Long term effects of a home visit to prevent childhood injury: three year follow up of a randomized trial
Bibliographic record
Abstract
OBJECTIVE: To assess the long term effect of a home safety visit on the rate of home injury. DESIGN: Telephone survey conducted 36 months after participation in a randomized controlled trial of a home safety intervention. A structured interview assessed participant knowledge, beliefs, or practices around injury prevention and the number of injuries requiring medical attention. SETTING: Five pediatric teaching hospitals in four Canadian urban centres. PARTICIPANTS: Children less than 8 years of age presenting to an emergency department with a targeted home injury (fall, scald, burn, poisoning or ingestion, choking, or head injury while riding a bicycle), a non-targeted injury, or a medical illness. RESULTS: We contacted 774 (66%) of the 1172 original participants. A higher proportion of participants in the intervention group (63%) reported that home visits changed their knowledge, beliefs, or practices around the prevention of home injuries compared with those in the non-intervention group (43%; p<0.001). Over the 36 month follow up period the rate of injury visits to the doctor was significantly less for the intervention group (rate ratio = 0.74; 95% CI 0.63 to 0.87), consistent with the original (12 month) study results (rate ratio = 0.69; 95% CI 0.54 to 0.88). However, the effectiveness of the intervention appears to be diminishing with time (rate ratio for the 12-36 month study interval = 0.80; 95% CI 0.64 to 1.00). CONCLUSIONS: A home safety visit was able to demonstrate sustained, but modest, effectiveness of an intervention aimed at improving home safety and reducing injury. This study reinforces the need of home safety programs to focus on passive intervention and a simple well defined message.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".