The Motor skills At Playtime intervention improves children's locomotor skills: A feasibility study
Bibliographic record
Abstract
BACKGROUND: Interventions are needed to teach fundamental motor skills (FMS) to preschoolers. There is a need to design more practical and effective interventions that can be successfully implemented by non-motor experts and fit within the existing gross motor opportunities such as outdoor free play at the preschool. The purpose of this study was to evaluate the feasibility and efficacy of a non-motor expert FMS intervention that was implemented during outdoor free play, Motor skills At Playtime (MAP). METHODS: = 4.7 ± 0.46 years; 41% boys) and were divided into a MAP (n = 30) or control (outdoor free play; n = 16) group. Children completed either a 1,350-min MAP intervention or control condition (outdoor free play) from January to April of 2018. FMS were assessed before and after each programme using both the Test of Gross Motor Development-3rd Edition and skill outcome measures (running speed, hopping speed, jump distance, throwing speed, kicking speed and catching percentage). Intervention implementation feasibility was measured through daily fidelity checks. Fidelity was evaluated as the percentage of intervention sessions that included all explicit intervention criteria. FMS data were analysed using linear mixed modelling. Models were fit with fixed effects of time and treatment, covariates of sex and height, and a random intercept for each individual. RESULTS: The non-motor expert was feasibly able to implement MAP with high fidelity (>93%). There was a significant treatment effect for MAP on process and product locomotor FMS (P < 0.05) and a trend for a treatment effect for MAP on total process FMS (P = 0.07). CONCLUSION: Results support that MAP was successfully implemented by a non-motor expert and led to improvements in children's FMS, especially locomotor FMS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".