Abstract
The study aim was to assess the reliability to active trunk movements measurement in four sitting positions in wheelchair basketball players and to check their trunk movements in these positions. Eighteen volunteer wheelchair basketball athletes, with a minimum of five years’ training experience, were asked to perform the maximum range of active trunk movement in three planes in four sitting positions (in a sports wheelchair with straps, without straps, on a table with feet on the floor, on a table without foot support). The range of movement was measured by the Kinect for Windows V2 sensor twice (with one-week interval). To assess the reliability, different statistical methods were used for each movement: significance of differences between the results (p-value), interclass correlation coefficient (ICC) and minimal detectable change (MDC). The limits of agreement analysis (LOA) were calculated. Differences between trunk movements in four positions were checked by the MANOVA (Wilk’s Lambda and ETA2 were calculated if data were normally distributed). The significance level was set at α < .05. Friedman ANOVA and non-parametric Wilcoxon test with the Bonferroni correction were applied when data were not normally distributed. The significance level after Bonferroni correction was set at α < .013 (α = p/k, where p = .05, k–number of positions = 4). The measurement of active trunk movement in each plane was reliable (p > .05, no differences between the results, “very good”ICC, between .96-.99). In the position with straps, the trunk movement was significantly bigger than in other positions (p < .05), except for the position without straps (p > .05). The Kinect for Windows V2 sensor measured active trunk movement in a reliable manner and it can be recommended as a reliable tool for measuring trunk function. Utilizing straps by wheelchair basketball players increases their trunk movement.
Highlights
Trunk function significantly influences the quality of movements in a chair in everyday activities of wheelchair users such as sitting, propelling a wheelchair, transferring, eating, dressing up/undressing, etc. [1,2,3,4,5,6,7]
Reliability of measurement of active trunk movement in wheelchair basketball players movement assessment is one of the main points to evaluate in the classification process in wheelchair sports, because sports activities are depended on trunk movement in three planes: the sagittal plane, the coronal plane and the transverse plane
The examination of validity and reliability of methods used for assessing trunk function is important, needed and supported by the International Paralympic Committee as a part of classification systems development; i.e., conducting research according to evidence-based classification approach in each parasport classification discipline to search a gold standard method to assess and divide players into classes [24]
Summary
Trunk function significantly influences the quality of movements in a chair in everyday activities of wheelchair users such as sitting, propelling a wheelchair, transferring, eating, dressing up/undressing, etc. [1,2,3,4,5,6,7]. Reliability of measurement of active trunk movement in wheelchair basketball players movement assessment is one of the main points to evaluate in the classification process in wheelchair sports, because sports activities are depended on trunk movement (flexion, extension, lateral flexion, rotation) in three planes: the sagittal plane (forward), the coronal plane (sideways) and the transverse plane (vertical). According to their trunk abilities, athletes are divided into different sports classes in many parasports like wheelchair rugby [9,10,11,12,13], wheelchair basketball [13,14,15,16,17,18], wheelchair fencing [19], wheelchair track [20], paraskiing [21,22,23] or wheelchair tennis. The examination of validity and reliability of methods used for assessing trunk function is important, needed and supported by the International Paralympic Committee as a part of classification systems development; i.e., conducting research according to evidence-based classification approach in each parasport classification discipline to search a gold standard method to assess and divide players into classes [24]
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