Are nurses at Swedish Departments of Infectious diseases prepared to care for patients with African viral haemorrhagic fever? - A survey study
Bibliographic record
Abstract
Background: The African viral haemorrhagic fevers have in recent years been the cause of large outbreaks with high mortality rates and elevated risks of global spread. These outbreaks put the Departments of Infectious diseases, both national and international, on high demand when caring for this patient group, in a patient- and staff-safe manner. The aim of the study was to describe nurses’ perceived ability and knowledge about caring for patients with suspected or verified African viral haemorrhagic fever at Departments of Infectious diseases in Sweden.Methods: A web survey was conducted to collect data. The results are presented through a descriptive design. The participants were registered nurses working in infectious diseases clinics; 216 survey results were registered.Results: Registered Nurses in Swedish Departments of Infectious diseases witnessed having limited knowledge about the African haemorrhagic fevers. The respondents also perceived having limited or very limited knowledge about various practival procedures, such as drawing blood samples to confirm the infection. The majority of the participants had not been given theoretical education, nor had been given the opportunity to sufficiently practice using personal protective equipment at their place of work. The nurses perceived fear for their personal safety while caring for this group of patients.Conclusions: The participants perceived fear, both limited theoretical and practical knowledge and training about caring for patients with African haemorrhagic fever, even though they had worked with infectious diseases for several years. There is a need for implementation of measures to ensure the healthcare professionals' safety and to prevent them from being infected with potentially lethal infections. It also poses a risk for the patient in the absence of specific nursing care, which can lead to an increased critical disease state.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".