Using psychometric techniques to improve the Balance Evaluation Systems Test: the mini-BESTest

Franco Franchignoni, Fay Horak, Marco Godi, Antonio Nardone, Andrea Giordano, Franco Franchignoni, Fay Horak, Marco Godi, Antonio Nardone, Andrea Giordano

Abstract

Objective: To improve, with the aid of psychometric analysis, the Balance Evaluation Systems Test (BESTest), a tool designed to analyse several postural control systems that may contribute to poor functional balance in adults.

Methods: Performance of the BESTest was examined in a convenience sample of 115 consecutive adult patients with diverse neurological diagnoses and disease severity, referred to rehabilitation for balance disorders. Factor (both explorative and confirmatory) and Rasch analysis were used to process the data in order to produce a new, reduced and coherent balance measurement tool.

Results: Factor analysis selected 24 out of the 36 original BESTest items likely to represent the unidimensional construct of "dynamic balance". Rasch analysis was then used to: (i) improve the rating categories, and (ii) delete 10 items (misfitting or showing local dependency). The model consisting of the remaining 14 tasks was verified with confirmatory factor analysis to meet the stringent requirements of modern measurement.

Conclusion: The new 14-item scale (dubbed mini-BESTest) focuses on dynamic balance, can be conducted in 10-15 min, and contains items belonging evenly to 4 of the 6 sections from the original BESTest. Further studies are needed to confirm the usefulness of the mini-BESTest in clinical settings.

Figures

Figure 1
Figure 1
Subject-ability and item-difficulty maps of the mini-BESTest (n=115). In both maps, the vertical line represents the measure of the variable, in linear logit units. The left-hand column locates each patient’s ability, from best to worst dynamic balance. The right-hand column locates each item’s relative difficulty for this sample (for each item, the difficulty estimate represents the mean calibration of the threshold parameters according to the partial credit model). From bottom to top, measures indicate better balance for patients and higher difficulty for items. By convention, the average difficulty of items in the test is set at 0 logits (and indicated with M’) and patients with average ability are located at M.
Figure 2
Figure 2
Expected scores for the mini-BESTest (n=115). Distance between points is equal-interval. Logit measure at top of key, centered at the mean item difficulty. The rating scale is collapsed from 4 to 3 categories renumbered 0 (severely impaired), 1 (moderately impaired), 2 (normal). The threshold between adjacent categories is marked by ‘:’. At the bottom is the distribution of the person measures (subject ability): each marker is a single person.

Source: PubMed

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