WHAT ARE THE RISK FACTORS FOR INJURY TO SKIERS AND SNOWBOARDERS IN TERRAIN PARKS AND WHICH STRATEGIES ARE EFFECTIVE IN REDUCING THE RISK OF INJURY? A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Background The prevalence of terrain parks (TPs) in ski areas has grown over the past two decades. TPs are specific areas of the slopes where terrain is modified to accommodate acrobatic maneuvers. There is evidence that TP injuries are more severe than injuries sustained on regular slopes. However, injury prevention strategies in TPs still need to be explored. Objective To identify the risk factors for skiing and snowboarding injuries in TPs and assess the effectiveness of injury prevention strategies. Participants/population Recreational skiing or snowboarding injuries in a TP. Methods Searches in electronic literature databases and hand-searches in Skiing Trauma volumes and bibliographies were performed. A search strategy involving a combination of Subject Headings and keywords and related synonyms using OR, with the Boolean operator AND was performed. Reviewers independently performed an initial screen of all titles and published abstracts for inclusion criteria to determine full text required. Criteria were (1) original data; (2) injury sustained in terrain parks/half-pipes; (3) recreational ski or snowboard injury; (4) study design with comparison group. Authors reviewed included papers and extracted data into structured tables. Results The search strategy identified 62 relevant studies. Only 11 studies met inclusion criteria including one intervention study. Results suggest that removing man-made jumps reduces the risk of severe injury. According to preliminary results, type of slope, age, gender, and skill level are common risk factors. Critical appraisal of articles is in process. An overview suggests that risk factors studies in this area (n=10) are heterogeneous. With primarily cross-sectional and case-control study designs, the risk of associated bias is significant. Conclusions One intervention study suggests that removing man-made jumps from TPs reduces the risk of severe injuries. Further research is needed to better understand injury prevention strategies that are effective in reducing the risk of injury in TPs.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".