New graduate nurses’ experiences with and perceptions of their mental health and well-being during the COVID-19 pandemic: An interpretive description study protocol
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had a significant impact on healthcare workers. Healthcare workplaces are high stress environments placing care providers such as Registered Nurses at high risk for occupational stress injuries related to poor mental health. Currently, healthcare authorities rely on new graduate nurses to help fill gaps in staffing; however, novice nurses are especially vulnerable to workplace illnesses, with the recent pandemic contributing to this risk. Research is needed to understand new graduate nurses' experiences and perceptions of their mental health and well-being as they transition to practice in the COVID-19 pandemic and the supportive resources they require to assist in contributing to healthy workplaces. OBJECTIVES: 1) To explore new graduate nurses' experiences and perceptions of their mental health and well-being as they transitioned to practice during the COVID-19 pandemic in Newfoundland and Labrador, Canada; 2) To understand new graduate nurses' awareness and use of available mental health supports and resources during the COVID-19 pandemic; and 3) To identify strategies and resources to support new graduate nurses' mental health and well-being as they transitioned to practice during a public health crisis. METHODS: An interpretive description research methodology will be used to conduct this study. The COnsolidated criteria for REporting Qualitative research (COREQ) checklist will be used to verify both the structure of the study and presentation of findings. Approximately forty semi-structured interviews will be conducted with new graduate nurses who worked in Newfoundland and Labrador in 2020, 2021 or 2022. Data collected will be analyzed using thematic analysis with descriptive statistics used to present demographic information. RESULTS: The results of this study will help inform changes to existing workplace programs and contribute to the development of new processes to support new graduate nurses' mental health and well-being as they transition to practice during a public health crisis such as COVID-19.
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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 | 0.056 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".