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Understanding clinical prediction models as ‘innovations’: a mixed methods study in UK family practice

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2016
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Mentioned by

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1 tweeter

Citations

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13 Dimensions

Readers on

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85 Mendeley
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Title
Understanding clinical prediction models as ‘innovations’: a mixed methods study in UK family practice
Published in
BMC Medical Informatics and Decision Making, August 2016
DOI 10.1186/s12911-016-0343-y
Authors

Benjamin Brown, Sudeh Cheraghi-Sohi, Thomas Jaki, Ting-Li Su, Iain Buchan, Matthew Sperrin

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 84 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 19%
Researcher 15 18%
Student > Master 13 15%
Other 7 8%
Professor 4 5%
Other 11 13%
Unknown 19 22%
Readers by discipline Count As %
Medicine and Dentistry 21 25%
Social Sciences 8 9%
Business, Management and Accounting 6 7%
Nursing and Health Professions 6 7%
Psychology 6 7%
Other 18 21%
Unknown 20 24%

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 13 March 2018.
All research outputs
#18,539,663
of 22,961,203 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,581
of 2,001 outputs
Outputs of similar age
#279,976
of 362,370 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 44 outputs
Altmetric has tracked 22,961,203 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 2,001 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 362,370 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.