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Midwifery-led antenatal care models: mapping a systematic review to an evidence-based quality framework to identify key components and characteristics of care

Overview of attention for article published in BMC Pregnancy and Childbirth, July 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
26 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
192 Mendeley
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Title
Midwifery-led antenatal care models: mapping a systematic review to an evidence-based quality framework to identify key components and characteristics of care
Published in
BMC Pregnancy and Childbirth, July 2016
DOI 10.1186/s12884-016-0944-6
Pubmed ID
Authors

Andrew Symon, Jan Pringle, Helen Cheyne, Soo Downe, Vanora Hundley, Elaine Lee, Fiona Lynn, Alison McFadden, Jenny McNeill, Mary J Renfrew, Mary Ross-Davie, Edwin van Teijlingen, Heather Whitford, Fiona Alderdice

Abstract

Implementing effective antenatal care models is a key global policy goal. However, the mechanisms of action of these multi-faceted models that would allow widespread implementation are seldom examined and poorly understood. In existing care model analyses there is little distinction between what is done, how it is done, and who does it. A new evidence-informed quality maternal and newborn care (QMNC) framework identifies key characteristics of quality care. This offers the opportunity to identify systematically the characteristics of care delivery that may be generalizable across contexts, thereby enhancing implementation. Our objective was to map the characteristics of antenatal care models tested in Randomised Controlled Trials (RCTs) to a new evidence-based framework for quality maternal and newborn care; thus facilitating the identification of characteristics of effective care. A systematic review of RCTs of midwifery-led antenatal care models. Mapping and evaluation of these models' characteristics to the QMNC framework using data extraction and scoring forms derived from the five framework components. Paired team members independently extracted data and conducted quality assessment using the QMNC framework and standard RCT criteria. From 13,050 citations initially retrieved we identified 17 RCTs of midwifery-led antenatal care models from Australia (7), the UK (4), China (2), and Sweden, Ireland, Mexico and Canada (1 each). QMNC framework scores ranged from 9 to 25 (possible range 0-32), with most models reporting fewer than half the characteristics associated with quality maternity care. Description of care model characteristics was lacking in many studies, but was better reported for the intervention arms. Organisation of care was the best-described component. Underlying values and philosophy of care were poorly reported. The QMNC framework facilitates assessment of the characteristics of antenatal care models. It is vital to understand all the characteristics of multi-faceted interventions such as care models; not only what is done but why it is done, by whom, and how this differed from the standard care package. By applying the QMNC framework we have established a foundation for future reports of intervention studies so that the characteristics of individual models can be evaluated, and the impact of any differences appraised.

Twitter Demographics

The data shown below were collected from the profiles of 26 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 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 192 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 40 21%
Student > Bachelor 20 10%
Student > Ph. D. Student 15 8%
Researcher 13 7%
Other 10 5%
Other 47 24%
Unknown 47 24%
Readers by discipline Count As %
Nursing and Health Professions 67 35%
Medicine and Dentistry 43 22%
Social Sciences 11 6%
Psychology 5 3%
Agricultural and Biological Sciences 3 2%
Other 12 6%
Unknown 51 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 41. 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 11 October 2019.
All research outputs
#549,902
of 16,008,324 outputs
Outputs from BMC Pregnancy and Childbirth
#103
of 2,946 outputs
Outputs of similar age
#14,399
of 266,848 outputs
Outputs of similar age from BMC Pregnancy and Childbirth
#1
of 1 outputs
Altmetric has tracked 16,008,324 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,946 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 96% 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 266,848 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them