Pedestrian navigation and public transit training interventions for youth with disabilities: a systematic review
Bibliographic record
Abstract
Purpose: Being able to travel independently, whether as a pedestrian or by taking public transportation, is a critical element to maintaining quality of life and participation in the community. The objective of this systematic review is to understand the best practices and effective components of pedestrian and public transit training interventions for youth with disabilities.Method: Systematic searches of seven international databases identified 29 studies meeting our inclusion criteria. We analyzed these studies based on participant characteristics, methods, results, and quality of evidence.Results: Among the 29 studies, 857 participants (aged 5–39, mean 18.3 years) were represented across 10 countries. Although the intervention outcomes varied across the studies, 24 of them reported an improvement in at least one of the following: pedestrian and general navigation skills, pedestrian safety, landmark recognition, route knowledge, and public transportation skills.Conclusions: Our findings highlight that pedestrian and public transit interventions have the potential to improve the participation and quality of life of children and youth with disabilities. More rigorous, theoretically informed interventions, using standardized measures are needed to enhance pedestrian and transit training skills among youth with disabilities.Implications for rehabilitationTravel training interventions have the potential to effectively support youth with disabilities in learning pedestrian and public transportation navigation skills.Clinicians and educators should encourage youth with disabilities to participate in travel training programs enhance their independence skills and participation in the community.Clinicians, educators, and program managers can help to build relevant content for travel training programs and connect youth to programs.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".