The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Clinical use of objective measures of physical activity
Abstract
With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.
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“In contrast to self-reports, wearable accelerometers enable the capturing of all components (intensity, type, or duration) of PA spread throughout the day and more accurately measure SB by offsetting recall and social desirability biases.22”
Citations
Cites
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The pandemic of physical inactivity: global action for public health
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Physical Fitness and All-Cause Mortality: A Prospective Study of Healthy Men and Women
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Using Pedometers to Increase Physical Activity and Improve Health: A Systematic Review
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., Stave, C. D., Olkin, I., & Sirard, J. R. (2007) · JAMA · doi:10.1001/jama.298.19.2296 · Cited by 2,064
American Academy of Family Physicians
(1966) · New England Journal of Medicine · doi:10.1056/nejm196611172752014 · Cited by 1,947
Comparison of Accelerometer Cut Points for Predicting Activity Intensity in Youth
TROST, S. G., LOPRINZI, P. D., MOORE, R., & PFEIFFER, K. A. (2011) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318206476e · Cited by 1,360
Methods of Measurement in epidemiology: Sedentary Behaviour
Atkin, A. J., Gorely, T., Clemes, S. A., Yates, T., Edwardson, C., Brage, S., Salmon, J., Marshall, S. J., & Biddle, S. J. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys118 · Cited by 518
Activity, Activity, Activity: Rethinking Our Physical Therapy Approach to Cerebral Palsy
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A Meta-Analysis of Pedometer-Based Walking Interventions and Weight Loss
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Cited by
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Hampl, S. E., Hassink, S. G., Skinner, A. C., Armstrong, S. C., Barlow, S. E., Bolling, C. F., Avila Edwards, K. C., Eneli, I., Hamre, R., Joseph, M. M., et al. (2023) · Pediatrics · doi:10.1542/peds.2022-060640 · Cited by 1,389
Sedentary behaviour and the risk of depression: a meta-analysis
Zhai, L., Zhang, Y., & Zhang, D. (2015) · British Journal of Sports Medicine · doi:10.1136/bjsports-2014-093613 · Cited by 500
Howlett, N., Trivedi, D., Troop, N. A., & Chater, A. M. (2019) · Translational Behavioral Medicine · doi:10.1093/tbm/iby010 · Cited by 448
Lobelo, F., Rohm Young, D., Sallis, R., Garber, M. D., Billinger, S. A., Duperly, J., Hutber, A., Pate, R. R., Thomas, R. J., Widlansky, M. E., et al. (2018) · Circulation · doi:10.1161/cir.0000000000000559 · Cited by 402
Validity of the Fitbit activity tracker for measuring steps in community-dwelling older adults
Paul, S. S., Tiedemann, A., Hassett, L. M., Ramsay, E., Kirkham, C., Chagpar, S., & Sherrington, C. (2015) · BMJ Open Sport & Exercise Medicine · doi:10.1136/bmjsem-2015-000013 · Cited by 164
“5 Nevertheless, future studies are needed to con fi rm the effectiveness of physical activity monitors such as the Fitbit for increasing physical activity levels in older adults who do not currently meet physical activity recommendations; 28 one such study is currently underway.”
Background
Metadata
- Authors
- Trost, S. G., & O'Neil, M.
- Affiliations
- The University of Queensland (AU)
- Corresponding author
- Trost, Stewart G
- ORCID
- Trost, Stewart G
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2013-12-05
- Volume
- 48
- Issue
- 3
- Pages
- 178-181
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W1558745131
- Cited by
- 139
- References
- 33
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 11 · 2023: 11 · 2022: 8 · 2021: 7 · 2020: 11 · 2019: 10 · 2018: 19 · 2017: 13 · 2016: 9 · 2015: 17 · 2014: 9
- FWCI
- 1.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Faculty of Health
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- 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
- Keywords
- objective physical activity measurement, heart rate monitoring, accelerometer, pedometers, clinical practice, self-report bias, recall bias, physical activity behavior
- MeSH terms
- Data Interpretation, Statistical, Heart Rate, Humans, Monitoring, Physiologic, Exercise, Walking, Monitoring, Ambulatory, Accelerometry
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