The intersection of gender and race in older adults’ decision to receive COVID-19 vaccines
Bibliographic record
Abstract
COVID-19 vaccines are essential public health tools for protecting older adults, who are at high risk of severe outcomes associated with COVID-19. Little is known, however, about how older adults approach the decision to receive a COVID-19 vaccine. We hypothesized that intersections between gender and race may provide unique insight into the decision-making process and the factors that lead to vaccine uptake among hesitant individuals. We performed in-depth interviews with 24 older adults who had been vaccinated against COVID-19 and used the framework approach with an intersectional lens to analyze data. Two typologies emerged: eager compliers did not question the need to vaccinate, whereas hesitant compliers were skeptical of the vaccine and underwent a thorough decision-making process prior to vaccination. For eager compliers, the vaccine offered protection from a disease that posed a serious threat, and few risks were perceived. In contrast, hesitant compliers perceived risks associated with the vaccine product or mistrusted the infrastructure that led to rapid vaccine development. Hesitancy was greater among Black participants, and only Black participants reported mistrust in vaccine infrastructure. At the intersection of gender and race, a 'White male effect' was observed, whereby White men perceived the fewest risks associated with the vaccine, and Black women were the most fearful of serious side effects. Nearly all hesitant compliers ultimately got vaccinated due to the threat of COVID-19. Convenient access through vaccine clinics in senior's buildings was pivotal for hesitant compliers and external and internal influences had differential impacts by race and gender. Emphasizing the risk of COVID-19, convenient and accessible opportunities for vaccination, and messages that are targeted to specific groups are likely to increase vaccine uptake among older adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".