New Training Frontiers in Golf Considerations from a neurosurgical perspective

Eyad Al Kahlout

Abstract

Background: Golf, a sport gaining popularity globally, poses unique risks to musculoskeletal health, particularly among older players. The repetitive nature of the golf swing and inadequate athletic preparation often lead to injuries, especially in the spine, shoulders, and elbows. This study explores the biomechanics of golf and evaluates innovative training methodologies to mitigate injury risks and enhance performance.

Materials and Methodology: The study integrates insights from sports science, neurosurgical assessments, and physical therapy to analyze common injury mechanisms in golf. Data from a comprehensive literature review, including clinical case studies and injury prevalence surveys, were combined with biomechanical evaluations. Modern training approaches such as the Gyrotonic Expansion System, MFT Proprioceptive Tables, and elastic resistance training were examined for their efficacy in improving flexibility, strength, and injury prevention.

Results: Findings highlight that injury risk peaks during the downswing and impact phases of the golf swing due to high muscular loads and sudden force application. Older golfers exhibit higher injury rates, attributed to age-related physiological changes such as reduced spinal flexibility and muscle strength. Implementing structured training programs significantly reduced injury incidences and enhanced golfers' biomechanical efficiency. Techniques like Gyrotonic and Body Blade improved spinal mobility and neuromuscular control, while MFT tables optimized balance and coordination.

Conclusion: Proper athletic preparation tailored to golfers' needs, incorporating multidisciplinary evaluations and advanced training systems, can mitigate injury risks and prolong active participation in the sport. Integrating these strategies, particularly for older players, enhances both safety and performance, underscoring the need for wider adoption in golf training protocols.