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Attention Score in Context
| Title |
Inventory of real world data sources in Parkinson’s disease
|
|---|---|
| Published in |
BMC Neurology, December 2017
|
| DOI | 10.1186/s12883-017-0985-0 |
| Pubmed ID | |
| Authors |
Audrey Tanguy, Linus Jönsson, Lianna Ishihara |
| Abstract |
Real world data have an important role to play in the evaluation of epidemiology and burden of disease; and in assisting health-care decision-makers, especially related to coverage and payment decisions. However, there is currently no overview of the existing longitudinal real world data sources in Parkinson's disease (PD) in the USA. Such an assessment can be very helpful, to support a future effort to harmonize real world data collection and use the available resources in an optimal way. The objective of this comprehensive literature review is to systematically identify and describe the longitudinal, real world data sources in PD in the USA, and to provide a summary of their measurements (categorized into 8 main dimensions: motor and neurological functions, cognition, psychiatry, activities of daily living, sleep, quality of life, autonomic symptoms and other). The literature search was performed using MEDLINE, EMBASE and internet key word search. Of the 53 data sources identified between May and August 2016, 16 were still ongoing. Current medications (81%) and comorbidities (79%) were frequently collected, in comparison to medical imaging (36%), genetic information (30%), caregiver burden (11%) and healthcare costs (2%). Many different measurements (n = 108) were performed and an interesting variability among used measurements was revealed. Many longitudinal real world data sources on PD exist. Different types of measurements have been performed over time. To allow comparison and pooling of these multiple data sources, it will be essential to harmonize practices in terms of types of measurements. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 15% |
| Student > Master | 12 | 15% |
| Researcher | 8 | 10% |
| Student > Doctoral Student | 6 | 7% |
| Student > Bachelor | 6 | 7% |
| Other | 9 | 11% |
| Unknown | 28 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 16% |
| Neuroscience | 7 | 9% |
| Engineering | 5 | 6% |
| Psychology | 4 | 5% |
| Social Sciences | 4 | 5% |
| Other | 16 | 20% |
| Unknown | 32 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 13 January 2020.
All research outputs
#2,380,856
of 23,011,300 outputs
Outputs from BMC Neurology
#247
of 2,459 outputs
Outputs of similar age
#55,950
of 439,767 outputs
Outputs of similar age from BMC Neurology
#3
of 24 outputs
Altmetric has tracked 23,011,300 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,459 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 89% 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 439,767 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 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.