Walking test procedures influence speed measurements in individuals with chronic stroke.

Clin Biomech (Bristol)

Brain Plasticity Lab, Department of Physical Therapy, College of Applied Health Sciences University of Illinois at Chicago, Chicago, IL, USA. Electronic address:

Published: December 2020

Background: Walking speed measurements are clinically important, but varying test procedures may influence measurements and impair clinical utility. This study assessed the concurrent validity of walking speed in individuals with chronic stroke measured during the 10-m walk test with variations in 1) the presence of an electronic mat, 2) the speed measurement device, and 3) the measurement distance relative to the total test distance.

Methods: Twenty-five individuals with chronic stroke performed walking tests at comfortable and maximal walking speeds under three conditions: 1) 10-m walk test (without electronic mat) measured by stopwatch, 2) 10-m walk test (partially over an electronic mat) measured by software, and 3) 10-m walk test (partially over an electronic mat) measured by stopwatch. Analyses of systematic bias, proportional bias, and absolute agreement were performed to determine concurrent validity between conditions.

Findings: Walking speeds were not different between measurements (P ≥ 0.11), except maximal walking speed was faster when speed was measured with software vs. stopwatch (P = 0.002). Absolute agreement between measurements was excellent (ICC ≥ 0.97, P < 0.001). There was proportional bias between software vs. stopwatch (R ≥ 0.19, P ≤ 0.03) and between tests with vs. without the electronic mat (R = 0.27, P = 0.008). Comparisons between conditions revealed that walking speed and concurrent validity may be influenced by walking test distance, presence of an electronic mat, speed measurement device, and relative measurement distance.

Interpretation: Walking test procedures influence walking speed and concurrent validity between measurements. Waking test procedures should be as similar as possible with normative data or between repeated measurements to optimize validity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749042PMC
http://dx.doi.org/10.1016/j.clinbiomech.2020.105197DOI Listing

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