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Characterizing individual painDETECT symptoms by average pain severity

Overview of attention for article published in ClinicoEconomics and Outcomes Research: CEOR, July 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
5 tweeters
googleplus
1 Google+ user

Readers on

mendeley
5 Mendeley
Title
Characterizing individual painDETECT symptoms by average pain severity
Published in
ClinicoEconomics and Outcomes Research: CEOR, July 2016
DOI 10.2147/ceor.s105402
Pubmed ID
Authors

Alesia Sadosky, Vijaya Koduru, E. Jay Bienen, Joseph Cappelleri

Abstract

painDETECT is a screening measure for neuropathic pain. The nine-item version consists of seven sensory items (burning, tingling/prickling, light touching, sudden pain attacks/electric shock-type pain, cold/heat, numbness, and slight pressure), a pain course pattern item, and a pain radiation item. The seven-item version consists only of the sensory items. Total scores of both versions discriminate average pain-severity levels (mild, moderate, and severe), but their ability to discriminate individual item severity has not been evaluated. Data were from a cross-sectional, observational study of six neuropathic pain conditions (N=624). Average pain severity was evaluated using the Brief Pain Inventory-Short Form, with severity levels defined using established cut points for distinguishing mild, moderate, and severe pain. The Wilcoxon rank sum test was followed by ridit analysis to represent the probability that a randomly selected subject from one average pain-severity level had a more favorable outcome on the specific painDETECT item relative to a randomly selected subject from a comparator severity level. A probability >50% for a better outcome (less severe pain) was significantly observed for each pain symptom item. The lowest probability was 56.3% (on numbness for mild vs moderate pain) and highest probability was 76.4% (on cold/heat for mild vs severe pain). The pain radiation item was significant (P<0.05) and consistent with pain symptoms, as well as with total scores for both painDETECT versions; only the pain course item did not differ. painDETECT differentiates severity such that the ability to discriminate average pain also distinguishes individual pain item severity in an interpretable manner. Pain-severity levels can serve as proxies to determine treatment effects, thus indicating probabilities for more favorable outcomes on pain symptoms.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 40%
Other 1 20%
Unknown 2 40%
Readers by discipline Count As %
Mathematics 1 20%
Nursing and Health Professions 1 20%
Engineering 1 20%
Unknown 2 40%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 August 2016.
All research outputs
#3,461,130
of 12,119,486 outputs
Outputs from ClinicoEconomics and Outcomes Research: CEOR
#101
of 328 outputs
Outputs of similar age
#88,195
of 266,518 outputs
Outputs of similar age from ClinicoEconomics and Outcomes Research: CEOR
#6
of 23 outputs
Altmetric has tracked 12,119,486 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 328 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 65% 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 266,518 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.