Pain in severe dementia: A comparison of a fine‐grained assessment approach to an observational checklist designed for clinical settings

BACKGROUND: Fine‐grained observational approaches to pain assessment (e.g. the Facial Action Coding System; FACS) are used to evaluate pain in individuals with and without dementia. These approaches are difficult to utilize in clinical settings as they require specialized training and equipment. Easy‐to‐use observational approaches (e.g. the Pain Assessment Checklist for Limited Ability to Communicate‐II; PACSLAC‐II) have been developed for clinical settings. Our goal was to compare a FACS‐based fine‐grained system to the PACSLAC‐II in differentiating painful from non‐painful states in older adults with and without dementia. METHOD: We video‐recorded older long‐term care residents with dementia and older adult outpatients without dementia, during a quiet baseline condition and while they took part in a physiotherapy examination designed to identify painful areas. Videos were coded using pain‐related behaviours from the FACS and the PACSLAC‐II. RESULTS: Both tools differentiated between painful and non‐painful states, but the PACSLAC‐II accounted for more variance than the FACS‐based approach. Participants with dementia scored higher on the PACSLAC‐II than participants without dementia. CONCLUSION: The results suggest that easy‐to‐use observational approaches for clinical settings are valid and that there may not be any clinically important advantages to using more resource‐intensive coding approaches based on FACS. We acknowledge, as a limitation of our study, that we used as baseline a quiet condition that did not involve significant patient movement. In contrast, our pain condition involved systematic patient movement. Future research should be aimed at replicating our results using a baseline condition that involves non‐painful movements. SIGNIFICANCE: Examining older adults with and without dementia, a brief observational clinical approach was found to be valid and accounted for more variance in differentiating pain‐related and non‐pain‐related states than did a detailed time‐consuming fine‐grained approach.