MétaCan
Menu
← Back to cohort
Record W4323308296 · doi:10.1249/mss.0000000000003146

Physical Activity Trajectories in Early Childhood: Investigating Personal, Environmental, and Participation Factors

2023· article· en· W4323308296 on OpenAlexafffund
Patrick G. McPhee, Natascja A. Di Cristofaro, Hilary A. T. Caldwell, Nicole A. Proudfoot, Sara King‐Dowling, Maureen J. MacDonald, John Cairney, Steven R. Bray, Brian W. Timmons

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsHealth Sciences CentreMcMaster University
FundersCanadian Institutes of Health Research
KeywordsDemographyPhysical activityEthnic groupMedicineQuality of life (healthcare)Generalized estimating equationPsychologyPhysical therapyMathematicsStatistics

Abstract

fetched live from OpenAlex

INTRODUCTION/PURPOSE: To determine personal, environmental, and participation factors that predict children's physical activity (PA) trajectories from preschool through to school years. METHODS: Two hundred seventy-nine children (4.5 ± 0.9 yr, 52% boys) were included in this study. Physical activity was collected via accelerometry at six different timepoints over 6.3 ± 0.6 yr. Time-stable variables were collected at baseline and included child's sex and ethnicity. Time-dependent variables were collected at six timepoints (age, years) and included household income (CAD), parental total PA, parental influence on PA, and parent-reported child's quality of life, child's sleep, and child's amount of weekend outdoor PA. Group-based trajectory modeling was applied to identify trajectories of moderate-to-vigorous PA (MVPA) and total PA (TPA). Multivariable regression analysis identified personal, environmental, and participation factors associated with trajectory membership. RESULTS: Three trajectories were identified for each of MVPA and TPA. Group 3 in MVPA and TPA expressed the most PA over time, with increased activity from timepoints 1 to 3, and then declining from timepoints 4 to 6. For the group 3 MVPA trajectory, male sex (β estimate, 3.437; P = 0.001) and quality of life (β estimate, 0.513; P < 0.001) were the only significant correlates for group membership. For the group 3 TPA trajectory, male sex (β estimate, 1.970; P = 0.035), greater household income (β estimate, 94.615; P < 0.001), and greater parental total PA (β estimate, 0.574; P = 0.023) increased the probability of belonging to this trajectory group. CONCLUSIONS: These findings suggest a need for interventions and public health campaigns to increase opportunities for PA engagement in girls starting in the early years. Policies and programs to address financial inequities, positive parental modeling, and improving quality of life are also warranted.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.295
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & Exercise→Same topicObesity, Physical Activity, Diet→French-language works237,207→