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Taking advantage of unexpected WebCONSORT results

Overview of attention for article published in BMC Medicine, December 2016
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  • Good Attention Score compared to outputs of the same age (68th percentile)

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Title
Taking advantage of unexpected WebCONSORT results
Published in
BMC Medicine, December 2016
DOI 10.1186/s12916-016-0758-4
Pubmed ID
Authors

Erik Cobo, José Antonio González

Abstract

To estimate treatment effects, trials are initiated by randomising patients to the interventions under study and finish by comparing patient evolution. In order to improve the trial report, the CONSORT statement provides authors and peer reviewers with a guide of the essential items that would allow research replication. Additionally, WebCONSORT aims to facilitate author reporting by providing the items from the different CONSORT extensions that are relevant to the trial being reported. WebCONSORT has been estimated to improve the proportion of reported items by 0.04 (95% CI, -0.02 to 0.10), interpreted as "no important difference", in accordance with the scheduled desired scenario of a 0.15 effect size improvement. However, in a non-scheduled analysis, it was found that, despite clear instructions, around a third of manuscripts selected for trials by the editorial staff were not actually randomised trials. We argue that surprises benefit science, and that further research should be conducted in order to improve the performance of editorial staff.Please see related research: http://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-016-0736-x.

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The data shown below were collected from the profiles of 5 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 27%
Student > Ph. D. Student 3 27%
Student > Bachelor 2 18%
Other 1 9%
Student > Doctoral Student 1 9%
Other 0 0%
Unknown 1 9%
Readers by discipline Count As %
Medicine and Dentistry 5 45%
Agricultural and Biological Sciences 1 9%
Mathematics 1 9%
Decision Sciences 1 9%
Computer Science 1 9%
Other 0 0%
Unknown 2 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 05 April 2017.
All research outputs
#7,159,304
of 22,908,162 outputs
Outputs from BMC Medicine
#2,541
of 3,444 outputs
Outputs of similar age
#130,902
of 415,991 outputs
Outputs of similar age from BMC Medicine
#50
of 70 outputs
Altmetric has tracked 22,908,162 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 3,444 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one is in the 26th percentile – i.e., 26% 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 415,991 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 68% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.