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    Pain assessment in dementia: Evaluation of a point-of-care technological solution

    Access Status
    Open access via publisher
    Authors
    Atee, M.
    Hoti, Kreshnik
    Parsons, R.
    Hughes, Jeff
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Atee, M. and Hoti, K. and Parsons, R. and Hughes, J. 2017. Pain assessment in dementia: Evaluation of a point-of-care technological solution. Journal of Alzheimer's Disease. 60 (1): pp. 137-150.
    Source Title
    Journal of Alzheimer's Disease
    DOI
    10.3233/JAD-170375
    ISSN
    1387-2877
    School
    School of Pharmacy
    URI
    http://hdl.handle.net/20.500.11937/58748
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 - IOS Press and the authors. Pain is common among people with moderate to severe dementia, but inability of patients to self-report means it often goes undetected and untreated. We developed the electronic Pain Assessment Tool (ePAT) to address this issue. A point-of-care App, it utilizes facial recognition technology to detect facial micro-expressions indicative of pain. ePAT also records the presence of pain-related behaviors under five additional domains (Voice, Movement, Behavior, Activity, and Body). In this observational study, we assessed the psychometric properties of ePAT compared to the Abbey Pain Scale (APS). Forty aged care residents (70 females) over the age of 60 years, with moderate to severe dementia and a history of pain-related condition(s) were recruited into the study. Three hundred and fifty-three paired pain assessments (either at rest or post-movement) were recorded and analyzed. The ePAT demonstrated excellent concurrent validity (r=0.882, 95 CI: 0.857-0.903) and good discriminant validity. Inter-rater reliability score was good overall (weighted ?=0.74, 95 CI: 0.68-0.80) while internal consistency was excellent. ePAT has psychometric properties which make it suitable for use in non-communicative patients with dementia. ePAT also has the advantage of automated facial expression assessment which provides objective and reproducible evidence of the presence of pain.

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