You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mapping the Knowledge Structure of Research on Patient Adherence: Knowledge Domain Visualization Based Co-Word Analysis and Social Network Analysis
|
|---|---|
| Published in |
PLOS ONE, April 2012
|
| DOI | 10.1371/journal.pone.0034497 |
| Pubmed ID | |
| Authors |
Juan Zhang, Jun Xie, Wanli Hou, Xiaochen Tu, Jing Xu, Fujian Song, Zhihong Wang, Zuxun Lu |
| Abstract |
Patient adherence is an important issue for health service providers and health researchers. However, the knowledge structure of diverse research on treatment adherence is unclear. This study used co-word analysis and social network analysis techniques to analyze research literature on adherence, and to show their knowledge structure and evolution over time. |
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 % |
|---|---|---|
| Germany | 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 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 2 | 2% |
| Japan | 1 | <1% |
| Portugal | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 123 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 24% |
| Researcher | 19 | 15% |
| Student > Master | 17 | 13% |
| Other | 9 | 7% |
| Professor | 7 | 5% |
| Other | 18 | 14% |
| Unknown | 27 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 23 | 18% |
| Computer Science | 18 | 14% |
| Business, Management and Accounting | 9 | 7% |
| Medicine and Dentistry | 9 | 7% |
| Engineering | 8 | 6% |
| Other | 29 | 23% |
| Unknown | 32 | 25% |
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 09 April 2012.
All research outputs
#15,242,847
of 22,664,267 outputs
Outputs from PLOS ONE
#129,806
of 193,506 outputs
Outputs of similar age
#102,516
of 161,283 outputs
Outputs of similar age from PLOS ONE
#2,379
of 3,716 outputs
Altmetric has tracked 22,664,267 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,506 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 24th percentile – i.e., 24% 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 161,283 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,716 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.