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Record W2512743176 · doi:10.1186/s12889-016-3423-0

Evaluation of Daily Physical Activity (DPA) policy implementation in Ontario: surveys of elementary school administrators and teachers

2016· article· en· W2512743176 on OpenAlexafffundabout
Kenneth R. Allison, Karen Vu‐Nguyen, Bessie Ng, Nour Schoueri‐Mychasiw, John J. M. Dwyer, Heather Manson, Erin Hobin, Steve Manske, Jennifer Robertson

Bibliographic record

VenueBMC Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsImpactUniversity of GuelphUniversity of WaterlooPublic Health Ontario
FundersMinistère de l’Éducation, Gouvernement de l’OntarioOntario Ministry of Health and Long-Term CareGovernment of Ontario
KeywordsBiostatisticsFidelityDescriptive statisticsMedical educationLogistic regressionMedicineChristian ministryPublic healthSample (material)Bivariate analysisPsychologyNursingComputer scienceStatisticsMathematicsPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: School-based structured opportunities for physical activity can provide health-related benefits to children and youth, and contribute to international guidelines recommending 60 min of moderate-to-vigorous physical activity (MVPA) per day. In 2005, the Ministry of Education in Ontario, Canada, released the Daily Physical Activity (DPA) policy requiring school boards to "ensure that all elementary students, including students with special needs, have a minimum of twenty minutes of sustained MVPA each school day during instructional time". This paper reports on the first provincial study evaluating implementation fidelity to the DPA policy in Ontario elementary schools and classrooms. Using an adapted conceptual framework, the study also examined associations between implementation of DPA and a number of predictors in each of these respective settings. METHODS: Separate cross-sectional online surveys were conducted in 2014 with Ontario elementary school administrators and classroom teachers, based on a representative random sample of schools and classrooms. An implementation fidelity score was developed based on six required components of the DPA policy. Other survey items measured potential predictors of implementation at the school and classroom levels. Descriptive analyses included frequency distributions of implementation fidelity and predictor variables. Bivariate analyses examining associations between implementation and predictors included binary logistic regression for school level data and generalized linear mixed models for classroom level data, in order to adjust for school-level clustering effects. RESULTS: Among administrators, 61.4 % reported implementation fidelity to the policy at the school level, while 50.0 % of teachers reported fidelity at the classroom level. Several factors were found to be significantly associated with implementation fidelity in both school and classroom settings including: awareness of policy requirements; scheduling; monitoring; use of resources and supports; perception that the policy is realistic and achievable; and specific barriers to implementation. CONCLUSIONS: Findings from the surveys indicate incomplete policy implementation and a number of factors significantly associated with implementation fidelity. The results indicate a number of important implications for policy, practice and further research, including the need for additional research to monitor implementation and its predictors, and assess the impacts of study recommendations and subsequent outcomes of a reinvigorated DPA moving forward.

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)0.006
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 score0.187
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 head0.092
GPT teacher head0.417
Teacher spread0.324 · 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

Citations74
Published2016
Admission routes3
Has abstractyes

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