Social-Ecological Correlates of Children’s Independent Mobility: A Systematic Review
Bibliographic record
Abstract
Children’s independent mobility (IM) is associated with a range of benefits and understanding the factors that influence IM can support creation of effective interventions. The review (Prospero CRD42016042174) systematically summarized the available literature for social-ecological correlates of children’s IM in school-aged children and youth (aged 5–17 years). In this case, 53 studies were included and evaluated six individual, 15 interpersonal, 12 social environment, and 19 built environment- level variables. Most studies originated from Australia (n = 15) and Canada (n = 8) with most published in 2011 or later (n = 48). Variables that were consistently (positively and/or negatively) associated with children’s IM were age, ethnicity/race, child’s perceived competence, ownership of a house/access to house keys, having siblings, parents’ attitude toward IM and perception of child’s confidence, children’s interest in environment and activities, parents’ concern around traffic, housing/residential density, length of residency in one’s home, distance to destinations, and proximity to green space. Given the inter-related social-ecological correlates identified, intervention to promote children’s IM will likely need a multi-level and multi-sectoral approach. However, focus areas of building children’s skills and confidence, helping parents gain confidence in their children’s abilities, assuaging parental traffic concerns, and building environments with shorter distances to destinations of interest for children should be prioritized.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".