Beliefs regarding COVID‐19 vaccines among Canadian workers in the intellectual disability sector prior to vaccine implementation
Bibliographic record
Abstract
BACKGROUND: Workers supporting adults with intellectual disabilities (ID) experience significant stress in their essential role during COVID-19 due to the high risk of their clients contracting COVID-19 and having adverse outcomes. The purpose of the current study was to describe the attitudes of workers towards COVID-19 vaccination prior to vaccination rollout, with a view to informing strategies to promote vaccine uptake within this high-risk sector. METHODS: An online survey was sent via email to workers supporting adults with ID in Ontario, Canada, between January 21 and February 3, 2021 by agency leadership and union representatives. RESULTS: Three thousand and three hundred and seventy-one workers, representing approximately 11.2% of Ontario workers supporting adults with ID completed an online survey. Most reported that they were very likely (62%) or likely (20%) to get a COVID-19 vaccine (vaccination intent) although 18% reported they were less likely to do so (vaccination nonintent). Workers with vaccination nonintent were younger and were more likely to endorse the beliefs that (1) it will not benefit them or those around them, (2) it was not part of their job, (3) rapid development confers uncertainties and risks, and (4) they were scared of potential vaccine side effects. CONCLUSIONS: There is need to address common misconceptions among workers supporting adults with ID to help activate them as vaccine advocates in the communities they serve. Partnered efforts between workers, unions and agency leadership with public health experts to address concerns are required.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".