Trunk Motion of Male Professional Golfers Using Two Different Golf Clubs
Bibliographic record
Abstract
Low back problems account for the largest proportion of injuries among amateur and professional golfers. However, there is little data on how the trunk or spine moves during a golf swing. Also, it may be that different golf clubs produce different trunk motion characteristics. The purpose of this study was to compare trunk range of motion (ROM) and velocity in three movement planes during the execution of a full golf swing using a driver and a 7-iron. Forty-four members of the Alberta Professional Golf Association volunteered to participate in this study. Trunk ROM and velocities in the sagittal, frontal, and transverse planes were measured using a triaxial electrogoniometer. Results showed that significantly more trunk flexion was required when setting up to hit the ball with the 7-iron compared to the driver,p< 0.05. During the swing, significantly greater maximum flexion and left-side-bend ROM occurred when using the 7-iron,p< 0.05. Maximum right-side-bending velocity during the golf swing was also significantly greater with a 7-iron. These findings suggest that differences in shaft length and ball positioning associated with the different clubs affects swing mechanics and trunk/spinal motion. In particular, the shorter club (7-iron) tended to place more emphasis on lateral trunk motion than did the driver. The results from this study may help clinicians better understand how the golf swing creates stress on the back as well as how club fitting may affect trunk motion characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".