Does the Brief-BESTest Meet Classical Test Theory and Rasch Analysis Requirements for Balance Assessment in People With Neurological Disorders?

Background The Brief Balance Evaluation Systems Test (Brief-BESTest) was recently proposed as a clinical tool for quickly measuring balance disorders, but its measurement properties warrant investigation. Objective The study objective was to perform a detailed analysis of the psychometric properties of the Brief-BESTest by means of Classical Test Theory and Rasch analysis. Design This was an observational measurement study. Methods Brief-BESTest data were collected from a sample of 244 participants. Internal consistency was analyzed with the Cronbach α and item-to-total correlations. Test-retest reliability and interrater reliability were investigated in a subgroup of 21 participants. The minimum detectable change at the 95% confidence level was calculated. Scale dimensionality was examined through Horn parallel analysis; this step was followed by exploratory factor analysis for ordinal data. Finally, data were examined using Rasch analysis (rating scale model). Results The Cronbach α was .89, and all item-to-total correlations were greater than .40. Test-retest reliability had an intraclass correlation coefficient (ICC) (2,1) of .94, and interrater reliability had an ICC (2,1) of .90. The minimum detectable change at the 95% confidence level was 4.30 points. The unidimensionality of the test was confirmed, but 1 item showed low communality. Rasch analysis revealed the inadequacy of response categories, 5 misfitting items, minor mistargeting, moderate person reliability (.80), and 2 pairs of locally dependent items. Limitations The sample was a cross-section of people who had balance disorders from different neurological etiologies and were recruited consecutively at a single rehabilitation facility. Conclusions The Brief-BESTest was confirmed to have some acceptable-to-good reliability indexes when calculated according to Classical Test Theory, but the scale showed fairly limited sensitivity to change. Rasch analysis indicated that item selection should be improved from a psychometric point of view. Item redundancy needs to be reduced, and the metric coverage of the measured construct needs to be improved with new items.