Effect of Rehabilitation Exercise in CAI for Elite Athletes: GEE

• Published in: Research quarterly for exercise and sport Vol. 87; no. S2; p. A37
• Main Authors: Kim, Sae-Hyung, Kim, Tae-Gyu
• Format: Journal Article
• Language: English
• Published: Washington Taylor & Francis Ltd 01.06.2016
• Subjects: Ankle; Badminton; Data Analysis; Predictor Variables; Rehabilitation; Variables
• ISSN: 0270-1367; 2168-3824

The purpose of this study was to analyze the effect of rehabilitation exercise in chronic ankle instability (CAI) for elite athletes using the generalized estimating Equation (GEE) model. The GEE model is an extension of the generalized linear model to longitudinal (repeated-measures) data analysis. Forty elite athletes who were diagnosed with CAI with chronic pain underwent rehabilitation exercise for 6 weeks and functional evaluation by the Cumberland Ankle Instability Tool (CAIT) scale score. Particularly, time (4 measurement times: beginning, 2 weeks, 4 weeks, 6 weeks) was the independent variable (IV) and the CAIT score ($ 0 and # 30.0) was the dependent variable (DV). Six confounding variables (events [Judo, fencing, hockey, handball, gymnastics, wrestling, badminton], gender [male, female], diagnosis [right ankle, left ankle], age, height, and weight) were controlled to consider spurious effects. The generalized log-logistic utilizing statistical software (Statistical Package for the Social Sciences Version 22.0) was applied to determine significant variables. Alpha level was set at .05. The time variable (IV) showed significant value (B ¼ 3.223, p , .001). More rehabilitation exercise provided more ankle stability to elite athletes. Among confounding variables, events (B ¼ 3.531, p , .001) and weight (B ¼ -0.072, p ¼ .008) showed significant value. Overall, rehabilitation exercise had a higher significant effect for badminton athletes compared with the other variables, and elite athletes with greater weight had a lower rehabilitation exercise effect than lowweight athletes. The other variables (gender, diagnosis, age, height) did not significantly affect the DV. This study statistically showed the effect of rehabilitation exercise for elite athletes who have CAI. Results provided support for using the rehabilitation exercise constantly to cure the CAI, and the GEE is a robust model to estimate repeated-measures data. Based on this study, another sample should be used to increase external validity.