Managing head injury risks in competitive skateboarding: what do we know?
Bibliographic record
Abstract
OBJECTIVES: The broad objective of this paper is to inform policy, practice and research regarding the management of head injury risks in competitive skateboarding. The main motivation for the current study was the question of mandating helmet use in competitive skateboarding. The specific aims are to present current knowledge on (A) head injury risks in skateboarding, (B) preliminary biomechanical data on falls and head injury risks in a selection of competitive skateboarding events similar to those planned for the Summer Olympics, (C) standards for skateboard-styled helmets and (D) impact performance of helmets commonly used in skateboarding. METHODS: A narrative review of the published literature on head injuries in skateboarding was conducted. Videos of skateboarding competitions from Vans Park Professional League, Street League Skateboarding and Dew Tour were reviewed to describe crashes and falls. Standards databases including the International Organization for Standardization (ISO), British Standards Institution (BSI), Snell, United States Consumer Product Safety Commission (CPSC) and American Society for Testing and Materials (ASTM) were searched for skateboarding-styled helmet standards. A sample of helmets considered suitable for skateboarding was tested in standard impact tests. RESULTS: The majority of previous literature focused on the paediatric population in a recreational setting with little data from competitive skateboarding. Head injuries comprised up to 75% of all injuries and helmet use was less than 35%. Video analysis identified high rates of falls and crashes during competitive skateboarding, but also a capacity for the athletes to control falls and limit head impacts. Less than 5% of competitive skateboarders wore helmets. In addition to dedicated national skateboard helmet standards, there are several national standards for skateboard-styled helmets. All helmets, with the exception of one uncertified helmet, had similar impact attenuation performance; that is, at 0.8 m drop height, 114-148 g; at 1.5 m, 173-220 g; and at 2.0 m, 219-259 g. Impact performance in the second impact was degraded in all helmets tested. CONCLUSION: Helmets styled for skateboarding are available 'off the shelf' that will offer protection to the head against skull fractures and intracranial injuries in competitive skateboarding. There is an urgent need to commence a programme of research and development to understanding and control head injury risks.
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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 | 0.008 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".