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Record W4220761653 · doi:10.1186/s12889-022-12883-w

A randomised controlled trial of an implementation strategy delivered at scale to increase outdoor free play opportunities in early childhood education and care (ECEC) services: a study protocol for the get outside get active (GOGA) trial

2022· article· en· W4220761653 on OpenAlexaff
Sze Lin Yoong, Nicole Pearson, Kathryn Reilly, Luke Wolfenden, Jannah Jones, Nicole Nathan, Anthony D. Okely, Patti‐Jean Naylor, Jacklyn Jackson, Luke Giles, Noor Imad, Karen Gillham, John Wiggers, Penny Reeves, Kate Highfield, Melanie Lum, Alice Grady

Bibliographic record

VenueBMC Public Health · 2022
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsUniversity of Victoria
FundersNational Health and Medical Research Council
KeywordsBiostatisticsMedicineRandomized controlled trialBaseline (sea)Early childhoodEarly childhood educationPublic healthNursingPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Increased outdoor play time in young children is associated with many health and developmental benefits. This study aims to evaluate the impact of a multi-strategy implementation strategy delivered at scale, to increase opportunities for outdoor free play in Early Childhood Education and Care (ECEC) services. METHODS: The study will employ a parallel-group randomised controlled trial design. One hundred ECEC services in the Hunter New England region of New South Wales, Australia, will be recruited and randomised to receive either a 6-month implementation strategy or usual care. The trial will seek to increase the implementation of an indoor-outdoor routine (whereby children are allowed to move freely between indoor and outdoor spaces during periods of free play), to increase their opportunity to engage in outdoor free play. Development of the strategy was informed by the Behaviour Change Wheel to address determinants identified in the Theoretical Domains Framework. ECEC services allocated to the control group will receive 'usual' implementation support delivered as part of state-wide obesity prevention programs. The primary trial outcome is the mean minutes/day (calculated across 5 consecutive days) of outdoor free play opportunities provided in ECEC services measured at baseline, 6-months (primary end point) and 18-months post baseline. Analyses will be performed using an intention-to-treat approach with ECEC services as the unit of analysis, using a linear mixed effects regression model to assess between-group differences. A sensitivity analysis will be undertaken, adjusting for service characteristics that appear imbalanced between groups at baseline, and a subgroup analysis examining potential intervention effect among services with the lowest baseline outdoor free play opportunities. DISCUSSION: Identifying effective strategies to support the implementation of indoor-outdoor routines in the ECEC setting at scale is essential to improve child population health. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ( ACTRN12621000987864 ). Prospectively registered 27th July 2021, ANZCTR - Registration.

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)0.020
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0100.005
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0360.005

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 head0.074
GPT teacher head0.403
Teacher spread0.329 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations28
Published2022
Admission routes1
Has abstractyes

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