Infectious Respiratory Disease Outbreaks and Pregnancy: Occupational Health and Safety Concerns of Canadian Nurses
Bibliographic record
Abstract
INTRODUCTION: This paper is a report of a qualitative study of emergency and critical care nurses' perceptions of occupational response and preparedness during infectious respiratory disease outbreaks including severe acute respiratory syndrome (SARS) and influenza. PROBLEM: Healthcare workers, predominantly female, face occupational and personal challenges in their roles as first responders/first receivers. Exposure to SARS or other respiratory pathogens during pregnancy represents additional occupational risk for healthcare workers. METHODS: Perceptions of occupational reproductive risk during response to infectious respiratory disease outbreaks were assessed qualitatively by five focus groups comprised of 100 Canadian nurses conducted between 2005 and 2006. RESULTS: Occupational health and safety issues anticipated by Canadian nurses for future infectious respiratory disease outbreaks were grouped into four major themes: (1) apprehension about occupational risks to pregnant nurses; (2) unknown pregnancy risks of anti-infective therapy/prophylaxis; (3) occupational risk communication for pregnant nurses; and (4) human resource strategies required for pregnant nurses during outbreaks. The reproductive risk perceptions voiced by Canadian nurses generally were consistent with reported case reports of pregnant women infected with SARS or emerging influenza strains. Nurses' fears of fertility risks posed by exposure to infectious agents or anti-infective therapy and prophylaxis are not well supported by the literature, with the former not biologically plausible and the latter lacking sufficient data. CONCLUSIONS: Reproductive risk assessments should be performed for each infectious respiratory disease outbreak to provide female healthcare workers and in particular pregnant women with guidelines regarding infection control and use of anti-infective therapy and prophylaxis.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".