The Children in Action Pilot Study
Bibliographic record
Abstract
Interventions that can successfully alter the trajectory toward obesity among high-risk children are critical if we are to effectively address this public health crisis. The goal of this pilot study was to implement and evaluate an innovative physical activity program with Hispanic-American (HA) preschool children attending Head Start. The Children in Action (CIA) program was a five month physical activity intervention. This intervention was a pilot study with 3- to 5-year-olds enrolled in four HA Head Start centers. After baseline assessment, centers were matched by enrollment and randomly assigned to either the intervention or the control condition. A total of 295 preschool children were randomly selected across the four centers. The primary endpoints of this study were favorable changes in physical activity levels and gross motor skills. Using mixed effect time-series regression models, changes in weight was a secondary endpoint. We did not observe a statistical difference between intervention and control groups in physical activity levels during the awake time, gross motor skills, or weight status. Process evaluation data showed that there was adherence to protocols and the intervention was delivered 92% of the time, four times per week, during the five month intervention. We demonstrated that it is feasible to conduct the SPARK-Early Childhood (EC) curriculum among preschool children attending Head Start centers but that an increased dose and/or longer intervention duration will be required to impact gross motor skills, physical activity levels and weight status during this critical early childhood development stage.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".