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Mendeley readers
Attention Score in Context
| Title |
Evaluation of the impact of disease prevention measures: a methodological note on defining incidence rates
|
|---|---|
| Published in |
BMC Medical Research Methodology, April 2017
|
| DOI | 10.1186/s12874-017-0350-4 |
| Pubmed ID | |
| Authors |
Yin-Bun Cheung, Ying Xu, Matthew Cairns, Paul Milligan |
| Abstract |
In studies of recurrent events, it is common to consider a person who has suffered a disease episode and received curative treatment to be not at risk of suffering a new episode for a duration of time. It is a common practice to deduct this duration from the person's observation time in the statistical analysis of the incidence data. We examined the concepts of incidence and protective efficacy from a real life point of view. We developed simple formulae to show the relationship between the incidence rate and protective efficacy between analyses with and without deducting the curative treatment time from the observation time. We used a malaria chemoprevention and a malaria vaccine study, both previously published, to illustrate the differences. Applying the formulae we derived to a range of disease incidence that covered the two case studies, we demonstrated the divergence of the two sets of estimates when incidence rate is approximately 1 per person-year or higher. In the malaria chemoprevention study, incidence was 5.40 per person-year after the deduction of curative treatment time from observation time but 4.48 per person-year without the deduction. The chemoprevention offered 56.6 and 50.7% protection calculated with and without the deduction, respectively. In the malaria vaccine study, where disease incidence was much lower than one, the results between the two ways of analysis were similar. For answering real life questions about disease burden in the population in a calendar year and the reduction that may be achieved if an intervention is implemented, the definition without deduction of curative treatment time should be used. The practice of deducting curative treatment time from observation time is not wrong, but it is not always the best approach. Investigators should consider the appropriateness of the two analytic procedures in relation to the specific research aims and the intended use of the results. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 40 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 20% |
| Student > Bachelor | 5 | 12% |
| Student > Master | 5 | 12% |
| Student > Ph. D. Student | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Other | 3 | 7% |
| Unknown | 15 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 22% |
| Agricultural and Biological Sciences | 3 | 7% |
| Social Sciences | 3 | 7% |
| Nursing and Health Professions | 2 | 5% |
| Immunology and Microbiology | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 16 | 39% |
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 23 April 2017.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from BMC Medical Research Methodology
#1,961
of 2,273 outputs
Outputs of similar age
#248,313
of 323,266 outputs
Outputs of similar age from BMC Medical Research Methodology
#31
of 36 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,273 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 6th percentile – i.e., 6% 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 323,266 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.