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Measures to assess commonly experienced symptoms for people with dementia in long-term care settings: a systematic review

Overview of attention for article published in BMC Medicine, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)

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21 tweeters
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1 Facebook page

Citations

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20 Dimensions

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130 Mendeley
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Title
Measures to assess commonly experienced symptoms for people with dementia in long-term care settings: a systematic review
Published in
BMC Medicine, February 2016
DOI 10.1186/s12916-016-0582-x
Pubmed ID
Authors

Clare Ellis-Smith, Catherine J. Evans, Anna E. Bone, Lesley A. Henson, Mendwas Dzingina, Pauline M. Kane, Irene J. Higginson, Barbara A. Daveson

Abstract

High symptom burden is common in long-term care residents with dementia and results in distress and behavioral challenges if undetected. Physicians may have limited time to regularly examine all residents, particularly those unable to self-report, and may rely on reports from caregivers who are frequently in a good position to detect symptoms quickly. We aimed to identify proxy-completed assessment measures of symptoms experienced by people with dementia, and critically appraise the psychometric properties and applicability for use in long-term care settings by caregivers. We searched Medline, EMBASE, PsycINFO, CINAHL and ASSIA from inception to 23 June 2015, supplemented by citation and reference searches. The search strategy used a combination of terms: dementia OR long-term care AND assessment AND symptoms (e.g. pain). Studies were included if they evaluated psychometric properties of proxy-completed symptom assessment measures for people with dementia in any setting or those of mixed cognitive abilities residing in long-term care settings. Measures were included if they did not require clinical training, and used proxy-observed behaviors to support assessment in verbally compromised people with dementia. Data were extracted on study setting and sample, measurement properties and psychometric properties. Measures were independently evaluated by two investigators using quality criteria for measurement properties, and evaluated for clinical applicability in long-term settings. Of the 19,942 studies identified, 40 studies evaluating 32 measures assessing pain (n = 12), oral health (n = 2), multiple neuropsychiatric symptoms (n = 2), depression (n = 8), anxiety (n = 2), psychological wellbeing (n = 4), and discomfort (n = 2) were included. The majority of studies (31/40) were conducted in long-term care settings although none of the neuropsychiatric or anxiety measures were validated in this setting. The pain assessments, PAINAD and PACSLAC had the strongest psychometric evidence. The oral health, discomfort, and three psychological wellbeing measures were validated in this setting but require further psychometric evaluation. Depression measures were poor at detecting depression in this population. All measures require further investigation into agreement, responsiveness and interpretability. Measures for pain are best developed for this population and setting. All other measures require further validation. A multi-symptom measure to support comprehensive assessment and monitoring in this population is required.

Twitter Demographics

The data shown below were collected from the profiles of 21 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 17%
Researcher 19 15%
Student > Bachelor 12 9%
Student > Ph. D. Student 12 9%
Student > Postgraduate 10 8%
Other 31 24%
Unknown 24 18%
Readers by discipline Count As %
Medicine and Dentistry 33 25%
Nursing and Health Professions 32 25%
Psychology 16 12%
Agricultural and Biological Sciences 2 2%
Social Sciences 2 2%
Other 17 13%
Unknown 28 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 06 September 2018.
All research outputs
#1,309,516
of 14,094,074 outputs
Outputs from BMC Medicine
#1,004
of 2,207 outputs
Outputs of similar age
#33,316
of 267,088 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 14,094,074 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,207 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.6. This one has gotten more attention than average, scoring higher than 54% 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 267,088 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 87% 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