Comfort with burn injury management among healthcare providers in a rural and remote region: a cross-sectional survey
Bibliographic record
Abstract
Background: Rural and remote communities often rely on primary care providers to complete the initial management and referral of burn injuries. This study aimed to assess frontline providers’ comfort with the initial assessment and management of burn injuries in a rural and remote setting. Methods: A cross-sectional survey was distributed to primary and wound care providers across 10 healthcare facilities in Northwestern Ontario between August and December 2024. Self-reported comfort levels with 15 aspects of burn care were assessed using a five-point Likert scale. Wilcoxon rank-sum tests were used to compare survey responses across practice characteristics. Results: Fifty-nine providers participated, including family physicians (44 %), nurse practitioners (20 %), emergency physicians (10 %), and others. While 90 % saw at least one burn injury per year, only 42 % saw more than five. Most respondents reported comfort with tetanus prophylaxis (72 %) and burn first aid (66 %). However, fewer felt comfortable assessing burn size (31 %) or depth (27 %), initiating fluid resuscitation (27 %), or applying the American Burn Association guidelines for burn center transfer (24 %). Providers managing five or more burns annually reported significantly greater comfort across multiple domains (p < 0.05). No significant differences were found between early- and late-career providers. Conclusion: This study demonstrates that providers working in a rural and remote region reported limited comfort with burn size and depth assessment, initiating fluid resuscitation, and applying burn center referral guidelines – important skills for initial injury management and referral. These findings highlight a need for system-level supports and educational resources for providers in regions remote from specialized burn centers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".