| 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% |