Sustaining a Workforce: Reflections on Work from Home and Community Care Nurses Transitioning out of the COVID-19 Pandemic
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has had an unprecedented impact on nurses' well-being and desire to practice; however, the experience of Canadian home and community care nurses remains less well understood. As the health human resources crisis in this sector persists, understanding these nurses' experiences may be vital in creating more effective retention strategies. Objective: The aim of this study was to explore how the COVID-19 pandemic shaped the working experiences, motivations, and attitudes of home and community care nurses in the Greater Toronto Area. Methods: Using an exploratory, descriptive, qualitative approach, 16 home and community care nurses participated in semistructured interviews. Data were analyzed using collaborative thematic analysis. Participants shared their reflections on work by detailing their experiences prepandemic, during crisis, transitioning out of crisis, and regarding pandemic recovery. Results: During the COVID-19 pandemic inadequate staffing resources during and beyond the crisis period disrupted many desirable facets of work for home and community care nurses such as stable, balanced, and flexible work conditions, and exacerbated the unfavorable aspects such as isolation and inconsistent support. Many nurses were reevaluating their careers: for some, this meant stronger professional attachment and for others, it meant intentions to leave. Improved sector preparedness, wages, and workplace support were identified as strategies to sustain this workforce beyond the pandemic. Conclusion: Home care organizations must consider ways to address the root cause of concerns expressed by nurses who wish to practice in a supportive environment that is sufficiently staffed and sensitive to workload expectations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".