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Record W2980729850 · doi:10.1177/1059840519881185

Characteristics of Canadian Youth Adhering to Physical Activity and Screen Time Recommendations

2019· article· en· W2980729850 on OpenAlexaffabout
Caroline Fitzpatrick, Robin Burkhalter, Mark Asbridge

Bibliographic record

VenueThe Journal of School Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsDalhousie UniversityImpactUniversity of WaterlooConcordia UniversityUniversité Sainte-Anne
Fundersnot available
KeywordsEthnic groupScreen timeResidenceSocial connectednessMedicineConfidence intervalPhysical activityFeelingHealth promotionYouth Risk Behavior SurveyMarijuana smokingPsychologyGerontologyClinical psychologyDemographyEnvironmental healthPublic healthSuicide preventionPoison controlPhysical therapySubstance useSocial psychologyNursing

Abstract

fetched live from OpenAlex

The purpose of the study was to describe adherence to screen time (ST) and physical activity (PA) recommendations among Canadian youth. The present study was based on a representative sample of Canadian students from Grades 7 through 12 ( N = 47,203). ST and PA as well as demographic (gender, ethnicity, grade, and province of residence) and individual (alcohol, tobacco and cannabis usage, school connectedness) correlates were self-reported by youth. In total, 49.2% (99% confidence interval [CI] = [46.3%, 52.2%]) of participants respected none of the recommendations, while 40.2% (99% CI [37.0%, 43.3%]) and 20.8% (99% CI [19.2%, 22.4%]) respected PA or ST recommendations, respectively. In terms of the correlates of health-related behavior, White ethnicity, alcohol use, and feeling more connected to school were positively correlated with adherence. Attending school in Quebec and smoking cannabis increased risk of poor compliance. The present findings may help the design of school-based health promotion strategies designed to increase PA and reduce ST.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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