Sandy Brauer

Bio: Sandy Brauer is an academic researcher from University of Oregon. The author has contributed to research in topics: Timed Up and Go test. The author has an hindex of 1, co-authored 1 publications receiving 2719 citations.

Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test.

Abstract: Background and Purpose. This study examined the sensitivity and specificity of the Timed Up & Go Test (TUG) under single-task versus dual-task conditions for identifying elderly individuals who are prone to falling. Subjects. Fifteen older adults with no history of falls (mean age578 years, SD56, range565‐ 85) and 15 older adults with a history of 2 or more falls in the previous 6 months (mean age586.2 years, SD56, range576 ‐95) participated. Methods. Time taken to complete the TUG under 3 conditions (TUG, TUG with a subtraction task [TUG cognitive], and TUG while carrying a full cup of water [TUG manual]) was measured. A multivariate analysis of variance and discriminant function and logistic regression analyses were performed. Results. The TUG was found to be a sensitive (sensitivity587%) and specific (specificity587%) measure for identifying elderly individuals who are prone to falls. For both groups of older adults, simultaneous performance of an additional task increased the time taken to complete the TUG, with the greatest effect in the older adults with a history of falls. The TUG scores with or without an additional task (cognitive or manual) were equivalent with respect to identifying fallers and nonfallers. Conclusions and Discussion. The results suggest that the TUG is a sensitive and specific measure for identifying communitydwelling adults who are at risk for falls. The ability to predict falls is not enhanced by adding a secondary task when performing the TUG. [Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Phys Ther. 2000;80:896 ‐903.]

Age- and Gender-Related Test Performance in Community-Dwelling Elderly People: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and Gait Speeds

Abstract: Background and Purpose. The interpretation of patient scores on clinical tests of physical mobility is limited by a lack of data describing the range of performance among people without disabilities. The purpose of this study was to provide data for 4 common clinical tests in a sample of community-dwelling older adults. Subjects. Ninety-six community-dwelling elderly people (61–89 years of age) with independent functioning performed 4 clinical tests. Methods. Data were collected on the Six-Minute Walk Test (6MW), Berg Balance Scale (BBS), and Timed Up & Go Test (TUG) and during comfortable- and fast-speed walking (CGS and FGS). Intraclass correlation coefficients (ICCs) were used to determine the test-retest reliability for the 6MW, TUG, CGS, and FGS measurements. Data were analyzed by gender and age (60–69, 70–79, and 80–89 years) cohorts, similar to previous studies. Means, standard deviations, and 95% confidence intervals for each measurement were calculated for each cohort. Results. The 6MW, TUG, CGS, and FGS measurements showed high test-retest reliability (ICC [2,1]=.95–.97). Mean test scores showed a trend of age-related declines for the 6MW, BBS, TUG, CGS, and FGS for both male and female subjects. Discussion and Conclusion. Preliminary descriptive data suggest that physical therapists should use age-related data when interpreting patient data obtained for the 6MW, BBS, TUG, CGS and FGS. Further data on these clinical tests with larger sample sizes are needed to serve as a reference for patient comparisons.

Reference values for the timed up and go test: a descriptive meta-analysis.

Abstract: Background and Purpose:The Timed Up and Go (TUG) test is widely employed in the examination of elders, but definitive normative reference values are lacking. This meta-analysis provided such values by consolidating data from multiple studies.Methods:Studies reporting TUG times for apparently

The Balance Evaluation Systems Test (BESTest) to Differentiate Balance Deficits

Abstract: Background: Current clinical balance assessment tools do not aim to help therapists identify the underlying postural control systems responsible for poor functional balance. By identifying the disordered systems underlying balance control, therapists can direct specific types of intervention for different types of balance problems. Objective: The goal of this study was to develop a clinical balance assessment tool that aims to target 6 different balance control systems so that specific rehabilitation approaches can be designed for different balance deficits. This article presents the theoretical framework, interrater reliability, and preliminary concurrent validity for this new instrument, the Balance Evaluation Systems Test (BESTest). Design: The BESTest consists of 36 items, grouped into 6 systems: “Biomechanical Constraints,” “Stability Limits/Verticality,” “Anticipatory Postural Adjustments,” “Postural Responses,” “Sensory Orientation,” and “Stability in Gait.” Methods: In 2 interrater trials, 22 subjects with and without balance disorders, ranging in age from 50 to 88 years, were rated concurrently on the BESTest by 19 therapists, students, and balance researchers. Concurrent validity was measured by correlation between the BESTest and balance confidence, as assessed with the Activities-specific Balance Confidence (ABC) Scale. Results: Consistent with our theoretical framework, subjects with different diagnoses scored poorly on different sections of the BESTest. The intraclass correlation coefficient (ICC) for interrater reliability for the test as a whole was .91, with the 6 section ICCs ranging from .79 to .96. The Kendall coefficient of concordance among raters ranged from .46 to 1.00 for the 36 individual items. Concurrent validity of the correlation between the BESTest and the ABC Scale was r =.636, P <.01. Limitations: Further testing is needed to determine whether: (1) the sections of the BESTest actually detect independent balance deficits, (2) other systems important for balance control should be added, and (3) a shorter version of the test is possible by eliminating redundant or insensitive items. Conclusions: The BESTest is easy to learn to administer, with excellent reliability and very good validity. It is unique in allowing clinicians to determine the type of balance problems to direct specific treatments for their patients. By organizing clinical balance test items already in use, combined with new items not currently available, the BESTest is the most comprehensive clinical balance tool available and warrants further development.