Evaluation of primary caregivers' perceptions on home trampoline use
Bibliographic record
Abstract
Trampolines are widely used by children, but trampoline injuries can be severe and may require hospital care or even surgery. This pilot study examined the effectiveness of an educational intervention on caregivers' perceptions of trampoline use and safety for their children. Primary caregivers were recruited from the orthopedic clinic at the Children's Hospital at our institution in 2015. Caregivers were asked to complete a survey at two time points, initially in clinic and one week post educational intervention. The educational intervention was a pamphlet outlining trampoline safety data. Data analysis occurred in 2016. From the 100 primary caregivers recruited, 39 caregivers owned a trampoline, and 10 had presented to the emergency department with their child for an injury related to trampoline use. After educational intervention, caregivers had higher rating of perceived danger associated with trampolines (6/10 vs. 8/10, p < 0.001). Additionally, a greater number of caregivers were more knowledgeable on the safe age of trampoline use (56% vs. 91%, p < 0.001) and safe number of jumpers (45% vs. 86%, p < 0.001). Finally, there was a 29% increase in the proportion of caregivers who at least agreed that trampolines are dangerous (pre: 44% vs. post: 73%, p < 0.001), however 50% of caregivers would still allow their child to use a trampoline. Overall, the results of this study show that a simple educational intervention can help to increase knowledge around safe trampoline practices and increase awareness of injury. Further, this study can act as initial evidence for future studies to implement this type of intervention long-term.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".