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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prognostic Risk Estimates of Patients with Multiple Sclerosis and Their Physicians: Comparison to an Online Analytical Risk Counseling Tool
|
|---|---|
| Published in |
PLOS ONE, May 2013
|
| DOI | 10.1371/journal.pone.0059042 |
| Pubmed ID | |
| Authors |
Christoph Heesen, Wolfgang Gaissmaier, Franziska Nguyen, Jan-Patrick Stellmann, Jürgen Kasper, Sascha Köpke, Christian Lederer, Anneke Neuhaus, Martin Daumer |
| Abstract |
Prognostic counseling in multiple sclerosis (MS) is difficult because of the high variability of disease progression. Simultaneously, patients and physicians are increasingly confronted with making treatment decisions at an early stage, which requires taking individual prognoses into account to strike a good balance between benefits and harms of treatments. It is therefore important to understand how patients and physicians estimate prognostic risk, and whether and how these estimates can be improved. An online analytical processing (OLAP) tool based on pooled data from placebo cohorts of clinical trials offers short-term prognostic estimates that can be used for individual risk counseling. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
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 | 1 | 2% |
| Portugal | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 48 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 24% |
| Researcher | 9 | 18% |
| Student > Doctoral Student | 9 | 18% |
| Professor | 4 | 8% |
| Other | 4 | 8% |
| Other | 7 | 14% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 31% |
| Social Sciences | 6 | 12% |
| Neuroscience | 5 | 10% |
| Psychology | 5 | 10% |
| Computer Science | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 12 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 28 November 2019.
All research outputs
#2,781,644
of 22,711,242 outputs
Outputs from PLOS ONE
#36,053
of 193,913 outputs
Outputs of similar age
#24,838
of 196,379 outputs
Outputs of similar age from PLOS ONE
#858
of 4,968 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193,913 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done well, scoring higher than 81% 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 196,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 4,968 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.