2.5. Statistical Analysis

All the data underwent normality testing utilising the Kolmogorov–Smirnov test. The data are deemed to follow a normal distribution when p > 0.05. Descriptive statistical analysis presented results as mean ± SD and a 95% confidence interval. To compare demographic variables between male and female participants, an independent t-test was employed. Additionally, paired t-tests were executed to evaluate potential systematic differences in gait parameters.

For each intrasession test, the intraclass correlation coefficient (ICC) was evaluated using the classification proposed by Landis and Koch. ICC values ranging between 0.20 and 0.40 were deemed to indicate reasonable reliability. Scores falling between 0.40 and 0.60 denoted moderate reliability, while those in the range of 0.60 to 0.80 represented considerable reliability. The highest category encompassed scores between 0.80 and 1.00, characterised as nearly perfect. Some authors suggest that an ICC value of at least 0.75 is necessary to establish reliability [28]. According to the recommendations of Portney and Watkins, clinical measurements with reliability coefficients surpassing 0.90 enhance the likelihood of the measurement being valid [29].

Coefficients of variation (CV) were computed to compare parameters directly in absolute terms. The CV was utilised to describe the connection between the mean magnitude and each studied variable’s variability.

The standard error of measurement (SEM) was used for each variable studied, and, for its best interpretation, it was expressed as a percentage of the mean (SEM%), (138) as follows: SEM is derived from the ICC and DS: SEM = DS × sqrt (1 − ICC), and SEM % = SEM/mean × 100%.

The minimum detectable change (MDC) was also determined. MDC refers to the extent of variation in the value of each scale below which a change can be interpreted as originating from the inherent variability of the assessment method itself, rather than an actual alteration in the patient’s clinical condition. The MDC was computed using a standardised mean (95% MDC), (139), following this formula: MDC is derived from SEM, where MDC = 1.96 × SEM × sqrt (MDC%). Statistical significance was established for p-values < 0.05. Finally, normality values were defined for the sample under study, encompassing all the variables obtained. These values were derived from VN = Mean ± 1.96 × SD.

All statistical analyses were conducted using SPSS 17.0 (SPSS Inc., Chicago, IL, USA). The measurement data collected before and after the implementation of the Morton’s extension were processed, considering both static and dynamic aspects within a repeated-measures design. Statistical significance was established at a p value of <0.05, and a confidence interval of 95% was utilised.