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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Pseudonymization of patient identifiers for translational research
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2013
|
| DOI | 10.1186/1472-6947-13-75 |
| Pubmed ID | |
| Authors |
Harald Aamot, Christian Dominik Kohl, Daniela Richter, Petra Knaup-Gregori |
| Abstract |
The usage of patient data for research poses risks concerning the patients' privacy and informational self-determination. Next-generation-sequencing technologies and various other methods gain data from biospecimen, both for translational research and personalized medicine. If these biospecimen are anonymized, individual research results from genomic research, which should be offered to patients in a clinically relevant timeframe, cannot be associated back to the individual. This raises an ethical concern and challenges the legitimacy of anonymized patient samples. In this paper we present a new approach which supports both data privacy and the possibility to give feedback to patients about their individual research results. |
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% |
| Unknown | 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 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 3% |
| Finland | 1 | <1% |
| Mexico | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 118 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 18% |
| Researcher | 18 | 14% |
| Student > Master | 15 | 12% |
| Other | 8 | 6% |
| Student > Bachelor | 7 | 6% |
| Other | 27 | 22% |
| Unknown | 27 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 35 | 28% |
| Medicine and Dentistry | 22 | 18% |
| Social Sciences | 5 | 4% |
| Unspecified | 5 | 4% |
| Agricultural and Biological Sciences | 4 | 3% |
| Other | 22 | 18% |
| Unknown | 32 | 26% |
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 02 August 2013.
All research outputs
#15,557,505
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,259
of 2,030 outputs
Outputs of similar age
#120,553
of 200,879 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#29
of 38 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 33rd percentile – i.e., 33% 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 200,879 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.