Shakra: Tracking and Sharing Daily Activity Levels with Unaugmented Mobile Phones
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Previous research has highlighted the benefits of stand-alone app-based interventions on individuals' awareness of eating behaviors and physical activity levels.
“Previous research has highlighted the benefits of stand-alone app-based interventions on individuals’ awareness of their eating behaviors and physical activity levels [15,16,42,45,46].”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [46]
Ability to integrate app use into one's daily routine is an important potential facilitator and/or barrier to intervention usage.
“The impact of users’ availability to interact with the app and take advantage of free moments echoes reports that ability to integrate app use into one’s daily routine is an important potential facilitator and/or barrier to intervention usage [16,24,32,46].”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [46]
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- Authors
- Anderson, I., Maitland, J., Sherwood, S., Barkhuus, L., Chalmers, M., Hall, M., Brown, B., & Muller, H.
- Affiliations
- University of Bristol (GB)
- University of Glasgow (GB)
- Corresponding author
- Anderson, Ian
- Venue
- Mobile Networks and Applications
- Published
- 2007-06
- Volume
- 12
- Issue
- 2-3
- Pages
- 185-199
- ISSN
- 1383-469X (ISSN-L)
- 1572-8153
- OpenAlex
- W2068021035
- Cited by
- 223
- References
- 20
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 5 · 2023: 4 · 2022: 1 · 2021: 9 · 2020: 13 · 2019: 11 · 2018: 24 · 2017: 14 · 2016: 14 · 2015: 23 · 2014: 22 · 2013: 19 · 2012: 20
- FWCI
- 12.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Mobile Networks and Applications (publishedVersion)
- Explore Bristol Research (publishedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Keywords
- mobile devices, activity monitoring, exercise monitoring, health promotion, artificial neural networks, motion detection, hidden Markov models, task modeling, unsupervised calibration, social sharing, motivation
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