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The SMART personalised self-management system for congestive heart failure: results of a realist evaluation

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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3 tweeters
facebook
1 Facebook page

Citations

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27 Dimensions

Readers on

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122 Mendeley
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1 CiteULike
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Title
The SMART personalised self-management system for congestive heart failure: results of a realist evaluation
Published in
BMC Medical Informatics and Decision Making, November 2014
DOI 10.1186/s12911-014-0109-3
Pubmed ID
Authors

Yvonne K Bartlett, Annette Haywood, Claire L Bentley, Jack Parker, Mark S Hawley, Gail A Mountain, Susan Mawson

Abstract

BackgroundTechnology has the potential to provide support for self-management to people with congestive heart failure (CHF). This paper describes the results of a realist evaluation of the SMART Personalised Self-Management System (PSMS) for CHF.MethodsThe PSMS was used, at home, by seven people with CHF. Data describing system usage and usability as well as questionnaire and interview data were evaluated in terms of the context, mechanism and outcome hypotheses (CMOs) integral to realist evaluation.ResultsThe CHF PSMS improved heart failure related knowledge in those with low levels of knowledge at baseline, through providing information and quizzes. Furthermore, participants perceived the self-regulatory aspects of the CHF PSMS as being useful in encouraging daily walking. The CMOs were revised to describe the context of use, and how this influences both the mechanisms and the outcomes.ConclusionsParticipants with CHF engaged with the PSMS despite some technological problems. Some positive effects on knowledge were observed as well as the potential to assist with changing physical activity behaviour. Knowledge of CHF and physical activity behaviour change are important self-management targets for CHF, and this study provides evidence to direct the further development of a technology to support these targets.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Spain 1 <1%
Netherlands 1 <1%
Denmark 1 <1%
Unknown 117 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 20%
Student > Ph. D. Student 22 18%
Researcher 21 17%
Student > Bachelor 10 8%
Student > Doctoral Student 6 5%
Other 22 18%
Unknown 16 13%
Readers by discipline Count As %
Medicine and Dentistry 29 24%
Nursing and Health Professions 23 19%
Computer Science 14 11%
Psychology 11 9%
Social Sciences 9 7%
Other 15 12%
Unknown 21 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 28 January 2015.
All research outputs
#6,680,091
of 12,409,138 outputs
Outputs from BMC Medical Informatics and Decision Making
#574
of 1,122 outputs
Outputs of similar age
#104,748
of 278,479 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#58
of 120 outputs
Altmetric has tracked 12,409,138 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,122 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 48th percentile – i.e., 48% 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 278,479 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.