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dc.contributor.authorAtee, Mustafa
dc.contributor.authorHoti, Kreshnik
dc.contributor.authorChivers, Paola
dc.contributor.authorHughes, Jeffery D
dc.date.accessioned2022-05-05T05:18:59Z
dc.date.available2022-05-05T05:18:59Z
dc.date.issued2022
dc.identifier.citationAtee, M. and Hoti, K. and Chivers, P. and Hughes, J.D. 2022. Faces of Pain in Dementia: Learnings From a Real-World Study Using a Technology-Enabled Pain Assessment Tool. Frontiers in Pain Research. 3: Article No. 827551.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/88396
dc.identifier.doi10.3389/fpain.2022.827551
dc.description.abstract

Pain is common in people living with dementia (PLWD), including those with limited verbal skills. Facial expressions are key behavioral indicators of the pain experience in this group. However, there is a lack of real-world studies to report the prevalence and associations of pain-relevant facial micro-expressions in PLWD. In this observational retrospective study, pain-related facial features were studied in a sample of 3,144 PLWD [mean age 83.3 years (SD = 9.0); 59.0% female] using the Face domain of PainChek®, a point-of-care medical device application. Pain assessments were completed by 389 users from two national dementia-specific care programs and 34 Australian aged care homes. Our analysis focused on the frequency, distribution, and associations of facial action units [AU(s)] with respect to various pain intensity groups. A total of 22,194 pain assessments were completed. Of the AUs present, AU7 (eyelid tightening) was the most frequent facial expression (48.6%) detected, followed by AU43 (closing eyes; 42.9%) and AU6 (cheek raising; 42.1%) during severe pain. AU20 (horizontal mouth stretch) was the most predictive facial action of higher pain scores. Eye-related AUs (AU6, AU7, AU43) and brow-related AUs (AU4) were more common than mouth-related AUs (e.g., AU20, AU25) during higher pain intensities. No significant effect was found for age or gender. These findings offer further understanding of facial expressions during clinical pain in PLWD and confirm the usefulness of artificial intelligence (AI)-enabled real-time analysis of the face as part of the assessment of pain in aged care clinical practice.

dc.languageeng
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectPainChek®
dc.subjectaction units
dc.subjectaged care
dc.subjectartificial intelligence
dc.subjectdementia
dc.subjectfacial expressions
dc.subjectpain
dc.subjectreal-world
dc.titleFaces of Pain in Dementia: Learnings From a Real-World Study Using a Technology-Enabled Pain Assessment Tool.
dc.typeJournal Article
dcterms.source.volume3
dcterms.source.startPage827551
dcterms.source.issn2673-561X
dcterms.source.titleFrontiers in Pain Research
dc.date.updated2022-05-05T05:18:59Z
curtin.departmentCurtin Medical School
curtin.accessStatusOpen access
curtin.facultyFaculty of Health Sciences
curtin.contributor.orcidAtee, Mustafa [0000-0002-0837-3245]
curtin.contributor.researcheridAtee, Mustafa [L-3636-2018]
dcterms.source.eissn2673-561X
curtin.contributor.scopusauthoridAtee, Mustafa [57195542382]


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