PONE-D-25-64323The psychological impact of major disasters on Japan's medical system: An SNS text analysisPLOS One

Dear Dr. Kitayama,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Feb 11 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Liviu-Adrian Cotfas

Academic Editor

PLOS One

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1.Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In your Methods section, please include additional information about your dataset and ensure that you have included a statement specifying whether the collection and analysis method complied with the terms and conditions for the source of the data.

3. Please note that your Data Availability Statement is currently missing the repository name. If your manuscript is accepted for publication, you will be asked to provide these details on a very short timeline. We therefore suggest that you provide this information now, though we will not hold up the peer review process if you are unable.

4. When completing the data availability statement of the submission form, you indicated that you will make your data available on acceptance. We strongly recommend all authors decide on a data sharing plan before acceptance, as the process can be lengthy and hold up publication timelines. Please note that, though access restrictions are acceptable now, your entire data will need to be made freely accessible if your manuscript is accepted for publication. This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If you are unable to adhere to our open data policy, please kindly revise your statement to explain your reasoning and we will seek the editor's input on an exemption. Please be assured that, once you have provided your new statement, the assessment of your exemption will not hold up the peer review process.

5. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

6.If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Additional Editor Comments:

The manuscript must fully comply with PLOS ONE’s publication criteria, particularly with respect to the robustness and support of its conclusions. For instance, the study employs the ML-Ask tool to evaluate emotions; however, the conclusions drawn from this analysis cannot be considered sufficiently supported by the presented results. The manuscript does not assess the performance or validity of ML-Ask on the specific dataset used in this study, leaving uncertainty as to whether the tool performs adequately in this context. Without such an evaluation, the reliability of the emotion analysis—and consequently the conclusions based on it—remains unclear.

[Note: HTML markup is below. Please do not edit.]

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This paper presents an analysis of Japanese tweets mentioning the country's prescription record systems before, right-after and after a major earthquake. Through sentiment and discourse analysis, the authors study the evolution of the topics associated with negative emotions. This works shows that, while the prevalence of emotions didn't change much, the topic associated evolved, with a strong concern about the system's usability right after the earthquake. It also shows that this effect was only short-lived, with pre-earthquake concerns topics returning a month after.

This study is interesting and provides valuable results. Some aspects of the methodology (particularly regarding data collection) should be more detailed, to facilitated reproducibility. To me, the main blind spot of the analysis lies in the tweet's authorship : where these written by users of the prescription records, family of these, health workers, journalists ? A quick qualitative analysis of a subset of the corpus, or a small review of literature about the use of Twitter/X in the Japanese population could lift this ambiguity.

Here follows a list of more precise comments and recommendations :

The introduction clearly describes the topic of prescription records, their implementation in Japan, and the specific challenging that arise during disaster situations. However, the authors do not explain why they choose to analyze it through X/Twitter : is that platform particularly used by health professional ? the population ? what other SNS platform could have been studied ?

The data collection process is presented quickly and some questions remain :

- How is the collection script used to collect tweets older than 7 days ? (I suppose that it was run at regular intervals but this should be explained)

- What API-plan was bought to collect X/Twitter data ?

- What are the limits of the keyword strategy used ? (are they other expressions used to talk about medicine record books ? are some Japanese users tweeting in other languages ?)

- Did the collected dataset require some post-processing or cleaning ?

The sentence "data obtained do not reflect the intent of the authors" is not very-clear and may require explanations (what aspects of the dataset do not meet the authors expectations ?).

The analysis process is described in details. Some general explanations and references on Sentiment analysis could have been provided (here or in the introduction). The section states that occurrences were counted on time periods, but these periods are only described in the result section. Some statistical tests (e.g. Tukey-Kramer) are mentioned but not described ; on the other hand, some procedures (e.g. Cramer's V association coefficient) are described in a lot of details. For a non-specialist like me, this section is therefore difficult to understand. Ethical consideration are clear and useful ; this subsection could be moved just after the one on data collection.

Trends in emotions are presented in detail, the table is very useful. Discussions of the correspondence analysis are clear. The deep dive in the fear, dislike and anger clusters are very interesting. The figures are useful but there is some avoidable redundancy in the paragraphs that follow each figure. It could have been interest, for contrast, to also analyze one or two clusters linked to positive emotions (relief, joy ...).

Conclusions are clear but a bit short. The generalization of this study to other areas and other type of crisis could be discussed. Future research avenues could be proposed.

Reviewer #2: 1. The paper contains conflicting date ranges across sections and figure captions. The Methods section states a collection window from “October 1, 2023 to March 31, 2024,” but multiple figure captions state “October 2024 to March 2025.” This is confusing and difficult to follow. Please make it clear which date range is represented in the data and what date range was used for the analysis.

2. The statistical design is not clearly defined relative to what constitutes an observation unit. The paper reports residual analysis formulas, Cramer’s V, a two-way ANOVA, and a Tukey-Kramer test, but does not define what data points were used for each test. The paper does not specify whether the inputs were daily counts, weekly aggregates, or per-post indicators, or how the denominator for percentages was calculated for each period. The paper reports Cramer’s V as 0.06383 and cites 0.15 as a relevance threshold, but does not justify this threshold choice in the context of this dataset. How exactly were periods and emotions arranged in the contingency table that produced 0.06383, and what were the exact row and column labels?

3. The use of ML Ask as the sentiment and emotion engine is presented as definitive without dataset-specific validation. The paper does not report any manual annotation, interrater agreement, or spot checks on a sampled subset of posts to compare ML Ask labels against human judgment. The paper does not state how negation and sarcasm, common in social media, were handled beyond one illustrative sentence example. The paper reduces downstream analysis to “Fear,” “Dislike,” and “Anger” based on frequency, but does not provide a formal criterion for excluding the remaining 7 emotion axes. The paper also does not report whether multi-label outputs from ML Ask were possible and how those posts were counted in Table 1.

4. A diversity-based analysis is important here because public reactions to medical systems can vary across user groups, and an aggregate trend can hide those differences. The paper does not report any diversity-based patterns, subgroup differences, or user level analysis in the emotion outputs. Several prior works, such as https://doi.org/10.3390/computers12110221 and https://doi.org/10.1016/j.ipm.2021.102541 have highlighted the role of demographic factors when performing similar studies. If performing a diversity-based analysis is not feasible at this point, it is suggested that the authors review a few such works and state this as a future scope of work.

5. The conclusions go beyond what is observed in the analysis. The paper states that negative sentiment toward electronic systems “may lead to a reliance on analog systems” but the paper does not define a measurable indicator of reliance, adoption, or behavioral shift. The paper does not include any triangulation with prescription records usage data, pharmacy-level indicators, or independent survey measures to align the SNS patterns with real system behavior. The paper also does not report whether posts from affected prefectures were distinguished from posts elsewhere in Japan. The paper also does not present a clear mapping from cluster-level terms to specific actionable system failures, such as power supply, authentication, or data access workflows.

**********

6. PLOS authors have the option to publish the peer review history of their article (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: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures

You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation.

NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

<p>The psychological impact of major disasters on Japan's medical system: An SNS text analysis

PONE-D-25-64323R1

Dear Dr. Kitayama,

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.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Liviu-Adrian Cotfas

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (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: No

Reviewer #2: No

**********