Safeguarding and Inspiring: Inpatient Nurse Managers’ Dual Roles during COVID-19
Bibliographic record
Abstract
In Canada, and internationally, in-patient nurse managers' leadership roles during the current COVID-19 pandemic have not been recognized. Yet these nurse managers play critical roles in safeguarding both staff and patients, and inspiring staff to provide complex patient care. This paper describes how 13 acute-care nurse managers enacted and experienced transformational and complexity leadership during COVID-19. This case study of leadership at one multi-site, academic health sciences centre, examined how the first phase of the pandemic impacted the first-line manager's role, the strategies used to navigate organizational and patient care challenges, supports available and overall key learnings about leadership during a pandemic. Results reveal the dual roles assumed by nurse managers during the COVID-19 crisis. Nurse managers in this organization safeguarded patients, families and staff while ensuring 24-hour unit operations. Through leader-staff relationships, managers inspired staff to keep going despite the constant uncertainty and ambiguity. Nurse leaders in this case study exemplified characteristics of transformational and complexity leadership as their roles intensified in the context of COVID-19. Recommendations for nursing and healthcare leaders regarding the ongoing and future pandemics are discussed.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".