Dear Dr. Lösch,

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PLOS ONE

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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: Yes

Reviewer #2: Yes

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

Reviewer #1: N/A

Reviewer #2: Yes

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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: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Dear authors, thank you for sharing this work. Integrating an online forum on the topic of interest in order to get information about consumer’s view seems to be a feasible alternative. Using a natural language processing (NLP) seems plausible, although raising some questions about selection bias. Adding some references about this would help to get information about that. Generally, it would be expected that people with very bad experiences or people being very satisfied with a certain intervention would be overrepresented. Are the publications regarding this kind of bias and how to deal with it using internet platforms on medical topics? Would be helpful to add this.

255 ff: “the study findings were assessed for relevance and accuracy by these professionals. “ � were there any criteria?

Discussion: you carefully ventilating possible pitfalls and dangers of using public forums like you did. You underline that a human should assess each AI step. How could you identify fake input in dokter.NL ?

Adding some aspects mentioned above may help this work to be even more practice relevant.

Reviewer #2: General comments

This manuscript presents a novel and timely application of natural language processing (NLP) to analyze patient experiences shared online for the purpose of informing clinical guideline development. The study is well-designed, methodologically sound, and addresses a significant gap in the integration of patient experiential knowledge into guidelines, particularly for conditions like scabies where traditional patient engagement methods are challenging. The findings are impactful, leading to tangible changes in the Dutch public health guideline for scabies.

1. Generalizability: While the method is promising, the study focuses solely on scabies and a single Dutch forum. The authors should briefly discuss the potential applicability to other diseases or cultural contexts.

2. Patient engagement: The lack of direct engagement with forum users (e.g., validation of themes) is noted as a limitation. A brief discussion on how to mitigate this in future studies (e.g., involving patient advocates) would strengthen the manuscript.

3. Technical details: The preprocessing steps (e.g., stop-word removal, stemming) are described, but additional details on model validation (e.g., inter-rater agreement for topic labeling) would enhance reproducibility.

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Reviewer #1: No

Reviewer #2: No

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Including patient experiences from online sources in guidelines: A natural language processing study on scabies

PONE-D-25-04246R1

Dear Dr. Lösch,

We’re 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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Abayeneh Girma

Academic Editor

PLOS One

Additional Editor Comments (optional):

Accept for publication.

This manuscript represents a valuable contribution to interdisciplinary research at the intersection of digital health, NLP, and evidence-based guideline development. It is innovative, ethically conducted, well-executed, and clearly communicated. The study advances both methodology and practice, offering a replicable model for future guideline developers seeking to incorporate patient voices in a scalable, low-burden manner.

Reviewers' comments:

None