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Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model

Overview of attention for article published in Population Health Metrics, July 2016
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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 (76th percentile)

Mentioned by

policy
1 policy source
twitter
1 tweeter
patent
1 patent

Citations

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82 Dimensions

Readers on

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248 Mendeley
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Title
Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model
Published in
Population Health Metrics, July 2016
DOI 10.1186/s12963-016-0091-3
Pubmed ID
Authors

Shaoman Yin, Rashid Njai, Lawrence Barker, Paul Z. Siegel, Youlian Liao

Abstract

Health-related quality of life (HRQOL) is a multi-dimensional concept commonly used to examine the impact of health status on quality of life. HRQOL is often measured by four core questions that asked about general health status and number of unhealthy days in the Behavioral Risk Factor Surveillance System (BRFSS). Use of these measures individually, however, may not provide a cohesive picture of overall HRQOL. To address this concern, this study developed and tested a method for combining these four measures into a summary score. Exploratory and confirmatory factor analyses were performed using BRFSS 2013 data to determine potential numerical relationships among the four HRQOL items. We also examined the stability of our proposed one-factor model over time by using BRFSS 2001-2010 and BRFSS 2011-2013 data sets. Both exploratory factor analysis and goodness of fit tests supported the notion that one summary factor could capture overall HRQOL. Confirmatory factor analysis indicated acceptable goodness of fit of this model. The predicted factor score showed good validity with all of the four HRQOL items. In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013. Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct. The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 248 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 41 17%
Student > Master 38 15%
Student > Ph. D. Student 23 9%
Researcher 18 7%
Student > Postgraduate 18 7%
Other 38 15%
Unknown 72 29%
Readers by discipline Count As %
Medicine and Dentistry 61 25%
Nursing and Health Professions 37 15%
Psychology 16 6%
Pharmacology, Toxicology and Pharmaceutical Science 14 6%
Social Sciences 12 5%
Other 31 13%
Unknown 77 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 July 2022.
All research outputs
#4,287,126
of 21,873,319 outputs
Outputs from Population Health Metrics
#131
of 389 outputs
Outputs of similar age
#64,995
of 273,870 outputs
Outputs of similar age from Population Health Metrics
#1
of 1 outputs
Altmetric has tracked 21,873,319 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 389 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 65% 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 273,870 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 76% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them