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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Ancillary study management systems: a review of needs
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2013
|
| DOI | 10.1186/1472-6947-13-5 |
| Pubmed ID | |
| Authors |
Elizabeth K Nelson, Britt Piehler, Adam Rauch, Sarah Ramsay, Drienna Holman, Smita Asare, Adam Asare, Mark Igra |
| Abstract |
The valuable clinical data, specimens, and assay results collected during a primary clinical trial or observational study can enable researchers to answer additional, pressing questions with relatively small investments in new measurements. However, management of such follow-on, "ancillary" studies is complex. It requires coordinating across institutions, sites, repositories, and approval boards, as well as distributing, integrating, and analyzing diverse data types. General-purpose software systems that simplify the management of ancillary studies have not yet been explored in the research literature. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 67% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 2 | 3% |
| Japan | 1 | 2% |
| Luxembourg | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 58 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Master | 9 | 14% |
| Student > Ph. D. Student | 6 | 10% |
| Student > Bachelor | 6 | 10% |
| Professor | 4 | 6% |
| Other | 13 | 21% |
| Unknown | 15 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 17% |
| Nursing and Health Professions | 9 | 14% |
| Computer Science | 6 | 10% |
| Engineering | 4 | 6% |
| Agricultural and Biological Sciences | 3 | 5% |
| Other | 15 | 24% |
| Unknown | 15 | 24% |
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 01 September 2017.
All research outputs
#1,867,405
of 22,691,736 outputs
Outputs from BMC Medical Informatics and Decision Making
#104
of 1,980 outputs
Outputs of similar age
#19,119
of 281,525 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#9
of 41 outputs
Altmetric has tracked 22,691,736 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 1,980 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 94% 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 281,525 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 93% of its contemporaries.
We're also able to compare this research output to 41 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.