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Mendeley readers
Attention Score in Context
| Title |
Optimal search strategies for identifying sound clinical prediction studies in EMBASE
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, April 2005
|
| DOI | 10.1186/1472-6947-5-11 |
| Pubmed ID | |
| Authors |
Jennifer L Holland, Nancy L Wilczynski, R Brian Haynes, The Hedges Team |
| Abstract |
Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Denmark | 1 | 2% |
| Peru | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 39 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 21% |
| Librarian | 8 | 19% |
| Professor > Associate Professor | 5 | 12% |
| Student > Doctoral Student | 3 | 7% |
| Student > Postgraduate | 3 | 7% |
| Other | 10 | 23% |
| Unknown | 5 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 53% |
| Computer Science | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 5% |
| Nursing and Health Professions | 1 | 2% |
| Mathematics | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 9 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 11 December 2014.
All research outputs
#15,312,760
of 22,774,233 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,309
of 1,984 outputs
Outputs of similar age
#51,457
of 57,925 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 3 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,984 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 57,925 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.