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Discriminative ability of quality of life measures in multiple sclerosis

Overview of attention for article published in Health and Quality of Life Outcomes, December 2017
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Title
Discriminative ability of quality of life measures in multiple sclerosis
Published in
Health and Quality of Life Outcomes, December 2017
DOI 10.1186/s12955-017-0828-0
Pubmed ID
Authors

Kirsten M. Fiest, Jamie Greenfield, Luanne M. Metz, Scott B. Patten, Nathalie Jetté, Ruth Ann Marrie

Abstract

Though many people with multiple sclerosis (MS) have comorbidities, the use of generic and disease-specific health related quality of life (HRQOL) scales to discriminate the effects of comorbidity has not been established. The utility of these scales to discriminate differences between persons with varying levels of disability is also unknown. Using online questionnaires, a convenience sample of Albertans with MS was recruited between July 2011 and March 2013. Participants completed demographic questions, a validated comorbidity questionnaire, a self-reported disability scale, and the following HRQOL scales: the Short Form (SF)-36, SF-6D, Health Utilities Index-Mark III (HUI-III), and Multiple Sclerosis Quality of Life-54 (MSQOL-54). The ability of each HRQOL scale to distinguish between comorbidity groups was assessed using a one-way analysis of covariance, adjusting for age, sex, disease course, and disability level. Five hundred sixty three participants completed all relevant questionnaires. All HRQOL measures distinguished between persons with or without depression, while none were able to distinguish between participants with or without hypertension, thyroid disease, irritable bowel syndrome, or osteoporosis. The SF-36 physical scale, SF-6D, HUI-III, and MSQOL-54 physical scales were able to distinguish between all disability groups, though the HUI-III was better able to distinguish between individuals with moderate versus severe disability. Disease-specific measures would discriminate better between those with and without comorbidities than generic-specific measures and the HUI-III would discriminate best between persons with differing severities of disability. Generic or disease-specific measures may be useful in future studies examining the effects of comorbidity in MS and the effects of treatment of comorbidities in MS.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 13%
Student > Bachelor 9 13%
Student > Ph. D. Student 6 9%
Other 5 7%
Student > Doctoral Student 3 4%
Other 9 13%
Unknown 27 40%
Readers by discipline Count As %
Medicine and Dentistry 13 19%
Nursing and Health Professions 9 13%
Neuroscience 3 4%
Biochemistry, Genetics and Molecular Biology 2 3%
Agricultural and Biological Sciences 2 3%
Other 8 12%
Unknown 31 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 December 2017.
All research outputs
#17,923,510
of 23,012,811 outputs
Outputs from Health and Quality of Life Outcomes
#1,512
of 2,186 outputs
Outputs of similar age
#308,735
of 440,658 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#48
of 64 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,186 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 21st percentile – i.e., 21% 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 440,658 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.