Xinyao Hu, Xin Sun, Zhongxu Wang, Meibian Zhang, Qing Xu, Mimi Yang, Xinwei Guo, Longlong Ma, Xingda Qu, Ning Jia
WHAT IS KNOWN ABOUT THIS TOPIC?: Carpal tunnel syndrome is a common work-related disorder that is affected by personal, biomechanical, and psychosocial factors. Existing risk assessment methods often lack precision, hindering early intervention. As of August 1, 2025, occupational musculoskeletal disorders were recognized in China, emphasizing the need for effective preventive tools.
WHAT HAS BEEN ADDED BY THIS REPORT?: This study developed machine learning models to identify carpal tunnel syndrome risk using a national dataset (n=88,609). The best model achieved 97.66% (3,130/3,131) accuracy, identifying key factors such as hand pain frequency and lifting load, and enhancing the early identification of high-risk workers.
WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICES?: These findings advocate for the use of data-driven screening tools in occupational health screening to enable early interventions. Employers should prioritize ergonomic improvements and symptom-reporting systems in alignment with China's proactive occupational disease policies.