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X Demographics
Mendeley readers
Attention Score in Context
Title |
Learning from Hackers: Open-Source Clinical Trials
|
---|---|
Published in |
Science Translational Medicine, May 2012
|
DOI | 10.1126/scitranslmed.3003682 |
Pubmed ID | |
Authors |
Adam G. Dunn, Richard O. Day, Kenneth D. Mandl, Enrico Coiera |
Abstract |
Open sharing of clinical trial data has been proposed as a way to address the gap between the production of clinical evidence and the decision-making of physicians. A similar gap was addressed in the software industry by their open-source software movement. Here, we examine how the social and technical principles of the movement can guide the growth of an open-source clinical trial community. |
X Demographics
The data shown below were collected from the profiles of 33 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 6 | 18% |
United States | 6 | 18% |
Finland | 2 | 6% |
United Kingdom | 2 | 6% |
Italy | 2 | 6% |
Netherlands | 1 | 3% |
Nigeria | 1 | 3% |
Belgium | 1 | 3% |
Switzerland | 1 | 3% |
Other | 5 | 15% |
Unknown | 6 | 18% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 21 | 64% |
Scientists | 7 | 21% |
Practitioners (doctors, other healthcare professionals) | 3 | 9% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Unknown | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 6% |
Spain | 2 | 4% |
United Kingdom | 1 | 2% |
Finland | 1 | 2% |
Unknown | 44 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 31% |
Other | 6 | 12% |
Student > Ph. D. Student | 5 | 10% |
Librarian | 3 | 6% |
Professor | 3 | 6% |
Other | 15 | 29% |
Unknown | 3 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 15 | 29% |
Agricultural and Biological Sciences | 9 | 18% |
Biochemistry, Genetics and Molecular Biology | 6 | 12% |
Social Sciences | 5 | 10% |
Computer Science | 3 | 6% |
Other | 9 | 18% |
Unknown | 4 | 8% |
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 03 July 2017.
All research outputs
#1,002,252
of 25,375,376 outputs
Outputs from Science Translational Medicine
#2,099
of 5,425 outputs
Outputs of similar age
#4,991
of 169,301 outputs
Outputs of similar age from Science Translational Medicine
#20
of 90 outputs
Altmetric has tracked 25,375,376 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 5,425 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 86.6. This one has gotten more attention than average, scoring higher than 61% 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 169,301 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 97% of its contemporaries.
We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.