Vaccination experiences and decision-making in older adult Korean immigrants living in Canada: A qualitative descriptive study
Bibliographic record
Abstract
Older adult immigrants face unique challenges in accessing healthcare and preventive health measures, including vaccines. While Asian immigrants in North America generally report high vaccine uptake, studies suggest that Korean immigrants may have lower willingness to vaccinate and experience barriers to healthcare utilization. Understanding the vaccination experiences and decision-making processes of this population is critical to addressing disparities in and improving vaccine uptake. Therefore, we conducted a qualitative descriptive study to explore the influenza, pneumococcal, and shingles vaccination experiences, perceptions, and decision-making among older adult Korean immigrants in Canada. Study participants were recruited using convenience, snowball, and purposeful sampling. Semi-structured interviews were conducted with 30 Korean immigrants aged 65 years and older residing in Montreal and Toronto, Canada from September 2023 to July 2024. Interview transcripts and field notes were thematically analyzed, guided by the socio-ecological model. Key themes across intrapersonal-, interpersonal-, institutional-, community-, and policy-levels were identified. Participants reported strong willingness to get vaccinated, largely influenced by healthcare provider recommendations, government guidance, and perceived disease risk. However, gaps in vaccine knowledge, concerns about vaccine safety, and lack of explicit healthcare provider recommendations contributed to non-vaccination. Participants identified trust in the Canadian government and medical professionals as primary motivators to adhere to vaccination guidelines. Some vaccination-specific facilitators and/or barriers were also identified (e.g., financial barriers to shingles vaccination). Strategies to improve vaccine uptake among older adult Korean immigrants could involve supporting healthcare providers or public health efforts to promote vaccinations, encouraging healthcare providers to address concerns and emphasize safety and benefits of vaccinations using shared decision making, and collaborating with faith-based communities to promote vaccinations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".