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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The new era of precision population health: insights for the All of Us Research Program and beyond
|
|---|---|
| Published in |
Journal of Translational Medicine, July 2018
|
| DOI | 10.1186/s12967-018-1585-5 |
| Pubmed ID | |
| Authors |
Courtney R. Lyles, Mitchell R. Lunn, Juno Obedin-Maliver, Kirsten Bibbins-Domingo |
| Abstract |
Although precision medicine has made advances in individualized patient treatments, there needs to be continued attention on tailored population health and prevention strategies (often termed "precision population health"). As we continue to link datasets and use "big data" approaches in medicine, inclusion of diverse populations and a focus on disparities reduction are key components within a precision population health framework. Specific recommendations from the All of Us Research Program and the Precision Public Health Summit provide examples for moving this field forward. |
X Demographics
The data shown below were collected from the profiles of 40 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 31 | 78% |
| United Kingdom | 1 | 3% |
| Australia | 1 | 3% |
| Colombia | 1 | 3% |
| Unknown | 6 | 15% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 63% |
| Scientists | 13 | 33% |
| Practitioners (doctors, other healthcare professionals) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 62 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 23% |
| Student > Ph. D. Student | 12 | 19% |
| Other | 5 | 8% |
| Professor | 4 | 6% |
| Student > Bachelor | 3 | 5% |
| Other | 12 | 19% |
| Unknown | 12 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 26% |
| Social Sciences | 9 | 15% |
| Nursing and Health Professions | 7 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Computer Science | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 18 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 32. 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 22 April 2019.
All research outputs
#1,100,290
of 23,577,654 outputs
Outputs from Journal of Translational Medicine
#198
of 4,186 outputs
Outputs of similar age
#25,015
of 331,423 outputs
Outputs of similar age from Journal of Translational Medicine
#7
of 87 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,186 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 95% 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 331,423 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.