Wearing, Thinking, and Moving: Testing the Feasibility of Fitness Tracking with Urban Youth
Abstract
Background: Wearable and mobile technologies are often used by people who wish to document their own health and lifestyle behaviors. The feasibility of health tracking among youth is unclear, particularly in low-resource communities where health strategies stand to have the greatest impact. Methods: Youth (n = 24) enrolled in an afterschool program in an urban school district were provided Fitbit physical activity monitors. Quantitative and qualitative data were collected over 6 months; logged data from Fitbit.com were examined to assess physical activity patterns and level engagement with the technology and focus groups were conducted to assess motivators and barriers to use. Results: Data logs revealed low continuous engagement that declined over time. Qualitative findings suggest that, when youth wore their devices, they noticed and engaged with their real-time device data in reflective ways. Some aspects of the device's form factor were problematic for these youth, and technology access, environmental constraints, and motivation were also barriers to continuous engagement. Translation to Health Education Practice: Taken together, these mixed methods findings suggest that effecting sustainable changes in youth behavior through health tracking alone is challenging. Adequate training, programmatic/staff support, technology access, and motivation may help sustain ongoing use and engagement. We recommend that health tracking in similar contexts be situated within educational curricula and/or a broader intervention that facilitates and motivates continuous engagement.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Wearable and mobile sensor technologies can be useful tools in precision nutrition research and practice.
“Wearable and mobile sensor technologies can be useful tools in precision nutrition research and practice”
From Wearable Technology to Quantify the Nutritional Intake of Adults: Validation Study (2020) · cites this paper as [13]
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 31 · Cited by 82
- Authors
- Schaefer, S. E., Ching, C. C., Breen, H., & German, J. B.
- Affiliations
- University of California, Davis (US)
- Corresponding author
- Schaefer, Sara E.
- Venue
- American Journal of Health Education
- Publisher
- Informa UK Limited
- Published
- 2016-01-02
- Volume
- 47
- Issue
- 1
- Pages
- 8-16
- ISSN
- 1932-5037 (ISSN-L)
- 2168-3751
- OpenAlex
- W2231777852
- Cited by
- 82
- References
- 31
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 1 · 2023: 7 · 2022: 7 · 2021: 11 · 2020: 17 · 2019: 11 · 2018: 13 · 2017: 7 · 2016: 2
- FWCI
- 20.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Health Education (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Keywords
- fitness tracking, wearable devices, Fitbit, children's physical activity, urban youth, underserved areas, technology engagement, barriers to use, motivation, after-school programs, health behavior change, health education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review