| Title |
Optimal Acupuncture Methods for Nonspecific Low Back Pain: A Systematic Review and Bayesian Network Meta-Analysis of Randomized Controlled Trials
|
|---|---|
| Published in |
Journal of Pain Research, April 2021
|
| DOI | 10.2147/jpr.s310385 |
| Pubmed ID | |
| Authors |
Linjia Wang, Zihan Yin, Yutong Zhang, Mingsheng Sun, Yang Yu, Yanming Lin, Ling Zhao |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 22% |
| Italy | 1 | 11% |
| Philippines | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 16% |
| Student > Master | 6 | 12% |
| Student > Bachelor | 5 | 10% |
| Librarian | 4 | 8% |
| Unspecified | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 17 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Nursing and Health Professions | 7 | 14% |
| Unspecified | 6 | 12% |
| Computer Science | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 22 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 25 April 2022.
All research outputs
#2,204,017
of 25,632,496 outputs
Outputs from Journal of Pain Research
#256
of 2,000 outputs
Outputs of similar age
#58,304
of 455,631 outputs
Outputs of similar age from Journal of Pain Research
#9
of 63 outputs
Altmetric has tracked 25,632,496 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,000 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one has done well, scoring higher than 87% 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 455,631 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.