Repeated Measures Models Applied to Cancer Patients Treated with Exergames.

Objective: The objective of this study was to define an appropriate linear model to analyse data on muscular fatigue in cancer patients over time through repeated measures techniques. Methods: Using the split plot in time system and linear mixed models, three groups of individuals were compared as to the methods used to reduce muscle fatigue. Group Cancer consisted of individuals who had already been treated; group Control consisted of healthy individuals and group Chemo / radio-therapy consisted of individuals diagnosed with cancer undergoing chemo and radiation therapy. Sessions were tested with exergames. A series of muscle strength data for each of the six muscles studied, in the pre-treatment, mid-treatment and final sessions. Result: The structure that best fit the covariance matrix was ARMA (1,1), according to AIC and BIC. There were significant differences and tendencies in the data series, especially for the left tibial muscle, in which the interactions between group and session and between group and time were significant, showing that exergames treatment increased muscle strength in debilitated patients and, with 20 sessions, the groups equalled in muscle strength. Conclusion: The linear mixed model proved to be efficient in modelling plots subdivided in time. Identifying the best structure of the covariance matrix allowed us to better estimate the effects, using tests appropriately to verify differences between factors that were not detected when using the median frequency of strength.