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Evaluation of quality improvement for cesarean sections programmes through mixed methods

Overview of attention for article published in Implementation Science, December 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
8 X users
facebook
1 Facebook page

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
95 Mendeley
citeulike
1 CiteULike
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Title
Evaluation of quality improvement for cesarean sections programmes through mixed methods
Published in
Implementation Science, December 2014
DOI 10.1186/s13012-014-0182-0
Pubmed ID
Authors

Clara Bermúdez-Tamayo, Mira Johri, Francisco Jose Perez-Ramos, Gracia Maroto-Navarro, Africa Caño-Aguilar, Leticia Garcia-Mochon, Longinos Aceituno, François Audibert, Nils Chaillet

Abstract

The rate of avoidable caesarean sections (CS) could be reduced through multifaceted strategies focusing on the involvement of health professionals and compliance with clinical practice guidelines (CPGs). Quality improvements for CS (QICS) programmes (QICS) based on this approach, have been implemented in Canada and Spain.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Congo, The Democratic Republic of the 1 1%
Unknown 94 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 22%
Student > Master 17 18%
Student > Ph. D. Student 9 9%
Student > Bachelor 8 8%
Professor 6 6%
Other 16 17%
Unknown 18 19%
Readers by discipline Count As %
Medicine and Dentistry 36 38%
Nursing and Health Professions 14 15%
Social Sciences 9 9%
Economics, Econometrics and Finance 4 4%
Psychology 4 4%
Other 6 6%
Unknown 22 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 January 2015.
All research outputs
#6,887,757
of 25,311,095 outputs
Outputs from Implementation Science
#1,096
of 1,798 outputs
Outputs of similar age
#88,046
of 373,824 outputs
Outputs of similar age from Implementation Science
#26
of 61 outputs
Altmetric has tracked 25,311,095 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,798 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one is in the 38th percentile – i.e., 38% 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 373,824 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 76% of its contemporaries.
We're also able to compare this research output to 61 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 59% of its contemporaries.