Covid-19 vaccination decisions and impacts of vaccine mandates: A cross sectional survey of healthcare workers in Ontario, Canada
Bibliographic record
Abstract
Abstract Background Since vaccination policies were introduced in the healthcare sector in the province of Ontario, Canada, most establishments implemented vaccination or termination requirements, with most enforcing them to this day. Researchers have shown a strong interest in the perceived problem of vaccine hesitancy among healthcare workers, yet not in their lived experience of the policy or in their views on the policy’s impact on the quality of patient care in the province. Goal To document the experience and views on mandated vaccination of healthcare workers in the province of Ontario, Canada. Methods Between February and March 2024, we conducted a cross-sectional survey of Ontario healthcare workers, recruited through professional contacts, social media, and word-of-mouth. Findings Most respondents, most with 16 or more years of professional experience, were unvaccinated, and most had been terminated due to non-compliance with mandates. As well, and regardless of vaccination status, most respondents reported safety concerns with vaccination, yet did not request an exemption due to their experience of high rejection rates by employers. Nevertheless, most unvaccinated workers reported satisfaction with their vaccination choices, although they also reported significant, negative impacts of the policy on their finances, their mental health, their social and personal relationships, and to a lesser degree, their physical health. In contrast, most respondents within the minority of vaccinated respondents reported being dissatisfied with their vaccination decisions, as well as having experienced mild to serious post vaccine adverse events, with about one-quarter within this group reporting having been coerced into taking further doses, under threat of termination, despite these events. Further, a large minority of respondents reported having witnessed underreporting or dismissal by hospital management of adverse events post vaccination among patients, worse treatment of unvaccinated patients, and concerning changes in practice protocols. Close to half also reported their intention to leave the healthcare industry. Discussion Our findings indicate that in Ontario, Canada, mandated vaccination in the health sector had an overall negative impact on the well-being of the healthcare labour force, on patient care, on the sustainability of the health system, and on ethical medical practice. Our study should be reproduced in other provinces, as well as in other countries that adopted comparable policies. Findings from this and similar studies should be seriously considered when planning for future health emergencies, to protect health systems in crisis due to severe labour shortages, as well as the right to informed consent of healthcare workers and members of the public.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".