A prospective study of injuries and illnesses among 910 amateur golfers during one season
Bibliographic record
Abstract
Objectives: Our aims were (a) to describe the prevalence and incidence of self-reported injuries and illnesses of amateur golfers over a 5-month period and (b) to investigate potential risk factors for injury. Methods: We recruited 910 amateur golfers (733 males [81%] and 177 females [19%]) from golf clubs in the USA and Switzerland. The median age was 60 (IQR: 47-67) and the median golfing handicap was 12 (IQR: 6-18). Participants' health was monitored weekly for 5 months using the Oslo Sports Trauma Research Centre Questionnaire on Health Problems. Players also completed a baseline questionnaire on personal and golf-specific characteristics and their medical history. Results: We distributed 19 406 questionnaires and received 11 180 responses (57.6%). The prevalence of injuries was 11.3% (95% CI: 9.8 to 12.8) and of illnesses was 2% (95% CI 1.7 to 2.2). The incidence of injuries and illnesses was 3.79 (95% CI 3.54 to 4.06) and 0.94 (95% CI 0.81 to 1.07) per golfer per year, respectively. The injury regions with the highest burden of injury (time-loss days per player per year) were lumbosacral spine (5.93), shoulder (3.47) and knee (2.08). Injury risk was higher with increased age, osteoarthritis and previous injury. Conclusion: The prevalence and incidence of injury and illness in amateur golf were low compared with many other sports. To further reduce the burden of injury, future research attention should be directed towards the lumbosacral spine, knee and shoulder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 0.000 |
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 teacher head, 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".