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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Factors of accepting pain management decision support systems by nurse anesthetists
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2013
|
| DOI | 10.1186/1472-6947-13-16 |
| Pubmed ID | |
| Authors |
Ju-Ling Hsiao, Wen-Chu Wu, Rai-Fu Chen |
| Abstract |
Pain management is a critical but complex issue for the relief of acute pain, particularly for postoperative pain and severe pain in cancer patients. It also plays important roles in promoting quality of care. The introduction of pain management decision support systems (PM-DSS) is considered a potential solution for addressing the complex problems encountered in pain management. This study aims to investigate factors affecting acceptance of PM-DSS from a nurse anesthetist perspective. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 67% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Unknown | 100 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 26% |
| Student > Master | 19 | 19% |
| Researcher | 10 | 10% |
| Student > Postgraduate | 7 | 7% |
| Student > Doctoral Student | 5 | 5% |
| Other | 20 | 20% |
| Unknown | 14 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 23% |
| Computer Science | 19 | 19% |
| Business, Management and Accounting | 17 | 17% |
| Nursing and Health Professions | 14 | 14% |
| Psychology | 5 | 5% |
| Other | 7 | 7% |
| Unknown | 17 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 05 November 2013.
All research outputs
#14,161,257
of 22,694,633 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,101
of 1,980 outputs
Outputs of similar age
#168,125
of 282,817 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#36
of 43 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,980 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 38th percentile – i.e., 38% 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 282,817 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.