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Record W2793868721 · doi:10.1186/s12889-018-5892-9

The relationship between sedentary behaviour and physical literacy in Canadian children: a cross-sectional analysis from the RBC-CAPL Learn to Play study

2018· article· en· W2793868721 on OpenAlexafffundabout
Travis J. Saunders, Dany J. MacDonald, Jennifer L. Copeland, Patricia E. Longmuir, Joel D. Barnes, Kevin Belanger, Brenda Bruner, Melanie Gregg, Nathan Hall, Angela M. Kolen, Barbi Law, Luc J. Martin, Dwayne P. Sheehan, Michelle Stone, Sarah J. Woodruff, Mark S. Tremblay

Bibliographic record

VenueBMC Public Health · 2018
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of WindsorMount Royal UniversityQueen's UniversityDalhousie UniversityUniversity of WinnipegChildren's Hospital of Eastern OntarioNipissing UniversitySt. Francis Xavier UniversityUniversity of LethbridgeUniversity of Prince Edward Island
FundersMitacsRoyal Bank of CanadaPublic Health AgencyPublic Health Agency of Canada
KeywordsSittingBiostatisticsScreen timeHealth literacySedentary behaviorMedicineCompetence (human resources)Sedentary lifestyleLiteracyConfidence intervalDevelopmental psychologyPhysical activityPsychologyPhysical therapyPublic healthSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Physical literacy is the foundation of a physically active lifestyle. Sedentary behaviour displays deleterious associations with important health indicators in children. However, the association between sedentary behaviour and physical literacy is unknown. The purpose of this study was to identify the aspects of physical literacy that are associated with key modes of sedentary behaviour among Canadian children participating in the RBC-CAPL Learn to Play study. METHODS: A total of 8,307 children aged 8.0-12.9 years were included in the present analysis. Physical literacy was assessed using the Canadian Assessment of Physical Literacy, which measures four domains (Physical Competence, Daily Behaviour, Motivation and Confidence, Knowledge and Understanding). Screen-based sedentary behaviours (TV viewing, computer and video game use), non-screen sedentary behaviours (reading, doing homework, sitting and talking to friends, drawing, etc.) and total sedentary behaviour were assessed via self-report questionnaire. Linear regression models were used to determine significant (p<0.05) correlates of each mode of sedentary behaviour. RESULTS: In comparison to girls, boys reported more screen time (2.7±2.0 vs 2.2±1.8 hours/day, Cohen's d=0.29), and total sedentary behaviour (4.3±2.6 vs 3.9±2.4 hours/day, Cohen's d=0.19), but lower non-screen-based sedentary behaviour (1.6±1.3 vs 1.7±1.3 hours/day, Cohen's d=0.08) (all p< 0.05). Physical Competence (standardized β's: -0.100 to -0.036, all p<0.05) and Motivation and Confidence (standardized β's: -0.274 to -0.083, all p<0.05) were negatively associated with all modes of sedentary behaviour in fully adjusted models. Knowledge and Understanding was negatively associated with screen-based modes of sedentary behaviour (standardized β's: -0.039 to -0.032, all p<0.05), and positively associated with non-screen sedentary behaviour (standardized β: 0.098, p<0.05). Progressive Aerobic Cardiovascular Endurance Run score and log-transformed plank score were negatively associated with all screen-based modes of sedentary behaviour, while the Canadian Agility and Movement Skill Assessment score was negatively associated with all modes of sedentary behaviour other than TV viewing (all p<0.05). CONCLUSIONS: These results highlight differences in the ways that screen and non-screen sedentary behaviours relate to physical literacy. Public health interventions should continue to target screen-based sedentary behaviours, given their potentially harmful associations with important aspects of physical literacy.

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)0.000
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 score0.114
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.057
GPT teacher head0.383
Teacher spread0.326 · 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

Citations33
Published2018
Admission routes3
Has abstractyes

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