Effectiveness of a Burn Prevention Campaign for Older Adults
Bibliographic record
Abstract
Older adults are involved in one fifth of burn injury admissions in the Province of Ontario Canada. Most burn injuries in this population occur at home while cooking, bathing, or smoking. The purpose of this study was to evaluate the effectiveness of an educational campaign to improve burn prevention knowledge in older adults of a major metropolitan city. Changes in participants' burn prevention knowledge were determined using standardized precampaign and postcampaign (4-6 weeks) surveys. Of 209 older adult participants, 126 (60.3%) completed the precampaign and postcampaign surveys. There was a significant increase (P <.05) in burn prevention knowledge postintervention. Age, education level, and living conditions did not influence the change in burn prevention knowledge. This burn prevention campaign for older adults was effective in improving burn prevention knowledge, but it remains unclear as to whether this will ultimately result in a change in burn prevention behavior.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".