Effect of a sports-medicine–guided football program on physical fitness in adolescents: A controlled school-based trial
Integrating artificial intelligence (AI) with sports medicine principles into school-based physical education may enhance physical fitness and reduce injury risk among adolescents. This study aimed to evaluate whether a 10-week sports-medicine-guided football curriculum augmented with explainable machine-learning feedback produces greater improvements in physical fitness and injury-prevention outcomes than a standard physical-education curriculum. A total of 195 healthy junior high school students (mean age 14.1 ± 0.7 years) participated in a controlled school-based intervention and were allocated to either an AI-supported sports-medicine curriculum (intervention) or a standard curriculum (control). Physical fitness outcomes, including lung capacity, estimated maximal oxygen uptake (VO2max), sprint performance, standing long jump, and middle-distance running performance (800 m girls/1000 m boys), were assessed before and after the 10-week program. Outcomes were analyzed using 2-way mixed analysis of variance to test Group × Time interactions. Injury risk prediction was supported by an explainable machine-learning ensemble model (CatBoost + Gradient Boosting) interpreted using SHAPley Additive explanations. Significant Group × Time interactions were observed for lung capacity (P < .01) and VO2max (P < .01), indicating greater improvements in the intervention group compared with controls. The intervention group also demonstrated superior improvements in sprint performance, middle-distance running, and lower-limb power (P < .05), while no significant between-group differences were observed for upper-body strength (P > .05). A school-based football curriculum integrating sports-medicine principles with explainable AI-driven feedback leads to significantly greater improvements in key physical-fitness outcomes than a standard physical-education curriculum. This approach directly supports individualized training adaptation and injury-risk awareness, offering a scalable model for enhancing adolescent health and safety in school physical education.
Authors
- Liuxiang Wei
- Lin Wang (ORCID: https://orcid.org/0000-0003-1026-0060)
- Tianlun Zheng
- Yuelong Ye
- Kaiyue Tang (ORCID: https://orcid.org/0009-0005-5238-2906)
- Ke Shi
- Jing Bin
Institutions
- Guilin Medical University (CN)
- Guilin University of Aerospace Technology (CN)
- Guilin University of Technology (CN)
- Guangzhou Vocational College of Science and Technology (CN)
- Russian State University for Physical Education Sport Youth and Tourism (RU)
- Guangdong Baiyun University (CN)
- Guilin University of Electronic Technology (CN)
- Southeast University (CN)
Publication Details
- Journal
- Medicine
- Published
- 2026-05-22
- DOI
- https://doi.org/10.1097/md.0000000000048649
- Primary Topic
- Cardiovascular Effects of Exercise
- Type
- article
- Field-Weighted Citation Impact
- 0.00