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Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

Overview of attention for article published in Quality of Life Research, June 2016
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Title
Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores
Published in
Quality of Life Research, June 2016
DOI 10.1007/s11136-016-1343-1
Pubmed ID
Authors

Kia-Chong Chua, Anna Brown, Ryan Little, David Matthews, Liam Morton, Vanessa Loftus, Caroline Watchurst, Rhian Tait, Renee Romeo, Sube Banerjee

Abstract

There is a need to determine whether health-related quality-of-life (HRQL) assessments in dementia capture what is important, to form a coherent basis for guiding research and clinical and policy decisions. This study investigated structural validity of HRQL assessments made using the DEMQOL system, with particular interest in studying domains that might be central to HRQL, and the external validity of these HRQL measurements. HRQL of people with dementia was evaluated by 868 self-reports (DEMQOL) and 909 proxy reports (DEMQOL-Proxy) at a community memory service. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted using bifactor models to investigate domains that might be central to general HRQL. Reliability of the general and specific factors measured by the bifactor models was examined using omega (ω) and omega hierarchical (ω h) coefficients. Multiple-indicators multiple-causes models were used to explore the external validity of these HRQL measurements in terms of their associations with other clinical assessments. Bifactor models showed adequate goodness of fit, supporting HRQL in dementia as a general construct that underlies a diverse range of health indicators. At the same time, additional factors were necessary to explain residual covariation of items within specific health domains identified from the literature. Based on these models, DEMQOL and DEMQOL-Proxy overall total scores showed excellent reliability (ω h > 0.8). After accounting for common variance due to a general factor, subscale scores were less reliable (ω h < 0.7) for informing on individual differences in specific HRQL domains. Depression was more strongly associated with general HRQL based on DEMQOL than on DEMQOL-Proxy (-0.55 vs -0.22). Cognitive impairment had no reliable association with general HRQL based on DEMQOL or DEMQOL-Proxy. The tenability of a bifactor model of HRQL in dementia suggests that it is possible to retain theoretical focus on the assessment of a general phenomenon, while exploring variation in specific HRQL domains for insights on what may lie at the 'heart' of HRQL for people with dementia. These data suggest that DEMQOL and DEMQOL-Proxy total scores are likely to be accurate measures of individual differences in HRQL, but that subscale scores should not be used. No specific domain was solely responsible for general HRQL at dementia diagnosis. Better HRQL was moderately associated with less depressive symptoms, but this was less apparent based on informant reports. HRQL was not associated with severity of cognitive impairment.

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The data shown below were collected from the profiles of 6 X users 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 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 103 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 18%
Student > Ph. D. Student 14 14%
Student > Bachelor 10 10%
Student > Doctoral Student 7 7%
Researcher 6 6%
Other 15 15%
Unknown 32 31%
Readers by discipline Count As %
Nursing and Health Professions 21 20%
Psychology 19 18%
Medicine and Dentistry 11 11%
Social Sciences 3 3%
Agricultural and Biological Sciences 2 2%
Other 11 11%
Unknown 36 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 28 November 2016.
All research outputs
#6,152,498
of 22,877,793 outputs
Outputs from Quality of Life Research
#581
of 2,849 outputs
Outputs of similar age
#102,106
of 353,574 outputs
Outputs of similar age from Quality of Life Research
#10
of 67 outputs
Altmetric has tracked 22,877,793 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,849 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 79% 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 353,574 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 71% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.