Changes in attitudes to vaccination as a result of the COVID-19 pandemic: A longitudinal study of older adults in the UK
Bibliographic record
Abstract
BACKGROUND: The rapid development of COVID-19 vaccines has brought an unprecedented focus on public attitudes to vaccines, with intention to accept a COVID-19 vaccine fluctuating during the pandemic. However, it is unclear how the pandemic may influence attitudes and behaviour in relation to vaccines in general. The aim of the current study is to examine older adults' changes in vaccination attitudes and behaviour over the first year of the pandemic. METHODS: In February-March 2020 (before the first COVID-19 national lockdown in the UK), 372 older adults (aged 65+) provided sociodemographic information, self-reported influenza vaccine uptake, and completed two measures of vaccination attitudes: the 5C scale and the Vaccination Attitudes Examination Scale. One-year later, following rollout of COVID-19 vaccines to older adults, participants provided information on their COVID-19 and influenza vaccine uptake in the previous 12 months, and completed the 5C and VAX scales again. Paired samples t-tests were used to examine changes in vaccination attitudes over time. RESULTS: Almost all participants (98.7%) had received at least one dose of a COVID-19 vaccine, and a significant increase in influenza uptake was identified (83.6% in 2020 to 91.6% in 2021). Complacency, mistrust of vaccine benefit, concerns about commercial profiteering, and constraints to vaccination had significantly decreased between Time 1 and Time 2, and collective responsibility had significant increased. However, calculation and worries about unforeseen future effects had increased, indicating that participants now perceived higher risks related to vaccination and were taking a more deliberative information-seeking approach. CONCLUSION: The results show significant changes in vaccination attitudes across the pandemic. These changes suggest that while older adults became less complacent about the importance of vaccines, concerns about potential risks associated with vaccination increased. It will be important for public health communication to address these concerns for all vaccines offered to this group.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".