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Level of agreement between patient-reported EQ-5D responses and EQ-5D responses mapped from the SF-12 in an injury population

Overview of attention for article published in Population Health Metrics, June 2015
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Title
Level of agreement between patient-reported EQ-5D responses and EQ-5D responses mapped from the SF-12 in an injury population
Published in
Population Health Metrics, June 2015
DOI 10.1186/s12963-015-0047-z
Pubmed ID
Authors

Belinda J Gabbe, Emma McDermott, Pam M Simpson, Sarah Derrett, Shanthi Ameratunga, Suzanne Polinder, Ronan A Lyons, Frederick P Rivara, James E Harrison

Abstract

Comparing health-related quality of life (HRQL) outcomes between studies is difficult due to the wide variety of instruments used. Comparing study outcomes and facilitating pooled data analyses requires valid "crosswalks" between HRQL instruments. Algorithms exist to map 12-item Short Form Health Survey (SF-12) responses to EQ-5D item responses and preference weights, but none have been validated in populations where disability is prevalent, such as injury. Data were extracted from the Validating and Improving injury Burden Estimates Study (Injury-VIBES) for 10,166 adult, hospitalized trauma patients, with both the three-level EQ-5D (EQ-5D-3L) and SF-12 data responses at six and 12-months postinjury. Agreement between actual (patient-reported) and estimated (mapped from SF-12) EQ-5D-3L item responses and preference weights was assessed using Kappa, Prevalence-Adjusted Bias-Adjusted Kappa statistics and Bland-Altman plots. Moderate agreement was observed for usual activities, pain/discomfort, and anxiety/depression. Agreement was substantial for mobility and self-care items. The mean differences in preference weights were -0.024 and -0.012 at six and 12 months (p < 0.001), respectively. The Bland-Altman plot limits of agreement were large compared to the range of valid preference weight values (-0.56 to 1.00). Estimated EQ-5D-3L responses under-reported disability for all items except pain/discomfort. Caution should be taken when using EQ-5D-3L responses mapped from the SF-12 to describe patient outcomes or when undertaking economic evaluation, due to the underestimation of disability associated with mapped values. The findings from this study could be used to adjust expected EQ-5D-3L preference weights when estimated from SF-12 item responses when combining data from studies that use either instrument.

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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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 48 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 8 16%
Student > Master 5 10%
Student > Doctoral Student 5 10%
Student > Bachelor 4 8%
Other 11 22%
Unknown 6 12%
Readers by discipline Count As %
Medicine and Dentistry 10 20%
Nursing and Health Professions 9 18%
Psychology 5 10%
Economics, Econometrics and Finance 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 8 16%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 March 2018.
All research outputs
#6,956,103
of 22,811,321 outputs
Outputs from Population Health Metrics
#199
of 392 outputs
Outputs of similar age
#81,531
of 264,753 outputs
Outputs of similar age from Population Health Metrics
#3
of 6 outputs
Altmetric has tracked 22,811,321 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
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 47th percentile – i.e., 47% 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 264,753 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 68% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.