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Mapping EQ-5D utilities to GBD 2010 and GBD 2013 disability weights: results of two pilot studies in Belgium

Overview of attention for article published in Archives of Public Health, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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11 tweeters

Citations

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8 Dimensions

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19 Mendeley
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Title
Mapping EQ-5D utilities to GBD 2010 and GBD 2013 disability weights: results of two pilot studies in Belgium
Published in
Archives of Public Health, February 2017
DOI 10.1186/s13690-017-0174-z
Pubmed ID
Authors

C. Maertens de Noordhout, B. Devleesschauwer, L. Gielens, M. H. D. Plasmans, J. A. Haagsma, N. Speybroeck

Abstract

Utilities and disability weights (DWs) are metrics used for calculating Quality-Adjusted Life Years and Disability-Adjusted Life Years (DALYs), respectively. Utilities can be obtained with multi-attribute instruments such as the EuroQol 5 dimensions questionnaire (EQ-5D). In 2010 and 2013, Salomon et al. proposed a set of DWs for 220 and 183 health states, respectively. The objective of this study is to develop an approach for mapping EQ-5D utilities to existing GBD 2010 and GBD 2013 DWs, allowing to predict new GBD 2010/2013 DWs based on EQ-5D utilities. We conducted two pilot studies including respectively four and twenty-seven health states selected from the 220 DWs of the GBD 2010 study. In the first study, each participant evaluated four health conditions using the standard written EQ-5D-5 L questionnaire. In the second study, each participant evaluated four health conditions randomly selected among the twenty-seven health states using a previously developed web-based EQ-5D-5 L questionnaire. The EQ-5D responses were translated into utilities using the model developed by Cleemput et al. A loess regression allowed to map EQ-5D utilities to logit transformed DWs. Overall, 81 and 393 respondents completed the first and the second survey, respectively. In the first study, a monotonic relationship between derived utilities and predicted GBD 2010/2013 DWs was observed, but not in the second study. There were some important differences in ranking of health states based on utilities versus GBD 2010/2013 DWs. The participants of the current study attributed a relatively higher severity level to musculoskeletal disorders such as 'Amputation of both legs' and a relatively lower severity level to non-functional disorders such as 'Headache migraine' compared to the participants of the GBD 2010/2013 studies. This study suggests the possibility to translate any utility derived from EQ-5D scores into a DW, but also highlights important caveats. We observed a satisfactory result of this methodology when utilities were derived from a population of public health students, a written questionnaire and a small number of health states in the presence of a study leader. However the results were unsatisfactory when utilities were derived from a sample of the general population, using a web-based questionnaire. We recommend to repeat the study in a larger and more diverse sample to obtain a more representative distribution of educational level and age.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 32%
Student > Ph. D. Student 3 16%
Student > Master 3 16%
Student > Doctoral Student 2 11%
Student > Bachelor 2 11%
Other 2 11%
Unknown 1 5%
Readers by discipline Count As %
Medicine and Dentistry 4 21%
Psychology 3 16%
Economics, Econometrics and Finance 2 11%
Business, Management and Accounting 2 11%
Veterinary Science and Veterinary Medicine 2 11%
Other 3 16%
Unknown 3 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 July 2017.
All research outputs
#3,733,388
of 16,054,112 outputs
Outputs from Archives of Public Health
#187
of 493 outputs
Outputs of similar age
#89,216
of 359,568 outputs
Outputs of similar age from Archives of Public Health
#3
of 7 outputs
Altmetric has tracked 16,054,112 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 493 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has gotten more attention than average, scoring higher than 61% 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 359,568 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 75% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.