Bystanders are less willing to resuscitate out-of-hospital cardiac arrest victims during the COVID-19 pandemic
Bibliographic record
Abstract
The COVID-19 pandemic may influence the willingness of bystanders to engage in resuscitation for out-of-hospital cardiac arrest. We sought to determine if and how the pandemic has changed willingness to intervene, and the impact of personal protective equipment (PPE). We distributed a 12-item survey to the general public through social media channels from June 4 to 23, 2020. We used 100-point scales to inquire about participants’ willingness to perform interventions on “strangers or unfamiliar persons” and “family members or familiar persons”, and compared mean willingness during time periods prior to and during the COVID-19 pandemic using paired t-tests. Survey participants (n = 1360) were from 26 countries; the median age was 38 years (IQR 24–50) and 45% were female. Compared to prior to the pandemic, there were significant decreases in willingness to check for breathing or a pulse (mean difference −10.7% [95%CI −11.8, −9.6] for stranger/unfamiliar persons, −1.2% [95%CI −1.6, −0.8] for family/familiar persons), perform chest compressions (−14.3% [95%CI −15.6, −13.0], −1.6% [95%CI −2.1, −1.1]), provide rescue breaths (−19.5% [95%CI −20.9, −18.1], −5.5% [95%CI −6.4, −4.6]), and apply an automated external defibrillator (−4.8% [95%CI −5.7, −4.0], −0.9% [95%CI −1.3, −0.5]) during the COVID-19 pandemic. Willingness to intervene increased significantly if PPE was available (+8.3% [95%CI 7.2, 9.5] for stranger/unfamiliar, and +1.4% [95%CI 0.8, 1.9] for family/familiar persons). Willingness to perform bystander resuscitation during the pandemic decreased, however this was ameliorated if simple PPE were available.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".