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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Application of disability-adjusted life years to predict the burden of injuries and fatalities due to public exposure to engineering technologies
|
|---|---|
| Published in |
Population Health Metrics, March 2014
|
| DOI | 10.1186/1478-7954-12-9 |
| Pubmed ID | |
| Authors |
Arun Veeramany, Srikanth Mangalam |
| Abstract |
As a public safety regulator, the Technical Standards and Safety Authority (TSSA) of Ontario, Canada predicts and measures the burden of injuries and fatalities as its primary means of characterizing the state of public safety and for decision-making purposes through the use of a simulation model. The paper proposes a simulation-based predictive model and the use of disability-adjusted life years (DALYs) as a population health metric for the purposes of reporting, benchmarking, public safety decision-making, and organizational goal setting. The proposed approach could be viewed as advancement in the application of traditional population health metrics, used primarily for public health policy decisions, for the measurement and prediction of safety risks across a wide variety of engineering technologies to which the general public is exposed. |
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 % |
|---|---|---|
| United States | 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Switzerland | 1 | 5% |
| Unknown | 17 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 16% |
| Student > Master | 3 | 16% |
| Student > Bachelor | 2 | 11% |
| Professor | 2 | 11% |
| Other | 1 | 5% |
| Other | 4 | 21% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 21% |
| Nursing and Health Professions | 3 | 16% |
| Computer Science | 2 | 11% |
| Psychology | 2 | 11% |
| Social Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 32% |
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 28 March 2014.
All research outputs
#18,369,403
of 22,751,628 outputs
Outputs from Population Health Metrics
#342
of 392 outputs
Outputs of similar age
#162,726
of 224,799 outputs
Outputs of similar age from Population Health Metrics
#9
of 10 outputs
Altmetric has tracked 22,751,628 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 392 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one is in the 3rd percentile – i.e., 3% 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 224,799 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one.