to enhance future activity tracking technologies for sustained user engagement and effective health self-management.
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