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Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D

Overview of attention for article published in Health and Quality of Life Outcomes, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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1 news outlet
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1 X user
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1 Facebook page
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1 Redditor

Citations

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17 Dimensions

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104 Mendeley
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Title
Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
Published in
Health and Quality of Life Outcomes, January 2017
DOI 10.1186/s12955-017-0585-0
Pubmed ID
Authors

Kim-Huong Nguyen, Brendan Mulhern, Sanjeewa Kularatna, Joshua Byrnes, Wendy Moyle, Tracy Comans

Abstract

With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, and this study aims to develop a dementia-specific health state classification system based on the Quality of Life for Alzheimer's disease (QOL-AD) instrument (nursing home version). This classification system will subsequently be valued to generate a preference-based measure for use in the economic evaluation of interventions for people with dementia. We assessed the dimensionality of the QOL-AD to develop a new classification system. This was done using exploratory and confirmatory factor analysis and further assessment of the structure of the measure to ensure coverage of the key areas of quality of life. Secondly, we used Rasch analysis to test the psychometric performance of the items, and select item(s) to describe each dimension. This was done on 13 items of the QOL-AD (excluding two general health items) using a sample of 284 residents living in long-term care facilities in Australia who had a diagnosis of dementia. A five dimension classification system is proposed resulting from the three factor structure (defined as 'interpersonal environment', 'physical health' and 'self-functioning') derived from the factor analysis and two factors ('memory' and 'mood') from the accompanying review. For the first three dimensions, Rasch analysis selected three questions of the QOL-AD ('living situation', 'physical health', and 'do fun things') with memory and mood questions representing their own dimensions. The resulting classification system (AD-5D) includes many of the health-related quality of life dimensions considered important to people with dementia, including mood, global function and skill in daily living. The development of the AD-5D classification system is an important step in the future application of the widely used QOL-AD in economic evaluations. Future valuation studies will enable this tool to be used to calculate quality adjusted life years to evaluate treatments and interventions for people diagnosed with mild to moderate dementia.

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X Demographics

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

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 20%
Student > Ph. D. Student 13 13%
Student > Bachelor 9 9%
Student > Doctoral Student 9 9%
Researcher 7 7%
Other 15 14%
Unknown 30 29%
Readers by discipline Count As %
Nursing and Health Professions 19 18%
Medicine and Dentistry 18 17%
Psychology 13 13%
Business, Management and Accounting 3 3%
Social Sciences 3 3%
Other 15 14%
Unknown 33 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 03 February 2017.
All research outputs
#3,087,030
of 22,947,506 outputs
Outputs from Health and Quality of Life Outcomes
#249
of 2,180 outputs
Outputs of similar age
#65,891
of 419,016 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#8
of 46 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,180 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 88% 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 419,016 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 84% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.