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Record W1778224320 · doi:10.1016/j.pmedr.2015.09.005

Does proximity to physical activity infrastructures predict maintenance of organized and unorganized physical activities in youth?

2015· article· en· W1778224320 on OpenAlexafffundabout
J. Mackenzie, Jennifer Brunet, Jonathan Boudreau, Horia-Daniel Iancu, Mathieu Bélanger

Bibliographic record

VenuePreventive Medicine Reports · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsVitalité Health NetworkDr. Georges-L.-Dumont University Hospital CentreUniversité de MonctonUniversity of OttawaUniversité de Sherbrooke
FundersSocial Sciences and Humanities Research CouncilFaculty of Medicine and Health, University of SydneySocial Sciences and Humanities Research Council of CanadaFondation de la recherche en santé du Nouveau-BrunswickUniversité de Sherbrooke
KeywordsPhysical activityHazardProportional hazards modelBaseline (sea)Hazard ratioAffect (linguistics)PsychologyDemographyGerontologyMedicinePhysical therapyBiologyInternal medicineSociologyConfidence intervalEcologyCommunication

Abstract

fetched live from OpenAlex

Physical activity (PA) infrastructures can provide youth chances to engage in PA. As determinants of organized and unorganized PA (OPA and UPA) may differ, we investigated if proximity to PA infrastructures (proximity) was associated with maintenance of OPA and UPA over 3 years. Youth from New Brunswick, Canada (n = 187; 10-12 years at baseline) reported participation in OPA and UPA every 4 months from 2011 to 2014 as part of the MATCH study. Proximity data were drawn from parent's questionnaires. Proximity scores were divided into tertiles. Kaplan-Meier and Cox proportional hazard models were used to assess associations between proximity and maintenance of OPA and UPA. There were no crude or adjusted differences in average maintenance of participation in OPA [mean number of survey cycle participation (95%CI) was 6.6 (5.7-7.5), 6.3 (5.5-7.1), and 5.8 (5.1-6.6)] or UPA [6.8 (6.2-7.4), 5.9 (5.3-6.5), and 6.6 (5.9-7.3)] across low, moderate, and high tertiles of proximity, respectively. Findings suggest that proximity does not affect maintenance of participation in OPA or UPA during adolescence. Other environmental aspects may have a greater effect. Further research is needed before conclusions can be made.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.308
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations18
Published2015
Admission routes3
Has abstractyes

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