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Record W4210815919 · doi:10.3390/ijerph19031604

Social-Ecological Correlates of Children’s Independent Mobility: A Systematic Review

2022· review· en· W4210815919 on OpenAlexaffabout
Negin A. Riazi, Kelly Wunderlich, Lira Yun, Derek C. Paterson, Guy Faulkner

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British ColumbiaBrock University
Fundersnot available
KeywordsPsychological interventionDestinationsEthnic groupPsychologyInterpersonal communicationConfidence intervalPerceptionCompetence (human resources)FriendshipDevelopmental psychologyGeographyMedicineSocial psychologySociologyTourism

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.858
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.158
GPT teacher head0.462
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2022
Admission routes2
Has abstractyes

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