Protective Factors of Nurses’ Mental Health and Professional Wellbeing During the COVID-19 Pandemic: A Multicenter Longitudinal Study
Bibliographic record
Abstract
Objective: Using a salutogenic approach, this study aimed to identify similarities in the protective factors of nurses' psychological Quality of Life (QoL) and professional wellbeing (PWB) in four countries and to assess their variability over time during the COVID-19 pandemic. Methods: This multicentric study used a longitudinal design with three measurements points: Autumn 2021, spring 2022, and autumn 2022. The study consisted in a self-administered online questionnaire addressed to nurses working in hospitals. Across all measurement times, 3,310 observations were collected in France, 603 in Switzerland, 458 in Portugal, and 278 in Canada. The outcomes were psychological QoL and PWB, and several potential protective factors were used as determinants. Results: Analyses revealed few changes over time in the outcomes. Across all countries, psychological QoL was associated positively with resilience and perceived social support, whereas PWB was associated positively with the ability to provide quality work and support from colleagues and superiors. Conclusion: The findings of this study highlighted the potential of several factors protective of nurses' psychological QoL and PWB. These should be fostered through policies and measures to support nurses.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".