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Identifying Antibiotic Prescribing Patterns Through Multi-Level Latent Profile Analyses: A Cross-Sectional Survey of Primary Care Physicians

Overview of attention for article published in Frontiers in Pharmacology, November 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

policy
1 policy source
twitter
1 X user

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Identifying Antibiotic Prescribing Patterns Through Multi-Level Latent Profile Analyses: A Cross-Sectional Survey of Primary Care Physicians
Published in
Frontiers in Pharmacology, November 2020
DOI 10.3389/fphar.2020.591709
Pubmed ID
Authors

Dan Wang, Chaojie Liu, Xinping Zhang, Chenxi Liu

Timeline

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X Demographics

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Student > Ph. D. Student 3 13%
Student > Postgraduate 2 8%
Unspecified 1 4%
Researcher 1 4%
Other 1 4%
Unknown 12 50%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 5 21%
Social Sciences 2 8%
Veterinary Science and Veterinary Medicine 1 4%
Nursing and Health Professions 1 4%
Unspecified 1 4%
Other 2 8%
Unknown 12 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 08 January 2023.
All research outputs
#7,609,077
of 23,842,189 outputs
Outputs from Frontiers in Pharmacology
#3,322
of 17,517 outputs
Outputs of similar age
#160,502
of 417,804 outputs
Outputs of similar age from Frontiers in Pharmacology
#101
of 472 outputs
Altmetric has tracked 23,842,189 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 17,517 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 80% of its peers.
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 417,804 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 61% of its contemporaries.
We're also able to compare this research output to 472 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.