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Pain Assessment in Elders with Osteoarthritis
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abstract
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Knee and hip osteoarthritis (OA) are highly prevalent (16.6%-33% for the knee and 10.4%-26.3% for the hip) and the leading causes of disability in elders. Activity instigates and aggravates pain in patients with severe knee or hip OA. Thus, unless they are assessed for pain while performing activities, elders with OA of the knee or hip may be misclassified as pain-free. The prevalence of arthritis in elders with and without cognitive impairment (CI) is comparable. However, elders with severe CI have diminished ability to verbally communicate their OA pain and are often excluded from pain research; as a result, it is difficult to evaluate the outcome of intervention strategies for elders with severe CI and OA of the knee or hip. None of the available pain measures for elders with severe CI focuses on activity-induced OA pain. Therefore, an alternative OA-specific non-verbal pain assessment method that can identify pain in elders with severe CI is urgently needed. This study is the foundation work for developing a non-verbal pain assessment method for elders with severe CI and OA. We will only recruit elders with no or mild CI in the proposed study because they are able to express their pain and can thus validate the usefulness of the proposed method in identifying elders with OA knee or hip pain. If the proposed method is able to identify elders with OA knee or hip pain, it could become a useful non-verbal pain assessment and outcomes assessment of pain interventions for elders with severe CI in the future. This proposed pain assessment method contains two non-verbal OA pain indicators: motor and gait patterns. Patients with OA of the knee or hip show disturbances of motor and gait patterns when they are in pain but whether motor and gait patterns can be used as diagnostic tools to identify elders with or without pain has not be tested. Thus, the specific aim of this study is to examine the sensitivity and specificity of a non-verbal pain assessment method that combines measures of motor and gait patterns to predict elders with or without self-report of knee or hip pain. The sample will consist of 184 elders with no or mild CI. Keefe's motor patterns observational method and the gait portion of the Tinetti Index will measure motor and gait patterns, respectively. The Verbal Descriptor Scale will measure self-report of pain. Logistic regression will be used to achieve the specific aim.
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label
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Pain Assessment in Elders with Osteoarthritis
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