N95 Respirators for a Diverse Population of Healthcare Workers: A Mixed-Methods, Pilot and Feasibility Study
Bibliographic record
Abstract
Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a global effect. While most of the transmission occurs through droplets produced by an infected individual, SARS-CoV-2 can be transmitted through virus-containing aerosols. The use of N95 respirators reduces the risk of infection; however, in the absence of standardized testing facilities, as well as supply chain and border challenges, Canadian healthcare workers (HCW) had to rely on United States (US) standards and respirators. In Canada, women represent 82% of HCWs, but most masks and respirators have been designed based on the anthropometrics of average men in the US and Europe. In the absence of a tight seal, female HCWs and any individual who does not fit the average male head and face, including individuals of different ethnicities, are at risk of contracting SARS-CoV-2 and other infectious diseases. Thus, there is a knowledge gap on the effects of gender and ethnicity on the fit of N95 respirators and the implications of poor fit on the physical and psychological well-being of HCWs. Objectives: Primary: Feasibility of a multi-center mixed-method study, with a sample size of 100, 50% of participants self-identifying as non-white and having at least 1 characteristic of interest. Secondary: (1) Generate quantitative evidence on N95 fit using a PortaCount fit test, (2) describe participant-reported feelings on fit and breathability, and (3) evaluate the impacts of the pandemic and limited supply of N95’s on a HCWs overall physical and mental well-being. Methods: This study was a mixed-method prospective pilot and feasibility study consisting of (1) a quantitative fit test and (2) a qualitative survey on N95 fit and comfort, as perceived by HCWs. The quantitative fit was assessed using a TSI PortaCount test and facial measurements of bizygomatic breadth and Menton-Sellion length. In parallel, a survey was administered to collect sociodemographic information, gauge the HCW's assessment of N95 fit and comfort, and assess the impact of PPE- related challenges on the physical and mental well-being of HCWs. Analysis: Primary: The sample size, the proportion of various HCWs, and the number of participants who completed both aspects of the study were reported using descriptive statistics. Secondary: The results of the quantitative fit test, as well as the domains assessed in the survey using Likert scales, were summarized using descriptive statistics. Additional patient-reported assessments were collated and presented to provide a comprehensive reflection of HCW's feelings and attitudes on respirator fit and comfort. Results: Following a study amendment to increase eligible sites, 37 of the 41 (90.2%) approached HCWs consented to participate, 36 of the 41 (97.3%) were successfully fitted, and all 36 HCWs completed the survey. Compared to the other included HCWs, female HCWs who identified as non-White had the lowest mean fit factor. Differences in Menton-sellion length and bizygomatic breadth were also observed between both male and female HCWs and between white and non-White HCWs. These results were corroborated by the survey data. On average, female HCWs reported lower scores in all measured domains, and the majority of HCWs reported physical discomfort, including headaches and itching, and negative impacts on their psychological well-being, as a result of fit, availability, and prolonged use of N95. Conclusion: Despite the challenges of conducting research in the context of the COVID-19 pandemic, we have identified gender and ethnicity as key factors in the fit of N95 respirators and the negative implications of existing respirator designs on the physical and psychological well-being of HCWs. Future studies, including a larger mixed-method study, and respirator designs should consider the effects of gender and ethnicity to ensure that they reflect the diverse demographic of HCWs.
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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 | 0.019 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".