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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Reducing prescribing of antibiotics for acute respiratory infections using a frontline nurse-led EHR-Integrated clinical decision support tool: protocol for a stepped wedge randomized control trial
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2023
|
| DOI | 10.1186/s12911-023-02368-0 |
| Pubmed ID | |
| Authors |
Elizabeth R. Stevens, Ruth Agbakoba, Devin M. Mann, Rachel Hess, Safiya I. Richardson, Thomas McGinn, Paul D. Smith, Wendy Halm, Marlon P. Mundt, Katherine L. Dauber-Decker, Simon A. Jones, Dawn M. Feldthouse, Eun Ji Kim, David A. Feldstein |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 1 | 6% |
| Unspecified | 1 | 6% |
| Professor | 1 | 6% |
| Student > Ph. D. Student | 1 | 6% |
| Researcher | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 11 | 69% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Neuroscience | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Unknown | 12 | 75% |
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 20 November 2023.
All research outputs
#17,348,916
of 25,457,858 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,410
of 2,143 outputs
Outputs of similar age
#187,876
of 347,946 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 34 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,143 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 347,946 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.