## 4 Discussion  
The study results showed that the rGMFM-66 reduced the time required for the assessment by approximately 50% (Table 2, Figure 1A). The study population consisted of children and adolescents with all GMFCS levels (Table 1). The agreement analysis demonstrated an excellent correlation between the GMFM-66 and rGMFM-66 score with an ICC of 0.970 (95%KI 0.942-0.983, Table 2). The ICC was slightly lower (0.970 vs. 0.997) compared to a previously published report (REF). Furthermore, the Bland-Altman statistic in this current study showed a greater spread than in the retrospective analysis by [PERSON] et al. (2022) ((-9.7; 6.5) vs. (-2.7; 2.9)) [13]. These differences are probably due to the fact that the current analysis involved two measurements of gross motor skills on two different days. For the retrospective analysis, the GMFM-66 and the rGMFM-66 were determined for the same measurement of gross motor skills. The current prospective study design therefore accounts, e.g., for diurnal fluctuations in gross motor function which are reflected in the evaluation of the agreement between the two scores  
Interestingly, the rGMFM-66 resulted in a slightly higher average score than the GMFM-66 (52.2 vs. 50.7 points, Table 2), with small but potentially clinically significant changes according to [PERSON] et al. (2006) being \(\geq\)1.5 points for small, \(\geq\)2.5 points for moderate, and \(\geq\)3.5-4.0 points for large changes [21]. This systematic deviation between the two scores was also not seen in the retrospective analysis of agreement. It can probably be explained by a learning effect, as the rGMFM-66 measurement always took place after the GMFM-66 measurement. This means that the children learned the test tasks  
Figure 2: Bland–Altman plot showing the agreement between the GMFM-66 and rGMFM-66 scores. The differences between the two measurements are plotted against their mean. The middle dashed-line represents the mean difference, and the other dashed lines indicate the limits of agreement (mean \(\pm\) 1.96 SD). during the rGMFM-66 measurement and were able to perform them somewhat better. The interval between the two measurements was 1 to max. 2 days, hence an effect induced by the therapy received during the rehabilitation program in which the study participants took part is unlikely. From a clinical perspective, this minor score increase should be interpreted cautiously, and future studies should examine whether this trend persists across different subgroups. The rGMFM-66 seems to be a valid alternative to the GMFM-66, offering a significant reduction in assessment time, and making it more efficient for use in clinical and rehabilitative settings. These findings align with the growing body of literature supporting the implementation of AI-based assessments to enhance efficiency while maintaining validity. Such advancements are particularly valuable in clinical practice, where time constraints often limit the feasibility of comprehensive assessments. Beyond the time savings, the rGMFM-66 offers practical advantages that support its clinical applicability. The reduced number of test items simplifies administration and lowers the burden on clinicians, allowing them to focus more on therapeutic evaluation. The software requires only minimal training for experienced therapists and integrates seamlessly into existing clinical routines. These features may lead to cost savings by enabling more patients to be assessed within the same timeframe. Moreover, the shorter duration of the test may enhance acceptance among children and caregivers, particularly in outpatient or community settings where attention spans and time are limited. These practical advantages support the broader applicability of the rGMFM-66 in everyday practice [22]. At the same time, it is crucial to address the challenge of enabling clinicians to integrate new technologies into clinical practice in a safe, effective, and equitable manner to ultimately improve outcomes for children.