Basic Life Support Knowledge Among a Nonmedical Population in Jeddah, Saudi Arabia: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Providing basic life support (BLS) at the site of an accident is crucial to increase the survival rates of the injured people. It is especially relevant when health care is far away. OBJECTIVE: The aim of our study is to assess the BLS knowledge level of the Saudi Arabian population and identify influencing factors associated with level of knowledge about BLS. METHODS: Our study is a cross-sectional descriptive study, which was conducted using a self-administered online questionnaire derived from the BLS practice test. The Saudi population was the target population. The questionnaire was divided into two parts: one contained demographic data and the second part contained questions to test the population's perception about how to perform BLS techniques properly. The data were collected between July and August 2017. Statistically significant differences were defined as those with a P value <.05, and a score of five or more was considered a passing score on the second part. We used SPSS version 21 for data analysis. RESULTS: Our study included 301 participants. Our participants' BLS online exam scores ranged from 0 to 10, with a mean of 4.1 (SD 1.7). Only 39.2% (118/301) of the participants passed the test. The percentage of bachelor's degree or higher holders constituted 60.1% (181/301) of the study population. In addition, higher income was significantly associated with higher scores on the test (P=.04). CONCLUSIONS: This study demonstrated that the theoretical knowledge level of BLS among the general population in Jeddah was below average. There is a critical need to increase the public's exposure to BLS education through raising awareness campaigns and government-funded training programs that aim to curb the incidence of out-of-hospital cardiac arrest mortalities in the Saudi community.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".