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Strengthening policy coding methodologies to improve COVID-19 disease modeling and policy responses: a proposed coding framework and recommendations

Overview of attention for article published in BMC Medical Research Methodology, December 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
45 Mendeley
Title
Strengthening policy coding methodologies to improve COVID-19 disease modeling and policy responses: a proposed coding framework and recommendations
Published in
BMC Medical Research Methodology, December 2020
DOI 10.1186/s12874-020-01174-w
Pubmed ID
Authors

Jeff Lane, Michelle M. Garrison, James Kelley, Priya Sarma, Aaron Katz

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 18%
Student > Master 4 9%
Student > Ph. D. Student 3 7%
Student > Bachelor 3 7%
Other 2 4%
Other 4 9%
Unknown 21 47%
Readers by discipline Count As %
Nursing and Health Professions 8 18%
Social Sciences 4 9%
Environmental Science 3 7%
Medicine and Dentistry 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 5 11%
Unknown 21 47%
Attention Score in Context

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 29 December 2020.
All research outputs
#12,907,845
of 23,269,984 outputs
Outputs from BMC Medical Research Methodology
#1,175
of 2,056 outputs
Outputs of similar age
#216,306
of 508,353 outputs
Outputs of similar age from BMC Medical Research Methodology
#32
of 51 outputs
Altmetric has tracked 23,269,984 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,056 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 41st percentile – i.e., 41% 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 508,353 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.