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Creating a literature database of low-calorie sweeteners and health studies: evidence mapping

Overview of attention for article published in BMC Medical Research Methodology, January 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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1 blog
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Citations

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90 Dimensions

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Title
Creating a literature database of low-calorie sweeteners and health studies: evidence mapping
Published in
BMC Medical Research Methodology, January 2016
DOI 10.1186/s12874-015-0105-z
Pubmed ID
Authors

Ding Ding Wang, Marissa Shams-White, Oliver John M. Bright, J. Scott Parrott, Mei Chung

Abstract

Evidence mapping is an emerging tool used to systematically identify, organize and summarize the quantity and focus of scientific evidence on a broad topic, but there are currently no methodological standards. Using the topic of low-calorie sweeteners (LCS) and selected health outcomes, we describe the process of creating an evidence-map database and demonstrate several example descriptive analyses using this database. The process of creating an evidence-map database is described in detail. The steps include: developing a comprehensive literature search strategy, establishing study eligibility criteria and a systematic study selection process, extracting data, developing outcome groups with input from expert stakeholders and tabulating data using descriptive analyses. The database was uploaded onto SRDR™ (Systematic Review Data Repository), an open public data repository. Our final LCS evidence-map database included 225 studies, of which 208 were interventional studies and 17 were cohort studies. An example bubble plot was produced to display the evidence-map data and visualize research gaps according to four parameters: comparison types, population baseline health status, outcome groups, and study sample size. This plot indicated a lack of studies assessing appetite and dietary intake related outcomes using LCS with a sugar intake comparison in people with diabetes. Evidence mapping is an important tool for the contextualization of in-depth systematic reviews within broader literature and identifies gaps in the evidence base, which can be used to inform future research. An open evidence-map database has the potential to promote knowledge translation from nutrition science to policy.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Greece 1 1%
Brazil 1 1%
Unknown 96 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 20%
Student > Ph. D. Student 13 13%
Student > Master 13 13%
Student > Bachelor 7 7%
Other 6 6%
Other 19 19%
Unknown 21 21%
Readers by discipline Count As %
Medicine and Dentistry 24 24%
Nursing and Health Professions 10 10%
Agricultural and Biological Sciences 8 8%
Computer Science 5 5%
Social Sciences 5 5%
Other 22 22%
Unknown 25 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 16 December 2016.
All research outputs
#1,899,057
of 25,655,374 outputs
Outputs from BMC Medical Research Methodology
#247
of 2,303 outputs
Outputs of similar age
#31,566
of 401,573 outputs
Outputs of similar age from BMC Medical Research Methodology
#4
of 23 outputs
Altmetric has tracked 25,655,374 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,303 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 89% 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 401,573 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 92% of its contemporaries.
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 has done well, scoring higher than 82% of its contemporaries.