The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Users' experiences of wearable activity trackers: a cross-sectional study
Open accessAbstract
BACKGROUND: Wearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users' experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use. METHODS: A cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests. RESULTS: Participants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18-74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5-7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51-81%) more commonly than they had their diet (14-40%) or sleep (11-24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties. CONCLUSIONS: Results suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Wearable activity trackers offer an appealing, low-cost tool to address physical inactivity.”
From Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses. (2022) · cites this paper as [4]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Lee, I.-M., Shiroma, E. J., Lobelo, F., Puska, P., Blair, S. N., & Katzmarzyk, P. T. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61031-9 · Cited by 8,215
Fit Yourself and Take Your Lungs to Heart
Palange, P., & Bonini, M. (2013) · Respiration · doi:10.1159/000350831 · Cited by 2,780
Systematic review of the validity and reliability of consumer-wearable activity trackers
Evenson, K. R., Goto, M. M., & Furberg, R. D. (2015) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-015-0314-1 · Cited by 1,232
Meerlo, P., Sgoifo, A., & Suchecki, D. (2008) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2007.07.007 · Cited by 948
Effects of poor and short sleep on glucose metabolism and obesity risk
Spiegel, K., Tasali, E., Leproult, R., & Van Cauter, E. (2009) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2009.23 · Cited by 857
Ferguson, T., Rowlands, A. V., Olds, T., & Maher, C. (2015) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-015-0201-9 · Cited by 468
Self-citationIt's not that i don't have problems, i'm just not putting them on facebook
Newman, M., Lauterbach, D., Munson, S. A., Resnick, P., & Morris, M. E. (2011) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/1958824.1958876 · Cited by 422
Persuasive technology in the real world
Fritz, T., Huang, E. M., Murphy, G. C., & Zimmermann, T. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557383 · Cited by 385
Guertler, D., Vandelanotte, C., Kirwan, M., & Duncan, M. J. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4339 · Cited by 147
Wellbeing in the Making: Peoples' Experiences with Wearable Activity Trackers
Karapanos, E., Gouveia, R., Hassenzahl, M., & Forlizzi, J. (2016) · Psychology of Well-Being · doi:10.1186/s13612-016-0042-6 · Cited by 124
Alley, S., Schöeppe, S., Guertler, D., Jennings, C. A., Duncan, M. J., & Vandelanotte, C. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-011243 · Cited by 108
Why a Global Strategy on Diet, Physical Activity and Health?
Waxman, A. (2005) · KARGER eBooks · doi:10.1159/000088302 · Cited by 40
Chang, R. C.-S., Lu, H., Yang, P., & Luarn, P. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.5637 · Cited by 35
Martinson, W. (2007) · Journal of Human Nutrition and Dietetics · doi:10.1111/j.1365-277x.2007.00754.x · Cited by 3
Research works printed but not linked: 1
- Ferguson T. Can consumer-level, body-worn accelerometers accurately measure physical activity in healthy adults in free-living conditions, and how easy are they to use? Honours thesis. Adelaide: University of South Australia; 2014.
Cited by
Sorted by citations
Ferguson, T., Olds, T., Curtis, R., Blake, H., Crozier, A. J., Dankiw, K., Dumuid, D., Kasai, D., O'Connor, E., Virgara, R., et al. (2022) · The Lancet Digital Health · doi:10.1016/s2589-7500(22)00111-x · Cited by 605
Self-citationChandrasekaran, R., Katthula, V., & Moustakas, E. (2020) · Journal of Medical Internet Research · doi:10.2196/22443 · Cited by 291
Attig, C., & Franke, T. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.025 · Cited by 187
Chan, A., Chan, D., Lee, H., Ng, C. C., & Yeo, A. H. L. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104696 · Cited by 129
Edney, S., Ryan, J. C., Olds, T., Monroe, C., Fraysse, F., Vandelanotte, C., Plotnikoff, R., Curtis, R., & Maher, C. (2019) · Journal of Medical Internet Research · doi:10.2196/14645 · Cited by 104
Self-citation
Metadata
- Authors
- Maher, C., Ryan, J., Ambrosi, C., & Edney, S.
- Affiliations
- University of South Australia (AU)
- Corresponding author
- Maher, Carol
- Venue
- BMC Public Health
- Published
- 2017-11-15
- Volume
- 17
- Issue
- 1
- Pages
- 880-880
- ISSN
- 1471-2458 (ISSN-L)
- PMC
- PMC5688726
- OpenAlex
- W2770689260
- Cited by
- 180
- References
- 14
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 18 · 2023: 24 · 2022: 18 · 2021: 30 · 2020: 28 · 2019: 29 · 2018: 7
- FWCI
- 28.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Public Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Australasian Journal of Paramedicine (submittedVersion, cc-by)
- National University of Singapore (submittedVersion)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion, cc-by)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- University of South Australia
- 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 › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Keywords
- wearable activity trackers, user experience, physical activity, diet, sleep, real-time feedback, battery life, Fitbit, Garmin, technology adoption, health behavior change
- MeSH terms
- Fitness Trackers, Wearable Electronic Devices, Adolescent, Adult, Aged, Australia, Cross-Sectional Studies, Diet, Female, Humans, Male, Middle Aged, Surveys and Questionnaires, Sleep, Health Behavior, Exercise, Young Adult, Social Media
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
