Results from the PROmoting Early Childhood Outside cluster randomized trial evaluating an outdoor play intervention in early childhood education centres
Bibliographic record
Abstract
Participation in outdoor play is beneficial for the health, well-being, and development of children. Early childhood education centers (ECECs) can provide equitable access to outdoor play. The PROmoting Early Childhood Outside (PRO-ECO) study is a pilot randomized trial that evaluates the PRO-ECO intervention on children's outdoor play participation. The PRO-ECO intervention included four components: ECEC outdoor play policy; educator training; ECEC outdoor space modification; and parent engagement. This study included eight ECECs delivering licensed care to children (n = 217) aged 2.5 to 6 years in Greater Vancouver, British Columbia, Canada. Using a wait-list control cluster randomized trial design, ECECs were randomly allocated to either the intervention arm (n = 4) or the wait-list control arm (n = 4). Change in the proportion and diversity of observed outdoor play behaviour during scheduled outdoor time was measured. Outcome data were collected at baseline, 6-month follow-up, and 12-month follow-up. The intervention effect on children's outdoor play participation was examined using logistic regression mixed effect models. Controlling for gender, weather and temperature, there were no changes in children's outdoor play participation following implementation of the PRO-ECO intervention in the between-group analysis. Within-group comparisons also revealed no change in play participation following the PRO-ECO intervention, however, the intervention group showed a positive effect (OR = 1.28, 95% CI = 0.97, 1.70) in play participation 6 months after implementation of the intervention. The findings indicate that further analyses on child- and ECEC-level outcomes collected as part of the PRO-ECO study, including the diversity of children's play, is required to effectively assess the impact of this intervention.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".