Health System Leadership for Psychological Health and Organizational Resilience During the COVID-19 Pandemic: Protocol for a Multimethod Study
Bibliographic record
Abstract
BACKGROUND: Since the World Health Organization declared COVID-19 a global pandemic, health systems and health system leaders have faced unprecedented challenges through the various stages of the crisis. Canada and other health systems were largely ill-prepared to handle this crisis. The longevity of the pandemic has profoundly affected health care systems and compounded the rates of negative psychological outcomes in health systems' leaders and staff, rates of emotional exhaustion, and burnout. OBJECTIVE: The purpose of this study is to investigate the experiences of health system leaders and nurses during COVID-19 and to develop recommendations to inform pre-, during-, and postcrisis leadership strategies and practices for health system leaders, which address leaders' and nurses' psychological health and well-being, as well as organizational resilience. METHODS: A 3-year multimethod approach will be adopted and include a qualitative exploratory inquiry informed by Geerts' 4-stage framework of imperatives for health system leaders to guide data collection and analysis. We will then conduct semistructured individual interviews with health system leaders in 3 provinces in Canada and hold focus group interviews (FGIs) with nurses from the same organizations. Data from the interviews and FGIs will be integrated to determine how health system leaders promoted their own health and how their leadership shaped nurses' psychological health and contributed to building organizational resilience. We will engage knowledge users using a nominal group technique in a 1-day forum to discuss how findings can be applied in professional contexts. We will conduct a thematic analysis of the aggregated data to identify and analyze themes to provide an interpretive explanation of health system leaders' experiences and organizational resilience during the COVID-19 pandemic, and how the leaders promoted nurses' psychological health and well-being. The protocol has been reviewed and approved by the University of Manitoba institutional review board (IRB), the University of Alberta IRB, and McMaster University Ontario IRB. RESULTS: As of September 6, 2024, this study has made significant progress. Data collection has been completed for individual interviews with health leaders in Alberta and Manitoba, and has commenced in Ontario. FGIs will be completed by the fall of 2025, data integration in early 2026, nominal group technique in the spring of 2026, and the final report will be written in the summer of 2026. CONCLUSIONS: The findings will support practices that health system leaders can implement to foster their own and nurses' psychological health and well-being and build organizational resilience. The benefits of this study aim to include evidence for effective health system leadership and support for nurses, crisis preparedness, and lessons from the pandemic to address leadership practices to operationalize the imperatives within the 4 stages of the crisis model. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/66402.
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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 | 0.076 | 0.074 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.096 | 0.019 |
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".