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The Balance Evaluation Systems Test (BESTest), a clinical balance measure, categorizes balance into 6 factors. The aim of this study was to determine which short versions of the BESTest, Mini-BESTest, and Brief-BESTest, were most appropriate for assessing balance impairments in older adults with femoral or vertebral fracture. Subjects were older adults (age ≥65 years), who could walk with out physical assistance. The models' fitting was evaluated for four BESTest models (BESTest, one-factor Mini-BESTest, four-factor Mini-BESTest, and Brief-BESTest). The four-factor Mini-BESTest model was the only model that had a good fit and reflected the balance ability in older adults with femoral or vertebral fracture. We suggest that the using the four-factor Mini-BESTest model and seeing dynamic balance as composed of four factors may help therapists in making clinical decisions. Objective: To clarify and compare the structural validity of 3 Balance Evaluation Systems Tests (BESTest, Mini-BESTest, and Brief-BESTest) in older adults with femoral or vertebral fractures. Design: Cross-sectional study. Subjects: Ninety-four older adults (age ≥65 years) with femoral or vertebral fractures, who could walk without physical assistance. Methods: Four BESTest models (BESTest, one-factor Mini-BESTest, four-factor Mini-BESTest, and Brief-BESTest) were examined using confirmatory factor analysis, and the models' goodness-of-fit was assessed. Unidimensionality of the best-fitting model was confirmed by Rasch principal component analysis on the residuals. Results: Confirmatory factor analysis showed that the four-factor Mini-BESTest model (comparative fit index = 0.952; Tucker-Lewis index = 0.937; root-mean square error of approximation = 0.060; standardized root-mean-square residual = 0.062) has a better structure than other models. The principal component analysis of standardized residuals showed that the variance attributable to Rasch factor was good, with eigenvalues < 2, confirming the factor's unidimensionality. Conclusion: The four-factor Mini-BESTest model shows good structural validity in older adults with femoral or vertebral fracture. Evaluating dynamic balance by focusing on 4 components (anticipatory postural adjustments, postural responses, sensory orientation, and stability in gait) may help therapists in making clinical decisions.

Background and Purpose: Hip fracture is a common injury in older adults, with a high proportion of hip fractures affecting women. After a hip fracture, the recovery of the patient's walking speed is very important; one of the key determinants of walking speed is balance. The Balance Evaluation Systems Test (BESTest), a clinical balance measure, categorizes balance into 6 postural control systems. However, the relationship between the walking speed level and the sections of the BESTest has not been explored for older women with hip fracture. Our objective was to establish section scores for the BESTest cutoff values for walking speed in older women with hip fracture. Methods: This was an observational study involving 46 older women 65 years or older with hip fracture. The BESTest was administered to all participants upon their discharge from the hospital. Participants were divided into groups on the basis of their walking speed levels, and receiver operating characteristic curves were determined for each section of the BESTest. We calculated the cutoff value, area under the curve (AUC), sensitivity, and specificity of each. Results: Section IV-Stability in Gait showed the highest AUC (0.92) compared with the other sections, and the cutoff value determined for the fast and slow walker groups was 64.3% (sensitivity = 0.82, specificity = 0.83). The sections with moderate AUC (0.7-0.9) were I-Biomechanical Constraints (cutoff = 70.0%), III-Anticipatory Postural Adjustments (cutoff = 66.5%), IV-Postural Responses (cutoff = 69.4%), and V-Sensory Orientation (cutoff = 83.4%). The sections with the highest sensitivity (0.82) were I-Biomechanical Constraints and VI-Stability in Gait, and that with the highest specificity (0.88) was II-Stability Limits and Verticality. Conclusions: Five of the BESTest sections (I-Biomechanical Constraints, III-Anticipatory Postural Adjustments, IV-Postural Responses, V-Sensory Orientation, and IV-Stability in Gait) were able to differentiate between fast and slow walkers among older women with hip fracture. Balance during gait and anticipatory postural adjustments were shown to be important components of balance, and their cutoff values were indicators of the balance required to reach fast walking levels.

The objective is to provide a quantitative technique to help managers to make decisions by objectively evaluating their Human Capital Management (HCM) and projecting profit increase generated by HCM. This study approach is divided into two steps. In the first step, this study selects and formulates the factors which represent HCM practices by means of principal component and factor analysis. In the second step, personnel adjusted added (PAV) value is defined as the corporate output. Multiple regression model is constructed to identify the HCM factors which influence PAV. This process establishes the model for objectively judging their success of HCM.