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

Mustafa Atee, Kreshnik Hoti, Richard Parsons, Jeffery D. Hughes

Research output: Contribution to journalArticle

Abstract

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 κ=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.

Original languageEnglish
Pages (from-to)137-150
Number of pages14
JournalJournal of Alzheimer's Disease
Volume60
Issue number1
DOIs
Publication statusPublished - 29 Aug 2017
Externally publishedYes

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