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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Academic Research Enhancement Awards (AREA) (R15)
Project #
1R15NR008405-01A1
Application #
6752698
Study Section
Nursing Science: Adults and Older Adults Study Section (NSAA)
Program Officer
Toward, Jeffrey I
Project Start
2004-05-01
Project End
2007-04-30
Budget Start
2004-05-01
Budget End
2007-04-30
Support Year
1
Fiscal Year
2004
Total Cost
$213,000
Indirect Cost
Name
University of Arkansas for Medical Sciences
Department
Type
Schools of Nursing
DUNS #
122452563
City
Little Rock
State
AR
Country
United States
Zip Code
72205
Tsai, Pao-Feng; Kuo, Yong-Fang; Beck, Cornelia et al. (2011) Non-verbal cues to osteoarthritic knee and/or hip pain in elders. Res Nurs Health 34:218-27
Tsai, Pao-Feng; Beck, Cornelia; Richards, Kathy C et al. (2008) The Pain Behaviors for Osteoarthritis Instrument for Cognitively Impaired Elders (PBOICIE). Res Gerontol Nurs 1:116-22