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Psychometric properties of the painDETECT questionnaire in rheumatoid arthritis, psoriatic arthritis and spondyloarthritis: Rasch analysis and test-retest reliability

Overview of attention for article published in Health and Quality of Life Outcomes, May 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

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13 tweeters
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3 Facebook pages
reddit
1 Redditor

Citations

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7 Dimensions

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43 Mendeley
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Title
Psychometric properties of the painDETECT questionnaire in rheumatoid arthritis, psoriatic arthritis and spondyloarthritis: Rasch analysis and test-retest reliability
Published in
Health and Quality of Life Outcomes, May 2017
DOI 10.1186/s12955-017-0681-1
Pubmed ID
Authors

Signe Rifbjerg-Madsen, Eva Ejlersen Wæhrens, Bente Danneskiold-Samsøe, Kirstine Amris

Abstract

Pain is inherent in rheumatoid arthritis (RA), psoriatic arthritis (PsA) and spondyloarthritis (SpA) and traditionally considered to be of nociceptive origin. Emerging data suggest a potential role of augmented central pain mechanisms in subsets of patients, thus, valid instruments that can identify underlying pain mechanisms are needed. The painDETECT questionnaire (PDQ) was originally designed to differentiate between pain phenotypes. The objectives were to evaluate the psychometric properties of the PDQ in patients with inflammatory arthritis by applying Rasch analysis and to explore the reliability of pain classification by test-retest. For the Rasch analysis 900 questionnaires from patients with RA, PsA and SpA (300 per diagnosis) were extracted from 'the DANBIO painDETECT study'. The analysis was directed at the seven items assessing somatosensory symptoms and included: 1) the performance of the six-category Likert scale; 2) whether a unidimensional construct was defined; 3) the reliability and precision of estimates. Another group of 30 patients diagnosed with RA, PsA or SpA participated in a test-retest study. Intraclass Correlation Coefficients (ICC) and classification consistency were calculated. The Rasch analysis revealed: (1) Acceptable psychometric rating scale properties; the frequency distribution peaked in category 0 except for item 5, threshold calibration >10 observations per category, no disorder in the category measures for all items, scale category outfit Mnsq <2.0, small distances (<1.4 logits) between thresholds for category 1, 2 and 3 for all items. (2) The principal component analysis supported unidimensionality; the standardized residuals showed that 53.7% of total variance was explained by the measure and the magnitude of first contrast had an eigenvalue of 1.5, no misfitting items, clinical insignificant different item hierarchies across diagnoses (DIF < 0.5 logits). (3) A targeted item-person map, person and item separation indices of 1.88(reliability = 0.78), and 13.04 (reliability = 0.99). The test-retest revealed: ICC: RA 0.86(0.56-0.96), PsA 0.96(0.74-0.99), SpA 0.93(0.76-98), overall 0.94(0.84-0.98). Classification consistency was: RA 70%, PsA 80%, SpA 90%, overall 80%. The results support that the PDQ can be used as a classification instrument and assist identification of underlying pain-mechanisms in patients suffering from inflammatory arthritis.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 16%
Researcher 5 12%
Other 5 12%
Student > Ph. D. Student 5 12%
Student > Bachelor 5 12%
Other 5 12%
Unknown 11 26%
Readers by discipline Count As %
Medicine and Dentistry 17 40%
Nursing and Health Professions 6 14%
Sports and Recreations 1 2%
Environmental Science 1 2%
Arts and Humanities 1 2%
Other 2 5%
Unknown 15 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 2017.
All research outputs
#2,522,127
of 16,079,906 outputs
Outputs from Health and Quality of Life Outcomes
#252
of 1,774 outputs
Outputs of similar age
#56,392
of 271,545 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#1
of 1 outputs
Altmetric has tracked 16,079,906 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,774 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 85% 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 271,545 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 79% of its contemporaries.
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