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Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions

Overview of attention for article published in Sports Medicine - Open, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Average Attention Score compared to outputs of the same age and source

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36 X users

Citations

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161 Mendeley
Title
Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions
Published in
Sports Medicine - Open, March 2017
DOI 10.1186/s40798-017-0077-0
Pubmed ID
Authors

Tom E. Nightingale, Peter C. Rouse, Dylan Thompson, James L. J. Bilzon

Abstract

Accurately measuring physical activity and energy expenditure in persons with chronic physical disabilities who use wheelchairs is a considerable and ongoing challenge. Quantifying various free-living lifestyle behaviours in this group is at present restricted by our understanding of appropriate measurement tools and analytical techniques. This review provides a detailed evaluation of the currently available measurement tools used to predict physical activity and energy expenditure in persons who use wheelchairs. It also outlines numerous considerations specific to this population and suggests suitable future directions for the field. Of the existing three self-report methods utilised in this population, the 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) telephone interview demonstrates the best reliability and validity. However, the complexity of interview administration and potential for recall bias are notable limitations. Objective measurement tools, which overcome such considerations, have been validated using controlled laboratory protocols. These have consistently demonstrated the arm or wrist as the most suitable anatomical location to wear accelerometers. Yet, more complex data analysis methodologies may be necessary to further improve energy expenditure prediction for more intricate movements or behaviours. Multi-sensor devices that incorporate physiological signals and acceleration have recently been adapted for persons who use wheelchairs. Population specific algorithms offer considerable improvements in energy expenditure prediction accuracy. This review highlights the progress in the field and aims to encourage the wider scientific community to develop innovative solutions to accurately quantify physical activity in this population.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 161 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 33 20%
Student > Master 27 17%
Student > Ph. D. Student 19 12%
Researcher 11 7%
Student > Doctoral Student 7 4%
Other 18 11%
Unknown 46 29%
Readers by discipline Count As %
Medicine and Dentistry 28 17%
Nursing and Health Professions 19 12%
Engineering 18 11%
Sports and Recreations 14 9%
Computer Science 6 4%
Other 24 15%
Unknown 52 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2021.
All research outputs
#1,537,251
of 23,605,418 outputs
Outputs from Sports Medicine - Open
#128
of 491 outputs
Outputs of similar age
#31,700
of 312,283 outputs
Outputs of similar age from Sports Medicine - Open
#5
of 8 outputs
Altmetric has tracked 23,605,418 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 491 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.3. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 312,283 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.