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Record W2584436518 · doi:10.1093/her/cyw053

Factors influencing implementation of a preschool-based physical activity intervention

2016· article· en· W2584436518 on OpenAlex
Erica Y. Lau, Ruth P. Saunders, Michael W. Beets, Bo Cai, Russell R. Pate

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Education Research · 2016
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of General Medical SciencesNational Institutes of HealthUniversity of South Carolina
KeywordsIntervention (counseling)ChecklistPsychologyPreschool educationPhysical activityComponent (thermodynamics)Applied psychologyDevelopmental psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Examining factors that influence implementation of key program components that underlie an intervention’s success provides important information to inform the development of effective dissemination strategies. We examined direct and indirect effects of preschool capacity, quality of prevention support system and teacher characteristics on implementation levels of a component, called Move Outside (i.e., preschool classroom teachers to provide at least 40 min of outdoor recess per day), that was fundamental to the success of a preschool-based physical activity intervention. Level of implementation, defined as the percent of daily goal met for the Move Outside component, was assessed via direct observation. Items assessing preschool capacity, quality of prevention support system and teacher characteristics were selected from surveys and an environmental checklist completed by preschool directors and teachers. Preschool classroom was used as the unit of analysis (Year 1: n = 19; Year 2: n = 17). Results from Bayesian path analyses showed that the three factors were not significantly associated with level of implementation in Year 1, but preschool capacity was directly associated with level of implementation in Year 2 (β= 0.528, 95% CI: 0.134, 0.827). The current findings suggest that factors that influence level of implementation appear to differ as an intervention evolved over time.

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.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.230
GPT teacher head0.611
Teacher spread0.381 · 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