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Mendeley readers
Attention Score in Context
Title |
Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data
|
---|---|
Published in |
PLOS ONE, September 2011
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DOI | 10.1371/journal.pone.0025348 |
Pubmed ID | |
Authors |
Brigitte Walther, Safayet Hossin, John Townend, Neil Abernethy, David Parker, David Jeffries |
Abstract |
Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) methods with the conventional approach with respect to duration of data capture and accuracy. It was performed in a West African setting, where clinical trials involve data collection from urban, rural and often remote locations. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 50% |
Ireland | 1 | 17% |
Canada | 1 | 17% |
Unknown | 1 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 67% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 189 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 2% |
Belgium | 2 | 1% |
Switzerland | 1 | <1% |
United Kingdom | 1 | <1% |
Netherlands | 1 | <1% |
Brazil | 1 | <1% |
Canada | 1 | <1% |
Unknown | 178 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 47 | 25% |
Student > Ph. D. Student | 28 | 15% |
Student > Master | 28 | 15% |
Student > Postgraduate | 17 | 9% |
Student > Bachelor | 12 | 6% |
Other | 31 | 16% |
Unknown | 26 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 58 | 31% |
Computer Science | 21 | 11% |
Agricultural and Biological Sciences | 15 | 8% |
Social Sciences | 11 | 6% |
Psychology | 9 | 5% |
Other | 47 | 25% |
Unknown | 28 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 15 August 2022.
All research outputs
#1,989,896
of 24,226,848 outputs
Outputs from PLOS ONE
#24,872
of 208,425 outputs
Outputs of similar age
#9,524
of 133,864 outputs
Outputs of similar age from PLOS ONE
#267
of 2,580 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 208,425 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done well, scoring higher than 88% 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 133,864 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 2,580 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.