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Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue

Overview of attention for article published in Population Health Metrics, October 2009
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1 X user
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1 peer review site

Citations

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32 Dimensions

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48 Mendeley
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4 CiteULike
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Title
Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue
Published in
Population Health Metrics, October 2009
DOI 10.1186/1478-7954-7-17
Pubmed ID
Authors

Eric Aslakson, Uté Vollmer-Conna, William C Reeves, Peter D White

Abstract

Chronic fatigue syndrome (CFS) is defined by self-reported symptoms. There are no diagnostic signs or laboratory markers, and the pathophysiology remains inchoate. In part, difficulties identifying and replicating biomarkers and elucidating the pathophysiology reflect the heterogeneous nature of the syndromic illness CFS. We conducted this analysis of people from defined metropolitan, urban, and rural populations to replicate our earlier empirical delineation of medically unexplained chronic fatigue and CFS into discrete endophenotypes. Both the earlier and current analyses utilized quantitative measures of functional impairment and symptoms as well as laboratory data. This study and the earlier one enrolled participants from defined populations and measured the internal milieu, which differentiates them from studies of clinic referrals that examine only clinical phenotypes.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Greece 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 27%
Student > Ph. D. Student 7 15%
Researcher 6 13%
Student > Master 5 10%
Student > Postgraduate 4 8%
Other 9 19%
Unknown 4 8%
Readers by discipline Count As %
Psychology 16 33%
Medicine and Dentistry 14 29%
Agricultural and Biological Sciences 3 6%
Computer Science 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 3 6%
Unknown 9 19%
Attention Score in Context

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 27 May 2014.
All research outputs
#14,770,397
of 22,738,543 outputs
Outputs from Population Health Metrics
#295
of 392 outputs
Outputs of similar age
#77,377
of 93,417 outputs
Outputs of similar age from Population Health Metrics
#3
of 3 outputs
Altmetric has tracked 22,738,543 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 392 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one is in the 22nd percentile – i.e., 22% 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 93,417 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.