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Record W4206528389 · doi:10.3934/publichealth.2022015

Impact of an outdoor loose parts intervention on Nova Scotia preschoolers' fundamental movement skills: a multi-methods randomized controlled trial

2021· article· en· W4206528389 on OpenAlexaffabout
Karina Branje, Daniel Stevens, Heather Hobson, Sara Kirk, Michelle Stone

Bibliographic record

VenueAIMS Public Health · 2021
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsMovement (music)Psychological interventionPsychologyRandomized controlled trialIntervention (counseling)Nova scotiaMovement assessmentCognitionEarly childhoodPerceptionDevelopmental psychologyMotor skillMedicineGeography

Abstract

fetched live from OpenAlex

Development of fundamental movement skills in early childhood supports lifelong health. The potential for outdoor play with loose parts to enhance fundamental movement skills has not been investigated. A multi-methods randomized controlled design was used to determine the efficacy of integrating outdoor loose parts play into Nova Scotia childcare centers (19 sites: 11 interventions, 8 control). Movement skills (n = 209, age 3-5 years) were assessed over a 6-month period to investigate changes in fundamental movement skills over time and between groups. Qualitative data was also collected on the educators' perceptions of outdoor loose parts play. Quantitative data (fundamental movement skills) revealed a non-intervention effect, however, educators spoke of outdoor loose parts play providing opportunities to combine/ repeat movements and take risks; supporting physical, cognitive and socio-emotional (holistic) development; and increasing awareness of children's physical development and how to support it. Our findings demonstrate value in outdoor loose parts play for the development of fundamental movement skills in childcare settings.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0030.000

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 head0.047
GPT teacher head0.429
Teacher spread0.383 · 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.

Study designRandomized trial
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

Citations27
Published2021
Admission routes2
Has abstractyes

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