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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An administrative data validation study of the accuracy of algorithms for identifying rheumatoid arthritis: the influence of the reference standard on algorithm performance
|
|---|---|
| Published in |
BMC Musculoskeletal Disorders, June 2014
|
| DOI | 10.1186/1471-2474-15-216 |
| Pubmed ID | |
| Authors |
Jessica Widdifield, Claire Bombardier, Sasha Bernatsky, J Michael Paterson, Diane Green, Jacqueline Young, Noah Ivers, Debra A Butt, R Liisa Jaakkimainen, J Carter Thorne, Karen Tu |
| Abstract |
We have previously validated administrative data algorithms to identify patients with rheumatoid arthritis (RA) using rheumatology clinic records as the reference standard. Here we reassessed the accuracy of the algorithms using primary care records as the reference standard. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 2% |
| United Kingdom | 1 | <1% |
| Unknown | 114 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 27% |
| Student > Master | 26 | 22% |
| Student > Ph. D. Student | 11 | 9% |
| Other | 7 | 6% |
| Student > Bachelor | 7 | 6% |
| Other | 19 | 16% |
| Unknown | 15 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 47 | 40% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 7% |
| Social Sciences | 8 | 7% |
| Nursing and Health Professions | 5 | 4% |
| Computer Science | 4 | 3% |
| Other | 23 | 20% |
| Unknown | 22 | 19% |
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 25 June 2014.
All research outputs
#17,722,431
of 22,757,541 outputs
Outputs from BMC Musculoskeletal Disorders
#2,890
of 4,037 outputs
Outputs of similar age
#155,703
of 228,089 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#66
of 113 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,037 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 22nd percentile – i.e., 22% 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 228,089 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.