Personal and trip characteristics associated with safety equipment use by injured adult bicyclists: a cross-sectional study
Bibliographic record
Abstract
Background: The aim of this study was to estimate use of helmets, lights, and visible clothing among cyclists and to examine trip and personal characteristics associated with their use. Methods Using data from a study of transportation infrastructure and injuries to 690 adult cyclists in Toronto and Vancouver, Canada, we examined the proportion who used bike lights, conspicuous clothing on the torso, and helmets on their injury trip. Multiple logistic regression was used to examine associations between personal and trip characteristics and each type of safety equipment. Results Bike lights were the least frequently used (20% of all trips) although they were used on 77% of trips at night. Conspicuous clothing (white, yellow, orange, red) was worn on 33% of trips. Helmets were used on 69% of trips, 76% in Vancouver where adult helmet use is required by law and 59% in Toronto where it is not. Factors positively associated with bike light use included night, dawn and dusk trips, poor weather conditions, weekday trips, male sex, and helmet use. Factors positively associated with conspicuous clothing use included good weather conditions, older age, and more frequent cycling. Factors positively associated with helmet use included bike light use, longer trip distances, hybrid bike type, not using alcohol in the 6 hours prior to the trip, female sex, older age, higher income, and higher education. Conclusions In two of Canada’s largest cities, helmets were the most widely used safety equipment. Measures to increase use of visibility aids on both daytime and night-time cycling trips may help prevent crashes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".