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Stroke patients’ utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2014
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Title
Stroke patients’ utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation
Published in
BMC Medical Informatics and Decision Making, June 2014
DOI 10.1186/1472-6947-14-46
Pubmed ID
Authors

Jack Parker, Susan Mawson, Gail Mountain, Nasrin Nasr, Huiru Zheng

Abstract

Evidence indicates that post - stroke rehabilitation improves function, independence and quality of life. A key aspect of rehabilitation is the provision of appropriate information and feedback to the learner.Advances in information and communications technology (ICT) have allowed for the development of various systems to complement stroke rehabilitation that could be used in the home setting. These systems may increase the provision of rehabilitation a stroke survivor receives and carries out, as well as providing a learning platform that facilitates long-term self-managed rehabilitation and behaviour change. This paper describes the application of an innovative evaluative methodology to explore the utilisation of feedback for post-stroke upper-limb rehabilitation in the home.

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The data shown below were collected from the profile of 1 X user 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 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 2%
Colombia 1 <1%
Switzerland 1 <1%
Denmark 1 <1%
Japan 1 <1%
United States 1 <1%
Unknown 161 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 17%
Student > Ph. D. Student 27 16%
Student > Master 18 11%
Student > Doctoral Student 14 8%
Student > Bachelor 12 7%
Other 33 19%
Unknown 37 22%
Readers by discipline Count As %
Medicine and Dentistry 23 14%
Psychology 20 12%
Social Sciences 18 11%
Nursing and Health Professions 13 8%
Engineering 12 7%
Other 34 20%
Unknown 50 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 June 2014.
All research outputs
#18,373,576
of 22,757,090 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,567
of 1,985 outputs
Outputs of similar age
#163,859
of 228,023 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#20
of 23 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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 228,023 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.