Community Awareness and Engagement in Bleeding Control: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Road traffic accidents (RTA) account for 4.7% of all deaths in the Kingdom of Saudi Arabia (KSA), with rates ranging from 17.4 to 24 per 100,000 people over the past decade. This study aims to enhance community engagement and understanding of bleeding control methods to empower effective responses to bleeding in accident scenarios. Method: This observational cross-sectional study evaluated the knowledge and willingness of the community to engage in bleeding control in the setting of medical emergencies. The study population was comprised of adults in Saudi Arabia who were over the age of 17 at the time of the research. Results: A total of 392 participants took part in the research. Of these, 66.3% (n = 260) were willing to assist a stranger bleeding as a result of a motor vehicle accident. There was no significant gender difference among those with past experiences of assisting someone after an accident. Only 15.5% (n = 61) had certified training, while the majority (77%, n = 47) held bachelor's degrees. Interest in educational workshops on bleeding control was shown by 55.1% (n = 216), with 32% (n = 126) undecided. Regarding tourniquet use, 20.1% (n = 38) believed this to be safe. Conclusion: This study highlighted the community's awareness of bleeding control and readiness to respond to bleeding situations after accidents. While more than half were likely to act, concerns about aggravating injuries, legal issues, and discomfort with blood were significant barriers, underscoring the need for public education and legal protection. Educational status, and particularly a bachelor's degree, was a stronger predictor of the likelihood to intervene than certified training. Significant knowledge gaps were noted with regard to tourniquet use, with few trusting their safety and many incorrectly applying them directly to the wound.
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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 | 0.030 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".