Effects of the COVID-19 Pandemic on the Decision and Doubts About Vaccination in Catalonia: Online Cross-sectional Questionnaire
Bibliographic record
Abstract
BACKGROUND: Hesitancy to get vaccinated during the COVID-19 pandemic may decrease vaccination coverage and facilitate the occurrence of local or global outbreaks. OBJECTIVE: The objective of this study was to analyze the impact of the COVID-19 pandemic in Catalonia on 3 aspects: the decision to get vaccinated against COVID-19, changes in opinion about vaccination in general, and the decision to get vaccinated against other diseases. METHODS: We performed an observational study with the population of Catalonia aged 18 years or over, obtaining information through a self-completed questionnaire in electronic format. Differences between groups were determined using the chi-square test, Mann-Whitney U test, or the Student t test. RESULTS: We analyzed the answers from 1188 respondents, of which 870 were women, 47.0% (558/1187) had sons or daughters under the age of 14 years, and 71.7% (852/1188) had studied at university. Regarding vaccination, 16.3% (193/1187) stated that they had refused a vaccine on some occasion, 76.3% (907/1188) totally agreed with vaccines, 1.9% (23/1188) were indifferent, and 3.5% (41/1188) and 1.2% (14/1188) slightly or totally disagreed with vaccination, respectively. As a result of the pandemic, 90.8% (1069/1177) stated that they would get vaccinated against COVID-19 when they are asked, while 9.2% (108/1177) stated the opposite. A greater intention to get vaccinated was observed among women; people older than 50 years; people without children under 15 years of age; people with beliefs, culture, or family in favor of vaccination; respondents who had not previously rejected other vaccines, were totally in favor of vaccines, or had not increased their doubts about vaccination; and respondents who had not changed their decision about vaccines as a result of the pandemic. Finally, 30.3% (359/1183) reported an increase in their doubts regarding vaccination, and 13.0% (154/1182) stated that they had changed their decision about routinely recommended vaccines as a result of the pandemic. CONCLUSIONS: The population studied was predominantly in favor of vaccination; however, the percentage of people specifically rejecting vaccination against COVID-19 was high. As a result of the pandemic, we detected an increase in doubts about vaccines. Although the final decision about vaccination did not primarily change, some of the respondents did change their opinion about routine vaccinations. This seed of doubt about vaccines may be worrisome as we aim to maintain high vaccination coverage.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".