The Value of Stakeholder-Engaged Research: Using Parent Voices in the Adaptation of the <i>Cool 2 Be Safe</i> Playground Safety Intervention Program
Bibliographic record
Abstract
Playground injuries are a leading cause of injury for children. Those who are 4 to 6 years of age are particularly vulnerable given their transitioning toward increased autonomy and less direct supervision. Most previous interventions have targeted environmental modifications or increased supervision to reduce playground injuries, though there is evidence of one child-focused intervention that targets behavior change. Specifically, for children 7+ years, the Cool 2 Be Safe Program has been shown to effectively reduce fall-risk behaviors on playgrounds. However, there are no behaviorally focused interventions for younger children. Addressing this gap, a stakeholder-engaged qualitative approach was used to identify the best ways to adapt and create the Cool 2 Be Safe Junior Program for children who are 4 to 6 years old. Two phases of interviews were conducted with parents, with feedback from the first phase of interviews used to modify lesson materials prior to the second phase of interviews. Parents provided perspectives about program content, as well as strengths and limitations of the program. Responses were analyzed using conventional content analysis. Parents’ feedback assisted in program modification that ultimately strengthened the intervention, as evidenced by parents’ overall positive ratings of the program. Implications for preventing playground injuries and program development for preschool children are discussed.
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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 | 0.081 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".