“If all of this was about health, I’d still be working:” Lived experiences of healthcare workers under COVID-19 vaccine mandates in British Columbia, Canada
Bibliographic record
Abstract
COVID-19 vaccine mandates for healthcare workers (HCWs) in British Columbia (BC) were implemented in October 2021 and remained effective until July 2024, despite public protests and opposition from some unions. This study explored HCWs’ lived experiences under these mandates, focusing on decision-making processes, personal and professional impacts, and perceived consequences for patient care. We conducted a reflexive thematic analysis of qualitative responses from 90 HCWs, collected through one open-ended survey question and elaborations on closed questions. The survey, conducted in May–June 2024, recruited a convenience sample of 166 HCWs of varying vaccination status, professions, and demographics through social media and professional networks. Findings are reported in accordance with the consolidated criteria for reporting qualitative studies (COREQ) checklist (Table A1). Most respondents were unvaccinated and had lost employment due to non-compliance. Participants reported significant personal losses and expressed overwhelmingly negative views on mandates. Six key themes emerged: (1) conflict with scientific evidence and clinical practice; (2) violations of medical ethics, especially informed consent; (3) dismissed personal and economic hardships; (4) overlooked vaccine-related physical harms; (5) discrimination against unvaccinated HCWs and patients; and (6) negative impacts on care delivery. Our findings suggest that vaccine mandates caused substantial social and economic harm, contributed to staffing shortages, degraded workplace morale, and compromised patient care. Drawing on respondents’ experiences and the scientific evidence available at the time, we conclude that mandatory COVID-19 vaccination for HCWs lacked scientific justification and violated foundational ethical principles in health-care policy and practice.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.019 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".