Nursing Student Experiences During a Clinical Re-assignment to Long Term Care in the Omicron Wave of the Pandemic
Bibliographic record
Abstract
Background: The peak of the Omicron wave of COVID-19 created a sudden and unanticipated shortage of health care workers, particularly in long-term care (LTC), triggering the provincial government’s call for aid. This culminated into a collaboration between universities and government to engage undergraduate nursing students to assist by re-assigning their clinical placements. This required a shift in location to LTC from acute care, and time frame, from end of semester to mid-semester. Purpose: The purpose of this descriptive qualitative study was to explore nursing students’ experiences at one university who participated in a clinical reassignment during the peak of the Omicron wave of the COVID-19 pandemic. Methods: Story theory (Liehr & Smith, 2019) provided the premise for this descriptive qualitative research. Nursing students (n = 104) were invited to participate in an open-ended online survey resulting in a total of 26 participants sharing their stories. Braun and Clarke’s (2006) thematic analysis guided the interpretation of the data. Results: Three major themes were identified. The first theme was Student Nurses Answer the Call in which student insights into the need to be flexible and to have a sense of professional responsibility and altruism, yet also recognizing that this experience had an impact on their academic and mental wellbeing. The second theme was Fear of Missing Out as participants expressed frustration of missed clinical learning opportunities. The third theme was Wanting a Voice in which participants wanted the opportunity to voice their thoughts and ideas pertaining to the decisions that would impact their learning during this reassignment. Conclusions: These findings add to the existing body of knowledge related to nursing students’ clinical learning during the pandemic. It is important to consider communication and decision-making opportunities for students in times of sudden and unanticipated change. The findings also brought to light students’ perceptions of LTC reinforcing to nurse educators the importance of promoting the transferability of professional values and skills development regardless of the clinical setting.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".