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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: 1. Data Policy: Plos One's data policy does not permit author contact to be the only source of the data set in most cases. This study does not, under my reading of the policy, meet any of the exceptions. The full data set should be uploaded to an open data repository.

2. Inadequate literature review. Other researchers have conducted qualitative and quantitative investigations into the impact of ethnicity and gender on respirator fit. These works are a) not mentioned in this paper and b) the originality / importance of this data are not established in relevance to prior work. While authors are correct sex has been more extensively studied than ethnicity, they are incorrect that ethnicity has not been much studied (lines 318-319). I would recommend the authors review the following literature on both gender and ethnicity:

--- Prospective observational study of gender and ethnicity biases in respiratory protective equipment for healthcare workers in the COVID-19 pandemic by C. Carvalho et al 2021

--- The influence of gender and ethnicity on facemasks and respiratory protective equipment fit: a systematic review and meta-analysis by J Chopra et al 2021

--- The effect of N95 designs on respirator fit and its associations with gender and facial dimensions by Hasni et al 2021

--- Respirator Fit and Facial Dimensions of Two Minority Groups by W Brazile et al 1998

--- The Effect of Subject Characteristics and Respirator Features on Respirator Fit by Z Zhuang et al 2005

--- The Effect of Gender and Respirator Brand on the Association of Respirator Fit with Facial Dimensions by R. Oestenstad et al 2007

--- P2/N95 filtering facepiece respirators: Results of a large-scale quantitative mask fit testing program in Australian health care workers by M Milosevic et all 2021

--- 316 Fit of N95 filtering facepiece respirators influenced by gender, design of facepiece, and activity engaged in use by Glass et all 2013

--- The PPE Pandemic: Sex-Related Discrepancies of N95 Mask Fit by L Christopher 2021

--- Evaluation of a Large-Scale Quantitative Respirator-Fit Testing Program for Healthcare Workers: Survey Results by Wilkinson et al 2010

3. Although this study was unable to obtain sufficient participants for statistical significance, I do believe the preliminary quantitative fit test findings are interesting and may potentially be of benefit to the scientific community. I am not sure that they warrant an original full paper - but if there is a brief report section, this would be a perfect fit. The significance of this paper, and it’s publish-ability, will depend partly on what it contributes in relation to existing literature (see point 2).

4. I would recommend the authors be more upfront / explicit about the inadequate sample size in the abstract and introduction. There is repeated mention of the study not meeting feasibility criteria. I would suggest changing the language to explicitly discuss the small sample size and reasons for this limitation. I believe the "feasibility" language currently used hides the utility of the study. Also, the current language is somewhat misleading - as this isn't a study to see if a method is feasible, as the method is well established in both scientific and industrial use.

5. The analysis of qualitative survey findings is lacking. If the qualitative findings are not robust enough to be useful, I would suggest leaving them out of the paper and instead making them available in the dataset for interested researchers. Otherwise, discussion and analysis are needed.

Reviewer #2: I have reviewed the above manuscript, which addresses an important and timely question about the fit, comfort, and breathability of N95 respirators among healthcare workers of diverse genders and ethnicities. The work is relevant to occupational health, equity in PPE design, and pandemic preparedness. The mixed-methods approach is appropriate and offers valuable context to the quantitative fit test results.

However, several areas would benefit from clarification and additional detail before the manuscript can be considered for publication. My major concerns relate to:

Comment 1: The integration of qualitative and quantitative results, which is mentioned but not described in enough methodological detail.

Comment 2: The aggregation of all non-White participants into one group, which may obscure important differences.

Comment 3: Limited discussion of the implications of the feasibility shortfall, both methodologically and in terms of generalizability.

Comment 4: Greater contextualization of the “out-of-range” anthropometric finding from Figure 2.

Below, I provide detailed comments, embedded within the manuscript text for ease of reference.

Sincerely,

Anahita Fakherpour

Embedded Reviewer Comments in Manuscript

Abstract (lines 23–48)

Comment 1: Clarify why the feasibility target was set at 100 participants, and what the reduced sample size means for interpreting both quantitative and qualitative results. Consider adding a sentence on whether this impacts the power to detect differences.

Background (lines 62–96)

Comment 2: The background section is strong, but the reliance on pre-pandemic anthropometric data references (e.g., 2005) should be supplemented with more recent post-COVID PPE design literature.

Comment 3: If any Canadian-specific anthropometric studies exist, briefly mention them to strengthen the rationale for conducting this work in Canada.

Methods (lines 106–198)

Comment 4: More detail is needed on how the “statistics-by-theme joint display” was created—did integration involve iterative coding, and how were disagreements resolved?

Comment 5: Justify the requirement that 50% of participants be non-White or have other specific characteristics. Was this based on effect size estimation, diversity representation targets, or prior literature?

Comment 6: Explain why no exploratory non-parametric statistics (e.g., Mann–Whitney U tests) were used, as these can be informative even in small samples.

Comment 7: Indicate whether fit testers were blinded to participant ethnicity and gender to reduce potential observer bias.

Comment 8: The exclusion criteria should be reported precisely.

Results – Feasibility (lines 200–231)

Comment 9: The feasibility shortfall is described, but more interpretation is needed. Were these challenges purely pandemic-related, or do they indicate systemic issues in recruiting HCWs for PPE research?

Comment 10: Consider quantifying the recruitment rate per week before and after the study amendment to better illustrate the impact of additional sites.

Results – Quantitative Fit Test (lines 233–259)

Comment 11: For anthropometric results, consider providing percentage differences to make the magnitude of differences more interpretable.

Comment 12: The finding that 75% of participants fall outside the NIOSH bivariate panel range is important—state briefly in Results what this implies for respirator design testing standards.

Results – Qualitative (lines 261–297)

Comment 13: Tables 4a and 4b should include scale anchors (e.g., 0 = poor, 4 = excellent) directly in the table for clarity.

Comment 14: In reporting comfort and breathability scores, you may wish to highlight how these subjective measures aligned—or conflicted—with quantitative fit factors.

Discussion (lines 299–360)

Comment 15: The comparison to prior literature is solid, but the discussion should explicitly address whether the trends observed (e.g., gender/ethnic disparities in fit) are likely to persist outside pandemic surge conditions.

Comment 16: Acknowledge the absence of participants with religious head coverings or facial hair, as this limits the generalizability to all HCW subgroups.

Conclusion (lines 362–368)

Comment 17: Strengthen the policy recommendations by explicitly calling for updates to the NIOSH bivariate panels and Canadian standards to incorporate gender and ethnic diversity in respirator design, along with specific recommendations for manufacturers.

Figures and Tables

Comment 18: Include sample sizes (n) in figure legends for transparency.

Comment 19: In Figure 2, annotate the proportion of participants outside the panel range for emphasis.

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what does this mean? ). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes:  Eugenia O'Kelly

Reviewer #2: No

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Attachments

Attachment

Submitted filename: Reviewers comments-PONE-D-25-34031.docx

Evaluating N95 Respirator Designs: A Mixed-Methods Pilot and Feasibility Study

PONE-D-25-34031R1

Dear Dr Fox-Robichaud, we are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Christophe Curti

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Thank you for your edits. I believe all my concerns have been adequately addressed.

Supporting information and data is clear and helpful.

I think the inclusion of survey qualitative findings greatly enhances the study.

Reviewer #2: (No Response)

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what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: Yes:  Eugenia O'Kelly

Reviewer #2: No

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