“I Called us the Sacrificial Lambs”: Experiences of Nurses Working in Border City Hospitals During the First Wave of the COVID-19 Pandemic
Bibliographic record
Abstract
Background The first wave of the COVID-19 pandemic had a significant impact on the personal and professional lives of frontline nurses. Purpose The purpose of this descriptive phenomenological study was to explore the experiences of Canadian Registered Nurses (RNs) working in Ontario or United States hospitals during the first wave of the COVID-19 pandemic. Methods Semi-structured interviews were conducted with 36 RNs living in Ontario and employed either at an Ontario or United States hospital. Three main themes were identified across both healthcare contexts. Results 1) The Initial Response to the pandemic included a rapid onset of chaos and confusion, with significant changes in structure and patient care, often exacerbated by hospital management. Ethical concerns arose (e.g., redeployment, allocation of resources) and participants described negative emotional reactions. 2) Nurses described Managing the Pandemic by finding new ways to nurse and enhanced teamwork/camaraderie; they reported both struggle and resiliency while trying to maintain work and home life balance. Community responses were met with both appreciation and stigma. 3) Participants said they were Looking Forward to a “new normal”, taking pride in patient improvements, accomplishments, and silver linings, with tempered optimism about the future. Many expressed a reaffirmation of their identities as nurses. Differences between participants working in the US and those working in Ontario were noted in several areas (e.g., initial levels of chaos, ethical concerns, community stigma). Conclusions The COVID-19 pandemic has been very difficult for nursing as a profession. Close attention to post-pandemic issues is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".