Changes in bicycling frequency in children and adults after bicycle skills training: A scoping review
Bibliographic record
Abstract
Encouraging more trips by bicycle is often an objective of bicycle skills training. Bicycle skills training programs have been implemented in several countries, cities, and schools, but few evaluations measure changes in bicycling. We conducted a scoping review to identify and describe evidence of changes in bicycling frequency associated with bicycle skills training. We also describe and compare the theoretical basis, context, and training content of bicycle skills trainings that might be associated with changes in bicycling. We searched six electronic databases, grey literature websites, Google Scholar, and citations in relevant articles for pre- and post-test studies of bicycle skill training interventions which measured bicycling frequency in children or adults. We assessed the theory, context, and content of the bicycle skills training interventions using pre-defined concepts and a behaviour change technique taxonomy. We found 12 studies. Six studies assessed programs for adult populations, of which five reported increases in overall bicycling and three reported increases in bicycling to work. Six studies assessed programs for children, of which five reported increases in overall bicycling and three reported increases in bicycling to school. Information about the statistical significance of these results was sometimes missing. Studies described intervention content adequately, but poorly reported details about intervention theory and context. No associations were found between intervention content and changes in bicycling frequency. Bicycle skills training increases participants’ bicycling, but evidence is heterogeneous among a small number of studies. Sparse reporting limited our ability to detect associations between changes in bicycling frequency and the training theory, context, or content. Future studies should strive to report details on theory, context, and content to help assess effectiveness and generalizability.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".