The effect of workload on the development of burnout syndrome in Covid-19 intensive care nurses: a systematic review
Bibliographic record
Abstract
BACKGROUND: Nowadays, it is well-known that burnout is a syndrome that mainly affects the helping professions. The nursing profession is obviously among those categories of workers that can develop burnout and, precisely because of its proximity to people who suffer associated with high workloads characterized by high emotional impacts. AIM: The aim of this systematic review is, therefore, to highlight whether the high nursing workload during the pandemic has contributed to the onset of burnout syndrome in nurses who served in intensive care units (ICUs) dedicated to the care of Covid-19 patients. METHODS: A systematic review was carried out. The main scientific databases were consulted, such as PubMed, Scopus, Web of Sciences and CINAHL analyzing all the papers present in literature. Using PRISMA guidelines, fifteen articles were included in the review. The protocol for this review has been registered on PROSPERO, the international prospective register of systematic reviews (PROSPERO ID: CRD42024502094). The quality assessment of the articles included in this review was conducted using the Newcastle-Ottawa Scale (NOS) for observational studies. RESULTS: In accordance with the literature, all the 15 included studies documented high levels of burnout among ICU professionals, nevertheless those levels were greater than the ones registered in the pre-pandemic period. In Covid-19 era, nurses experienced higher levels of burnout compared to other professions and working as a nurse was identified as an independent risk factor for increased risk of burnout. As reported by all included studies, the overwhelming severity of Covid-19 patients entailed a significant increase in workload for health care providers, particularly nurses. Ultimately, this increase showed a significant correlation with increased burnout risk. CONCLUSIONS: The review highlights the correlation between workload and burnout of nurses in Covid-19 intensive care units. It is expected that this and other studies will contribute to a better understanding of the importance of assigning the adequate workload to nurses.
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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 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".