Gender, Socioeconomic Status, Race, and Ethnic Disparities in Bystander Cardiopulmonary Resuscitation and Education—A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Social determinants are associated with survival from out-of-hospital sudden cardiac arrest (SCA). Because prompt delivery of bystander CPR (B-CPR) doubles survival and B-CPR rates are low, we sought to assess whether gender, socioeconomic status (SES), race, and ethnicity are associated with lower rates of B-CPR and CPR training. METHODS: This scoping review was conducted as part of the continuous evidence evaluation process for the 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care as part of the Resuscitation Education Science section. We searched PubMed and excluded citations that were abstracts only, letters or editorials, and pediatric studies. RESULTS: We reviewed 762 manuscripts and identified 24 as relevant; 4 explored gender disparities; 12 explored SES; 11 explored race and ethnicity; and 3 had overlapping themes, all of which examined B-CPR or CPR training. Females were less likely to receive B-CPR than males in public locations. Observed gender disparities in B-CPR may be associated with individuals fearing accusations of inappropriate touching or injuring female victims. Studies demonstrated that low-SES neighborhoods were associated with lower rates of B-CPR and CPR training. In the US, predominantly Black and Hispanic neighborhoods were associated with lower rates of B-CPR and CPR training. Language barriers were associated with lack of CPR training. CONCLUSION: Gender, SES, race, and ethnicity impact receiving B-CPR and obtaining CPR training. The impact of this is that these populations are less likely to receive B-CPR, which decreases their odds of surviving SCA. These health disparities must be addressed. Our work can inform future research, education, and public health initiatives to promote equity in B-CPR knowledge and provision. As an immediate next step, organizations that develop and deliver CPR curricula to potential bystanders should engage affected communities to determine how best to improve training and delivery of B-CPR.
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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 | 0.008 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".