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Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS®)

Overview of attention for article published in Health and Quality of Life Outcomes, June 2016
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Title
Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS®)
Published in
Health and Quality of Life Outcomes, June 2016
DOI 10.1186/s12955-016-0483-x
Pubmed ID
Authors

John E. Ware, Barbara Gandek, Rick Guyer, Nina Deng

Abstract

To document the development and evaluation of the Quality of life Disease Impact Scale (QDIS®), a measure that standardizes item content and scoring across chronic conditions and provides a summary, norm-based QOL impact score for each disease. A bank of 49 disease impact items was constructed from previously-used descriptions of health impact to represent ten frequently-measured quality of life (QOL) content areas and operational definitions successfully utilized in generic QOL surveys. In contrast to health in general, all items were administered with attribution to a specific disease (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, chronic kidney disease (CKD), diabetes, asthma, or COPD). Responses from 5418 adults were analyzed as five disease groups: arthritis, cardiovascular, CKD, diabetes, and respiratory. Unidimensionality, item parameter and scale-level invariance, reliability, validity and responsiveness to change during 9-month follow-up were evaluated by disease group and for all groups combined using multi-group confirmatory factor analysis (MGCFA), item response theory (IRT) and analysis of variance methods. QDIS was normed in an independent chronically ill US population sample (N = 4120). MGCFA confirmed a 1-factor model, justifying a summary score estimated using equal parameters for each item across disease groups. In support of standardized IRT-based scoring, correlations were very high between disease-specific and standardized IRT item slopes (r = 0.88-0.96), thresholds (r = 0.93-0.99) and person-level scores (r ≥ 0.99). Internal consistency, test-retest and person-level IRT reliability were consistently satisfactory across groups. In support of interpreting QDIS as a disease-specific measure, in comparison with generic measures, QDIS consistently discriminated markedly better across disease severity levels, correlated higher with other disease-specific measures in cross-sectional tests, and was more responsive in comparisons of groups with better, same or worse evaluations of disease-specific outcomes at the 9-month follow-up. Standardization of content and scoring across diseases was shown to be justified psychometrically and enabled the first summary measure of disease-specific QOL impact normed in the chronically ill population. This disease-specific approach substantially improves discriminant validity and responsiveness over generic measures and provides a basis for better understanding the relative QOL impact of multiple chronic conditions in research and clinical practice.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Denmark 1 <1%
Unknown 164 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 14%
Student > Ph. D. Student 21 13%
Researcher 16 10%
Student > Postgraduate 14 8%
Other 12 7%
Other 39 23%
Unknown 41 25%
Readers by discipline Count As %
Medicine and Dentistry 43 26%
Nursing and Health Professions 20 12%
Psychology 16 10%
Agricultural and Biological Sciences 6 4%
Economics, Econometrics and Finance 6 4%
Other 25 15%
Unknown 50 30%
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 02 June 2016.
All research outputs
#18,461,618
of 22,875,477 outputs
Outputs from Health and Quality of Life Outcomes
#1,671
of 2,160 outputs
Outputs of similar age
#254,892
of 339,291 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#22
of 41 outputs
Altmetric has tracked 22,875,477 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,160 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.