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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Public health utility of cause of death data: applying empirical algorithms to improve data quality
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2021
|
| DOI | 10.1186/s12911-021-01501-1 |
| Pubmed ID | |
| Authors |
Sarah Charlotte Johnson, Matthew Cunningham, Ilse N. Dippenaar, Fablina Sharara, Eve E. Wool, Kareha M. Agesa, Chieh Han, Molly K. Miller-Petrie, Shadrach Wilson, John E. Fuller, Shelly Balassyano, Gregory J. Bertolacci, Nicole Davis Weaver, Alan D. Lopez, Christopher J. L. Murray, Mohsen Naghavi |
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 % |
|---|---|---|
| Nigeria | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 16% |
| Student > Bachelor | 5 | 7% |
| Student > Master | 4 | 6% |
| Student > Doctoral Student | 4 | 6% |
| Unspecified | 3 | 4% |
| Other | 18 | 26% |
| Unknown | 23 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 13% |
| Nursing and Health Professions | 8 | 12% |
| Social Sciences | 4 | 6% |
| Economics, Econometrics and Finance | 3 | 4% |
| Computer Science | 3 | 4% |
| Other | 16 | 24% |
| Unknown | 25 | 37% |
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 02 June 2021.
All research outputs
#18,809,260
of 23,310,485 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,598
of 2,024 outputs
Outputs of similar age
#323,377
of 448,075 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#51
of 62 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,024 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 448,075 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.