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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Performance of four computer-coded verbal autopsy methods for cause of death assignment compared with physician coding on 24,000 deaths in low- and middle-income countries
|
|---|---|
| Published in |
BMC Medicine, February 2014
|
| DOI | 10.1186/1741-7015-12-20 |
| Pubmed ID | |
| Authors |
Nikita Desai, Lukasz Aleksandrowicz, Pierre Miasnikof, Ying Lu, Jordana Leitao, Peter Byass, Stephen Tollman, Paul Mee, Dewan Alam, Suresh Kumar Rathi, Abhishek Singh, Rajesh Kumar, Faujdar Ram, Prabhat Jha |
| Abstract |
Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 2 | 40% |
| Bangladesh | 1 | 20% |
| United Kingdom | 1 | 20% |
| India | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 40% |
| Members of the public | 2 | 40% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| France | 1 | 1% |
| Unknown | 74 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 20% |
| Student > Master | 13 | 17% |
| Student > Ph. D. Student | 11 | 14% |
| Student > Postgraduate | 5 | 7% |
| Student > Doctoral Student | 4 | 5% |
| Other | 15 | 20% |
| Unknown | 13 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 34 | 45% |
| Social Sciences | 8 | 11% |
| Agricultural and Biological Sciences | 7 | 9% |
| Computer Science | 5 | 7% |
| Nursing and Health Professions | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 15 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 February 2014.
All research outputs
#12,832,347
of 22,743,667 outputs
Outputs from BMC Medicine
#2,694
of 3,413 outputs
Outputs of similar age
#154,871
of 307,189 outputs
Outputs of similar age from BMC Medicine
#46
of 59 outputs
Altmetric has tracked 22,743,667 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,413 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.5. This one is in the 20th percentile – i.e., 20% 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 307,189 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.