Knowledge of and attitudes towards concussion in cycling: A preliminary study
Bibliographic record
Abstract
The aim of this study wasto investigate the knowledge of and attitudes towards concussion in cycling. An abbreviated Rosenbaum Concussion Knowledge and attitudes Survey (RoCKAS) was distributed online via social media and completed by 1990 respondents involved in cycling. The RoCKAS comprised separate sections to determine a concussion knowledge index (CKI) providing a score between 0-33, and a concussion attitudes index (CAI) with possible scores between 7-20. Mean scores were 25.9 ± 11.0 and 17.7 ± 3.0 for CKI and CAI, respectively. However, there remained several concussion knowledge misconceptions and disparity between reported knowledge and attitudes and actions, with 16% of respondents admitting to riding despite having concussive symptoms and 18.7% stating they would hide a concussion to stay in an event. The results of this survey indicate those involved with cycling reported reasonable knowledge of concussion symptoms and safe/desirable attitudes towards concussion education. However, despite reporting safe attitudes, the actions of those involved in cycling may be of greater concern, as a considerable number of respondents were still willing to take risks by continuing to cycle knowing they had concussive symptoms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".