The perspectives of young people on barriers to and facilitators of bicycle helmet and booster seat use
Bibliographic record
Abstract
BACKGROUND: Mandatory bicycle helmet and booster seat laws for children are now common across Canada and the United States. Previous research has found that despite legislation, child compliance is often low. Our objectives were to identify and compare children's perspectives on barriers to and facilitators of their use of bicycle helmets and booster seats. METHODS: Eleven focus groups were conducted with a total of 76 children; five groups of children between the ages of 4 and 8 years discussed booster seats and bicycle helmets, and six groups of children between the ages of 9 and 13 years discussed bicycle helmets. Efforts were made to include diverse participants from a variety of ethno-cultural and socioeconomic backgrounds. RESULTS: Poor fit and physical discomfort were most often described as barriers to bicycle helmet use. Helmet appearance was a barrier for some children but acted as a facilitator for others. Booster seat facilitators included convenient features such as drink cup holders and being able to sit higher up in order to have a better view, while barriers included fear of being teased, and wanting to feel and be seen as more mature by wearing a seatbelt only. CONCLUSIONS: The main barriers to usage of bicycle helmets and booster seats identified by young people were modifiable and fit within a theory of planned behaviour framework that includes subjective norms, child attitudes towards safety equipment and perceived behavioural control of its usage. Recommendations were made regarding how these elements can be utilized in future injury prevention campaigns.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".