Awareness, knowledge, and attitude towards basic life support among healthcare professional students in Bangladesh
Bibliographic record
Abstract
A comprehensive understanding of emergency care is an essential skill for all medical students to effectively manage emergency situations. The aim of this study was to evaluate healthcare professional students' understanding of basic life support (BLS) and to identify the factors that influence this knowledge. A Multi-center cross-sectional study was conducted across eight educational institutions in the Dhaka, Jashore, and Sylhet divisions of Bangladesh from January to June 2024, which included final-year medicine, physiotherapy, and nursing students. A total of 486 participants were selected by the convenience sampling method. A bi-variable and multi-variable logistic regression analysis was carried out and the p-value was set at <0.05. In this study, 73.3% of participants had inadequate knowledge in basic component (BC) and 82.5% of participant had inadequate knowledge in individual component (IC) of BLS. Medicine students demonstrated a threefold increased understanding of BLS in its BC (AOR 2.80; 95% CI 1.70-4.61, p = 0.001). Participants who completed the BLS course demonstrated a twofold increase in knowledge of BLS (AOR 2.14; 95% CI 0.82-5.60, p = 0.123) regarding the BC. In contrast, female students demonstrated significantly lower knowledge of the IC of basic life support (AOR 0.56; 95% CI 0.33-0.93, p = 0.025). Medicine students (AOR 2.36; 95% CI 1.25-4.46, p = 0.009) and nursing students (AOR 2.26; 95% CI 1.18-4.32, p = 0.014) exhibited a significantly better understanding of the IC of BLS. Participants who had already taken the BLS course knew four times as much about each part of BLS (AOR 3.98; 95% CI 1.54-10.27, p = 0.004). This research indicates that healthcare professional students in Bangladesh possess insufficient knowledge of BLS. It is crucial for national health policymakers to priorities this finding and implement training programs for students, as well as professionals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".