Prevalence of helmet use by users of bicycles, push scooters, inline skates and skateboards in Toronto and the surrounding area in the absence of comprehensive legislation: an observational study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Legislation in the province of Ontario, Canada, mandates users under the age of 18 to wear a helmet when they ride a bicycle, and legislation has been shown to significantly increase rates of bicycle helmet use. Legislation does not exist in Ontario for older bicyclists or for users of other non-motorised modes of transportation, and there are no current data available regarding rates of helmet use in these categories. This study was designed to determine the prevalence of helmet use among users of bicycles, skateboards, push scooters and inline skates in Toronto, Ontario, and the surrounding area. Further analysis was performed to examine factors associated with helmet use. METHODS: We performed a cross-sectional, observational study. Three trained, stationary observers captured 6038 users of bicycles (5783), skateboards (77), inline skates (165) and push scooters (13) in the summer of 2009. Observations were separated into three time periods capturing commuters, midday users and recreational users. A general linear model was used to assess the factors associated with helmet use among bicyclists. RESULTS: Helmets were worn by 48.9% of all users observed and 50.0% of all bicyclists. Among bicyclists, females were more likely to wear helmets than males (prevalence ratio 1.27, 95% CI 1.17 to 1.36), while children were significantly more likely to wear helmets than adults (prevalence ratio 1.17, 95% CI 1.37 to 2.15). Significant behavioural variation was observed among users during the three observation periods (p<0.001), with commuters being the most likely to wear a helmet. CONCLUSION: In the absence of comprehensive legislation encompassing all ages of users, only half of users of non-motorised, wheeled transportation devices are choosing to wear a helmet to protect against traumatic brain injury. Implementation of evidence-based strategies to increase helmet use, such as the introduction of legislation encompassing all ages and all equipment, is required.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it