Perspectives on Work in the Continuing Care Sector during and after the COVID-19 Pandemic: A Mixed-Method Design
Bibliographic record
Abstract
Background. Improving the recruitment and retention of healthcare workers in the continuing care sector is critical to ensuring adequate care for older adults, which was highlighted following the COVID-19 pandemic. Purpose. The purpose of this study was to understand the perceptions of prospective registered nurses about working in the continuing care sector and identify workplace attributes that attract prospective nurses to the sector. Methods. A sequential mixed methods study was conducted with nursing students at Ontario Tech University. Focus groups (n = 14) asked students to comment on views about working in the continuing care sector, and job attributes that may attract them to the sector. Focus group data were analyzed using thematic analysis. Subsequently, a cross-sectional survey asked students to respond to elicited choice job scenarios that varied job attributes. The job attributes were shaped by the focus group interview data. To assess respondent’s preferences, the survey data (n = 139) were analyzed to generate willingness-to-pay (WTP) values for each job attribute. Results. Focus group interviews suggested that fair compensation, optimal client-to-staff ratios, unionized work environments, comprehensive benefits packages, and flexible work arrangements were important job attributes. In survey results, 18.0% expressed interest in working in the continuing care sector compared to 75.5% in acute care. Regression analysis suggested that higher amounts of paid vacation (WTP: −5.983; 95% CI: −13.749 and −0.037) and higher risk of injury (WTP: 0.684; 95% CI: 0.124 and 1.208) were associated with work in the continuing care sector. Impact. Continuing care workplaces can attract nurses by offering flexible options such as part-time positions and paid vacation and by taking actions that can mitigate the risk of workplace injury, violence, and abuse. Nursing students should be shown the positive aspects of working with older adults and dispel negative perceptions about the continuing care sector. Further research is needed to understand the preferences for work and risk perceptions among currently employed nursing staff.
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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 | 0.002 | 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 | 0.000 | 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".