Abstract Su406: Acceptability and Effectiveness of a Novel, Video-Based CPR and AED Education Program in Canadian Schools
Bibliographic record
Abstract
Background: Early cardiopulmonary resuscitation (CPR) and defibrillation are critical for favorable outcomes after sudden cardiac arrest (SCA). Scientific evidence supports CPR and Automated External Defibrillator (AED) training in school-age children. Few studies have used gamified, video-based training to teach students. This national project aimed to assess the acceptability and effectiveness of a brief, video-based educational program (CardiacCrash™), developed by the Heart and Stroke Foundation to teach students hands-only CPR and AED use within a classroom setting. Methods/Results: This study reports preliminary data from two Canadian provinces (Ontario, Alberta). The acceptability and effectiveness of training was measured using a pre/post survey evaluating students’ self-confidence in recognizing SCA, calling for help, and providing bystander CPR, including the use of an AED. CPR performance was measured by using Little Anne QCPR manikins that collected data on CPR effectiveness throughout the training session. Results are stratified by student cohort (elementary—grades 4-8, and secondary—grades 9-12). A total of 1273 students from 6 Ontario and 7 Alberta schools were trained between October 2023 to April 2024. The average age for elementary students (n=729; 47.3% male) was 11.2 ± 1.3 years, and 39.9% had previous CPR training. The average age for secondary students (n=544; 54.4% male) was 15.5 ± 1.1, and 42.6% had previous CPR training. Both groups thought the training was easy (86%), fun (81%), the correct duration (59%) and would recommend it to their friends (85%). All outcome variables improved post-training for both elementary and secondary students, including the self-confidence to recognize and assist in cases of SCA (p=0.008 for both cohorts), (Figure 1). Secondary students were significantly better at providing effective compressions vs. elementary for most CPR measures (Table 2). Conclusion: Preliminary data suggest that CardiacCrash™, a video-based educational program, is acceptable to school-age students and effective at teaching them to perform CPR and use an AED. While both elementary and secondary students achieved acceptable CPR performance, secondary students performed higher quality CPR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".