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Bettina Von Kampen

Asia University, Taiwan

Title: Adapting the Tinetti tool for balance and gait for person with dementia

Biography

Biography: Bettina Von Kampen

Abstract

Background: A recent review of the literature reveals an absence of standardized measures to assess mobility in persons with advanced dementia. Persons with moderate to severe dementia have significant difficulty adhering to instructions. The aim of the study was to develop a standardized measure of gait and balance for use with persons with dementia. We chose to modify the ‘Tinetti Assessment Tool for Balance and Gait’ because many of the items are based on observation. Modification of test items requires analysis of reliability prior to establishing validity. Objective: To determine the inter-rater and test-retest reliability of ‘Tinetti Assessment Tool for Balance and Gait-Dementia’ Methods: Inter-rater reliability: Participants were observed and scored simultaneously by two raters familiar with the written instructions (physiotherapy, occupational therapy or nursing staff). Test-retest reliability: The test was re-administered after 10 to 30 minutes. Results: A total of n=20 participants were recruited and included. The mean age of participants was 75 with the majority being female (n=11, 55%). All were diagnosed with dementia or cognitive impairment. Secondary diagnoses include heart disease, diabetes and Parkinson’s disease. The mean cognitive assessment (SMMSE) score was 8.5/30 (n=12). Inter-rater reliability of the total score was high (r=0.90) as was test-retest reliability (r=0.92). Discussion: These results are comparable to established reliability of the original Tinetti tool (r>0.8). The results indicate that the modified measure has sufficient reliability to commence validity testing. Developing a measure that assesses functional changes in this population is important for determining the impact of mobilization and least restraint programs for people with dementia in long term care. Further study will establish validity of the cut score for predicting falls risk.

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