Background The decline in health-related physical fitness resulting from physical inactivity remains a critical global public health concern. Technology-supported fitness self-testing has the potential not only to improve students’ testing experiences but also to enhance their health-related fitness. However, the effectiveness of such approaches has not yet been systematically examined, and their validity within university populations remains largely unestablished. Method A quasi-experimental research design with a control group ( n = 45) and an experimental group ( n = 44), incorporating pre- and post-tests, was employed in this study. The experimental group completed monthly self-testing sessions accompanied by GAI-generated instant feedback over a 16-week period, whereas the control group participated in general physical education classes that included multiple physical activities. Health-related fitness (HRF) was assessed using BMI, the one-mile run, pull-ups, and sit and reach tests. VO₂max was included as a covariate to control for baseline differences in HRF between the two groups. Repeated-measures multivariate analysis of covariance (RM-MANCOVA) was conducted to examine the effects of the intervention on HRF outcomes. Results After controlling for baseline VO 2 max, RM-MANCOVA indicated significant time × group interaction for sit and reach ( p < 0.001) and one-mile run ( p < 0.05), with the intervention group demonstrating significant improvement in both tests. However, no significant differences were observed between groups for body mass index (BMI) and the pull-ups test. Conclusions These findings suggested that HRF self-testing with instant GAI feedback was an effective intervention for improving certain HRF components, particularly flexibility and aerobic fitness. Further research is necessary to explore the long-term effects of self-testing and its application across diverse populations.
Wang et al. (2026) studied this question.